bioRxiv Subject Collection: Neuroscience's Journal

Pro-Inflammatory Molecules Implicated in Multiple Sclerosis Divert the Development of Human Oligodendrocyte Lineage Cells
Background and Objectives: Oligodendrocytes (OL) and their myelin-forming processes are targeted and lost during the disease course of Multiple Sclerosis (MS), targeted by infiltrating leukocytes and their effector cytokines. Myelin repair is considered to be dependent on recruitment and differentiation of oligodendrocyte precursor cells (OPCs). The basis of failure of re-myelination during the disease course of MS remains to be defined. The aim of this study is to determine the impact of pro-inflammatory molecules tumor necrosis factor (TNF) and interferon gamma (IFN) on the differentiation of human OPCs. Methods: We generated human OPCs from induced pluripotent stem cells with a reporter gene under the OL-specific transcription factor SOX10. We treated the cells in vitro with TNF or IFN and evaluated effects in terms of cell viability, expression of OL-lineage markers, and co-expression of astrocyte markers. To relate our findings to the molecular properties of OPCs as found in the MS brain we re-analyzed publicly available single nuclear RNAseq datasets. Results: Our analysis indicated that both TNF and IFN decreased the proportion of cells differentiating into the OL-lineage; consistent with previous reports. We now observe the TNF effect is linked to aberrant OPC differentiation. A subset of O4+, reporter-positive cells co-expressed the astrocytic marker Aquaporin-4 (AQP4). On the transcriptomic level, the cells acquire an astrocyte-like signature alongside a conserved reactive phenotype. Analysis of single-nuclear RNAseq datasets from human MS brain revealed a subset of OPCs expressing an astrocytic signature. Discussion: In the context of MS, these results imply that OPCs are present but inhibited from differentiating along the OL-lineage, with a subset acquiring a reactive and stem-cell like phenotype, reducing their capacity to contribute towards repair. These findings help define a potential basis for the impaired myelin repair in MS and provide a prospective route for regenerative treatment.

Changes in Muscle Synergy Structure and Activation Patterns Underlie Force Field Adaptation, Retention, and Generalization
Humans can adapt their motor commands in response to errors when they perform reaching movements in new dynamic conditions, a process called motor adaptation. They acquire knowledge about the new dynamics, which they can use when they are re-exposed and, limitedly, generalize to untrained reaching directions. While force field adaptation, retention, and generalization have been thoroughly investigated at a kinematic and kinetic task level, the underlying coordination at a muscular level remains unclear. Many studies propose that the central nervous system uses low-dimensional control, i.e., coordinates muscles in functional groups: so-called muscle synergies. Accordingly, we hypothesized that changes in muscle synergy structure and activation patterns represent the acquired knowledge underlying force field adaptation, retention, and generalization. To test this, 36 male humans practiced reaching to a single target in a viscous force field and were tested for retention and generalization to new directions, while we simultaneously measured muscle activity from 13 upper-body muscles. We found that muscle synergies used for unperturbed reaching cannot explain the muscle patterns when adapted. Instead, muscle synergies specific to this adapted state were necessary, alongside a novel four-phasic pattern of muscle synergy activation. Furthermore, these structural changes and patterns were also evident during retention and generalization. Our results suggest that reaching in an environment with altered dynamics requires structural changes to muscle synergies compared to unperturbed reaching, and that these changes facilitate retention and generalization. These findings provide new insights into how the central nervous system coordinates the muscles underlying motor adaptation, retention, and generalization.

PinkyCaMP a mScarlet-based calcium sensor with exceptional brightness, photostability, and multiplexing capabilities
Genetically encoded calcium (Ca2+) indicators (GECIs) are widely used for imaging neuronal activity, yet current limitations of existing red fluorescent GECIs have constrained their applicability. The inherently dim fluorescence and low signal-to-noise ratio of red-shifted GECIs have posed significant challenges. More critically, several red-fluorescent GECIs exhibit photoswitching when exposed to blue light, thereby limiting their applicability in all-optical experimental approaches. Here, we present the development of PinkyCaMP, the first mScarlet-based Ca2+ sensor that outperforms current red fluorescent sensors in brightness, photostability, signal-to-noise ratio, and compatibility with optogenetics and neurotransmitter imaging. PinkyCaMP is well-tolerated by neurons, showing no toxicity or aggregation, both in vitro and in vivo. All imaging approaches, including single-photon excitation methods such as fiber photometry, widefield imaging, miniscope imaging, as well as two-photon imaging in awake mice, are fully compatible with PinkyCaMP.

Na+/Ca2+ exchanger triggers transient disruption of axon initial segments in hippocampal granule cells after brief ischemia.
The axon initial segment (AIS) is the site of action potential initiation in many cell types. The large density of Na+ channels and the small intraluminal volume of the AIS underlie the largest spike-dependent Na+ raise along the neuron. Our Na+ and Ca2+ imaging experiments in dentate granule cells reveal that the Na+/Ca2+ exchanger contributes to fast Na+ clearance at the expense of Ca2+ entry specifically at the AIS during short bursts of action potentials. The AIS is thought to be irreversibly disrupted during brain ischemia by the Ca2+-dependent protease calpain, as an early step leading to neuronal death. We find here that brief transitory ischemia produces a similar calpain-dependent disruption of the AIS in the dentate gyrus. However, this is not an irreversible process: a few days following the brief ischemic stress, intact initial segments re-appear, and calpain activity in the dentate gyrus returns to normal. Moreover, pharmacological blockade of Ca2+ entry through the Na+/Ca2+ exchanger prevents AIS disruption in vivo and in slice preparations. Our results unveil a highly dynamic anoxia driven disruption-reconstruction of AIS, which is mediated by a previously unnoticed Ca2+ entry through the Na+/Ca2+ exchanger in the axon initial segment of hippocampal granule cells.

Confinement stress with movement restriction suppresses male courtship in Drosophila through dopamine-dependent neuroplasticity
Stress disturbs the physiological and psychological balance in animals, leading to changes in brain function. Here, we show that stress in a small space with movement restriction (SS stress) suppresses male courtship in Drosophila and that alterations in dopamine signaling induced by SS stress are responsible for the persistence of this suppression after the stress experience. We found that SS stress activates numerous dopamine neurons in the brain. Pharmacological and genetic analyses revealed that dopamine synthesis, release, and reception are essential for the persistence of SS-stress-induced courtship suppression. A specific subset of dopamine neurons projects to the mushroom body (MB), a brain region where various sensory inputs are integrated. We identified that SS-stress-induced dopamine release plastically depresses the activity of a subset of MB neurons, and this neuronal depression contributes to the sustained suppression of male courtship behavior following stress exposure. This novel stress model using Drosophila provides valuable insights into dopamine-mediated stress mechanisms, particularly those related to confined spaces.

Age-Related Changes in Functional Balance Ability Predict Alpha Activity During Multisensory Integration
The increased multisensory integration and weaker attentional control experienced by older adults during audiovisual processing can result in inaccurate perceptions of their dynamic, everyday environment. These inaccurate representations of our environment can contribute to increased fall risk in older adults. A neural correlate of the attentional difference between younger and older adults could be oscillatory alpha activity (8-12Hz), indexing inhibitory processes during multisensory integration. The current study investigated whether age-related changes in alpha activity underlie weaker attentional control in older adults during a multisensory task, and if alpha associates with fall risk. Thirty-six younger (18-35 years old) and thirty-six older (60-80 years old) adults completed a cued-spatial-attention stream-bounce task, assessing audiovisual integration when attending to validly-cued or invalidly-cued locations, at 0ms or 300ms stimulus-onset asynchronies. Oscillatory alpha activity was recorded throughout using EEG to index participants' inhibitory abilities. Functional ability and balance were measured to index fall risk. Multiple linear regression models revealed that even when attending to the validly-cued location, less accurate multisensory integration was exhibited by older adults compared to younger adults, suggesting that older adults demonstrate weaker top-down modulation of multisensory integration through failing to inhibit task-irrelevant information. However, alpha power across the trials did not predict the extent of multisensory integration within the task. A significant interaction between age and functional ability scores predicted alpha power, suggesting that older adults may rely on attentional mechanisms for functional ability more than younger adults do. Potential implications in the design of clinical treatments to reduce falls are discussed.

Fast FEM-based Electric Field Calculations for Transcranial Magnetic Stimulation
Objective: To provide a Finite-Element Method (FEM) for rapid, repeated evaluations of the electric field induced by transcranial magnetic stimulation (TMS) in the brain for changing coil positions. Approach: Previously, we introduced a first-order tetrahedral FEM enhanced by super-convergent patch recovery (SPR), striking a good balance between computational efficiency and accuracy (Saturnino et al 2019 J. Neural Eng. 16 066032). In this study, we refined the method to accommodate repeated simulations with varying TMS coil position. Starting from a fast direct solver, streamlining the pre- and SPR-based post-calculation steps using weight matrices computed during initialization strongly improved the computational efficiency. Additional speedups were achieved through efficient multi-core and GPU acceleration, alongside the optimization of the volume conductor model of the head for TMS. Main Results: For an anatomically detailed head model with ~4.4 million tetrahedra, the optimized implementation achieves update rates above 1 Hz for electric field calculations in bilateral gray matter, resulting in a 60-fold speedup over the previous method with identical accuracy. An optimized model without neck and with adaptive spatial resolution scaled in dependence to the distance to brain grey matter, resulting in ~1.9 million tetrahedra, increased update rates up to 10 Hz, with ~3% numerical error and ~4% deviation from the standard model. Region-of-interest (ROI) optimized models focused on the left motor, premotor and dorsolateral prefrontal cortices reached update rates over 20 Hz, maintaining a difference of <4% from standard results. Our approach allows efficient switching between coil types and ROI during runtime which greatly enhances the flexibility. Significance: The optimized FEM enhances speed, accuracy and flexibility and benefits various applications. This includes the planning and optimization of coil positions, pre-calculation and training procedures for real-time electric field simulations based on surrogate models as well as targeting and dose control during neuronavigated TMS.

An Exploratory EEG Comparison of Good and Bad Readers
Reading is a crucial skill for critical thinking and cognitive development, yet many individuals experience difficulties that impact their daily lives. This study examines the neurophysiological differences between proficient and struggling readers using electroencephalography (EEG). The analysis focuses on the alpha (8-12 Hz) and beta (13-30 Hz) frequency bands, which are prominently involved in cognitive and language-related processes, although other frequency bands also contribute significantly to language comprehension and cognitive control. Eighteen participants (9 good readers and 9 poor readers) were selected based on standardized reading assessments. Resting-state EEG recordings were collected with a 64-channel system while participants were at rest with their eyes closed. After preprocessing to remove artifacts, the power spectra were analyzed, emphasizing relative power and alpha peak activity. Functional connectivity was measured using the corrected imaginary part of the phase-locking value (ciPLV), ensuring accuracy by minimizing volume conduction effects. Results revealed that good readers displayed increased beta power in frontal regions and enhanced synchronization within fronto-central-parietal networks compared to poor readers. Alpha band activity showed complex associations with factors such as age, reading skills, and verbal fluency, indicating nuanced relationships between neural development and literacy. The heightened beta activity in good readers is consistent with its role in cognitive control and language processing, while their stronger network connectivity suggests more efficient neural communication. These findings provide valuable insights into the neural basis of reading proficiency and emphasize the importance of distributed brain networks in skilled reading. Future research should replicate these results with larger samples and longitudinal designs to better understand the neural mechanisms underlying literacy development.

Modulation of Common Synaptic Inputs and Motor Unit Recruitment Threshold in TricepsSurae Muscles: Effects of Ankle Position
The objective of this study was to investigate how altering muscle length by changing ankle position affects motor unit coherence within and across triceps surae muscles, force control and motor unit recruitment. Sixteen healthy young adults performed isometric plantarflexion (PF) at three ankle positions with the ankle plantarflexed at 20{degrees} (PF20{degrees}), at the neural position (PF0{degrees}) and dorsiflexed at 20{degrees} (DF20{degrees}). High-density surface electromyography was used to record the medial and lateral heads of the gastrocnemius muscle (GM and GL), and the medial and lateral portions of the soleus muscle (SL and SM). Motor unit cumulative spike trains (MUCST) were used to calculate intramuscular, intermuscular, and Force-MUCST coherence in the delta (0-5 Hz), alpha (5-15 Hz), and beta (15-35 Hz) frequency bands. Changing the ankle position from a shortened to lengthened position resulted in increased GM-SM coherence in the delta and alpha bands and improved force steadiness, while intramuscular coherence and Force-MUCST coherence decreased in the alpha band. However, there were minimal changes in beta band coherence. Motor unit recruitment thresholds of GM and SL reduced with muscle lengthening, while GL showed greater thresholds at lengthened positions, and SM was unaffected by ankle position. These findings highlight the role of inhibitory inputs associated with changes in muscle length and the modulation of these inputs by neighboring synergistic muscles. This study reveals a neuromuscular control strategy that modulates common synaptic inputs and motor unit recruitment of triceps surae to maintain force output during isometric plantarflexions at varying muscle lengths.

Rapid long-range synaptic remodeling in hyperacute ischemic stroke
Physiological mechanisms of the key hyperacute (0-24 hours) stage of stroke remain incompletely understood, hampering development of new stroke therapies. Synaptic plasticity has been strongly implicated in early stages of neurodegenerative and neurodevelopmental disorders. Here, we describe rapid region-specific patterns of synaptic remodeling in stroke, arising within 4 hours of onset. While the ischemic core exhibits profound structural and functional synaptic decline, synapses in the mildly ischemic penumbra largely retain their structure, decreasing synaptic function. Conversely, synapses in the contralateral cortex across the brain show widespread structural and functional increase. Mechanistically, hyperacute stroke triggers synaptic recruitment of NMDA receptors in the ischemic core and penumbra, while NMDA receptor blockade exacerbates structural synaptic decline in the penumbra and abolishes contralateral synaptic enhancement. Proteomic analysis confirms cross-brain synaptic strengthening and reveals emergence of metabolic rearrangement in the penumbra, while RNAseq indicates broad downregulation of synaptic gene expression in the penumbra. These findings identify brain-wide homeostatic synaptic rebalancing as a potential mechanism for rapid-response functional compensation in early stroke, highlighting the extent of brain resilience to acute perturbation.

The effect of spherical projection on spin tests for brain maps
Statistical comparison between brain maps is a standard procedure in neuroimaging. Numerous inferential methods have been developed to account for the effect of spatial autocorrelation when evaluating map-to-map similarity. A popular method to generate surrogate maps with preserved spatial autocorrelation is the spin test. Here we show that a key component of the procedure - projecting brain maps to a spherical surface - distorts distance relationships between vertices. These distortions result in surrogate maps that imperfectly preserve spatial autocorrelation, yielding inflated false positive rates. We then confirm that targeted removal of individual spins with high distortion reduces false positive rates. Collectively, this work highlights the importance of accurately representing and manipulating cortical geometry when generating surrogate maps for use in map-to-map comparisons.

Neuronal expression of E2F4DN restores adult neurogenesis in homozygous 5xFAD mice via TrkB signaling
The etiology of Alzheimer's disease (AD) has been associated with impaired neurogenesis in the adult subventricular zone (SVZ), but the molecular mechanism leading to this impairment remains poorly understood. Neuronal dysfunction in the AD-affected brain might lead to reduced production of neuron-derived paracrine factors acting through receptors necessary for adult SVZ neurogenesis (ASN). To test this hypothesis, we focused on the TrkB receptor, which can transduce signals from the neurotrophins BDNF and NT4/5, since TrkB is known to regulate the ASN process and its function becomes altered in AD. Here we show that ASN is impaired in the SVZ of homozygous 5xFAD (h5xFAD) mice. This impairment is prevented by administering an AAV.PHP.eB vector that expresses in neurons the transcription factor E2F4 carrying the Thr249Ala/Th251Ala mutation (E2F4DN), a gene therapeutic approach previously demonstrated to exert multifactorial effects in this mouse model of AD. The use of culture media conditioned by primary cortical neurons expressing E2F4DN was able to recover the proliferative and differentiative capacity of neural stem cells (NSCs) isolated from h5xFAD mice. This effect was blocked by inhibiting the TrkB receptor. Accordingly, TrkB activation mimicked the effect of the E2F4DN-conditioned medium on the proliferative and differentiative capacity of h5xFAD NSCs, a finding consistent with the upregulation of NT4/5 expression in the E2F4DN-transduced neurons. We conclude that the activation of TrkB by neurotrophins released by E2F4DN-expressing neurons can recover the ASN phenotype in 5xFAD mice. Therefore, the multifactorial therapeutic capacity of E2F4DN includes the recovery of impaired ASN through the upregulation of TrkB signaling in NSCs.

Investigating saccade-onset locked EEG signatures of face perception during free-viewing in a naturalistic virtual environment
Current research strives to investigate cognitive processes under natural conditions. Virtual reality and EEG are promising techniques combining naturalistic settings with close experimental control. However, many questions and technical challenges remain, e.g., are fixation or saccade onsets a suitable replacement as key events in continuous gaze trajectories (Amme et al., 2024), and can VR effectively capture differences across experimental conditions (Rossion & Jacques, 2008)? To address both questions, we investigate the N170 face effect in a free-viewing immersive VR study that contained houses, various background stimuli, and, notably, static and moving pedestrians to study face perception under naturalistic conditions. Our results show that aligning trials to saccade-onset leads to more well-defined ERPs, especially for the P100 component, and support that saccade-onset ERPs are the better-suited analysis method than fixation-onset ERPs for this type of experiment. Further, we observe an evolution of condition-based differences, i.e., face vs. background fixations, compatible with previous reports but extending in a large temporal window and including all electrode sites at different points in time. In summary, experiments combining VR, EEG, and eye-tracking provide further insights into the processing of faces and the relevance of saccadic onsets as event triggers under natural conditions.

From spiking neuronal networks to interpretable dynamics: a diffusion-approximation framework
Modeling and interpreting the complex recurrent dynamics of neuronal spiking activity is essential to understanding how networks implement behavior and cognition. Nonlinear Hawkes process models can capture a large range of spiking dynamics, but remain difficult to interpret, due to their discontinuous and stochastic nature. To address this challenge, we introduce a novel framework based on a piecewise deterministic Markov process representation of the nonlinear Hawkes process (NH-PDMP) followed by a diffusion approximation. We analytically derive stability conditions and dynamical properties of the obtained diffusion processes for single-neuron and network models. We established the accuracy of the diffusion approximation framework by comparing it with exact continuous-time simulations of the original neuronal NH-PDMP models. Our framework offers an analytical and geometric account of the neuronal dynamics repertoire captured by nonlinear Hawkes process models, both for the canonical responses of single-neurons and neuronal-network dynamics, such as winner-take-all and traveling wave phenomena. Applied to human and nonhuman primate recordings of neuronal spiking activity during speech processing and motor tasks, respectively, our approach revealed that task features can be retrieved from the dynamical landscape of the fitted models. The combination of NH-PDMP representations and diffusion approximations thus provides a novel dynamical analysis framework to reveal single-neuron and neuronal-population dynamics directly from models fitted to spiking data.

Lysine deacetylation inhibition reverses TDP-43 mislocalization and in combination with arimoclomol ameliorates neuromuscular pathology
Background: Cytoplasmic inclusions containing TAR DNA-binding protein 43 kDa (TDP-43) are recognized as a major pathological feature of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, but more recently have been associated with several neurodegenerative conditions. Cyclophilin A (PPIA), a foldase and molecular chaperone, interacts with TDP-43 and influences its aggregation and function. The interaction between PPIA and TDP-43 is facilitated by PPIA Lysacetylation, which is reduced in peripheral blood mononuclear cells (PBMCs) of ALS patients showing signs of TDP-43 proteinopathy. In this study, we investigated the effect of lysine deacetylation inhibition to uncover the underlying mechanisms of TDP-43 proteinopathy in relation to PPIA acetylation, and to identify new therapeutic avenues. Methods: Through a screening of histone deacetylase (HDAC) inhibitors in a cellular model of TDP-43 proteinopathy, we identified vorinostat/SAHA, capable of increasing PPIA acetylation, as the most effective in reversing TDP-43 mislocalization. We confirmed its effect in PBMCs from ALS patients. Next, we explored its impact on proteinopathy and PPIA acetylation in a severe and fast-progressing TDP-43 overexpressing mouse model (Thy1-hTDP-43), using several molecular biomarkers as outcome measures, including neurofilament light chain (NfL) in plasma. Results: Thy1-hTDP-43 mice treated with SAHA showed a delayed onset of TDP-43 pathology, associated with PPIA nucleus-cytoplasm redistribution, lower levels of neurodegeneration and neuroinflammation markers, and improved neuromuscular function markers. However, over time, the broad-spectrum inhibitor SAHA was unable to counteract the two-fold overexpression of TDP-43 and led to the accumulation of side effects. When combined with the heat shock protein (HSP) co-inducer arimoclomol, a mitigation of the neurodegeneration was sustained. Moreover, a synergistic effect was observed in periphery, greatly enhancing tubulin acetylation and reducing pTDP-43 accumulation in the sciatic nerve. This resulted in a more pronounced reduction of NfL in plasma and acetylcholine receptor (AChR) {gamma}-subunit expression in gastrocnemius muscle, indicating reduced axonal transport impairment and muscle denervation. Conclusions: This study suggests that HDAC inhibition, by increasing acetylated PPIA, could be beneficial in restoring TDP-43 localization and function. The combination of lysine deacetylation inhibition and HSP induction shows a synergistic effect in vivo and has potential as a therapeutic approach for patients.

Astrocytic Signatures in Neuronal Activity: A Machine Learning-Based Identification Approach
This study investigates the expanding role of astrocytes, the predominant glial cells, in brain function, focusing on whether and how their presence influences neuronal network activity. We focus on particular network activities identified as synchronous and asynchronous. Using computational modeling to generate synthetic data, we examine these network states and find that astrocytes significantly affect synaptic communication, mainly in synchronous states. We use different methods of extracting data from a network and compare which is best for identifying glial cells, with mean firing rate emerging with higher accuracy. To reach the aforementioned conclusions, we applied various machine learning techniques, including Decision Trees, Random Forests, Bagging, Gradient Boosting, and Feedforward Neural Networks, the latter outperforming other models. Our findings reveal that glial cells play a crucial role in modulating synaptic activity, especially in synchronous networks, highlighting potential avenues for their detection with machine learning models through experimental accessible measures.

Individual Alpha Frequency Predicts the Sensitivity of Time Perception
A growing body of research links individual differences in the frequency of alpha-band oscillations to temporal aspects of perception. However, whether the human alpha rhythm is a correlate of time perception itself has remained controversial. This multi-day study combined EEG with multiple duration estimation and discrimination tasks in order to evaluate whether individual alpha frequency (IAF) is associated with sensitivity or bias in judging visual durations across a range of peri-second durations (spanning 1200 to 100ms). In a temporal estimation task, participants (n = 55) reported the duration of a single stimulus between 300-1200ms. In a temporal discrimination task, participants reported which of two stimuli was longer: a standard (100, 600, or 1200ms) or comparison (50-150% of the standard). Stimuli also varied in whether their luminance was static or dynamic (varying randomly over time). We found that IAF was significantly related to the variance of duration estimates, a measure of precision (or sensitivity), but not average duration estimates, a measure of bias. Further supporting this relationship, psychometric function slopes obtained from independent duration discrimination tasks were correlated with IAF, particularly for the static stimulus conditions. These effects were largely consistent across the range of stimulus durations tested and held when controlling for participant age. Taken together, these results suggest that IAF plays a role in shaping individual differences in the sensitivity of time perception. However, we did not observe effects of spontaneous fluctuations in single-trial alpha frequency, suggesting the effect is primarily observable at the cross-subject level.

Evidence for white matter intrinsic connectivity networks at rest and during a task: a large-scale study and templates
Understanding white matter (WM) functional connectivity is crucial for unraveling brain function and dysfunction. In this study, we present a novel WM intrinsic connectivity network (ICN) template derived from over 100,000 fMRI scans, identifying 97 robust WM ICNs using spatially constrained independent component analysis (scICA). This WM template, combined with a previously identified gray matter (GM) ICN template from the same dataset, was applied to analyze a resting-state fMRI (rs-fMRI) dataset from the Bipolar-Schizophrenia Network on Intermediate Phenotypes 2 (BSNIP2; 590 subjects) and a task-based fMRI dataset from the MIND Clinical Imaging Consortium (MCIC; 75 subjects). Our analysis highlights distinct spatial maps for WM and GM ICNs, with WM ICNs showing higher frequency profiles. Modular structure within WM ICNs and interactions between WM and GM modules were identified. Task-based fMRI revealed event-related BOLD signals in WM ICNs, particularly within the corticospinal tract, lateralized to finger movement. Notable differences in static functional network connectivity (sFNC) matrices were observed between controls (HC) and schizophrenia (SZ) subjects in both WM and GM networks. This open-source WM NeuroMark template and automated pipeline offer a powerful tool for advancing WM connectivity research across diverse datasets.

CDNF rescues human iPSCs-derived dopamine neurons through direct binding to unfolded protein response sensors PERK and IRE1α
Cerebral dopamine neurotrophic factor (CDNF) is an unconventional trophic factor that protects dopamine neurons in cellular and animal models of Parkinson's disease (PD). CDNF was safe and well tolerated in phase 1 clinical trials for PD treatment, and currently, its peptide analogue is under investigation in phase 1 clinical trials for PD. Despite prominent neuroprotective and neurorestorative activity, the receptors and exact mechanism of CDNF functioning have been obscure. Intracellularly acting CDNF exerts cytoprotection by attenuating endoplasmic reticulum (ER) stress and unfolded protein response (UPR). We demonstrated that this activity occurs through the direct binding of CDNF to ER transmembrane UPR sensors PERK and IRE1 for purified proteins and in cells. We identified CDNF mutants deficient for binding to UPR sensors. CDNF binding to PERK and IRE1 appeared to be crucial for the survival of mouse dopamine neurons in culture. Importantly for clinical translation, CDNF rescues human induced pluripotent stem cell-derived dopamine neurons and promotes their regeneration. CDNF binding to UPR sensors alleviated terminal UPR and promoted neurite outgrowth of human dopamine neurons through direct binding to PERK and IRE1. CDNF binding to BiP was dispensable for the neuroprotective and neurorestorative activity of CDNF. Therefore, CDNF, or small molecules mimicking its binding to UPR sensors and acting selectively on dopamine neurons with activated UPR, are promising drug candidates for PD treatment.

Assessment of cortical excitability in awake rhesus macaques with transcranial magnetic stimulation: translational insights from recruitment curves
Background and objectives: Cortical excitability (CE) is commonly assessed by recording motor-evoked potentials (MEPs) in response to single-pulse transcranial magnetic stimulation (sp-TMS). While the motor threshold (MT) remains the most widely used measure of CE, it provides a one-dimensional, criterion-based assessment. In contrast, the recruitment curve (RC) offers a more comprehensive characterization of the full dynamics of cortical recruitment. Yet, only a few preclinical studies involving translationally relevant non-human primates were conducted, and most were under anaesthesia. Hence, we aimed to characterise CE in awake rhesus macaques by recording traditionally defined MT and RCs. Methods: Traditional MT with a 100 V MEP criterion ('tradMT') was measured in 8 awake adult male rhesus macaques using C-B65 coil and MagVenture stimulator. RCs were recorded at nine relative intensity levels (0.5 - 1.5 * tradMT) in 4 macaques. A sigmoid function was fitted to obtain key CE parameters: the inflection point, lower ankle point, and plateau. Results: TradMT values were stable and replicable, and aligned most closely with the inflection point of the RC. The lower ankle points were found around at 0.9 * tradMT, marking the transition from a constant to a logarithmic phase, representing a physiologically relevant threshold. Plateau MEP amplitudes were substantially smaller compared to those reported in humans. Conclusion: Fitted RC parameters revealed a distinction between tradMT and the physiologically relevant threshold. The overall RC shape was consistent with human data, suggesting similar recruitment processes, leading to high translational validity. However, the marked difference in maximal MEP magnitude emphasises the importance of species-specific adaptations.

In vivo human neurite exchange imaging (NEXI) at 500 mT/m diffusion gradients
Evaluating tissue microstructure and membrane integrity in the living human brain through diffusion-water exchange imaging is challenging due to requirements for a high signal-to-noise ratio and short diffusion times dictated by relatively fast exchange processes. The goal of this work was to demonstrate the feasibility of in vivo imaging of tissue micro-geometries and water exchange within the brain gray matter using the state-of-the-art Connectome 2.0 scanner equipped with an ultra-high-performance gradient system (maximum gradient strength=500 mT/m, maximum slew rate=600 T/m/s). We performed diffusion MRI measurements in 15 healthy volunteers at multiple diffusion times (13-30 ms) and b-values up to 17.5 ms/m2. The anisotropic Karger model was applied to estimate the exchange time between intra-neurite and extracellular water in gray matter. The estimated exchange time across the cortical ribbon was around (median{+/-}interquartile range) 13{+/-}8 ms on Connectome 2.0, substantially faster than that measured using an imaging protocol compatible with Connectome 1.0-alike systems on the same cohort. Our investigation suggested that the NEXI exchange time estimation using a Connectome 1.0 compatible protocol was more prone to residual noise floor biases due to the small time-dependent signal contrasts across diffusion times when the exchange is fast ([≤]20 ms). Furthermore, spatial variation of exchange time was observed across the cortex, where the motor cortex, somatosensory cortex and visual cortex exhibit longer exchange times compared to other cortical regions. Non-linear fitting for the anisotropic Karger model was accelerated 100 times using a GPU-based pipeline compared to the conventional CPU-based approach. This study highlighted the importance of the chosen diffusion times and measures to address Rician noise in dMRI data, which can have a substantial impact on the estimated NEXI exchange time and require extra attention when comparing NEXI results between various hardware setups.

Sex Differences in Auditory Brainstem Responses in the Hispid Pocket Mouse (Chaetodipus hispidus)
The hispid pocket mouse (C. hispidus) is a solitary semi-fossorial rodent that has been the subject of various ecological and genetic studies. However, no previous studies have characterized its hearing ability, which is important for its survival and fitness. We collected auditory brainstem responses (ABRs) from C. hispidus and measured craniofacial and pinna morphological features to assess hearing ability and test differences in hearing thresholds, monaural and binaural ABR amplitudes and latencies between the sexes. ABR recordings revealed that similar to other small mammals, C. hispidus displayed the lowest threshold to sounds between 8-16 kHz, indicating best hearing across those frequencies. We found significant differences in auditory thresholds of the ABRs between the sexes, with females showing lower frequency hearing compared to males. However, no significant differences were detected in monaural and binaural ABR amplitudes and latencies between the sexes. We also found no significant differences in craniofacial and pinna dimensions between the sexes. These findings shed novel insights into the auditory systems across species and highlighted for the first time sex differences in auditory thresholds for this rodent species.

Repeated head-exposures to a 5G-3.5 GHz signal do not alter behavior but modify intracerebral gene expression in adult male mice.
The 5th generation (5G) of mobile communications promotes human exposures to electromagnetic fields exploiting the 3.5 GHz frequency band. We have analyzed behaviors, cognitive functions and gene expression in mice submitted to asymmetrical head-exposures to a 5G-modulated 3.5 GHz signal. The exposures were applied 1h daily, 5 days per week over a six-week period, at a specific absorption rate (SAR) averaging 0.19 W/kg over the brain. Locomotor activity in an open-field, object-place and object recognition memories were assessed repeatedly after four weeks of exposure and did not reveal any significant effect on the locomotion/exploration, anxiety level or memory processes. mRNA profiling was performed at the end of the exposure period in two symmetrical areas of the right and left cerebral cortex in which the SAR values were 0.43 and 0.14 W/kg, respectively. We found significant changes in the expression of less than 1% of the expressed genes with over-representations of genes related to glutamatergic synapses. The right cortical area differed from the left one by an over-representation of responsive genes encoded by the mitochondrial genome. Our data show that repeated head-exposures to a 5G-3.5 GHz signal can trigger mild transcriptome alterations without change in memory capacities or emotional state.

Multimodal normative modeling in Alzheimer Disease with introspective variational autoencoders
Normative models in neuroimaging learn patterns of healthy brain distributions to identify deviations in disease subjects, such as those with Alzheimer Disease (AD). This study addresses two key limitations of variational autoencoder (VAE)-based normative models: (1) VAEs often struggle to accurately model healthy control distributions, resulting in high reconstruction errors and false positives, and (2) traditional multimodal aggregation methods, like Product-of-Experts (PoE) and Mixture-of-Experts (MoE), can produce uninformative latent representations. To overcome these challenges, we developed a multimodal introspective VAE that enhances normative modeling by achieving more precise representations of healthy anatomy in both the latent space and reconstructions. Additionally, we implemented a Mixture-of-Product-of-Experts (MOPOE) approach, leveraging the strengths of PoE and MoE to efficiently aggregate multimodal information and improve abnormality detection in the latent space. Using multimodal neuroimaging biomarkers from the Alzheimer Disease Neuroimaging Initiative (ADNI) dataset, our proposed multimodal introspective VAE demonstrated superior reconstruction of healthy controls and outperformed baseline methods in detecting outliers. Deviations calculated in the aggregated latent space effectively integrated complementary information from multiple modalities, leading to higher likelihood ratios. The model exhibited strong performance in Out-of-Distribution (OOD) detection, achieving clear separation between control and disease cohorts. Additionally, Z-score deviations in specific latent dimensions were mapped to feature-space abnormalities, enabling interpretable identification of brain regions associated with AD pathology.

The striatal compartments, striosome and matrix, are embedded in largely distinct resting state functional networks
The striatum is divided into two interdigitated tissue compartments, the striosome and matrix. These compartments exhibit distinct anatomical, neurochemical, and pharmacological characteristics and have separable roles in motor and mood functions. Little is known about the functions of these compartments in humans. While compartment-specific roles in neuropsychiatric diseases have been hypothesized, they have yet to be directly tested. Investigating compartment-specific functions is crucial for understanding the symptoms produced by striatal injury, and to elucidating the roles of each compartment in healthy human skills and behaviors. We mapped the functional networks of striosome and matrix in humans in vivo. We utilized a diverse cohort of 674 healthy adults, derived from the Human Connectome Project, including all subjects with complete diffusion and functional MRI data and excluding subjects with substance use disorders. We identified striatal voxels with striosome-like and matrix-like structural connectivity using probabilistic diffusion tractography. We then investigated resting state functional connectivity (rsFC) using these compartment-like voxels as seeds. We found widespread differences in rsFC between striosome-like and matrix-like seeds (p < 0.05, FWE corrected for multiple comparisons), suggesting that striosome and matrix occupy distinct functional networks. Slightly shifting seed voxel locations (<4 mm) eliminated these rsFC differences, underscoring the anatomic precision of these networks. Striosome-seeded networks exhibited ipsilateral dominance; matrix-seeded networks had contralateral dominance. Next, we assessed compartment-specific engagement with the triple-network model (default mode, salience, and frontoparietal networks). Striosome-like voxels dominated rsFC with the default mode network bilaterally. The anterior insula (a primary node in the salience network) had higher rsFC with striosome-like voxels. The inferior and middle frontal cortices (primary nodes, frontoparietal network) had stronger rsFC with matrix-like voxels on the left, and striosome-like voxels on the right. Since striosome-like and matrix-like voxels occupy highly segregated rsFC networks, striosome-selective injury may produce different motor, cognitive, and behavioral symptoms than matrix-selective injury. Moreover, compartment-specific rsFC abnormalities may be identifiable before disease-related structural injuries are evident. Localizing rsFC differences provides an anatomic substrate for understanding how the tissue-level organization of the striatum underpins complex brain networks, and how compartment-specific injury may contribute to the symptoms of specific neuropsychiatric disorders.

Chronic Behavioral and Seizure Outcomes following Experimental Traumatic Brain Injury and Comorbid Klebsiella pneumoniae Lung Infection in Mice
Traumatic brain injury (TBI) is a leading cause of long-term disability, and infections such as pneumonia represent a common and serious complication for TBI patients in the acute and subacute post-injury period. While the acute effects of infections have been documented, their long-term consequences on neurological and behavioral recovery as well as the potential precipitation of seizures after TBI remain unclear. This study aimed to investigate the chronic effects of Klebsiella pneumoniae infection following TBI, focusing on post-traumatic seizure development and neurobehavioral changes. Using a mouse model, we assessed the long-term effects of TBI and K. pneumoniae infection both in isolation and in combination. We found that, while infection with K. pneumoniae resulted in loss of body weight and increased mortality compared to vehicle-inoculated mice, there was no additional mortality in TBI animals. Further, although TBI alone induced chronic hyperactivity and reduced anxiety-like behaviors, K. pneumoniae lung infection had no lasting effect on these long-term outcomes. Thirdly, while TBI resulted in both spontaneous and evoked seizures long-term post-injury, early post-injury K. pneumoniae infection did not affect late onset seizure susceptibility. Together with recent findings on acute outcomes in this combined insult model of TBI and K. pneumoniae infection, this study suggests that K. pneumoniae does not significantly alter long-term neurobehavioral outcomes or the development of post-traumatic epilepsy. This research highlights the need to further explore the interplay between additional immune insults such as infection that may influence long-term recovery.

A Brain Reward Circuit Inhibited By Next-Generation Weight Loss Drugs
Glucagon-like peptide-1 receptor agonists (GLP1RAs) effectively reduce body weight and improve metabolic outcomes, yet established peptide-based therapies require injections and complex manufacturing. Small-molecule GLP1RAs promise oral bioavailability and scalable manufacturing, but their selective binding to human versus rodent receptors has limited mechanistic studies. The neural circuits through which these emerging therapeutics modulate feeding behavior remain undefined, particularly in comparison to established peptide-based GLP1RAs. Here, we developed humanized GLP1R mouse models to investigate how small-molecule GLP1RAs influence feeding behavior. Integrating genetic manipulations, calcium imaging, and behavior profiling, we discovered that these compounds regulate both homeostatic and hedonic feeding through parallel neural circuits. Beyond engaging canonical hypothalamic and hindbrain networks that control metabolic homeostasis, GLP1RAs recruit a discrete population of Glp1r-expressing neurons in the central amygdala, which selectively suppress the consumption of palatable foods by reducing dopamine release in the nucleus accumbens. Stimulating these central amygdalar neurons curtail hedonic feeding, whereas targeted deletion of the receptor in this cell population specifically diminishes the anorectic efficacy of GLP1RAs for reward-driven intake. These findings reveal a dedicated neural circuit through which small molecule GLP1RAs modulate reward processing, suggesting broad therapeutic potential in conditions of dysregulated dopamine signaling including substance use disorder and binge eating.

Computational modeling reveals biological mechanisms underlying the whisker-flick EEG
Whisker flick stimulation is a commonly used protocol to investigate somatosensory processing in rodents. Neural activity in the brain evoked by whisker flicks produces a characteristic EEG waveform recorded at the skull, known as a somatosensory evoked potential. In this paper, we use in silico modeling to identify the neural populations that serve as sources and targets of the synaptic currents contributing to this signal (presynaptic and postsynaptic populations, respectively). The initial positive deflection of the EEG waveform is driven largely by direct thalamic inputs to Layer 2/3 and Layer 5 pyramidal cells, though interestingly, L5-L5 inhibition plays a modulatory role, reducing the amplitude and width of the deflection. This suggests that increasing thalamocortical connectivity and decreasing L5-L5 inhibition may be responsible for some of the changes observed in the EEG waveform over the course of development. The negative deflection is driven by a more complex mix of sources, including both thalamic and recurrent cortical connectivity. We demonstrate that small changes to the local connectivity of the circuit, particularly to perisomatic inhibitory targeting, can have an important impact on the recorded EEG, without substantially affecting firing rates, suggesting that EEG may be useful in constraining in silico neural models.

Neural dynamics of reselecting visual and motor contents in working memory after external interference
In everyday tasks, we must often shift our focus away from internal representations held in working memory to engage with perceptual events in the external world. Here, we investigated how our internal focus is reestablished following an interrupting task by tracking the reselection of visual representations and their associated action plans in working memory. Specifically, we ask whether reselection occurs for both visual and motor memory attributes and when this reselection occurs. We developed a visual-motor working-memory task in which participants were retrospectively cued to select one of two memory items before being interrupted by a perceptual discrimination task. To determine when internal representations were reselected, the interrupting task was presented at one of three distinct time points following the retro-cue. To determine what information was reselected, the memory items had distinct visual and motor attributes. We employed electroencephalography time-frequency analyses to track the initial selection and later reselection of visual and motor representations, as operationalized through modulations of posterior alpha (8-12 Hz) activity relative to the memorized item location (visual) and of central beta (13-30 Hz) activity relative to the required response hand (motor). Our results showed that internal visual and motor contents were concurrently reselected immediately after completing the interrupting task, rather than only when internal information was required for memory-guided behavior. Thus, following interruption, we swiftly resume our internal focus in working memory through the simultaneous reselection of memorized visual representations and their associated action plans, thereby restoring internal contents to a ready-to-use state.

Control of odor sensation by light and cryptochrome in the Drosophila antenna
Olfaction is a sense employed by insects to differentiate safe from harmful food options, evaluate potential mates, and identify oviposition sites. Here, we found that the fruit fly, Drosophila melanogaster, responds differently to a set of repulsive odors depending on ambient light conditions. Ultraviolet (UV) or blue light reduces the behavioral aversion and electrophysiological responses of olfactory receptor neurons (ORNs) to certain repellent odors, such as benzaldehyde. We found that cryptochrome (cry) is strongly expressed in the antennal support cells that lie adjacent to ORNs, and mutation of cry eliminates the light-dependent reduction in aversion. Thus, these data demonstrate that support cells in an olfactory organ serve a sensory function as light receptor cells. It has been shown that light activation of Cry creates reactive oxygen species (ROS), and ROS activates the TRPA1 channel. We demonstrate that the TRPA1-C isoform is expressed and required in ORNs for benzaldehyde repulsion, and that TRPA1-C is activated in vitro by benzaldehyde. Overexpression of dual oxygenase, which generates hydrogen peroxide, reduced the aversion under dark conditions. Our data support the model that light-dependent creation of hydrogen peroxide persistently activates TRPA1-C. Consequently, the channel is no longer effectively activated by benzaldehyde. Since flies sleep much more at night, and begin feeding at dawn, we propose that the light-induced reduction in aversion to certain odors provides a mechanism to lower the barrier to feeding following the transition from night to day.

The selfish yet forgetful brain: Stable cerebral oxygen metabolism during hypoglycemia but impaired memory consolidation
The continuous supply of glucose and oxygen is essential for healthy brain function. Accordingly, the Selfish Brain Theory proposes that the human brain prioritizes its own energy demands, making it less vulnerable to fluctuations in systemic energy availability. Although studies have reported decreases in cerebral glucose metabolism, alternative energy sources other than glucose might be oxidized for ATP production. However, cerebral oxygen metabolism (CMRO2) has never been quantified across the human brain. In this study, we investigated the influence of insulin-induced hypoglycemia on CMRO2 in healthy male participants. Additionally, we explored the prolonged effects of hypoglycemia on cognitive function following the restoration of euglycemia. We found that CMRO2 remained stable under hypoglycemia, even at blood glucose levels below 49 mg/dL. Interestingly, we detected a significant increase in cerebral blood flow (CBF) of up to 11%, particularly in regions involved in higher cognitive processing. Despite stable rates of oxygen metabolism, we identified a selective impairment in memory consolidation following hypoglycemia, even after normal glucose levels were restored, with no effects observed in memory encoding or attention. In favor of the Selfish Brain Theory, the stability in CMRO2 suggests that the brain efficiently shifts to alternate energy pathways under hypoglycemia, potentially using astrocytic glycogen. Despite this metabolic flexibility, our results indicate that prior hypoglycemia imposes long-lasting effects on memory consolidation, possibly linked to glycogen depletion and impaired glutamate synthesis. In summary, our study suggests that clinical states of hypoglycemia pose a critical impact on patient brain health and functioning.

Insular cortex encodes task alignment
Animals can learn complex behaviors. Animal behavior in the lab has traditionally been studied via summary statistics such as trial-based success rates. However, animal behavior is much more fine-grained: a trial in an experiment often consists of multiple actions, and more than one strategy can lead to a successful completion of a trial. To understand how the brain controls behavior, a fine-grained yet compact description of behavior is necessary. We describe here an approach for estimating the strategies animals use for a large family of tasks from first principles. Using reinforcement learning with informational constraints on policies, we compute a rich set of candidate policies with a small number of meaningful parameters, and match observed behavior to these policies. In a sample rat task, our approach revealed ongoing learning for more than 100 days after the saturation of success rates. Moreover, we showed that many neurons in the insular cortex of rats track the instantaneous task engagement of the rats with a resolution of a few minutes. Due to its generic formulation in reinforcement learning terminology, our work is directly applicable to the majority of animal tasks in use today.

Functional fingerprinting for the developing brain using deep metric learning: an ABCD study
Brain fingerprinting is a promising approach for characterizing the uniqueness of individual brain functioning using functional magnetic resonance imaging (fMRI) data. Here, we propose a novel deep learning framework, the metric-BoIT, for brain fingerprinting and demonstrate its effectiveness in capturing individual variability among early adolescents undergoing dramatic brain changes. Utilizing resting-state fMRI data from the Adolescent Brain Cognitive Development (ABCD) dataset, we identified brain functional fingerprints that achieved remarkable individual identification accuracy, reaching 97.6% within a single session and maintaining 86.6% accuracy over a four-year developmental period. Annotation analysis revealed that higher-order association regions, particularly those within the default-mode network, contributed most significantly to these distinctive brain fingerprints (t = 5.618, p < 0.001). Moreover, these brain fingerprints were relevant to cognitive functions, as evidenced by significant correlations with fluid intelligence (F = 1.282, p = 0.027) and crystallized intelligence (F = 1.405, p < 0.001). The extracted brain fingerprints were additionally associated with genetics, showing that individuals with strong genomic relationships exhibited more similar brain fingerprint patterns (t = -12.330, p < 0.001). Together, our study not only presents an innovative approach to brain functional fingerprinting but also provides valuable insights into the individual variability underlying adolescent neurodevelopment.

Single-Nucleus Neuronal Transcriptional Profiling of Male C. elegans Uncovers Regulators of Sex-Specific and Sex-Shared Behaviors
Sexual differentiation of the nervous system causes differences in neuroanatomy, synaptic connectivity, and physiology. These sexually-dimorphic phenotypes ultimately translate into profound behavioral differences. C. elegans' two sexes, XO males and XX hermaphrodites, demonstrate differences in neurobiology and behavior. However, the neuron class and sex-specific transcriptomic differences, particularly at the single-neuron level, that cause such phenotypic divergence remains understudied. Here, using single-nucleus RNA sequencing, we assessed and compared adult male and hermaphrodite C. elegans neuronal transcriptomes, identifying sex-specific neurons, including previously-unannotated male neurons. Sex-shared neurons displayed large expression differences, with some neuron classes clustering as distinct neurons between the sexes. Males express ~100 male-specific GPCRs, largely limited to a subset of neurons. We identified the most highly-divergent neurons between the sexes, and functionally characterized a sex-shared target, vhp-1, in male-specific pheromone chemotaxis. Our data provide a resource for discovering nervous-system-wide sex transcriptomic differences and the molecular basis of sex-specific behaviors.

EEG-based Assessment of Long-Term Vigilance and Lapses of Attention using a User-Centered Frequency-Tagging Approach
Sustaining vigilance over extended periods is crucial for many critical operations but remains challenging due to the cognitive resources required. Fatigue and other factors contribute to fluctuations in vigilance, causing attentional focus to drift from task-relevant information. Such lapses of attention, common in prolonged tasks, lead to decreased performance and missed critical information, with potentially serious consequences. Identifying physiological markers that predict inattention is key to developing preventive strategies. Previous research has established electroencephalography (EEG) responses to periodic visual stimuli, known as steady-state visual evoked potentials (SSVEP), as sensitive markers of attention. In this study, we evaluated a minimally intrusive SSVEP-based approach for tracking vigilance in healthy participants (N = 16) during two sessions of a 45-minute sustained visual attention task (Mackworth's clock task). A 14 Hz frequency-tagging flicker was either superimposed on the task or absent. Results revealed that SSVEP responses were lower prior to lapses of attention, while other spectral EEG markers, such as frontal theta and parietal alpha activity, did not reliably distinguish between detected and missed attention probes. Importantly, the flicker did not affect task performance or participant experience. This non-intrusive frequency-tagging method provides a continuous measure of vigilance, effectively detecting attention lapses in prolonged tasks. It holds promise for integration into passive brain-computer interfaces, offering a practical solution for real-time vigilance monitoring in high-stakes settings like air traffic control or driving.

Enhanced Subjective Performance Achievement in Wind Instrument Playing through Positive Memory Recall: Effects of Sympathetic Activation and Emotional Valence
Controlling physiological and psychological states before a performance is essential for professional musicians to realize their full potential. However, the characteristics of the optimal pre-performance state remain unclear. While an increase in sympathetic nervous system activity is typically observed before performance, when associated with anxiety, it can degrade the performance quality. This study examined whether recalling positive autobiographical performance memories enhances subjective performance achievement, accompanied by increased emotional arousal, valence, and autonomic nervous system activity. Thirty-six professional wind instrument players participated in the study. Prior to performing musical pieces, participants engaged in one of three conditions: (1) recalling positive autobiographical memories, (2) recalling negative autobiographical memories, or (3) imagining routine pre-performance activities (no-memory condition). During the memory recall phase, heart rate was measured. After each performance, participants rated their subjective arousal, valence, and performance achievement. We calculated the heart rate variability indices, specifically SD1 (reflecting parasympathetic nervous system activity) and SD2/SD1 (reflecting sympathetic nervous system activity). The results showed that performance achievement, arousal, and valence were significantly higher in the positive than in the negative condition. Our path analysis further revealed that an increase in SD2/SD1 did not directly predict performance achievement; instead, it was associated with an increase in emotional valence, which in turn led to improved performance. These findings suggest that recalling positive performance memories activates sympathetic nervous system activity and fosters positive emotions, thereby enhancing the performance achievement of professional musicians.

Cerebral Venous Blood Flow Regulates Brain Fluid Clearance via Dural Lymphatics
The vascular system regulates brain clearance through arterial blood flow and lymphatic drainage of cerebrospinal fluid (CSF). Idiopathic intracranial hypertension (IIH), characterized by elevated intracranial pressure and dural venous sinus stenoses, can be treated by restoring venous blood flow via venous stenting, suggesting a role for venous blood flow in brain fluid clearance. Using magnetic resonance imaging (MRI) in IIH patients and healthy controls, we identified that dural venous stenoses in IIH were associated with impaired lymphatic drainage, perivenous fluid retention, and brain fluid accumulation. To investigate this further, we developed a mouse model with bilateral jugular vein ligation (JVL), which recapitulated key human findings, including intracranial hypertension, calvarial lymphatic regression, and brain swelling due to impaired clearance. To further dissect the respective roles of dural lymphatics and venous blood flow in brain clearance, we performed JVL in mice with dural lymphatic depletion. These mice exhibited spontaneous elevated intracranial pressure, but JVL did not further exacerbate this effect. Moreover, the synchronous restoration of brain clearance and dural lymphatics observed in mice after JVL was absent in lymphatic-deficient mice.Transcriptomic analyses revealed that lymphatic remodeling induced by JVL was driven by VEGF-C signaling between dural mesenchymal and lymphatic endothelial cells. These findings establish the dural venous sinuses as a critical platform where venous blood flow interacts with mesenchymal cells to preserve dural lymphatic integrity and function, essential for brain fluid clearance.

Caloric restriction: A potential approach for mitigating neuronal damage: Lesson from cellular model of Alzheimer Disease
Alzheimer's disease is a neurodegenerative disorder and characterized by amyloid beta accumulation, synaptic dysfunction, and oxidative stress, lacks effective therapies. Caloric restriction mimetics such as fisetin and chlorogenic acid, natural polyphenols with antioxidant and autophagy-inducing properties, show promise in mitigating age-related diseases. This study investigates their neuroprotective effects against amyloid beta induced toxicity in differentiated human neuroblastoma SHSY5Y cells. Amyloid beta exposure disrupted redox homeostasis, impaired autophagy, induced mitochondrial dysfunction, and exacerbating neuronal degeneration. Fisetin and chlorogenic acid treatments reversed these deleterious effects by restoring redox balance, suppressing reactive oxygen species and upregulating critical antioxidant enzymes like SOD1, GSR, and catalase. These compounds also attenuated amyloid beta induced mitophagy via reduced PINK1 expression and restored mitochondrial fusion by upregulating Mfn2. Autophagy-related pathways were significantly modulated, evidenced by increased AMPK and decreased mTOR mRNA levels, alongside elevated expression of ATG101, ATG13, ULK1, P62 and reduced ATG5 levels. Docking studies also revealed binding of fisetin and CGA within the binding pockets of AMPK and FKBP12 supporting their interaction. Furthermore, fisetin and CGA improved synaptic integrity by upregulating PSD95 and synaptophysin and reducing acetylcholinesterase expression. These findings highlight their potential in ameliorating amyloid beta induced neuronal toxicity through autophagy activation, synaptic preservation, and mitochondrial function enhancement. While this study demonstrates the transcriptional impact and binding affinities of these caloric restriction mimetics further translational and biophysical analyses are required to elucidate their mechanisms and confirm their therapeutic viability. This research underscores the potential of fisetin and CGA as neuroprotective agents, offering promising therapeutic avenues for combating related Alzheimer's disease neuropathies

Diminished functional gradient of the precuneus during altered states of consciousness
The relationship between the default mode network (DMN) and task-positive networks, such as the frontoparietal control network (FPCN), is a prominent feature of functional connectivity (FC) in the human brain. This relationship is primarily anticorrelated at rest in healthy brains and is disrupted in altered states of consciousness. Although the DMN and FPCN seem to perform distinct and even opposing roles, they are anatomically adjacent and exhibit ambiguous boundaries. To test the hypothesis that the DMN-FPCN distinction manifests probabilistically rather than having absolute anatomical boundaries, we examined the differences in FC along the dorsal-ventral (d-v) axis in the posterior precuneus (PCu), which serves a convergence zone between the DMN and FPCN. Our findings indicate that the connectivity differences along this axis are continuous as characterized by linear slopes. Notably, these linear relationships (i.e., functional gradients of the precuneus/FGp) are present only within the territories of the DMN and FPCN, respectively associating with positive and negative slopes. Furthermore, the gradient is functionally relevant, as its spatial configurations change in specific ways in altered states of consciousness (ASC): the magnitude of FGp is similarly impaired across different types of ASC, while the spatial entropy of FGp differs between psychedelic and sedative states. These results suggest that the DMN and FPCN, while appearing distinct, may originate from a single, integrated mechanism.

Behavioral and metabolic effects of extended hippocampal overexpression of the myokine Irisin in an Alzheimers Disease mouse model
Lifestyle interventions such as exercise are promising strategies to reduce the detrimental effects faced by aging populations. In particular, the exercise-induced myokine Irisin could act as a mediator of positive effects of exercise, even as a potential therapeutic option for Alzheimers disease (AD). However, the fundamental roles of Irisin in counteracting AD neuropathology and other effects have not been fully determined. In addition, whether centrally produced Irisin has any effects is unclear. Here we examined the neurobehavioral effects of overexpressing Irisin directly in the hippocampus of an AD transgenic mouse line (TgCRND8), using adult male mice stereotaxically injected with Irisin-AAV vector. To further mimic chronic exercise, spatial memory and exploratory behaviors were assessed using the novel object recognition (NOR)/open field test (OFT) and Y-Maze tests after 8 weeks. Our results showed that Irisin expression led to several behavioral changes, including increased grooming behavior and slightly improved spatial memory performance in short interval NOR test in Tg mice. In the Y-Maze test however, we observed an increase in time spent in familiar spaces, which could indicate heightened anxiety-like behaviors in mice injected with Irisin-AAV. In addition, we observed significant differences in body and liver size, and in circulating metabolites such as ketone bodies, that were differentially regulated in NTg or Tg mice. Overall, our findings show important neurobehavioral effects of long-lasting overexpression of the exerkine Irisin in the hippocampus. Our results also raise questions about potential detrimental effects and thus warrant further studies to fully dissect how this exercise mediator affects the brain.

cfos principal cells and interneurons are strongly reactivated by sharp wave ripples
The hippocampal formation is central for the learning and consolidation of spatial memories. While it is known that the high-frequency oscillations, called sharp wave ripples, play a critical role for memory processes, it is unclear if they interact with the memory engram and spatial engram cells. Here we identify the effect of these oscillations on engram cells as mice explored two environments over several days. We found that both principal cells and interneurons are part of the cfos-tagged engram. cfos-tagged principal cells, place cells and interneurons are highly reactivated by SWRs, whereas none of the negatively SWR-modulated cells are part of the engram. Together, our findings reveal a critical link between cellular and network mechanisms for memory formation and imply that interneurons play a key role in it.

Modulating Motor Cortex Plasticity via Cortical and Peripheral Somatosensory Stimulation
The interaction between the motor and somatosensory systems is essential for effective motor control, with evidence indicating that somatosensory stimulation influences the excitability of the primary motor cortex (M1). However, the mechanisms by which repetitive stimulation of both cortical and peripheral somatosensory systems affects M1 plasticity are not well understood. To investigate this, we examined the effects of continuous theta-burst stimulation (cTBS) applied to the primary somatosensory cortex (S1) and transcutaneous electrical nerve stimulation (TENS) of the median nerve on various measures of corticospinal excitability and M1 intracortical circuits. Specifically, we assessed motor-evoked potentials (MEPs), short-latency intracortical inhibition (SICI), intracortical facilitation (ICF), and short-latency afferent inhibition (SAI) before and after administering cTBS and TENS. Our results demonstrated that cTBS increased MEPs for at least 50 minutes, whereas TENS increased MEPs for 10 minutes. Neither cTBS nor TENS had an impact on SICI and ICF. However, cTBS decreased SAI, while TENS did not affect SAI. The sham procedures for both cTBS and TENS did not produce significant changes in MEPs, SICI, ICF, or SAI. These findings suggest that both cortical and peripheral somatosensory stimulation modulate corticospinal excitability, with the effects of cortical stimulation being more prolonged. Neither type of stimulation influences inhibitory and excitatory intracortical neural circuitry within M1. Notably, cortical somatosensory stimulation modulates the interaction between M1 and S1, whereas peripheral somatosensory stimulation does not. This study elucidates distinct mechanisms through which cortical and peripheral somatosensory stimulation influence M1 plasticity.

Instantaneous Frequency: A New Functional Biomarker for Dynamic Brain Causal Networks
This study introduces instantaneous frequency (IF) analysis as a novel method for characterizing dynamic brain causal networks from fMRI blood-oxygen-level-dependent (BOLD) signals. Effective connectivity, estimated using dynamic causal modeling (DCM), is analyzed to derive IF sequences, with the average IF across brain regions serving as a potential biomarker for global network oscillatory behavior. Analysis of data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Open Access Series of Imaging Studies (OASIS), and Human Connectome Project (HCP) demonstrates the method's efficacy in distinguishing between clinical and demographic groups, such as cognitive decline stages, sex differences, and sleep quality levels. Statistical analyses reveal significant group differences in IF metrics, highlighting its potential as a sensitive indicator for early diagnosis and monitoring of neurodegenerative and cognitive conditions.

Asymmetric Activation of Retinal ON and OFF Pathways by AOSLO Raster-Scanned Visual Stimuli
Adaptive optics scanning light ophthalmoscopy (AOSLO) enables high-resolution retinal imaging, eye tracking, and stimulus delivery in the living eye. AOSLO-mediated visual stimuli are created by temporally modulating the excitation light as it scans across the retina. As a result, each location within the field of view receives a brief flash of light during each scanner cycle (every 33-40 ms). Here we used in vivo calcium imaging with AOSLO to investigate the impact of this intermittent stimulation on the retinal ON and OFF pathways. Raster-scanned backgrounds exaggerated existing ON-OFF pathway asymmetries leading to high baseline activity in ON cells and increased response rectification in OFF cells.

Time-Resolved Neural Oscillations Across Sleep Stages: Associations with Sleep Quality and Aging
Sleep is a fundamental physiological process critical to cognitive function, memory consolidation, emotional regulation, and overall health. This study investigates the relationship between EEG spectral power dynamics and key sleep metrics, including percentage of N3, biological age, percentage of REM, and total sleep time (TST). Using high-resolution spectral analysis, we examine how power across multiple frequency bands (0.1 - 50 Hz) evolves temporally across sleep stages and influences sleep architecture. Our results reveal an inverse relationship between high-frequency power (sigma, beta, and gamma) during the N1 and N2 stages and the subsequent percentage of N3, suggesting that excessive low-frequency power in N2 may disrupt the smooth progression into deep sleep. Additionally, we identify a negative correlation between low delta power (0.1 - 0.5 Hz) during N2 and both percentages of N3 and TST, challenging traditional views on the role of delta activity in sleep regulation. These findings advance the understanding of how brain activity across frequencies modulates sleep depth and duration, with implications for addressing age-related sleep declines.

A2A-positive neurons in the nucleus accumbens core regulate effort exertion
Previous work has implicated the nucleus accumbens (NAc) in the regulation of effort, defined as the amount of work an animal is willing to perform for a given reward, but little is known about the specific contributions of neuronal populations within the NAc to effort regulation. In this study, we examined the contributions of direct pathway and indirect pathway neurons in the NAc core using an operant effort regulation task, in which the effort requirement is the number of lever presses needed for earning a food reward. Using optogenetics, we manipulated the activity of direct pathway spiny projection neurons (dSPNs, D1+) and indirect pathway SPNs (iSPNs, A2A+). Activating dSPNs reduced lever pressing regardless of the effort requirement, as it elicited gnawing, a competing consummatory behavior. On the other hand, activating iSPNs in the NAc core (but not in the shell) reduced lever pressing in an effort- dependent manner: stimulation inducted reduction in performance was greater at higher ratio requirements. In contrast, optogenetically inhibiting NAc core iSPN output resulted in increased effort exertion. Our results show that the indirect pathway output from the NAc core can bidirectionally regulate effort exertion.

Neuroimmune mechanisms of a mouse model of chronic back pain
Chronic back pain (CBP) is the leading cause of disability affecting 1 in 10 people worldwide. Symptoms are marked by persistent lower back pain, reduced mobility, and heightened cold sensitivity. Here, we utilize a mouse model of CBP induced by injecting urokinase-type plasminogen activator (uPA), a proinflammatory agent in the fibrinolytic pathway, between the L2/L3 lumbar vertebrae. We identified neuroimmune interactions contributing to uPA-induced CBP (henceforth, uPA-CBP) in mouse dorsal root ganglia (DRG), where nociceptive neurons reside. Flow cytometric data reveal that uPA-CBP increases CD45+CD11b+ cells in the DRG, a population characteristically implicated in other chronic pain models. Blocking colony stimulating factor 1 receptor (CSF1R) signaling using PLX5622 partially reduced pain, suggesting CD45+CD11b+ macrophage involvement. Whole-cell patch-clamp electrophysiology data indicated DRG neuron hyperexcitability in CBP mice compared to controls. RNA sequencing revealed upregulation of pain- and inflammation-related genes involved in leukocyte migration. Together, these findings underscore the importance of the DRG neuroimmune axis in mediating chronic back pain.

Natural speech re-synthesis from direct cortical recordings using a pre-trained encoder-decoder framework
Reconstructing perceived speech stimuli from neural recordings is not only advancing the understanding of the neural coding underlying speech processing but also an important building block for brain-computer interfaces and neuroprosthetics. However, previous attempts to directly re-synthesize speech from neural decoding suffer from low re-synthesis quality. With the limited neural data and complex speech representation space, it is hard to build decoding model that directly map neural signal into high-fidelity speech. In this work, we proposed a pre-trained encoder-decoder framework to address these problems. We recorded high-density electrocorticography (ECoG) signals when participants listening to natural speech. We built a pre-trained speech re-synthesizing network that consists of a context-dependent speech encoding network and a generative adversarial network (GAN) for high-fidelity speech synthesis. This model was pre-trained on a large naturalistic speech corpus and can extract critical features for speech re-synthesize. We then built a light-weight neural decoding network that mapped the ECoG signal into the latent space of the pre-trained network, and used the GAN decoder to synthesize natural speech. Using only 20 minutes of intracranial neural data, our neural-driven speech re-synthesis model demonstrated promising performance, with phoneme error rate (PER) at 28.6%, and human listeners were able to recognize 71.6% of the words in the re-synthesized speech. This work demonstrates the feasibility of using pre-trained self-supervised model and feature alignment to build efficient neural-to-speech decoding model.

Estimates of quantal synaptic parameters in light of more complex vesicle pool models
The subdivision of synaptic vesicles (SVs) into discrete pools is a leading concept of synaptic physiology. To better explain specific properties of transmission and plasticity, it has been suggested initially that the readily releasable pool (RRP) of SVs is subdivided into two parallel pools differing in their release probability. More recently, evidence was provided that sequential pools with a single RRP and a series-connected finite-size replacement pool (RP) inserted between the reserve pool (RSP) and RRP equally well or even better account for most aspects of transmission and plasticity. It was further suggest that a fraction of the presynaptic release sites (N) are initially unoccupied by SVs, with vesicle recruitment occurring rapidly during activity, and furthermore that the number of release sites itself changes with rapid dynamics during activity. Here we propose a framework that identifies specific signs of the presence of the series-connected RP, using a combination of two experimental electrophysiological standard methods, cumulative analysis (CumAna) and multiple probability fluctuation analysis (MPFA). In particular we show that if the y-intercept (y(0)) of CumAna is larger than N reported by MPFA (y(0) > NMPFA) this is a strong indication for a series-connected RP. This is due to the fact that y(0) reports the sum of RRP and RP. Our analysis further suggests that this result is not affected by unoccupied release sites, as such empty sites contribute to both estimates, y(0) and NMPFA. We discuss experimental findings and models in the recent literature in the light of our theoretical considerations.

Synchronous 3D patterning of diverse CNS progenitors generates motor neurons of broad axial identity
In vitro human organoid models have become transformative tools for studying organogenesis, enabling the generation of spinal cord organoids (SCOs) that mimic aspects of spinal cord biology. However current models do not produce spinal motor neurons (spMNs) with a wide range of axial identities along spinal cord segments within a single structure, limiting their utility in understanding human neural axial specification and the selective vulnerability of spMN subpopulations in motor neuron diseases. Here we present a novel approach to enhance spMN axial heterogeneity in an advanced SCO model derived from neural stem cells (NSCs) and retinoic acid (RA)-primed neuromesodermal progenitors (NMPs). RA priming guided NMP differentiation into caudal neural progenitors, generating SCOs enriched in spMNs with posterior axial identities. To further diversify spMN populations, we optimized differentiation by synchronously patterning NSCs with RA-primed NMPs. Incorporating an endothelial-like network and skeletal muscle cells enhanced the organoid physiological complexity and neural maturation and organoid cell viability. This comprehensive approach, termed CASCO, provides a robust platform to study human spMN specification and model neurodegenerative diseases.

Dissociating Contributions of Theta and Alpha Oscillations from Aperiodic Neural Activity in Human Visual Working Memory
While visual working memory (WM) is strongly associated with reductions in occipitoparietal 8-12 Hz alpha power, the role of 4-7 Hz frontal midline theta power is less clear, with both increases and decreases widely reported. Here, we test the hypothesis that this theta paradox can be explained by non-oscillatory, aperiodic neural activity dynamics. Because traditional time-frequency analyses of electroencephalopgraphy (EEG) data conflate oscillations and aperiodic activity, event-related changes in aperiodic activity can manifest as task-related changes in apparent oscillations, even when none are present. Reanalyzing EEG data from two visual WM experiments (n = 74), and leveraging spectral parameterization, we found systematic changes in aperiodic activity with WM load, and we replicated classic alpha, but not theta, oscillatory effects after controlling for aperiodic changes. Aperiodic activity decreased during WM retention, and further flattened over the occipitoparietal cortex with an increase in WM load. After controlling for these dynamics, aperiodic-adjusted alpha power decreased with increasing WM load. In contrast, aperiodic-adjusted theta power increased during WM retention, but because aperiodic activity reduces more, it falsely appears as though theta oscillatory power (e.g., bandpower) is reduced. Furthermore, only a minority of participants (31/74) had a detectable degree of theta oscillations. These results offer a potential resolution to the theta paradox where studies show contrasting power changes. We identify novel aperiodic dynamics during human visual WM that mask the potential role that neural oscillations play in cognition and behavior.

Evidence for systematic - yet task- and motor-contingent - rhythmicity of auditory perceptual judgements
Numerous studies advocate for a rhythmic mode of perception; however, the evidence in the context of auditory perception remains inconsistent. We propose that the divergent conclusions drawn from previous work stem from conceptual and methodological issues. These include ambiguous assumptions regarding the origin of perceptual rhythmicity, variations in listening tasks and attentional demands, differing analytical approaches, and the reliance on fixed participant samples for statistical testing. To systematically address these points, we conducted a series of experiments in which human participants performed auditory tasks involving monaural target sounds presented against binaural white noise backgrounds, while also recording eye movements. These experiments varied in whether stimuli were presented randomly or required motor initialization by the participant, the necessity of memory across trials and the manipulation of attentional demands across modalities. Our findings challenge the notion of universal rhythmicity in hearing, but support the existence of paradigm- and ear-specific fluctuations in perceptual sensitivity and response bias that emerge at multiple frequencies. Notably, the rhythmicity for sounds in the left and right ears appears to be largely independent among participants, and the strength of rhythmicity in behavioural data is linked to oculomotor activity and attentional requirements of the task. Overall, these results resolve conflicting conclusions drawn in previous work and provide specific avenues for further studies into the rhythmicity of auditory perception.

Continuous Prediction of Mice Lever-Pressing Kinematic Parameters by Background Removed Single-photon Calcium Images
Calcium imaging has gained extensive application in neural decoding tasks because of its high precision in observing cortical neural activity. Nevertheless, the immense data volume and complexity of automated signal extraction algorithms in calcium imaging result in significant delays in extracting neuronal calcium fluorescence signals, greatly constraining the efficiency of neural decoding research and its applicability in real-time tasks. Although a few studies have successfully used partial neuronal signals from calcium imaging data for real-time neural decoding and brain-computer interface tasks, they fail to leverage the complete neuronal dataset from experiments, which limits their ability to decode continuous and complex movements. In response to this challenge, we introduce a neural decoding method based on background-removed single-photon calcium images. This approach extracts three-dimensional spatiotemporal representations of neuronal activity via background removal and employs a decoder combining 3D-ResNet and RNN networks to enable continuous and rapid decoding of mouse lever-pressing kinematic parameters. Compared with traditional methods for neural decoding using single-photon calcium imaging, this approach offers higher accuracy and faster speed. Combined with real-time motion correction algorithms, the proposed neural decoding approach meets real-time decoding requirements at a 20Hz acquisition frame rate, achieving single decoding in just 21.8ms. This advancement significantly improves the efficiency of single-photon calcium imaging-based neural decoding, offering solutions for its application in real-time tasks, such as optical brain-computer interfaces.

MIND-Map; A Comprehensive Toolbox for Estimating Brain Dynamic States
Studying dynamic brain states has offered new insights into understanding functional connectivity. One of the promising approaches for estimating these brain states is the hidden semi-Markov model (HSMM). However, despite its potential, its adoption in the neuroscience community has been limited due to its complexity. We developed the Markov Inference Dynamic Mapping (MIND-Map) toolbox to overcome this limitation. This interactive user-friendly toolbox leverages HSMM to identify brain states, analyze their dynamics, and perform two-sample statistical comparisons of network dynamics. Furthermore, it introduces a new approach, not yet used in conjunction with these models, for determining the optimal number of states, addressing a key challenge in the field. We assessed the performance of the HSMM and our method for identifying the optimal number of states using two datasets, including a unique dataset explicitly developed for this purpose.

Non-Caloric Sweeteners combined with glucose affect hypothalamic glucose sensing-induced insulin secretion, food re-intake through neuronal cellular metabolism: An in vivo and in vitro approaches
Changes in brain activity associated with deleterious metabolic effects of non-caloric sweeteners (NCS) have been demonstrated in humans, particularly when their intake is concomitant with that of glucose. Here, we have focused on hypothalamic glucose sensing in rats, detecting increases in circulating glucose levels and in turn triggering various physiological controls. The identification of sweet-taste receptors in the hypothalamus has suggested that they participate in glucosensing mechanism, but the existence of a dialogue between different pathways has never been studied. Here, we tested the acute effects of hypothalamic glucosensing combined with a NCS (sucralose or acesulfame potassium (aceK)), the latter binding only to sweet-taste receptors, without producing energy. Our working hypothesis was that the concomitance of two contradictory signals (energetic, sweet glucose vs. non-energetic, sweet NCS) could be responsible for deleterious physiological effects. After validation that sweet taste receptors and their signaling expressions were indeed present in the rat hypothalamus, insulin secretion induced by hypothalamic glucosensing (increased glucose level) in the presence of sucralose and aceK was examined. Insulin release was reduced compared to glucose alone, while the two NCS alone have no effect. Regarding the satiety-inducing effect of glucose, concomitant injection of each NCS with glucose produced the opposite effect to that observed with glucose alone, with food intake being increased, an effect also present with NCS injected alone. Using the GT1-7 hypothalamic cell line expressing sweet-taste receptors, we showed that the ATP concentration which normally increases with rising glucose levels was dose-dependently decreased in the presence of NCS, an effect which is inhibited in the presence of gurmarin, a specific inhibitor of sweet-taste receptors. The increase in ROS production in response to rising glucose levels was enhanced in the presence of NCS, an effect that was blocked in the presence of gurmarin. In both cases, NCS have an inhibitory effect on stimulated mitochondrial respiration. Taken together, these results suggest that NCS via sweet-taste receptors interfere with mitochondrial signaling and/or energy production during hypothalamic glucose sensing.

What makes human cortical pyramidal neurons functionally complex
Humans exhibit unique cognitive abilities within the animal kingdom, but the neural mechanisms driving these advanced capabilities remain poorly understood. Human cortical neurons differ from those of other species, such as rodents, in both their morphological and physiological characteristics. Could the distinct properties of human cortical neurons help explain the superior cognitive capabilities of humans? Understanding this relationship requires a metric to quantify how neuronal properties contribute to the functional complexity of single neurons, yet no such standardized measure currently exists. Here, we propose the Functional Complexity Index (FCI), a generalized, deep learning-based framework to assess the input-output complexity of neurons. By comparing the FCI of cortical pyramidal neurons from different layers in rats and humans, we identified key morpho-electrical factors that underlie functional complexity. Human cortical pyramidal neurons were found to be significantly more functionally complex than their rat counterparts, primarily due to differences in dendritic membrane area and branching pattern, as well as density and nonlinearity of NMDA-mediated synaptic receptors. These findings reveal the structural-biophysical basis for the enhanced functional properties of human neurons.

The resource elasticity of control
The ability to determine how much the environment can be controlled through our actions has long been viewed as fundamental to adaptive behavior. While traditional accounts treat controllability as a fixed property of the environment, in the real-world this property often depends on the effort, time, and money that we are willing and able to invest. In such cases, controllability can be said to be elastic to invested resources. Here we propose that inferring this elasticity is essential for efficient resource allocation, and thus, elasticity misestimations result in maladaptive behavior. To test these hypotheses, we developed a novel treasure hunt game where participants encountered environments with varying degrees of controllability and elasticity. Across two pre-registered studies (N=514), we first demonstrate that people infer elasticity and adapt their resource allocation accordingly. We then present a computational model that explains how people make this inference, and identify individual elasticity biases that lead to suboptimal resource allocation. Finally, we show that overestimation of elasticity is associated with elevated psychopathology involving an impaired sense of control. These findings establish the elasticity of control as a distinct cognitive construct guiding adaptive behavior, and a computational marker for control-related maladaptive behavior.

Brain maps of general cognitive function and spatial correlations with neurobiological cortical profiles
In this paper, we attempt to answer two questions: 1) which regions of the human brain, in terms of morphometry, are most strongly related to individual differences in domain-general cognitive functioning (g)? and 2) what are the underlying neurobiological properties of those regions? We meta-analyse vertex-wise g-cortical morphometry (volume, surface area, thickness, curvature and sulcal depth) associations using data from 3 cohorts: the UK Biobank (UKB), Generation Scotland (GenScot), and the Lothian Birth Cohort 1936 (LBC1936), with the meta-analytic N = 38,379 (age range = 44 to 84 years old). These g-morphometry associations vary in magnitude and direction across the cortex (|{beta}| range = -0.12 to 0.17 across morphometry measures) and show good cross-cohort agreement (mean spatial correlation r = 0.57, SD = 0.18). Then, to address (2), we bring together existing - and derive new - cortical maps of 33 neurobiological characteristics from multiple modalities (including neurotransmitter receptor densities, gene expression, functional connectivity, metabolism, and cytoarchitectural similarity). We discover that these 33 profiles spatially covary along four major dimensions of cortical organisation (accounting for 65.9% of the variance) and denote aspects of neurobiological scaffolding that underpin the spatial patterning of MRI-cognitive associations we observe (significant |r| range = 0.21 to 0.56). Alongside the cortical maps from these analyses, which we make openly accessible, we provide a compendium of cortex-wide and within-region spatial correlations among general and specific facets of brain cortical organisation and higher order cognitive functioning, which we hope will serve as a framework for analysing other aspects of behaviour-brain MRI associations.

Physiological activity within peripheral nerves influences neural output in response to electrical stimulation: an in vivo study
Neuromodulation therapies are often applied to peripheral nerves. These nerves can have physiological activity that interacts with the activity evoked by electrical stimulation, potentially influencing targeted neural output and clinical outcomes. Our goal was to quantify changes in sensory neural unit activity in response to variations in electrical stimulation frequency and amplitude. In a feline model, we applied cutaneous brushing to evoke pudendal nerve afferent activity with and without electrical stimulation via a pudendal nerve cuff electrode. We recorded neural output with microelectrode arrays implanted in ipsilateral sacral dorsal root ganglia (DRG). Combined inter-spike interval distributions for all DRG units showed ranges of flattening, increases, and shifts in response to electrical stimulation. These distributions and changes within them due to electrical stimulation were largely driven by a select few units. Mixed-effects models revealed that quicker firing units generally decreased in firing rate in response to electrical stimulation and, conversely, slower firing units increased in firing rate. A unit's underlying firing rate also drove the magnitude of change in mean output firing rate in response to stimulation. Further, the models reported a small, negative correlation between the output mean unit firing rate and the applied electrical stimulation frequency. These results demonstrate the potential impact of electrical stimulation on underlying neural firing activity and output. Peripheral neuromodulation may normalize abnormal firing patterns in nerves contributing to pathological disorders or alter unrelated physiological activity in off-target neurons. These factors should be considered when selecting neuromodulation settings in animal subjects and human patients.

Centralized brain networks underlie body part coordination during grooming
Animals must coordinate multiple body parts to perform important tasks such as grooming, or locomotion. How this movement synchronization is achieved by the nervous system remains largely unknown. Here, we uncover the neural basis of body part coordination during goal-directed antennal grooming in the fly, Drosophila melanogaster. We find that unilateral or bilateral grooming of one or both antenna, respectively, arises from synchronized movements of the head, antennae, and forelegs. Simulated replay of these body part kinematics in a biomechanical model shows that this coordination makes grooming more efficient by permitting unobstructed, forceful collisions between the foreleg tibiae and antennae. Movements of one body part do not require proprioceptive sensory feedback from the others: neither amputation of the forelegs or antennae, nor immobilization of the head prevented movements of the other unperturbed body parts. By constructing a comprehensive antennal grooming network from the fly brain connectome, we find that centralized interneurons and shared premotor neurons interconnect and thus likely synchronize neck, antennal, and foreleg motor networks. A simulated activation screen of neurons in this network reveals cell classes required for the coordination of antennal movements during unilateral grooming. These cells form two coupled circuit motifs that enable robust body part synchronization: a recurrent excitatory subnetwork that promotes contralateral antennal pitch and broadcast inhibition that suppresses ipsilateral antennal pitch. Similarly centralized controllers may enable the flexible co-recruitment of multiple body parts to subserve a variety of behaviors.

Integrating multi-system environmental factors to predict brain and behavior in adolescents
ObjectiveEnvironmental factors have long been shown to influence brain structure and adolescent psychopathology. However, almost no research has included environmental factors spanning micro-to-macro-systems, brain structure, and psychopathology in an integrated framework. Here, we assessed the ways and degree to which multi-system environmental factors during late childhood predict subcortical volume and psychopathology during early adolescence.

MethodWe used the baseline and 2-year follow-up data from the Adolescent Brain Cognitive DevelopmentSM Study (N = 2,766). A Bayesian latent profile analysis was applied to obtain distinct multi-system environmental profiles during late childhood. The profiles were used in a path analysis to predict their direct and indirect effects on subcortical volume and psychopathology during early adolescence.

ResultsBayesian latent profile analysis revealed nine environmental profiles. Two distinct profiles predicted greater externalizing problems in adolescents: (i) adversity across, family, school, and neighborhood systems and (ii) family conflict and low school involvement. In contrast, a profile of family and neighborhood affluence predicted fewer externalizing difficulties. Further, family and neighborhood affluence predicted higher subcortical volume, which in turn, predicted fewer externalizing problems; whereas, family economic and neighborhood adversity predicted lower subcortical volume, which in turn, predicted greater externalizing difficulties.

ConclusionWe captured direct and indirect influences of environmental factors across multiple systems on externalizing psychopathology. Specifying the equifinal pathways to externalizing psychopathology serves to provide an evidence base for establishing different types of interventions based on the needs and risk profiles of youth.

Diversity and Inclusion StatementThe current study is part of the ongoing Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study(R)) for which youth are recruited from elementary schools in the United States that are informed by gender, race, ethnicity, socioeconomic status, and urbanicity. The ABCD Study(R) aims to recruit youth longitudinally by sampling the sociodemographic makeup of the US population. Two of the authors self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One of the authors identifies as a part of an underrepresented gender group in science. The authors also are representative of the communities for which data was collected and contributed to design, analysis, and/or interpretation of the work. Finally, every effort was made to cite the work of authors from underrepresented and minoritized groups in academic research.

Imaging the dancing brain: Decoding sensory, motor and social processes during dyadic dance
Real-world social cognition requires processing and adapting to multiple dynamic information streams. Interpreting neural activity in such ecological conditions remains a key challenge for neuroscience. This study leverages advancements in de-noising techniques and multivariate modeling to extract interpretable EEG signals from pairs of participants engaged in spontaneous dyadic dance. Using multivariate temporal response functions (mTRFs), we investigated how music acoustics, self-generated kinematics, other-generated kinematics, and social coordination each uniquely contributed to EEG activity. Electromyogram recordings from ocular, face, and neck muscles were also modelled to control for muscle artifacts. The mTRFs effectively disentangled neural signals associated with four key processes: (I) auditory tracking of music, (II) control of self-generated movements, (III) visual monitoring of partner movements, and (IV) visual tracking of social coordination accuracy. We show that the first three neural signals are driven by event-related potentials: the P50-N100-P200 triggered by acoustic events, the central lateralized readiness potential triggered by movement initiation, and the occipital N170 triggered by movement observation. Notably, the (previously unknown) neural marker of social coordination encodes the spatiotemporal alignment between dancers, surpassing the encoding of self- or partner-related kinematics taken alone. This marker emerges when partners make visual contact, relies on visual cortical areas, and is specifically driven by movement observation rather than initiation. Using data-driven kinematic decomposition, we further show that vertical movements best drive observers' EEG activity. These findings highlight the potential of real-world neuroimaging, combined with multivariate modelling, to uncover the mechanisms underlying complex yet natural social behaviors.

Visual and vestibular processing of vertical motion: a psychophysical study
The motion of objects and ourselves along the vertical is affected by gravitational acceleration. However, the visual system is poorly sensitive to accelerations, and the vestibular otoliths do not disassociate gravitational and inertial accelerations of ego-motion. Here, we tested the hypothesis that the brain resolves visual and vestibular ambiguities about vertical motion with internal models of gravity, which predict that downward motions are accelerated and upward motions are decelerated by gravity. In visual sessions, a target moved up or down while participants remained stationary. In vestibular sessions, participants were moved up or down, while they fixated an imaginary target moving along. In visual-vestibular sessions, participants were moved up or down while the visual target remained fixed. We found that downward motions of either the visual target or the participant were systematically perceived as lasting less than upward motions of the same duration, and vice-versa for the opposite direction of motion, consistent with the prior assumption that downward motion is accelerated and upward motion is decelerated by gravity. In visual-vestibular sessions, there was no significant difference in the average estimates of duration of downward and upward motion of the participant. However, there was large inter-subject variability of these estimates.

A low-cost FPGA-based approach for pile-up corrected high-speed in vivo FLIM imaging
Intensity-based two-photon microscopy (2PM) is a cornerstone of biomedical research but lacks the ability to measure concentrations, a pivotal task for longitudinal studies and quantitative comparisons. Fluorescence Lifetime Imaging (FLIM) based on Time-Correlated Single Photon Counting (TCSPC) can overcome those limits but suffers from "pile-up" distortions at high photon count rates, severely limiting acquisition speed. We introduce the "laser period blind time" (LPBT) method to correct pile-up distortions in photon counting electronics, enabling reliable low-cost TCSPC-FLIM at high count rates. The correction was implemented on low-cost hardware based on a field programable gate array (FPGA) and validated using a combination of in silico simulations and in vitro, ex vivo and in vivo measurements. The LBPT approach achieves <3% error in lifetime measurements at count rates more than ten times higher than traditional limits, allowing robust FLIM imaging of sub-second metabolite dynamics with subcellular resolution. Our work enables high-precision, cost-effective FLIM imaging at rates comparable to commercial systems and at a fraction of the cost, facilitating the adoption of FLIM across all areas of research needing affordable, quantitative live imaging solutions.

Psilocybin causes sex, time, and dose dependent alterations in brain signaling pathways
Psilocybin is a psychedelic tryptamine that has emerged as a potential candidate for the treatment of a variety of conditions, including treatment resistant depression and post-traumatic stress disorder. Clinical trials which have assessed the efficacy of psilocybin for these conditions report a rapid and sustained improvement in patient- and clinician-rated depression scores. The established mechanism of action for psychedelics such as psilocybin is agonism of the serotonin 2A receptor (5HT2AR), however, the downstream molecular processes mediating their therapeutic effects remain unknown. As high doses of psychedelics are known to induce strong perceptual alterations, an additional outstanding question is whether subperceptual doses induce similar molecular effects as psychoactive dosages. Here, we report the first analysis of dose- and sex-dependent transcriptional changes in forebrains of female and male mice at 3 timepoints (8 hours, 24 hours, and 7 days) following a single administration of psilocybin at low (0.25 mg/kg) or high (1 mg/kg) doses. Grouped analysis of both sexes reveals dose- and time-dependent transcriptomic alterations. We report more rapid transcriptional changes and attenuation of such changes in females following a single low-dose relative to males treated identically. Females also responded more robustly to high-dose administration relative to males at 8 and 24 hours, with signal attenuation in both sexes by 7 days. A notable observation was the persistent transcriptional effect of low-dose psilocybin at 7 days, which outlasted high-dose changes, and which suggests that low doses may have prolonged biological effects. A myriad of pathways were altered depending on sex and timepoint, but common features included functions related to neuronal differentiation, neurogenesis, and changes in receptor signaling. These data reveal dose- and sex-dependent molecular effects of psilocybin and support previous studies demonstrating its effect on dendritogenesis. Given ongoing clinical interest in psilocybin for treating mental health disorders, our results suggest that these sexually divergent changes should be considered when weighing treatment strategies. Additional consideration should be given to temporal effects of low vs high dosages on gene transcription, especially when timing psilocybin with adjuvant cognitive behavioral therapy.

Periaqueductal gray passes over disappointment and signals continuity of remaining reward expectancy
Disappointment is a vital factor in the learning and adjustment of strategies in reward-seeking behaviors. It helps them conserve energy in environments where rewards are scarce, while also increasing their chances of maximizing rewards by prompting them to escape to environments where richer rewards are anticipated (e.g., migration). However, another key factor in obtaining the reward is the ability to monitor the remaining possibilities of obtaining the outcome and to tolerate the disappointment in order to continue with subsequent actions. The periaqueductal gray (PAG) has been reported as one of the key brain regions in regulating negative emotions and escape behaviors in animals. The present study suggests that the PAG could also play a critical role in inhibiting escape behaviors and facilitating ongoing motivated behaviors to overcome disappointing events. We found that PAG activity is tonically suppressed by reward expectancy as animals engage in a task to acquire a reward outcome. This tonic suppression of PAG activity was sustained during a series of sequential task procedures as long as the expectancy of reward outcomes persisted. Notably, the tonic suppression of PAG activity showed a significant correlation with the persistence of animals reward-seeking behavior while overcoming intermittent disappointing events. This finding highlights that the balance between distinct tonic signaling in the PAG, which signals remaining reward expectancy, and phasic signaling in the LHb, which signals disappointment, could play a crucial role in determining whether animals continue or discontinue reward-seeking behaviors when they encounter an unexpected negative event. This mechanism would be essential for animals to efficiently navigate complex environments with various reward volatilities and ultimately contributes to maximizing their reward acquisition.

Reduced enteric BDNF-TrkB signaling drives glucocorticoid-mediated GI dysmotility
Stress affects gastrointestinal (GI) function causing dysmotility, especially in disorders of gut-brain interactions (DGBI) patients. GI motility is regulated by the enteric nervous system (ENS), suggesting that stress alters ENS biology to cause dysmotility. While stress increases glucocorticoid levels through the hypothalamus-pituitary-adrenal axis, how glucocorticoids affect GI motility is not known. Glucocorticoid signaling reduces expression of specific transcriptional isoforms of brain-derived neurotrophic factor (BDNF) in the central nervous system, altering signaling through its receptor Tropomyosin-related kinase B (TrkB) to cause behavioral defects. However, since the nature of ENS-specific Bdnf isoforms and their response to glucocorticoids remains unknown, we are limited in studying how stress impacts the ENS to cause dysmotility. Here, in male and female mice, we establish that stress-responsive Bdnf isoforms that are transcriptionally regulated at exons 4 and 6 represent >85% of all Bdnf isoforms in the post-natal ENS, and that Bdnf and Ntrk2 (TrkB) are expressed by enteric neurons. We further show using male mice dosed with a synthetic glucocorticoid receptor (GR) agonist dexamethasone (Dexa), that increased glucocorticoid signaling in ENS significantly reduces the expression of Bdnf transcripts and protein and that it significantly reduces GI motility. Finally, by using HIOC, a specific synthetic agonist of TrkB, we observe that HIOC treatment significantly improved GI motility of a cohort of Dexa-treated male mice, when compared to Dexa-treated and HIOC-untreated mice. Our results implicate BDNF- TrkB signaling in the etiology of stress-associated dysmotility and suggest that TrkB is a putative therapeutic target for dysmotility in DGBI patients.

Significance statementThe mechanism through which stress-associated increase in glucocorticoid signaling causes gastrointestinal (GI) dysmotility is not well understood. GI motility is regulated by the enteric nervous system, which depends on optimal signaling between brain-derived neurotrophic factor (BDNF) and its receptor tropomyosin related kinase B (TrkB). The lack of clarity on whether glucocorticoid impact BDNF signaling in the ENS, analogous to the manner they affect BDNF in brain, has limited our understanding of stress-associated dysmotility. Here, by identifying the nature of Bdnf isoforms expressed in ENS, studying their response to increased glucocorticoid signaling, and testing the effect of TrkB agonist to promote healthy gut motility in a model of glucocorticoid-driven dysmotility, we implicate altered BDNF-TrkB signaling as the mechanism driving stress-associated dysmotility.

Optogenetic inhibition quenches the integration of sensory input in the cortex
Significance: Many fundamental processes of brain computation, such as sensory perception and motor control, heavily rely on the mesoscopic dynamics of activity across the cerebral cortex. Manipulating mesoscale activity and observing its effects across multiple brain regions is crucial for understanding the causal link between cortical dynamics and behavior. Objective: The goal of this study was to develop a novel all-optical system that allows inhibition of excitatory neurons while simultaneously monitoring cortical responses at arbitrary sites across the entire dorsal cortex of mice. Methods: We combined wide-field imaging and optogenetics to create a mesoscale all-optical approach, enabling simultaneous monitoring and manipulation of cortical activity using light. Intravenous injection of two PHP.eB AAVs enabled the whole-brain co-expression of the red-shifted calcium indicator jRCaMP1b and the inhibitory actuator stGtACR2, with stable expression over several weeks. This system was calibrated, and the effects of inhibition on sensory responses were tested. Results: Increasing laser power progressively reduced spontaneous activity at the site of irradiation. A single 5-second pulse on the barrel field cortex significantly decreased the amplitude of sensory-evoked responses, not only in the stimulated region but across the entire stimulated hemisphere. Conclusions: This novel all-optical system enables targeted inhibition while concurrently monitoring mesoscale cortical activity. It provides insights into the dynamics of cortical circuits and offers a milestone for investigating the causal links between neuronal activity and behavior. Future research can use this tool to address sensory responsiveness impairments in neurological and neuropsychiatric disorders.

Mutation in Wdr45 leads to early motor dysfunction and widespread aberrant axon terminals in a beta-propeller protein associated neurodegeneration (BPAN) patient-inspired mouse model
Beta-propeller Protein Associated Neurodegeneration (BPAN) is a devastating neurodevelopmental and neurodegenerative disease linked to variants in WDR45. Currently, there is no cure or disease altering treatment for this disease. This is, in part, due to a lack of insight into early phenotypes of BPAN progression and WDR45s role in establishing and maintaining neurological function. Here we generated and characterized a mouse model bearing a c52C>T BPAN patient variant in Wdr45. We show this mutation ablates WDR45 protein expression and alters autophagy in the brain. Behavioral analysis of these mice revealed characteristic signs of BPAN including cognitive impairment, hyperactivity, and motor decline. We show these behaviors coincide with widespread neuroinflammation and development of axonal spheroids in multiple neuron subclasses throughout the brain. Several lines of evidence suggest these spheroids arise from axon terminals. Transcriptomic analysis uncovered multiple disrupted pathways in the cortex including genes associated with synapses, neurites, endosomes, endoplasmic reticulum, and ferroptosis. This is supported by accumulation of the iron regulating transferrin receptor 1 (TFRC) and the endoplasmic reticulum resident calreticulin (CALR) in the cortex as these animals age. CALR forms spheroid structures similar to the axonal spheroids seen in these animals. Taken together, our data demonstrate that WDR45 is necessary for healthy brain function and maintenance of axon terminals. This model opens the door to therapeutics targeting BPAN and further exploration of the role of WDR45 in neuronal function.

Mechanisms of Alpha-Synuclein Seeded Aggregation in Neurons Revealed by Fluorescence Lifetime Imaging
1The brains of Parkinsons disease (PD) patients are characterized by the presence of Lewy body inclusions enriched with fibrillar forms of the presynaptic protein alpha-synuclein (aSyn). Despite related evidence that Lewy pathology spreads across different brain regions as the disease progresses, the underlying mechanism hence the fundamental cause of PD progression is unknown. The propagation of aSyn pathology is thought to potentially occur through the release of aSyn aggregates from diseased neurons, their uptake by neighboring healthy neurons via endocytosis, and subsequent seeding of native aSyn aggregation in the cytosol. A critical aspect of this process is believed to involve the escape of internalized ag-gregates from the endolysosomal compartment, though direct evidence of this mechanism in cultured neuron models remains lacking. In this study, we utilize a custom-built, time-gated fluorescence lifetime imaging microscope (FLIM) to investigate the progression of seeded ag-gregation over time in live cortical neurons. By establishing fluorescence lifetime sensitivity to aSyn aggregation level, we are able to monitor the proteins aggregation state. Through a FLIM analysis of neurons expressing aSyn-mVenus and exposed to aSyn preformed fibrils labeled with the acid-responsive dye pHrodo, we reveal the proteins aggregation state in both the cytosol and the endolysosomal compartment. The results indicate that aSyn seeds undergo partial disassembly prior to escaping the endocytic pathway, and that this escape is closely linked to the aggregation of cytosolic aSyn. In certain neurons, monomeric aSyn is found to translocate from the cytosol into the endolysosomal compartment, where it appar-ently forms aggregates in proximity to retained seeds. Additional analyses reveals zones of neuritic aSyn aggregates that overlaps with regions of microtubule disruption. Collectively, these findings enhance our understanding of aSyn pathology propagation in PD and other synucleinopathies, motivate additional experiments along these lines, and offer a path to guide the development of disease-modifying therapies.

Dimorphic Neural Network Architecture Prioritizes Sexual-related Behaviors in Male C.elegans
Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on the neural network architectures of male and hermaphrodite C. elegans and the association with sexually dimorphic behaviors. We applied graph theory and computational neuroscience methods to systematically discern the features of these two neural networks. Our findings revealed that a small percentage of sexual-specific neurons exerted dominance throughout the entire male neural net-work, suggesting males prioritized sexual-related behavior outputs. Based on the structural and dynamical characteristics of two complete neural networks, sub-networks containing sex-specific neurons and their immediate neighbors, or sub-networks exclusively comprising sex-shared neurons, we predicted dimorphic behavioral outcomes for males and hermaphrodites. To verify the prediction, we performed behavioral and calcium imaging experiments and dissected a circuit that is specific for the increased spontaneous local search in males for mate-searching. Our research sheds light on the neural circuits that underlie sexually dimorphic behaviors in C. elegans, and provides significant insights into the inter-connected relationship between network architecture and functional outcomes at the whole-brain level.

G protein Inactivation as a Mechanism for Addiction Treatment
The endogenous dynorphin/kappa opioid receptor (KOR) system in the brain mediates the dysphoric effects of stress, and KOR antagonists may have therapeutic potential for the treatment of drug addiction, depression, and psychosis. One class of KOR antagonists, the long-acting norBNI-like antagonists, have been suggested to act by causing KOR inactivation through a cJun-kinase mechanism rather than by competitive inhibition. In this study, we screened for other opioid ligands that might produce norBNI-like KOR inactivation and found that nalfurafine (a G-biased KOR agonist) and nalmefene (a KOR partial agonist) also produce long-lasting KOR inactivation. Neither nalfurafine nor nalmefene are completely selective KOR ligands, but KOR inactivation was observed at doses 10-100 fold lower than necessary for mu opioid receptor actions. Daily microdosing with nalfurafine or nalmefene blocked KORs responsible for antinociceptive effects, blocked KORs mediating stress-induced aversion, and mitigated the aversion during acute and protracted withdrawal in fentanyl-dependent mice. Both nalfurafine and nalmefene have long histories of safety and use in humans and could potentially be repurposed for the treatment of dynorphin-mediated stress disorders.

Differential temporal filtering in the fly optic lobe
Visual interneurons come in many different flavors, representing luminance changes at one location as ON or OFF signals with different dynamics, ranging from purely sustained to sharply transient responses. While the functional relevance of this representation for subsequent computations like direction-selective motion detection is well understood, the mechanisms by which these differences in dynamics arise are unclear. Here, I study this question in the fly optic lobe. Taking advantage of the known connectome I simulate a network of five adjacent optical columns each comprising 65 different cell types. Each neuron is modeled as an electrically compact single compartment, conductance-based element that receives input from other neurons within its column and from its neighboring columns according to the intra- and inter-columnar connectivity matrix. The sign of the input is determined according to the known transmitter type of the presynaptic neuron and the receptor on the postsynaptic side. In addition, some of the neurons are given voltage-dependent conductances known from the fly transcriptome. As free parameters, each neuron has an input and an output gain, applied to all its input and output synapses, respectively. The parameters are adjusted such that the spatio-temporal receptive field properties of 13 out of the 65 simulated neurons match the experimentally determined ones as closely as possible. Despite the fact that all neurons have identical leak conductance and membrane capacitance, this procedure leads to a surprisingly good fit to the data, where specific neurons respond transiently while others respond in a sustained way to luminance changes. This fit critically depends on the presence of an H-current in some of the first-order interneurons, i.e., lamina cells L1 and L2: turning off the H-current eliminates the transient response nature of many neurons leaving only sustained responses in all of the examined interneurons. I conclude that the diverse dynamic response behavior of the columnar neurons in the fly optic lobe starts in the lamina and is created by their different intrinsic membrane properties. I predict that eliminating the hyperpolarization-activated current by RNAi should strongly affect the dynamics of many medulla neurons and, consequently, also higher-order functions depending on them like direction-selectivity in T4 and T5 neurons.

Neural dynamics hierarchy in motor cortex and striatum across naturalistic behaviors
Mammals perform a wide range of movements actuated by diverse patterns of muscle activity. Primary motor cortex (M1) and striatum are implicated in controlling these movements, but how their activity dynamics are organized to accommodate such diversity is poorly understood. We developed a paradigm that enabled us to investigate neural dynamics across diverse motor behaviors in mice. In contrast to existing views, we found neither behavior-specific nor behavior-invariant organization in single-neuron activity, population-level covariation, and muscle activity correlation. Instead, the similarity of activity dynamics between behaviors varied differentially across behavior pairs, forming a hierarchical organization. The same hierarchical organization was shared between M1 and striatum, despite stronger muscle activity correlation in M1 and greater behavior specificity in striatum. Network modeling indicated that striatal activity is sufficient to drive hierarchical dynamics in muscle pattern-generating circuits. These hierarchical dynamics may reflect a tradeoff between behavioral specialization and generalization in motor system function.

Where do I go? Decoding temporal neural dynamics of scene processing and visuospatial memory interactions using CNNs
Visual scene perception enables rapid interpretation of the surrounding environment by integrating multiple visual features related to task demands and context, which is essential for goal-directed behavior. In the present work, we investigated the temporal neural dynamics underlying the interaction between the processing of visual features (i.e., bottom-up processes) and contextual knowledge (i.e., top-down processes) during scene perception. We analyzed EEG data from 30 participants performing scene memory and visuospatial memory tasks in which we manipulated the number of navigational affordances available (i.e., the number of open doors) while controlling for similar low-level visual features across tasks. We used convolutional neural networks (CNN) coupled with gradient-weighted class activation mapping (Grad-CAM) to assess the main channels and time points underlying neural processing for each task. We found that early occipitoparietal activity (50-250 ms post-stimulus) contributed most to the classification of several aspects of visual perception, including scene color, navigational affordances, and spatial memory content. In addition, we showed that the CNN successfully trained to detect affordances during scene perception was unable to detect the same affordances in the spatial memory task after learning, whereas a similarly trained and tested model for detecting wall color was able to generalize across tasks. Taken together, these results reveal an early common window of integration for scene and visuospatial memory information, with a specific and immediate influence of newly acquired spatial knowledge on early neural correlates of scene perception.

Lifespan Normative Modeling of Brain Microstructure
Normative models of brain metrics based on large populations could be extremely valuable for detecting brain abnormalities in patients with a variety of disorders, including degenerative, psychiatric and neurodevelopmental conditions, but no such models exist for the brains white matter (WM) microstructure. Here we present the first large-scale normative model of brain WM microstructure-based on 19 international diffusion MRI datasets covering almost the entire lifespan (totaling N=54,583 individuals; age: 4-91 years). We extracted regional diffusion tensor imaging (DTI) metrics using a standardized analysis and quality control protocol and used hierarchical Bayesian regression (HBR) to model the statistical distribution of derived WM metrics as a function of age and sex. We extracted the average lifespan trajectories and corresponding centile curves for each WM region. We illustrate the utility of the method by applying it to detect and visualize profiles of WM microstructural deviations in a variety of contexts: in mild cognitive impairment, Alzheimers disease, and 22q11.2 deletion syndrome - a neurogenetic condition that markedly increases risk for schizophrenia. The resulting large-scale model provides a common reference to identify disease effects on the brains microstructure in individuals or groups, and to compare disorders, and discover factors affecting WM abnormalities. The derived normative models are a new resource publicly available to the community, adaptable and extendable to future datasets as the available data expands.

Naturalistic language comprehension engages a cascade of widespread brain networks in the one second following comprehension
Language comprehension (LC) is a cornerstone of human cognition, enabling the extraction of meaning from written and spoken communication with remarkable efficiency. Decades of neuroimaging research have identified the brain networks associated with LC, but limitations in spatial and temporal resolution have hindered a comprehensive characterization of the whole-brain (millimeter scale), real-time (millisecond precision) dynamics underlying this process. To overcome these constraints, we applied a fusion of multimodal brain imaging techniques (fMRI and EEG) in healthy adults (n = 30) to map the spatiotemporal progression of neural network engagement during LC in the one second following comprehension. Our findings reveal a cascade of brain network activations, beginning with the occipitotemporal perceptual word processing network (250 ms), followed by the temporoparietal semantic retrieval network (400 ms), the posterior default mode inferential network (500 ms), the frontotemporal semantic integration network (600 ms), and finally, a distributed goal-directed comprehension network (700 ms). Crucially, inferential processing emerged as a "hinge point," linking early word processing to later higher-order networks. Efficient LC was associated with greater mediation by this inferential network and reduced reliance on top-down semantic integration. These findings provide evidence that naturalistic LC relies on rapid, dynamic interactions across widespread brain networks, with individual differences in LC reflecting specific subnetwork interactions. This work offers a framework for investigating the temporal evolution of distributed brain network dynamics in complex cognition across domains and clinical populations.

A three-dimensional histological cell atlas of the developing human brain
The human brain is believed to contain a full complement of neurons by the time of birth together with a substantial amount of the connectivity architecture, even though a significant amount of growth occurs postnatally. The developmental process leading to this outcome is not well understood in humans in comparison with model organisms. Previous magnetic resonance imaging (MRI) studies give three-dimensional coverage but not cellular resolution. In contrast, sparsely sampled histological or spatial omics analyses have provided cellular resolution but not dense whole brain coverage. To address the unmet need to provide a quantitative spatiotemporal map of developing human brain at cellular resolution, we leveraged tape-transfer assisted serial section histology to obtain contiguous histological series and unbiased imaging with dense coverage. Interleaved 20 thick Nissl and H&E series and MRI volumes are co-registered into multimodal reference volumes with 60 isotropic resolution, together with atlas annotations and a stereotactic coordinate system based on skull landmarks. The histological atlas volumes have significantly more contrast and texture than the MRI volumes. We computationally detect cells brain-wide to obtain quantitative characterization of the cytoarchitecture of the developing brain at 13-14 and 20-21 gestational weeks, providing the first comprehensive regional cell counts and characterizing the differential growth of the different brain compartments. Morphological characteristics permit segmentation of cell types from histology. We detected and quantified brain-wide distribution of mitotic figures representing dividing cells, providing an unprecedented spatiotemporal atlas of proliferative dynamics in the developing human brain. Further, we characterized the abundance and distribution of Cajal-Retzius cells, a transient cell population that plays essential roles in organizing glutamatergic cortical neurons into layers. Together, our study provides an unprecedented quantitative window into the developing human brain and the reference volumes and coordinate space should be useful for integrating spatial omics data sets with dense histological context.

Reanalysis of metabolomics data reveals that microbiota transfer therapy modulates important fecal and plasma metabolite profiles in children with autism spectrum disorders
While Autism Spectrum Disorder (ASD) is diagnosed through behavioral symptoms and psychometric evaluations, it has also been associated with distinct metabolomic patterns. A previous clinical trial of Microbiome Transfer Therapy (MTT) in children with ASD and gastrointestinal (GI) issues revealed significant differences in plasma metabolomics between children with ASD and their typically developing (TD) counterparts, which diminished after MTT. The objective of this study was to reanalyze the plasma and fecal samples using updated metabolomics libraries at Metabolon, applying a comprehensive panel of statistical methods. This approach aimed to provide deeper insights into ASD-related metabolic differences and the impact of MTT. The reanalysis identified more statistically significant metabolites and highlighted specific metabolites whose relative intensities differed between the ASD and TD groups, as well as metabolites with significant changes in intensity post-MTT. Several plasma metabolites, including sarcosine, iminodiacetate, caproate, and caprylate, initially showed significant differences between the ASD and TD groups but shifted to resemble TD levels after MTT treatment. In fecal samples, p-cresol sulfate and sphingolipids emerged as metabolites with altered intensities following MTT treatment. Multivariate Fishers Discriminant Analysis (FDA) with leave-one-out cross-validation revealed that a set of metabolites--including p-cresol sulfate, hydroxyproline, and caprylate--could robustly classify the ASD and TD cohorts pre-treatment. However, after treatment, the same FDA model could not distinguish the two groups, as the FDA scores became similar to those of the TD cohort. Our findings enhance the understanding of ASD-associated metabolic changes and highlight the potential of MTT to influence these profiles. This underscores the importance of reanalysis using updated databases and robust statistical methods for comparative analysis. Further studies with larger cohorts and placebo-controlled trials are necessary to validate these results and explore the biochemical pathways involved, paving the way for personalized treatment approaches.

Synaptic facilitation enhances the reliability and precision of high frequency neurotransmission
The small and tortuous volume of synaptic clefts limits the diffusion of Ca2+ ions during high frequency spiking. Extracellular Ca2+ levels ([Ca2+]o) of 0.8 mM or lower have been measured or calculated for different synapses. Here, we recorded evoked postsynaptic potentials (EPSP) and action potentials (AP) from young adult male and female mouse auditory brainstem principal neurons to investigate the relationship between neurotransmission reliability, stimulation frequency and [Ca2+]o. In 0.8 mM [Ca2+]o, we observed AP failures during afferent fiber stimulation at 100 Hz. Surprisingly, AP failures, EPSP-AP latency and jitter were all greatly reduced when stimulation frequency was increased to 500 Hz. Analysis of the EPSP/AP waveform revealed marked facilitation at 500 Hz that was not present at 100 Hz. Raising [Ca2+]o to 1.2 mM or 2.0 mM reduced or eliminated facilitation and, in these conditions, stimulation at 500 Hz increased the number of AP failures. In 0.8 mM [Ca2+]o, afferent fiber stimulation over a broad range of frequencies from 10-1000 Hz produced three different types of spiking responses: Type I cells exhibited band-pass filtering, with best response at approximately 500 Hz, Type II cells exhibited low-pass filtering above 600 Hz, and Type III cells exhibited shallow band-pass filtering centered at approximately 300 Hz. To predict AP success or failure, we built a model based on three factors: size of the EPSP, membrane potential immediately prior to the synaptic event and the number of preceding failures. We conclude that synaptic facilitation can contribute positively to the maintenance of reliable and precise high frequency neurotransmission in the auditory brainstem.