bioRxiv Subject Collection: Neuroscience's Journal

LRRK2 mediates haloperidol-induced changes in indirect pathway striatal projection neurons
Haloperidol is used to manage psychotic symptoms in several neurological disorders through mechanisms that involve antagonism of dopamine D2 receptors that are highly expressed in the striatum. Significant side effects of haloperidol, known as extrapyramidal symptoms, lead to motor deficits similar to those seen in Parkinson's disease and present a major challenge in clinical settings. The underlying molecular mechanisms responsible for these side effects remain poorly understood. Parkinson's disease-associated LRRK2 kinase has an important role in striatal physiology and a known link to dopamine D2 receptor signaling. Here, we systematically explore convergent signaling of haloperidol and LRRK2 through pharmacological or genetic inhibition of LRRK2 kinase, as well as knock-in mouse models expressing pathogenic mutant LRRK2 with increased kinase activity. Behavioral assays show that LRRK2 kinase inhibition ameliorates haloperidol-induced motor changes in mice. A combination of electrophysiological and anatomical approaches reveals that LRRK2 kinase inhibition interferes with haloperidol-induced changes, specifically in striatal neurons of the indirect pathway. Proteomic studies and targeted intracellular pathway analyses demonstrate that haloperidol induces a similar pattern of intracellular signaling as increased LRRK2 kinase activity. Our study suggests that LRRK2 kinase plays a key role in striatal dopamine D2 receptor signaling underlying the undesirable motor side effects of haloperidol. This work opens up new therapeutic avenues for dopamine-related disorders, such as psychosis, also furthering our understanding of Parkinson's disease pathophysiology.

PAM: Predictive attention mechanism for neural decoding of visual perception
Attention mechanisms enhance deep learning models by focusing on the most relevant parts of the input data. We introduce predictive attention mechanisms (PAMs) -- a novel approach that dynamically derives queries during training which is beneficial when predefined queries are unavailable. We applied PAMs to neural decoding, a field challenged by the inherent complexity of neural data that prevents access to queries. Concretely, we designed a PAM to reconstruct perceived images from brain activity via the latent space of a generative adversarial network (GAN). We processed stimulus-evoked brain activity from various visual areas with separate attention heads, transforming it into a latent vector which was then fed to the GAN's generator to reconstruct the visual stimulus. Driven by prediction-target discrepancies during training, PAMs optimized their queries to identify and prioritize the most relevant neural patterns that required focused attention. We validated our PAM with two datasets: the first dataset (B2G) with GAN-synthesized images, their original latents and multi-unit activity data; the second dataset (GOD) with real photographs, their inverted latents and functional magnetic resonance imaging data. Our findings demonstrate state-of-the-art reconstructions of perception and show that attention weights increasingly favor downstream visual areas. Moreover, visualizing the values from different brain areas enhanced interpretability in terms of their contribution to the final image reconstruction. Interestingly, the values from downstream areas (IT for B2G; LOC for GOD) appeared visually distinct from the stimuli despite receiving the most attention. This suggests that these values help guide the model to important latent regions, integrating information necessary for high-quality reconstructions. Taken together, this work advances visual neuroscience and sets a new standard for machine learning applications in interpreting complex data.

Dynamic Resting-State EEG Alpha Connectivity: Quantifying Brain Network State Evolution in Individuals with Psychosis
This study introduces a novel pipeline for investigating brain activity in psychosis using dynamic connectivity from resting-state EEG. Seventy-eight individuals with psychosis and sixty control subjects were analyzed. Source estimation was performed using eLORETA, and connectivity in the alpha band was assessed with wPLI. A modified k-means algorithm was employed to cluster connectivity matrices into distinct brain network states (BNS), from which several metrics were extracted. The segmentation revealed five distinct BNS. The control group exhibited significantly higher connectivity power, while the psychosis group showed greater duration dispersion. In the control group, correlations were found between BNS metrics and cognitive scales. Negative correlations were identified between BNS metrics and the SANS scales in the psychosis group. These results underscore the variability of neural dynamics in individuals with psychosis, as demonstrated by this novel methodology.

Transcranial Brain Atlas Based on Photon Measurement Density Function in a Triple-Parameter Standard Channel Space
Functional near-infrared spectroscopy (fNIRS) is a widely used transcranial brain imaging technique in neuroscience research. Nevertheless, its lack of anatomical information poses challenges for designing appropriate optode montage and localizing fNIRS signals to underlying anatomical regions. The photon measurement density function (PMDF) is often employed to address these issues, as it accurately measures the sensitivity of a fNIRS signal channel to perturbations of absorption coefficients at any brain locations. However, existing PMDF-based localization methods have two limitations: a limited channel space, and PMDF estimation based on single standard head models, which differ anatomically from individual subjects. To overcome these limitations, this study proposes a continuous fNIRS standard channel space and constructs a PMDF-based transcranial brain atlas (PMDF-TBA) by calculating PMDFs based on MRI images of 48 adults. PMDF-TBA contains group-averaged sensitivities of channels to gray matter and brain regions of atlases, such as Brodmann, AAL2, and LPBA40. Through leave-one-out cross-validation, we evaluated the prediction ability of PMDF-TBA for sensitivity of unseen individuals and found that it outperformed PMDFs based on single standard head models. Thus, PMDF-TBA serves as a more generalizable fNIRS spatial localization tool. Therefore, PMDF-TBA can be utilized to optimize optode montage design, improve channel sensitivity to target brain regions, and assist in the source localization of fNIRS data, thereby promoting the application of fNIRS in neuroscience research.

Amygdala Self-Neuromodulation Capacity as a Window for Process-Related Network Recruitment
Neurofeedback (NF) has emerged as a promising avenue for demonstrating process-related neuroplasticity, enabling self-regulation of brain function. NF targeting the amygdala has drawn attention for therapeutic potential in psychiatry, by potentially harnessing emotion-regulation processes. However, not all individuals respond equally to NF training, possibly due to varying self-regulation abilities. This underscores the importance of understanding the mechanisms behind successful neuromodulation (i.e. capacity). This study aimed to investigate the establishment and neural correlates of neuromodulation capacity by using data from repeated sessions of Amygdala Electrical Finger Print (EFP)-NF and post-training fMRI-NF session. Results from 97 psychiatric patients and healthy participants revealed increased amygdala-EFP neuromodulation capacity over training, associated with post-training amygdala fMRI modulation-capacity and improvements in alexithymia. Individual differences in this capacity were associated with pre-training amygdala reactivity and initial neuromodulation success. Additionally, amygdala down-regulation during fMRI-NF co-modulated with other regions such as the posterior-insula and parahippocampal gyrus. This combined modulation better explained EFP-modulation capacity and improvement in alexithymia than the amygdala modulation alone, suggesting the relevance of this broader network to the gained capacity. These findings support a network-based approach for NF and highlight the need to consider individual differences in brain function and modulation capacity to optimize NF interventions.

Ribosome-Associated Vesicles promote activity-dependent local translation
Local protein synthesis in axons and dendrites underpins synaptic plasticity. However, the composition of the protein synthesis machinery in distal neuronal processes and the mechanisms for its activity-driven deployment to local translation sites remain unclear. Here, we employed cryo-electron tomography, volume electron microscopy, and live-cell imaging to identify Ribosome-Associated Vesicles (RAVs) as a dynamic platform for moving ribosomes to distal processes. Stimulation via chemically-induced long-term potentiation causes RAV accumulation in distal sites to drive local translation. We also demonstrate activity-driven changes in RAV generation and dynamics in vivo, identifying tubular ER shaping proteins in RAV biogenesis. Together, our work identifies a mechanism for ribosomal delivery to distal sites in neurons to promote activity-dependent local translation.

Microstructural Correlates of Cognitive and Motor Functioning Revealed via Multimodal Multivariate Analysis
Recent advances in cognitive neuroscience emphasise the importance of healthy white matter (WM) in optimal behavioural functioning. It is now widely accepted that brain connectivity via WM contributes to the emergence of behaviour. However, the association between the microstructure of WM fibres and behaviour is poorly understood. This is in part due to indirect and overlapping methods of assessing microstructure, and the use of overly simplistic approaches in assessing behaviour. Here, we used the Mahalanobis Distance (D2) to integrate 10 metrics of WM derived from multimodal neuroimaging that have strong ties to microstructure. The D2 metric was chosen because it accounts for metrics' covariance as it measures the voxelwise distance between every subject and the average; thus providing a robust multiparametric assessment of microstructure. To examine WM-behaviour associations, we used multivariate correlation to examine the voxelwise correlates of 2 cognitive and 2 motor tasks, which allowed us to compare within and across domains in WM. We observed that behaviour is organised in cognitive, motor, and integrative variables that are widespread in their associations with WM, from frontal to parietal regions. Our results highlight the complex nature of microstructure and behaviour, and show the need for multivariate modelling when examining brain-behaviour associations.

Impairment of brain function in a mouse model of Alzheimer's disease during the pre-depositing phase: the role of alpha7 nicotinic acetylcholine receptors
Alzheimer's disease (AD) is an age-dependent incurable neurodegenerative disorder accompanied by neuroinflammation, amyloid accumulation and memory impairment. It begins decades before the first clinical symptoms appear, and identifying early biomarkers is key for developing disease-modifying therapies. We show now in a mouse model of AD that before any amyloid deposition the brains of 1.5-month-old mice contain increased levels of pro-inflammatory cytokines IL-1beta and IL-6, decreased levels of nicotinic acetylcholine receptors (nAChRs) in the brain and brain mitochondria and increased amounts of alpha7 nAChR-bound Abeta1-42, along with impaired episodic memory and increased risk of apoptosis. Both acute (1-week-long) and chronic (4-month-long) treatments with alpha7-selective agonist PNU282987, starting at 1.5 months of age, were well tolerated. The acute treatment did not affect the levels of soluble Abeta1-42 but consistently upregulated the alpha7 nAChR expression, decreased the level of alpha7-Abeta1-42 complexes and improved episodic memory of 1.5-month-old mice. The chronic treatment, covering the disease development phase, strongly upregulated the expression of all abundant brain nAChRs, reduced both free and alpha7-coupled Abeta1-42 within the brain, had anti-inflammatory and antiapoptotic effects, and potently upregulated cognition, thus identifying alpha7 nAChRs as both early biomarker and potent therapeutic target for fighting this devastating disease.

TLR4 deficiency does not alter glaucomatous progression in a mouse model of chronic glaucoma
Glaucoma is a leading cause of irreversible blindness worldwide. Toll-like receptor 4 (TLR4) is a pattern-recognition transmembrane receptor that induces neuroinflammatory processes in response to injury. Tlr4 is highly expressed in ocular tissues and is known to modulate inflammatory processes in both anterior and posterior segment tissues. TLR4 activation can lead to mitochondrial dysfunction and metabolic deficits in inflammatory disorders. Due to its effects on inflammation and metabolism, TLR4 is a candidate to participate in glaucoma pathogenesis. It has been suggested as a therapeutic target based on studies using acute models, such as experimentally raising IOP to ischemia-inducing levels. Nevertheless, its role in chronic glaucoma needs further evaluation. In the current study, we investigated the role of TLR4 in an inherited mouse model of chronic glaucoma, DBA/2J. To do this, we analyzed the effect of Tlr4 knockout (Tlr4-/-) on glaucoma-associated phenotypes in DBA/2J mice. Our studies found no significant differences in intraocular pressure, iris disease, or glaucomatous progression in Tlr4-/- compared to Tlr4+/+ DBA/2J mice. These data do not identify a role for TLR4 in this chronic glaucoma, but further research is warranted to understand its role in other glaucoma models and different genetic contexts.

Nanoporous Platinum Microelectrode Arrays for Neuroscience Applications
Microelectrode arrays are invaluable tools for investigating the electrophysiological behaviour of neuronal networks with high spatiotemporal precision. In recent years, it has become increasingly common to functionalize such electrodes with highly porous platinum to increase their effective surface area, and hence their signal-to-noise ratio. Although such functionalization significantly improves the electrochemical performance of the electrodes, the impact of various electrode morphologies on biocompatibility and electrophysiological performance in cell cultures remains poorly understood. In this study, we introduce reproducible protocols for depositing highly porous platinum with varying morphologies on microelectrodes designed for neural cell cultures. We also evaluate the impact of morphology and electrode size on the signal-to-noise ratio in recordings from rat cortical neurons cultured on these electrodes. Our results indicate that electrodes with a uniform layer of highly nanoporous platinum offer the best trade-off between biocompatibility, electrochemical, and electrophysiological performance. While more microporous electrodes exhibited lower impedance, nanoporous electrodes detected higher extracellular signal amplitudes from neurons, suggesting reduced distance between perisomatic neuronal areas and the electrodes. Additionally, these nanoporous electrodes showed fewer thickness variations at their edges compared to the more porous electrodes. Such edges can be mechanically broken off during cell culturing and contribute to long-term cytotoxic effects, which is highly undesirable. We hope this work will contribute to better standardization in creating and utilizing nanoporous platinum microelectrodes for neuroscience applications. Improving the accessibility and reproducibility of this technology is crucial for enhancing the quality of electrophysiological data and advancing our understanding of neuronal network function and dysfunction.

Increased stomach-brain coupling indexes a dimensional signature of negative mental health symptoms.
Visceral rhythms orchestrate the physiological states underlying human emotion. Chronic aberrations in these brain-body interactions are implicated in a broad spectrum of mental health disorders. However, the specific contributions of the gastric-brain coupling to affective symptoms remain poorly understood. We investigated the relationship between this novel interoceptive axis and mental health symptoms in 243 participants, using a cross validated machine learning approach. We find that frontal parietal brain coupling to the gastric rhythm indexes a dimensional signature of mental health spanning anxiety, depression, stress, and well-being. Control analyses confirm the specificity of these interactions to the gastric-brain axis. Our study establishes coupling between the stomach and brain as a factor in the pathology of mental health, and offers new targets for interventions remediating aberrant brain-body coupling.

A replicable and generalizable neuroimaging-based indicator of pain sensitivity across individuals
Developing neural indicators of pain sensitivity is crucial for revealing the neural basis of individual differences in pain and advancing individualized treatment of pain. However, it still remains elusive whether pain-evoked neural responses can encode pain sensitivity. To address this issue, we analyzed five large functional magnetic resonance imaging (fMRI) datasets (total N = 1010), where healthy participants received painful and nonpainful tactile, auditory, and visual stimuli, and different pain treatments, including placebo and transcutaneous electrical neural stimulation. We systematically (1) investigated the correlation between pain-evoked fMRI responses and pain sensitivity, (2) evaluated the correlation's replicability in independent datasets and generalizability across different types of pain, (3) examined whether the correlation between fMRI responses and sensory sensitivity is unique to pain, and (4) how sample sizes affect the relationship between fMRI responses and pain sensitivity. We found that, with a sufficiently large sample size, there were replicable and generalizable correlations between pain-evoked fMRI responses and pain sensitivity across individuals for laser heat, contact heat, and mechanical pains. Despite lacking pain selectivity, fMRI signals exhibited larger correlations with pain sensitivity than with tactile, auditory, and visual sensitivity. Importantly, we developed a machine learning model that could accurately predict not only pain sensitivity to laser heat, contact heat, and mechanical stimuli, but also pain relief from pain treatments. Notably, our findings were influenced considerably by sample sizes, requiring >200 for univariate correlation analysis to reveal the relationship between pain sensitivity and fMRI responses, and >150 for multivariate analysis to decode pain sensitivity with fMRI responses. Altogether, given an enormous sample size, we convincingly showed the validity to decode pain sensitivity and predict analgesic effects using pain-evoked fMRI responses, which holds significant clinical promise in tailoring individualized pain treatments.

Ultrasound system for precise neuromodulation of human deep brain circuits
Transcranial ultrasound stimulation (TUS) has emerged as a promising technique for non-invasive neuromodulation, but current systems lack the precision to target deep brain structures effectively. Here, we introduce an advanced TUS system that achieves unprecedented precision in deep brain neuromodulation. The system features a 256-element, helmet-shaped transducer array operating at 555 kHz, coupled with a stereotactic positioning system, individualised treatment planning, and real-time monitoring using functional MRI. In a series of experiments, we demonstrate the system's ability to selectively modulate the activity of the lateral geniculate nucleus (LGN) and its functionally connected regions in the visual cortex. Participants exhibited significantly increased visual cortex activity during concurrent TUS and visual stimulation, with high reproducibility across individuals. Moreover, a theta-burst TUS protocol induced robust neuromodulatory effects, with decreased visual cortex activity observed for at least 40 minutes post-stimulation. These neuromodulatory effects were specific to the targeted LGN, as confirmed by control experiments. Our findings highlight the potential of this advanced TUS system to non-invasively modulate deep brain circuits with high precision and specificity, offering new avenues for studying brain function and developing targeted therapies for neurological and psychiatric disorders. The unprecedented spatial resolution and prolonged neuromodulatory effects demonstrate the transformative potential of this technology for both research and clinical applications, paving the way for a new era of non-invasive deep brain neuromodulation.

EEG Responses to Upper Limb Pinprick Stimulation in Acute and Early Subacute Motor and Sensorimotor Stroke
Background: Electroencephalography (EEG) during pinprick stimulation has the potential to unveil neural mechanisms underlying sensorimotor impairments post-stroke. This study explored event-related peak pinprick amplitude and oscillatory responses in healthy controls, in people with motor and sensorimotor in acute and early subacute stroke, their relationship and to what extent EEG somatosensory responses can predict sensorimotor impairment. Methods: In this study, involving 26 individuals, 10 people with a (sub-)acute sensorimotor stroke, 6 people with a (sub)acute motor stroke and 10 age-matched controls, pinpricks were applied to the dorsa of the impaired hand to collect somatosensory evoked potentials. Time(-frequency) analyses of somatosensory evoked potential (SEP) data at electrodes C3 and C4 explored peak pinprick amplitude and oscillatory responses across the three groups. Also, in stroke, (sensori-)motor impairments were assessed at baseline Fugl Meyer Assessment Upper Extremity (FMA-UE) and Erasmus modified Nottingham Sensory Assessment (EmNSA) at baseline and 7 to 14 days later including Fugl Meyer Assessment Upper Extremity (FMA-UE) and Erasmus modified Nottingham Sensory Assessment (EmNSA). Mixed model analyses were used to address objectives. Results: It was demonstrated that increased beta desynchronization magnitude correlated with milder motor impairments (R2adjusted=0.213), whereas increased beta resynchronization and delta power were associated to milder somatosensory impairment (R2adjusted=0.550). At the second session, larger peak-to-peak SEP amplitude and beta band resynchronization at baseline were related to greater improvements in EMNSA and FMA-UE score, respectively, in sensorimotor stroke group. Conclusions: These findings highlight the potential of EEG combined with somatosensory stimuli to differentiate between sensorimotor and motor impairments in stroke, offering preliminary insights into both diagnostic and prognostic aspects of upper limb recovery.

Astrocyte-induced firing in primary afferent axons
The mesencephalic trigeminal nucleus is unique in that it contains the cell bodies of large-caliber primary afferents that are usually located in the periphery in the dorsal root ganglia or trigeminal ganglia. The activity of these afferents is typically associated with proprioception of the jaw-closing muscles or mechanoreception on the teeth and periodontal ligament. However, like other large-caliber afferents from the body which display ectopic firing in neuropathic pain models, these afferents exhibit increased excitability and ectopic discharges even in a relatively mild muscle pain model. These discharges normally emerge from subthreshold membrane oscillations (SMOs) supported by a persistent sodium current (INaP) which is exquisitely sensitive to extracellular Ca2+-decreases. We have shown in the trigeminal main sensory nucleus that the release of a Ca2+-binding astrocytic protein, S100{beta}, is sufficient to modulate this sodium current. Here, we explore if this astrocyte-dependent mechanism contributes to the emergence of this hyperexcitability and aim to localize the cellular site where ectopic discharge may arise using whole-cell patch-clamp recordings, confocal imaging, and immunohistochemistry methods on mice brain slices. We found that astrocytes, by lowering [Ca2+]e at focal points along the axons of NVmes neurons through S100{beta}, enhance the amplitude of the NaV1.6-dependent SMOs leading to ectopic firing. These findings suggest a crucial role for astrocytes in excitability regulation and raise questions about this neuron-astrocyte interaction as a key contributor to hyperexcitability in several pathologies.

The polyadenylation landscape after in vivo long-term potentiation in the rat brain
Local protein synthesis in neurons is vital for synaptic plasticity, yet the regulatory mechanisms, particularly cytoplasmic polyadenylation, are not fully understood. This study employed nanopore sequencing to examine transcriptomic responses in rat hippocampi during in vivo long-term potentiation (LTP) and in synaptoneurosomes after in vitro stimulation. Our long-read transcriptomic dataset allows for detailed analysis of mRNA 3'-ends, poly(A) tail lengths, and composition. We observed dynamic shifts in polyadenylation site preference post-LTP induction, with significant poly(A) tail lengthening restricted to transcriptionally induced mRNAs. Poly(A) tails of these genes showed increased non-adenosine abundance. In synaptoneurosomes, chemical stimulation led to shortening of poly(A) tails on preexisting mRNAs, indicating translation-induced deadenylation. Additionally, we discovered a group of neuronal transcripts abundant in non-adenosine residues poly(A) tails. These tails are semi-templated and derived from extremely adenosine-rich 3'UTRs. This study provides a comprehensive overview of mRNA 3'-end dynamics during LTP, offering insights into post-transcriptional regulation in neuronal activation.

Peptidomimetic inhibitors targeting TrkB/PSD-95 signaling improves cognition and seizure outcomes in an Angelman Syndrome mouse model
Angelman syndrome (AS) is a rare genetic neurodevelopmental disorder with profoundly debilitating symptoms with no FDA-approved cure or therapeutic. Brain-derived neurotrophic factor (BDNF), and its receptor TrkB, have a well-established role as regulators of synaptic plasticity, dendritic outgrowth, dendritic spine formation and maintenance. Previously, we reported that the association of PSD-95 with TrkB is critical for intact BDNF signaling in the AS mouse model, as illustrated by attenuated PLCg and PI3K signaling and intact MAPK pathway signaling. These data suggest that drugs tailored to enhance the TrkB-PSD-95 interaction may provide a novel approach for the treatment of AS and a variety of NDDs. To evaluate this critical interaction, we synthesized a class of high-affinity PSD-95 ligands that bind specifically to the PDZ3 domain of PSD-95, denoted as Syn3 peptidomimetic ligands. We evaluated Syn3 and its analog D-Syn3 (engineered using dextrorotary (D)-amino acids) in vivo using the Ube3a exon 2 deletion mouse model of AS. Following systemic administration of Syn3 and D-Syn3, we demonstrated improvement in the seizure domain of AS. Learning and memory using the novel object recognition assay also illustrated improved cognition following Syn3 and D-Syn3, along with restored long-term potentiation. Finally, D-Syn3 treated mice showed a partial rescue in motor learning. Neither Syn3 nor D-Syn3 improved gross exploratory locomotion deficits, nor gait impairments that have been well documented in the AS rodent models. These findings highlight the need for further investigation of this compound class as a potential therapeutic for AS and other genetic NDDs.

Parkinson's LRRK2-G2019S risk gene mutation drives sex-specific behavioral and cellular adaptations to chronic variable stress
Anxiety is a psychiatric non-motor symptom of Parkinson's that can appear in the prodromal period, prior to significant loss of brainstem dopamine neurons and motor symptoms. Parkinson's-related anxiety affects females more than males, despite the greater prevalence of Parkinson's in males. How stress, anxiety and Parkinson's are related and the basis for a sex-specific impact of stress in Parkinson's are not clear. We addressed this using young adult male and female mice carrying a G2019S knockin mutation of leucine-rich repeat kinase 2 (Lrrk2-G2019S) and Lrrk2-WT control mice. In humans, LRRK2-G2019S significantly elevates the risk of late-onset Parkinson's. To assess within-sex differences between Lrrk2-G2019S and control mice in stress-induced anxiety-like behaviors in young adulthood, we used a within-subject design whereby Lrrk2-G2019S and Lrrk-2WT control mice underwent tests of anxiety-like behaviors before (baseline) and following a 28 day (d) variable stress paradigm. There were no differences in behavioral measures between genotypes in males or females at baseline, indicating that the mutation alone does not produce anxiety-like responses. Following chronic stress, male Lrrk2-G2019S mice were affected similarly to male wildtype mice except for novelty-suppressed feeding, where stress had no impact on Lrrk2-G2019S mice while significantly increasing latency to feed in Lrrk2-WT control mice. Female Lrrk2-G2019S mice were impacted by chronic stress similarly to wildtype females across all behavioral measures. Subsequent post-stress analyses compared cFos immunolabeling-based cellular activity patterns across several stress-relevant brain regions. The density of cFos-activated neurons across brain regions in both male and female Lrrk2-G2019S mice was generally lower compared to stressed Lrrk2-WT mice, except for the nucleus accumbens of male Lrrk2-G2019S mice, where cFos-labeled cell density was significantly higher than all other groups. Together, these data suggest that the Lrrk2-G2019S mutation differentially impacts anxiety-like behavioral responses to chronic stress in males and females that may reflect sex-specific adaptations observed in circuit activation patterns in stress-related brain regions.

Spike Reliability is Cell-Type Specific and Shapes Excitation and Inhibition in the Cortex
Neurons encode information in the highly variable spiking activity of neuronal populations, so that different repetitions of the same stimulus can generate action potentials that vary significantly in terms of the count and timing. How does spiking variability originate, and does it have a functional purpose? Leveraging the Allen Institute cell types dataset, we relate the spiking reliability of cortical neurons in-vitro during the intracellular injection of current resembling synaptic inputs to their morphologic, electrophysiologic, and transcriptomic classes. Our findings demonstrate that parvalbumin+ (PV) interneurons, a subclass of inhibitory neurons, show high reliability compared to other neuronal subclasses, particularly excitatory neurons. Through computational modeling, we predict that the high reliability of PV interneurons allows for strong and precise inhibition in downstream neurons, while the lower reliability of excitatory neurons allows for integrating multiple synaptic inputs leading to a spiking rate code. These findings illuminate how spiking variability in different neuronal classes affect information propagation in the brain, leading to precise inhibition and spiking rate codes.

NeuroNella: A Robust Unsupervised Algorithm for Identification of Neural Activity from Multielectrode Arrays
We introduce NeuroNella, an automated algorithm developed for the identification of neuronal activity from multichannel electrode arrays. In evaluations conducted on recordings from implanted probes in the nervous system of rodents and primates, the algorithm demonstrated remarkable accuracy, showcasing an error rate of less than 1% compared to ground-truth patch clamp signals. Notably, the proposed algorithm handles large datasets efficiently without the necessity of a GPU system. The results highlighted the algorithm's efficacy in detecting sources in a wide amplitude range and its adaptability in accommodating minor probe shifts. Moreover, the high robustness exhibited by the algorithm in decomposing recordings lasting up to 30 minutes underscores its potential for enabling longitudinal studies and prolonged recording sessions, thus opening new avenues for future brain/machine interface applications.

Spiking networks that efficiently process dynamic sensory features explain receptor information mixing in somatosensory cortex
How do biological neural systems efficiently encode, transform and propagate information between the sensory periphery and the sensory cortex about sensory features evolving at different time scales? Are these computations efficient in normative information processing terms? While previous work has suggested that biologically plausible models of of such neural information processing may be implemented efficiently within a single processing layer, how such computations extend across several processing layers is less clear. Here, we model propagation of multiple time-varying sensory features across a sensory pathway, by extending the theory of efficient coding with spikes to efficient encoding, transformation and transmission of sensory signals. These computations are optimally realized by a multilayer spiking network with feedforward networks of spiking neurons (receptor layer) and recurrent excitatory-inhibitory networks of generalized leaky integrate-and-fire neurons (recurrent layers). Our model efficiently realizes a broad class of feature transformations, including positive and negative interaction across features, through specific and biologically plausible structures of feedforward connectivity. We find that mixing of sensory features in the activity of single neurons is beneficial because it lowers the metabolic cost at the network level. We apply the model to the somatosensory pathway by constraining it with parameters measured empirically and include in its last node, analogous to the primary somatosensory cortex (S1), two types of inhibitory neurons: parvalbumin-positive neurons realizing lateral inhibition, and somatostatin-positive neurons realizing winner-take-all inhibition. By implementing a negative interaction across stimulus features, this model captures several intriguing empirical observations from the somatosensory system of the mouse, including a decrease of sustained responses from subcortical networks to S1, a non-linear effect of the knock-out of receptor neuron types on the activity in S1, and amplification of weak signals from sensory neurons across the pathway.

RESPAN: an accurate, unbiased and automated pipeline for analysis of dendritic morphology and dendritic spine mapping
Accurate and unbiased reconstructions of neuronal morphology, including quantification of dendritic spine morphology and distribution, are widely used in neuroscience but remain a major roadblock for large-scale analysis. Traditionally, spine analysis has required labor-intensive manual annotation, which is prone to human error and impractical for large 3D datasets. Previous automated tools for reconstructing neuronal morphology and quantitative dendritic spine analysis face challenges in generating accurate results and, following close inspection, often require extensive manual correction. While recent tools leveraging deep learning approaches have substantially increased accuracy, they lack functionality and useful outputs, necessitating additional tools to perform a complete analysis and limiting their utility. In this paper, we describe Restoration Enhanced SPine And Neuron (RESPAN) analysis, a new comprehensive pipeline developed as an open-source, easily deployable solution that harnesses recent advances in deep learning and GPU processing. Our approach demonstrates high accuracy and robustness, validated extensively across a range of imaging modalities for automated dendrite and spine mapping. It also offers extensive visual and tabulated data outputs, including detailed morphological and spatial metrics, dendritic spine classification, and 3D renderings. Additionally, RESPAN includes tools for validating results, ensuring scientific rigor and reproducibility.

High-bandwidth, low-profile, long-term wireless EEG telemetry allows for optogenetic entrainment of natural cortical oscillations in freely-moving rats
Recording of whole-brain or multi-unit neuronal activity in the rodent brain is a powerful and widely used technique in neuroscience research. However, the acquisition of data from freely-moving animals is subject to a range of compromises. If a high bandwidth of data digitisation is needed, animals will either need to be tethered to the acquisition system or any telemetry used will have a short working battery life. For freely-moving experiments, especially those requiring careful behavioural measurements, such tethers and/or headstages incorporating e.g. optogenetic stimulation systems may prove to be confounding or limiting in the experiments which may be performed. Here we present the refinement and deployment of a wirelessly-charged, self-contained EEG telemeter at high data bandwidths (2kHz) with integrated optogenetic stimulator (473nm) and fully subcutaneous fibre routing and implantation. This approach has allowed for rats to be recorded long-term (6 months) without requiring device explants, charging or maintenance, with an outward appearance identical to an unimplanted rodent. We have demonstrated the use of this system to stimulate cortical networks at a range of frequencies in freely-moving and acutely-anaesthetised rats allowing for the boosting or entrainment of physiological oscillations at will.

Noise induces intercellular Ca2+ signaling waves and the unfolded protein response in the hearing cochlea
Exposure to loud noise is a common cause of acquired hearing loss. Disruption of subcellular calcium homeostasis and downstream stress pathways in the endoplasmic reticulum and mitochondria, including the unfolded protein response, have been implicated in the pathophysiology of noise-induced hearing loss. However, studies on the association between calcium homeostasis and stress pathways has been limited due to limited ability to measure calcium dynamics in mature-hearing, noise-exposed mice. We used a genetically encoded calcium indicator mouse model in which GcAMP is expressed specifically in hair cells or supporting cells under control of Myo15Cre or Sox2Cre, respectively. We performed live calcium imaging and UPR gene expression analysis in 8-week-old mice exposed to levels of noise that cause cochlear synaptopathy (98 db SPL) or permanent hearing loss (106 dB SPL). UPR activation occurred immediately after noise exposure and was noise dose-dependent, with the pro-apoptotic pathway upregulated only after 106 dB noise exposure. Spontaneous calcium transients in hair cells and intercellular calcium waves in supporting cells, which are present in neonatal cochleae, were quiescent in mature-hearing cochleae, but re-activated upon noise exposure. 106 dB noise exposure was associated with more persistent and expansive ICS wave activity. These findings demonstrate a strong and dose-dependent association between noise exposure, UPR activation, and changes in calcium homeostasis in hair cells and supporting cells, suggesting that targeting these pathways may be effective to develop treatments for noise-induced hearing loss.

Sleep, NMDA Receptor Subunits, and the Compensatory Pathway: Understanding Contextual Fear Conditioning in the Absence of the Dorsal Hippocampus
The loss of the dorsal hippocampus (DH) results in profound deficits in contextual fear-conditioned (CxFC) memory. Nonetheless, CxFC memories can still form without the DH, specifically with multiple trials at three-day intervals. The infralimbic cortex (IL) is pivotal in initiating this compensatory process post-DH loss, but the precise factors remain elusive. Our study aims to delineate key factors of compensatory CxFC in DH absence by investigating the effects of sleep deprivation (SD) and NMDA receptor subunits NR2A and NR2B. Using a DH-lesioned rat model, we conducted two conditioning trials separated by three days and assessed fear response during the subsequent test. We observed that DH-lesioned animals exhibited to SD (DHL-SD) did not elicit a compensatory CxFC response, displaying significantly impaired freezing during the second test. Conversely, DH-lesioned non-sleep-deprived animals (DHL-NSD) compensated for DH loss and exhibited robust CxFC responses during the second test. Moreover, inhibiting NR2B subunits in the IL during initial CxFC training disrupted the formation of compensatory fear memory in DH-lesioned animals, while NR2A subunit blockade showed no significant effect. These emphasize the adverse impact of SD on compensatory memory and the critical role of NR2B subunits in facilitating compensatory CxFC memory formation following DH loss.

The impact of parvalbumin interneurons on visual discrimination depends on strength and timing of activation and task difficulty
Parvalbumin-expressing (PV) cells are the most common class of inhibitory interneurons in the visual cortex. They are densely connected to excitatory cells and play important roles in balancing cortical circuit activity and learning. PV cell activation is a tool to inactivate cortical regions to establish their role in visual processing. However, it is not established how moderate activation affects behaviour and how effects depend on activation strength, timing and task difficulty. We therefore investigated how these three major factors affect performance of mice in a go/no-go orientation discrimination task. We tested discrimination performance with different strength and timing of PV cell activation in V1 and with different task difficulty levels. We found that PV cell activation improved performance in easy discriminations when stimulating with moderate laser powers only during the initial 120 ms from stimulus onset, corresponding to the initial feedforward processing sweep across the cortical hierarchy. In the same animals, PV cell activation did not aid performance in difficult discriminations. However, in both easy and difficult discriminations, optimal behavioural performance required undisturbed late phase activity beyond 120 ms, highlighting the importance of sustained activity in V1. Combining the optogenetic activation of PV cells with two-photon imaging showed that behavioural changes were associated with changes in stimulus response selectivity in V1. Thus, our results demonstrate that early and sustained activity in V1 is crucial for perceptual discrimination and delineate specific conditions when PV cell activation shapes neuronal selectivity to improve behaviour.

Lower motor performance is linked with poor sleep quality, depressive symptoms, and grey matter volume alterations
Motor performance (MP) is essential for functional independence and well-being, particularly in later life. However, the relationship between behavioural aspects such as sleep quality and depressive symptoms, which contribute to MP, and the underlying structural brain substrates of their interplay remains unclear. This study used three population-based cohorts of younger and older adults (n=1,950) from the Human Connectome Project-Young Adult (HCP-YA), HCP-Aging (HCP-A), and enhanced Nathan Kline Institute-Rockland sample (eNKI-RS). Several canonical correlation analyses were computed within a machine learning framework to assess the associations between each of the three domains (sleep quality, depressive symptoms, grey matter volume (GMV)) and MP. The HCP-YA analyses showed progressively stronger associations between MP and each domain: depressive symptoms (unexpectedly positive, r=0.13, SD=0.06), sleep quality (r=0.17, SD=0.05), and GMV (r=0.19, SD=0.06). Combining sleep and depressive symptoms significantly improved the canonical correlations (r=0.25, SD=0.05), while the addition of GMV exhibited no further increase (r=0.23, SD=0.06). In young adults, better sleep quality, mild depressive symptoms, and GMV of several brain regions were associated with better MP. This was conceptually replicated in young adults from the eNKI-RS cohort. In HCP-Aging, better sleep quality, fewer depressive symptoms, and increased GMV were associated with MP. Robust multivariate associations were observed between sleep quality, depressive symptoms and GMV with MP, as well as age-related variations in these factors. Future studies should further explore these associations and consider interventions targeting sleep and mental health to test the potential effects on MP across the lifespan.

Preventing acute neurotoxicity of CNS therapeutic oligonucleotides with the addition of Ca2+ and Mg2+ in the formulation
Oligonucleotide therapeutics (ASOs and siRNAs) have been explored for modulation of gene expression in the central nervous system (CNS), with several drugs approved and many in clinical evaluation. Administration of highly concentrated oligonucleotides to the CNS can induce acute neurotoxicity. We demonstrate that delivery of concentrated oligonucleotides to the CSF in awake mice induces acute toxicity, observable within seconds of injection. Electroencephalography (EEG) and electromyography (EMG) in awake mice demonstrated seizures. Using ion chromatography, we show that siRNAs can tightly bind Ca2+ and Mg2+ up to molar equivalents of the phosphodiester (PO)/phosphorothioate (PS) bonds independently of the structure or phosphorothioate content. Optimization of the formulation by adding high concentrations (above biological levels) of divalent cations (Ca2+ alone, Mg2+ alone, or Ca2+ and Mg2+) prevents seizures with no impact on the distribution or efficacy of the oligonucleotide. The data here establishes the importance of adding Ca2+ and Mg2+ to the formulation for the safety of CNS administration of therapeutic oligonucleotides.

Neural basis of cognitive control signals in anterior cingulate cortex during delay discounting
Cognitive control involves allocating cognitive effort according to internal needs and task demands and the Anterior Cingulate Cortex (ACC) is hypothesized to play a central role in this process. We investigated the neural basis of cognitive control in the ACC of rats performing an adjusting-amount delay discounting task. Decision-making in this this task can be guided by using either a lever-value tracking strategy, requiring a resource-based form of cognitive effort or a lever-biased strategy requiring a resistance-based form of cognitive effort. We found that ACC ensembles always tightly tracked lever value on each trial, indicative of a resource-based control signal. These signals were prevalent in the neural recordings and were influenced by the delay. A shorter delay was associated with devaluing of the immediate option and a longer delay was associated with overvaluing of the immediate option. In addition, ACC theta (6-12Hz) oscillations were observed at the choice point of rats exhibiting a resistance-based strategy. These data provide candidates of neural activity patterns in the ACC that underlie the use of resource-based and resistance-based cognitive effort. Furthermore, these data illustrate how strategies can be engaged under different conditions in individual subjects.

Bursts boost nonlinear encoding in electroreceptor afferents
Nonlinear mechanisms are at the heart of neuronal information processing, for example to fire an action potential, the membrane voltage must exceed a threshold nonlinearity. Even though, linear encoding schemes are commonly used and often successfully describe large parts of sensory encoding nonlinear mechanisms such as thresholds and saturations are well known to be crucial to encode behaviorally relevant features in the stimulus space not captured by linear methods. Here we analyze the role of bursts in p-type electroreceptor afferents (P-units) in the weakly electric fish Apteronotus leptorhynchus. It is long known that subpopulations of these cells fire bursts of action potentials while others do not. Previous research suggests, that the non-bursting cells are better at encoding the stimulus time-course while bursting neurons are better suited to encode special features in the stimulus. We here show, based on the analysis of experimental data and modelling, that burst affect the linear as well as the nonlinear encoding. Theoretical work predicts that in simple leaky-integrate-and-fire model neurons, two periodic stimuli interact nonlinearly when the sum of the two frequencies matches the neuron's baseline firing rate as quantified by the second-order susceptibility. Indeed, such nonlinear responses have been found in non-bursting P-units when stimulated by two beats simultaneously but only in those cells, that exhibit very low levels of intrinsic noise. In this study, we found that bursts strongly enhance these nonlinear responses which may play a critical role for the detection of weak intruder signals in the presence of a strong female signal, i.e. an electrosensory cocktail party.

Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson's disease
Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using single cell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson's disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2G2019S knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.

Decreased scene-selective activity within the posterior intraparietal cortex in amblyopic adults
Amblyopia is a developmental disorder associated with reduced performance in visually guided tasks, including binocular navigation within natural environments. To help understand the underlying neurological disorder, we used fMRI to test the impact of amblyopia on the functional organization of scene-selective cortical areas, including the posterior intraparietal gyrus scene-selective (PIGS) area, a recently discovered region that responds selectively to ego-motion within naturalistic environments (Kennedy et al., 2024). Nineteen amblyopic adults (10 female) and thirty age-matched controls (12 female) participated in this study. Amblyopic participants spanned a wide range of amblyopia severity, based on their interocular visual acuity difference and stereoacuity. The visual function questionnaire (VFQ-39) was used to assess the participants perception of their visual capabilities. Compared to controls, we found weaker scene-selective activity within the PIGS area in amblyopic individuals. By contrast, the level of scene-selective activity across the occipital place area (OPA), parahippocampal place area (PPA), and retrosplenial cortex (RSC)) remained comparable between amblyopic and control participants. The subjects scores on general vision (VFQ-39 subscale) correlated with the level of scene-selective activity in PIGS. These results provide novel and direct evidence for amblyopia-related changes in scene-processing networks, thus enabling future studies to potentially link these changes across the spectrum of documented disabilities in amblyopia.

A spontaneous mutation in ADIPOR1 causes retinal degeneration in mice
Adiponectin receptor 1 (ADIPOR1) is a transmembrane protein necessary for normal anatomy and physiology in the retina. In a recent study of complement factor H knockout mice (Cfh-/-), our lab discovered a flecked retina phenotype and retinal thinning by fundus imaging and optical coherence tomography (OCT), respectively. The phenotype was observed in a subset (50%) of Cfh-/- mice. The thinning observed in vivo is due to an early degeneration of rod photoreceptors. This phenotype has not been reported in published studies of Cfh-/- mice. AdipoR1 knockout mice (AdipoR1-/-) and mice deficient in Membrane Frizzled Related Protein (MFRP) exhibit this phenotype, suggesting an involvement in the emergence of the retinal degeneration observed in a subset of Cfh-/- mice. Cfh and AdipoR1 are located in close proximity on mouse Chromosome 1 (Chr1) and a complementation cross between Cfh and AdipoR1 mice with retinal degeneration produced 100% progeny with retinal degeneration. Sequencing of the Cfh-/- mice revealed a c.841 C > T mutation in AdipoR1. Furthermore, one Cfh wildtype (of Cfh+/+) and 2 heterozygous (of Cfh+/-) mice exhibited retinal degeneration and were homozygous for the point mutation. The c.841 C > T mutation results in a proline to serine conversion at position 281 (P281S) in ADIPOR1. This residue is critical for ADIPOR1 open and closed conformations in the membrane. In silico modeling of candidate ADIPOR1 ligands, 11-cis-retinaldehyde and docosahexaenoic acid (DHA), that are deficient in AdipoR1-/-, suggests that ADIPOR1 is involved in trafficking retinoids and fatty acids and their combined deficiency in the ADIPOR1 mutant retinas might explain the retinal degeneration phenotype.

Insula uses overlapping codes for emotion in self and others
In daily life, we must recognize others' emotions so we can respond appropriately. This ability may rely, at least in part, on neural responses similar to those associated with our own emotions. We hypothesized that the insula, a cortical region near the junction of the temporal, parietal, and frontal lobes, may play a key role in this process. We recorded local field potential (LFP) activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one on identifying facial emotional responses in others. We found matching patterns of gamma- and high-gamma band activity for the two tasks in the insula. Three other regions (MTL, ACC, and OFC) clearly encoded both self- and other- emotions, but used orthogonal activity patterns to do so. These results support the hypothesis that the insula plays a particularly important role in mediating between experienced vs. observed emotions.

Ternary representation of contextual information along the CA1 transverse axis
The function of CA1 region in the rat hippocampus is transversely organized, aligning with input profiles from the entorhinal cortex and the CA3-CA2 region. We asked how CA1 neurons respond diversely to various contextual changes along the transverse axis, and how it may be influenced by selective inputs from upstream brain regions. Neuronal activity across the entire proximo-distal extent of CA1 in Long-Evans rats was monitored under manipulations of spatial or non-spatial environmental cues. Our results identified three distinct patterns of cue representation that varied from the proximal to the distal end of CA1: a descending gradient in spatial information processing, an ascending gradient in representation of local object features, and a reverse J-shaped pattern in response to non-spatial cue manipulation. This heterogeneity is closely linked to the nature of information altered in the environment, suggesting an involvement of upstream cue-selective neurons in shaping CA1 function.

The ventral CA2 region of the hippocampus and its differential contributions to social memory and social aggression
Although it is well-known that the hippocampus mediates declarative memory (the repository of information of people, places, things and events) and influences behavior, the differential contributions of the dorsal and ventral hippocampus to specific forms of memory and behavior remain largely unknown. Studies to date show that the dorsal hippocampal CA1 region is important for cognitive and spatial tasks whereas the ventral CA1 region is associated with affective or emotional processing. Whether other regions and forms of hippocampal-dependent memory and behavior show a similar distinction remains unclear. Here we examine how social memory and related social behaviors are encoded across the dorso-ventral axis of the hippocampus. Although recent studies show that the dorsal hippocampal CA2 region is required for social memory and acts to promote social aggression, the behavioral role of ventral CA2 remains unknown. Indeed, whether a defined CA2 region extends throughout ventral hippocampus is controversial. Here, we report that a molecularly, anatomically and electrophysiologically defined CA2 region extends to the extreme ventral pole of hippocampus, with both similarities and important differences in its projection patterns and synaptic impact compared to dorsal CA2. Of particular importance, we find that ventral CA2 is not required for social memory but is critical for promoting social aggression. These results support the view that the ventral region of hippocampus is more generally tuned for emotionally-related behaviors compared to the cognitively-tuned dorsal hippocampus.

Diet-microbiome interactions promote enteric nervous system resilience following spinal cord injury
Spinal cord injury (SCI) results in a plethora of physiological dysfunctions across all body systems, including intestinal dysmotility and atrophy of the enteric nervous system (ENS). Typically, the ENS has capacity to recover from perturbation, so it is unclear why intestinal pathophysiologies persist after traumatic spinal injury. With emerging evidence demonstrating SCI-induced alterations to the gut microbiome composition, we hypothesized that modulation of the gut microbiome could contribute to enteric nervous system recovery after injury. Here, we show that intervention with the dietary fiber, inulin prevents ENS atrophy and limits SCI-induced intestinal dysmotility in mice. However, SCI-associated microbiomes and exposure to specific SCI-sensitive gut microbes are not sufficient to modulate injury-induced intestinal dysmotility. Intervention with microbially-derived short-chain fatty acid (SCFA) metabolites prevents ENS dysfunctions and phenocopies inulin treatment in injured mice, implicating these microbiome metabolites in protection of the ENS. Notably, inulin-mediated resilience is dependent on signaling by the cytokine IL-10, highlighting a critical diet-microbiome-immune axis that promotes ENS resilience following SCI. Overall, we demonstrate that diet and microbially-derived signals distinctly impact recovery of the ENS after traumatic spinal injury. This protective diet-microbiome-immune axis may represent a foundation to uncover etiological mechanisms and future therapeutics for SCI-induced neurogenic bowel.

Menstrual cycle phase modulates causal connectivity in the resting-state brain of healthy females.
Background: Ovarian hormones exert direct and indirect influences on the brain; however, little is known about how these hormones impact causal brain connectivity. Studying the female brain at a single time point may be confounded by distinct hormone phases. Despite this, the menstrual cycle is often overlooked. The primary objective of this pilot study was to evaluate resting-state causal connectivity during the early follicular and mid-luteal menstrual phases corresponding to low vs high estradiol and progesterone, respectively. Methods: Fourteen healthy control females (M = 20.36 years, SD =2.02) participated in this study. Participants were scheduled for two resting-state electroencephalography (EEG) scans during their monthly menstrual cycle. A saliva sample was also collected at each EEG session for hormone analyses. Causal connectivity was quantified using information flow rate of EEG source data. Demographic information, emotional empathy, and sleep quality were obtained from self-report questionnaires. Results: Progesterone levels were significantly higher in the mid-luteal phase compared to the early follicular phase (p = .041). We observed distinct patterns of causal connectivity along the menstrual cycle. Connectivity in the early follicular phase was centralized and shifted posteriorly during the mid-luteal phase. During the early follicular phase, the primary regions driving activity were the right central and left/right parietal regions, with the left central region being the predominant receiver of activity. During the mid-luteal phase, connections were primarily transmitted from the right side and the main receiver region was the left occipital region. Network topology during the mid-luteal phase was found to be significantly more assortative compared to the early follicular phase. Conclusions: The observed difference in causal connectivity demonstrates how network dynamics reorganize as a function of menstrual phase and level of progesterone. In the mid-luteal phase, there was a strong shift for information flow to be directed at visual spatial processing and visual attention areas, whereas in the follicular phase, there was strong information flow primarily within the sensory-motor regions. The mid-luteal phase was significantly more assortative, suggesting greater network efficiency and resilience. These results contribute to the emerging literature on brain-hormone interactions.

SpyDen: Automating molecular and structural analysis across spines and dendrites
Investigating the molecular composition across neural compartments such as axons, dendrites, or synapses is critical for our understanding of learning and memory. State-of-the-art microscopy techniques can now resolve individual molecules and pinpoint their position with micrometre or even nanometre resolution across tens or hundreds of micrometres, allowing the labelling of multiple structures of interest simultaneously. Algorithmically, tracking individual molecules across hundreds of micrometres and determining whether they are inside any cellular compartment of interest can be challenging. Historically, microscopy images are annotated manually, often using multiple software packages to detect fluorescence puncta (e.g. labelled mRNAs) and then trace and quantify cellular compartments of interest. Advanced ANN-based automated tools, while powerful, are often able to help only with selected parts of the data analysis pipeline, may be optimised for specific spatial resolutions or cell preparations or may not be fully open source and open access to be sufficiently customisable. To address these challenges, we developed SpyDen. SpyDen is a Python package based upon three principles: i) ease of use for multi-task scenarios, ii) open-source accessibility and data export to a common, open data format, iii) the ability to edit any software-generated annotation and generalise across spatial resolutions. Equipped with a graphical user interface and accompanied by video tutorials, SpyDen provides a collection of powerful algorithms that can be used for neurite and synapse detection as well as fluorescent puncta and intensity analysis. We validated SpyDen using expert annotation across numerous use cases to prove a powerful, integrated platform for efficient and reproducible molecular imaging analysis.

EEG is better when cleaning effectively targets artifacts
Electroencephalography (EEG) is a useful tool to measure neural activity. However, EEG data are usually contaminated with non-neural artifacts, including voltage shifts generated by eye movements and muscle activity, and other artifacts that are less easily characterizable. The confounding influence of artifacts is often addressed by decomposing data into components, subtracting probable artifactual components, then reconstructing data back into the electrode space. This approach is commonly applied using independent component analysis (ICA). Here, we demonstrate the counterintuitive finding that due to imperfect component separation, component subtraction can artificially inflate effect sizes for event-related potentials (ERPs) and connectivity measures, bias source localisation estimates, and remove neural signals. To address this issue, we developed a method that targets cleaning to the artifact periods of eye movement components and artifact frequencies of muscle components. When tested across different EEG systems and cognitive tasks, our results showed that the targeted artifact reduction method is effective in cleaning artifacts while also reducing the artificial inflation of ERP and connectivity effect sizes and minimizing source localisation biases. Our results suggest EEG pre-processing is better when targeted cleaning is applied, as this improves preservation of neural signals and mitigates effect size inflation and source localisation biases that result from approaches which subtract artifact components across the entire time-series. These improvements enhance the reliability and validity of EEG data analysis. Our method is provided in the freely available RELAX pipeline, which includes a graphical user interface for ease of use and is available as an EEGLAB plugin (https://github.com/NeilwBailey/RELAX).

The do not eat me signal CD47 contributes to microglial phagocytosis defects and autism-like behaviors in 16p11.2 deletion mice
Various pathological characteristics of autism spectrum disorder (ASD) stem from abnormalities in brain resident immune cells, specifically microglia, to prune unnecessary synapses or neural connections during early development. Animal models of ASD exhibit an abundance of synapses in different brain regions, which is strongly linked to the appearance of ASD behaviors. Overexpression of CD47 on neurons acts as a do not eat me signal, safeguarding synapses from inappropriate pruning by microglia. Indeed, CD47 overexpression occurs in 16p11.2 deletion carriers, causing decreased synaptic phagocytosis and the manifestation of ASD characteristics. However, the role of CD47 in synaptic pruning impairment leading to ASD phenotypes in the 16p11.2 deletion mouse model is unclear. Moreover, whether blocking CD47 can alleviate ASD mice's behavioral deficits remains unknown. Here, we demonstrate a strong link between increased CD47 expression, decreased microglia phagocytosis capacity, and increased impairment in social novelty preference in the 16p11.2 deletion mice. The reduction in microglia phagocytosis caused a rise in excitatory synapses and transmission in the prefrontal cortex of 16p11.2 deletion mice. Importantly, blocking CD47 using a specific CD47 antibody or reducing CD47 expression using a specific shRNA enhanced the microglia phagocytosis and reduced excitatory transmission. Reduction in CD47 expression improved social novelty preference deficits in 16p11.2 mice. These findings demonstrate that CD47 contributes to the ASD phenotypes in the 16p11.2 deletion mice and could be a promising target for the development of treatment for ASD.

Structure of the Ion Channel Kir7.1 and Implications for its Function in Normal and Pathophysiologic States
Hereditary defects in the function of the Kir7.1 in the retinal pigment epithelium are associated with the ocular diseases retinitis pigmentosa, Leber congenital amaurosis, and snowflake vitreal degeneration. Studies also suggest that Kir7.1 may be regulated by a GPCR, the melanocortin-4 receptor, in certain hypothalamic neurons. We present the first structures of human Kir7.1 and describe the conformational bias displayed by two pathogenic mutations, R162Q and E276A, to provide an explanation for the basis of disease and illuminate the gating pathway. We also demonstrate the structural basis for the blockade of the channel by a small molecule ML418 and demonstrate that channel blockade in vivo activates MC4R neurons in the paraventricular nucleus of the hypothalamus (PVH), inhibiting food intake and inducing weight loss. Preliminary purification, and structural and pharmacological characterization of an in tandem construct of MC4R and Kir7.1 suggests that the fusion protein forms a homotetrameric channel that retains regulation by liganded MC4R molecules.

Global Progress in Competitive Co-Evolution: a Systematic Comparison of Alternative Methods
We investigate the use of competitive co-evolution for synthesizing progressively better solutions. Specifically, we introduce a set of methods to measure historical and global progress. We discuss the factors that facilitate genuine progress. Finally, we compare the efficacy of four qualitatively different algorithms. The selected algorithms promote genuine progress by creating an archive of opponents used to evaluate evolving individuals, generating archives that include high-performing and well-differentiated opponents, identifying and discarding variations that lead to local progress only (i.e. progress against a subset of possible opponents and retrogressing against a larger set). The results obtained in a predator-prey scenario, commonly used to study competitive evolution, demonstrate that all the considered methods lead to global progress in the long term. However, the rate of progress and the ratio of progress versus retrogressions vary significantly among algorithms.

Emotional Distractors Capture Attention even at Very Low Contrast Levels: ERP evidence
Emotional visual stimuli, whether appealing or aversive, preferentially capture exogenous attention due to their evolutionary significance. This study assessed whether such capacity persists at low contrast levels, where stimuli are minimally perceived. To this end, we recorded behavioral and electrophysiological (event-related potentials, ERPs) indices of attentional capture from 38 participants who were exposed to negative, neutral, and positive scenes, each presented at four distinct contrast levels. These contrast levels had previously resulted in a correct recognition rate of up to 25%, 50%, 75%, and 100% in a previous sample of 235 participants. Participants were presented with these scenes as distractors while simultaneously performing a perceptual task involving line orientation discrimination. The ERP results confirmed the expected emotional effect on exogenous attention and, critically, unveiled its persistence across all contrast levels. Specifically, occipito-parietal P1 (88-119 ms) was larger for negative than for positive distractors, while in a spreaded N2 component, positive distractors elicited larger amplitudes relative to both negative (213-354 ms) and neutral (213-525 ms) images. These findings reinforce the advantage of emotional distractors in accessing neural processing automatically and highlight the existence of a temporal negativity bias. Importantly, our novel findings emphasize the robustness of this exogenous attention pattern, present even under limited perceptual conditions.

Fast and Accurate EEG/MEG BEM-Based Forward Problem Solution for High-Resolution Head Models
A BEM (boundary element method) based approach is developed to accurately solve an EEG/MEG forward problem for a modern high-resolution head model in approximately 60 seconds using a common workstation. The method utilizes a charge-based BEM with fast multipole acceleration (BEM-FMM) and a "smart" mesh pre-refinement (called b-refinement) close to the singular source(s). No costly matrix-filling or direct solution steps typical for the standard BEM are required; the method generates on-skin voltages as well as MEG magnetic fields for high-resolution head models in approximately 60 seconds after initial model assembly. The method is verified both theoretically and experimentally.

Maternal Immune Activation imprints translational dysregulation and differential MAP2 phosphorylation in descendant neural stem cells
Alterations induced by maternal immune activation (MIA) during gestation impact the subsequent neurodevelopment of progeny, a process that in humans, has been linked to the development of several neuropsychiatric conditions. To undertake a comprehensive examination of the molecular mechanisms governing MIA, we have devised an in vitro model based on neural stem cells (NSCs) sourced from fetuses carried by animals subjected to Poly I:C treatment. These neural progenitors demonstrate proliferative capacity and can be effectively differentiated into both neurons and glial cells. Transcriptomic, proteomic, and phosphoproteomic analyses conducted on these cellular models, in conjunction with counterparts from control treatments, revealed discernible shifts in the expression levels of a specific subset of proteins implicated in neuronal function. Noteworthy, we found an absence of congruence between these alterations at the transcriptomic level, suggesting that differences in protein translation contribute to the observed dysregulation. Furthermore, the phosphoproteomic data highlighted a discernible discrepancy in the basal phosphorylation of proteins between differentiated cells from both experimental groups, particularly within proteins associated with cytoskeletal architecture and synaptic functionality, notably those belonging to the MAP family. Observed alterations in MAP phosphorylation were found to potentially have functional consequences as they correlate with changes in neuronal plasticity and the establishment of neuronal synapses. Our data agrees with previous published observations and further underscore the importance of MAP2 phosphorylation state on its function and the impact that this protein has in neuronal structure and function.

Social valence dictates sex differences in identity recognition
Social valence is the directional emotional significance affiliated with social experiences. Maladaptive processing of negative social valence (NSV) has been linked to mood disorder susceptibility, which is more prevalent in women. To determine whether there are sex differences in NSV processing, we developed social valence tasks where the identity recognition of conspecifics with distinct valences served as the readout. Male mice demonstrated identity recognition regardless of social valence. Conversely, female mice did not show identity recognition following the NSV task. In vivo calcium imaging of the dorsal CA1 further revealed sex differences in NSV processing with reduced hippocampal representation of social information in female mice. These results suggest the imprecise encoding of NSV may contribute to the heightened vulnerability to social stress-related mood disorders in women.

Mechanism of an Intrinsic Oscillation in Rat Geniculate Interneurons
Depolarizing current injections produced a rhythmic bursting of action potentials, a bursting oscillation, in a set of local interneurons in the lateral geniculate nucleus (LGN) of rats. The current dynamics underlying this firing pattern have not been determined, though this cell type constitutes an important cellular component of thalamocortical circuitry, and contributes to both pathologic and non-pathologic brain states. We thus investigated the source of the bursting oscillation using pharmacological manipulations in LGN slices in vitro and in silico. 1. Selective blockade of calcium channel subtypes revealed that high-threshold calcium currents IL and IP contributed strongly to the oscillation. 2. Increased extracellular K+ concentration (decreased K+ currents) eliminated the oscillation. 3. Selective blockade of K+ channel subtypes demonstrated that the calcium-sensitive potassium current (IAHP ) was of primary importance. A morphologically simplified, multicompartment model of the thalamic interneuron characterized the oscillation as follows: 1. The low-threshold calcium current (IT ) provided the strong initial burst characteristic of the oscillation. 2. Alternating fluxes through high-threshold calcium channels and IAHP then provided the continuing burst oscillation and interburst periods respectively. This interplay between IL and IAHP contrasts with the current dynamics underlying oscillations in thalamocortical and reticularis neurons, which primarily involve IT and IH, or IT and IAHP respectively. These findings thus point to a novel electrophysiological mechanism for generating intrinsic oscillations in a major thalamic cell type. Because local interneurons can sculpt the behavior of thalamocortical circuits, these results suggest new targets for the manipulation of ascending thalamocortical network activity.

On the epistemic role of hippocampal cells: the case of splitter cells
Over the past decades, the hippocampal formation has undergone extensive study leading researchers to identify a vast array of cells with functional properties (place cells, splitter cells, etc). In the present work, we aim at investigating whether the activity of those cells derives from the anatomy and inner circuitry of the hippocampal formation or derives instead from the actual behavior of the animal. To do so, we simulated an agent navigating inside an 8-shaped track, making alternating choices (T-maze alternating task). We designed a random network, based on the reservoir computing paradigm, that processes distance-based sensors and outputs a direction change (constant speed). Despite its simplicity, the model successfully solved the task while bearing no structural similarity with the hippocampal formation. We subsequently followed the comprehensive and recent review on splitter cells by Duvelle et al. (eLife, 2019), and applied the exact same analysis onto the activity on the cells composing our model. We were able to identify splitter cells (as well as place cells, head direction cells and decision cells) and confirm a significant portion of the theoretical hypotheses of Duvelle et al. regarding splitter cells. Beyond these results, this work strongly suggests that the activity of such cells originates from the actual behavior of the agent as opposed to any structural or anatomical origin: any model doing the same task might exhibit the same cell activity. From a broader point of view, this work questions the epistemic role of such cells in our understanding of the hippocampal formation.

Association of GLOD4 with Alzheimers Disease in Humans and Mice
Glyoxylase domain containing protein (GLOD4) is associated with Alzheimers disease (AD). We quantified GLOD4 in human AD brains, mouse AD model, and neuroblastoma N2a-APPswe cells. We found that GLOD4 was downregulated in human AD patients compared to non-AD controls. Glod4 was similarly downregulated in Blmh-/-5xFAD mouse model of AD. Downregulated Glod4 was associated with elevated A{beta} and worsened memory/sensorimotor performance in Blmh-/-5xFAD mice. Glod4 depletion in N2a-APPswe cells upregulated A{beta}PP and downregulated autophagy-related Atg5 and p62 genes. These findings suggest that Glod4 interacts with A{beta}PP and the autophagy pathway, disruption of these interactions leads to A{beta} accumulation and cognitive/neurosensory deficits.

Spatial frequency adaptation modulates population receptive field sizes
The spatial tuning of neuronal populations in the early visual cortical regions is related to the spatial frequency (SF) selectivity of neurons. However, there has been no direct investigation into how this relationship is reflected in population receptive field (pRF) sizes despite the common application of pRF mapping in visual neuroscience. We hypothesised that adaptation to high/low SF would decrease the sensitivity of neurons with respectively small/large receptive field sizes, resulting in a change in pRF sizes as measured by functional magnetic resonance imaging (fMRI). To test this hypothesis, we first quantified the SF aftereffect using a psychophysical paradigm where observers made SF judgments following adaptation to high/low SF noise patterns. We then incorporated the same adaptation technique into a standard pRF mapping procedure, to investigate the spatial tuning of the early visual cortex following SF adaptation. Results showed that adaptation to a low/high SF resulted in smaller/larger pRFs respectively, as hypothesised. Our results provide the most direct evidence to date that the spatial tuning of the visual cortex, as measured by pRF mapping, is related to the SF selectivity of visual neural populations. This has implications for various domains of visual processing, including size perception and visual acuity.

Internalized α-synuclein fibrils become truncated and resist degradation in neurons while glial cells rapidly degrade α-synuclein fibrils.
Parkinson's disease (PD) and other -synucleinopathies are characterized by the accumulation of -synuclein (S) pathology that can spread via the cell-to-cell transmission of S aggregates. To better understand how various brain cells contribute to the spreading of S pathology, we examined the metabolism of S aggreges or pre-formed fibrils (PFFs) in neuronal and glial cells (microglia, astrocytes, and oligodendrocytes). In neurons, while the full-length S rapidly disappeared following S PFF uptake, truncated S accumulated with a half-life of days rather than hours. Epitope mapping and fractionation studies indicate that S PFF was truncated at the C-terminal region following uptake and remained insoluble/aggregated. In contrast, microglia and astrocytes rapidly metabolized S PFF as the half-lives of S PFF in these glial cells were <6 hours. Differential processing of S by neurons was recapitulated in cell lines as differentiated CLU neuronal cell lines stably accumulate truncated S while undifferentiated cells rapidly metabolize S. Immunolocalization and subcellular fractionation studies show that internalized S PFF is initially localized to endosomes followed by lysosomes. The lysosome is largely responsible for the degradation of internalized S PFF as the inhibition of lysosomal function leads to the stabilization of S in all cell types. Significantly, S PFF causes lysosomal dysfunction in neurons. In summary, we show that neurons are inefficient in metabolizing internalized S aggregates, partially because S aggregates cause lysosomal dysfunction, potentially generating aggregation-prone truncated S. In contrast, glial cells may protect neurons from S aggregates by rapidly clearing S aggregates.

Disruption of Core Stress Granule Protein Aggregates Promotes CNS Axon Regeneration
Depletion or inhibition of core stress granule proteins, G3BP1 in mammals and TIAR-2 in C. elegans, increases axon regeneration in injured neurons that show spontaneous regeneration. Inhibition of G3BP1 by expression of its acidic or B-domain accelerates axon regeneration after nerve injury bringing a potential therapeutic intervention to promote neural repair in the peripheral nervous system. Here, we asked if G3BP1 inhibition is a viable strategy to promote regeneration in the injured mammalian central nervous system where axons do not regenerate spontaneously. G3BP1 B-domain expression was found to promote axon regeneration in both the mammalian spinal cord and optic nerve. Moreover, a cell permeable peptide to a subregion of G3BP1 B-domain (rodent G3BP1 amino acids 190-208) accelerated axon regeneration after peripheral nerve injury and promoted the regrowth of reticulospinal axons into the distal transected spinal cord through a bridging peripheral nerve graft. The rodent and human G3BP1 peptides promoted axon growth from rodent and human neurons cultured on permissive substrates, and this function required alternating Glu/Asp-Pro repeats that impart a unique predicted tertiary structure. These studies point to G3BP1 granules as a critical impediment to CNS axon regeneration and indicate that G3BP1 granule disassembly represents a novel therapeutic strategy for promoting neural repair after CNS injury.

Visual Identification of Conspecifics Shapes Social Behavior in Mice
Recognizing conspecifics in order to determine how to interact with them appropriately is a fundamental goal of animal sensory systems. It has undergone selective pressure in nearly all species. Mice have a large repertoire of social behaviors that are the subject of a rapidly growing field of study in neuroscience. Mouse social interactions likely incorporate all available sensory modalities, and the vast majority of studies have not attempted to isolate them. Specifically the role of vision in mouse social interactions remains unclear. We developed a behavioral platform that allowed us to present a subject mouse the visual information of stimulus mice in isolation from olfactory, acoustic, and tactile cues. Our results indicate that the visual identification of the sex or individual identity of other mice influences behavior. These findings highlight the underappreciated role of vision in mouse social interactions and open new avenues to study the visual circuits underlying social behavior.

Concurrent emergence of view invariance, sensitivity to critical features, and identity face classification through visual experience: Insights from deep learning algorithms
Visual experience is known to play a critical role in face recognition. This experience is believed to enable the formation of a view-invariant representation, by learning which features are critical for face identification across views. Discovering these critical features and the type of experience that is needed to uncover them is challenging. We have recently revealed a subset of facial features that are critical for human face recognition. We further revealed that deep convolutional neural networks (DCNNs) that are trained on face classification, but not on object categorization, are sensitive to these facial features, highlighting the importance of experience with faces for the system to reveal these critical features. These findings enable us now to ask what type of experience with faces is required for the network to become sensitive to these human-like critical features and whether it is associated with the formation of a view-invariant representation and face classification performance. To that end, we systematically manipulated the number of within-identity and between-identity face images and examined its effect on the network performance on face classification, view-invariant representation, and sensitivity to human-like critical facial features. Results show that increasing the number of images per identity as well as the number of identities were both required for the simultaneous development of a view-invariant representation, sensitivity to human-like critical features, and successful identity classification. The concurrent emergence of sensitivity to critical features, view invariance and classification performance through experience implies that they depend on similar features. Overall, we show how systematic manipulation of the training diet of DCNNs can shed light on the role of experience on the generation of human-like representations.

Cell type specific roles of FOXP1 during early neocortical murine development
Cortical development is a tightly controlled process and any deviation during development may increase the susceptibility to neurodevelopmental disorders, such as autism spectrum disorders (ASD). Numerous studies identified mutations in FOXP1, a transcription factor enriched in the neocortex, as causal for ASD and FOXP1 syndrome. Our group has shown that Foxp1 deletion in the mouse cortex leads to overall reduced cortex thickness, alterations in cortical lamination, and changes in the relative thickness of cortical layers. However, the developmental and cell type-specific mechanisms underlying these changes remained unclear. This work characterizes the developmental requirement of neocortical Foxp1 at key embryonic and perinatal ages using a conditional knock-out of Foxp1. We find that Foxp1 deletion results in accelerated pseudo-age during early neurogenesis, increased cell cycle exit during late neurogenesis, altered gene expression and chromatin accessibility, and selective migration deficits in a subset of upper-layer neurons. These data explain the postnatal differences observed in cortical layers and relative cortical thickness. We also highlight genes regulated by FOXP1 and their enrichment with high-confidence ASD or synaptic genes. Together, these results underscore a network of neurodevelopmental disorder-related genes that may serve as potential modulatory targets for postnatal modification relevant to ASD and FOXP1 syndrome.

Sigh generation in preBötzinger Complex
We explored neural mechanisms underlying sighing. Photostimulation of parafacial (pF) neuromedin B (NMB) or gastrin releasing peptide (GRP), or preBotzinger Complex (preBotC) NMBR or GRPR neurons elicited ectopic sighs with latency inversely related to time from preceding endogenous sigh. Of particular note, ectopic sighs could be produced without involvement of these peptides or their receptors in preBotC. Moreover, chemogenetic or optogenetic activation of preBotC SST neurons induced sighing, even in the presence of NMBR and/or GRPR antagonists. We propose that an increase in the excitability of preBotC NMBR or GRPR neurons not requiring activation of their peptide receptors activates partially overlapping pathways to generate sighs, and that preBotC SST neurons are a downstream element in the sigh generation circuit that converts normal breaths into sighs.

Three-dimensional chromatin mapping of sensory neurons reveals that cohesin-dependent genomic domains are required for axonal regeneration
The in vivo three-dimensional genomic architecture of adult mature neurons at homeostasis and after medically relevant perturbations such as axonal injury remains elusive. Here we address this knowledge gap by mapping the three-dimensional chromatin architecture and gene expression programme at homeostasis and after sciatic nerve injury in wild-type and cohesin-deficient mouse sensory dorsal root ganglia neurons via combinatorial Hi-C and RNA-seq. We find that cohesin is required for the full induction of the regenerative transcriptional program, by organising 3D genomic domains required for the activation of regenerative genes. Importantly, loss of cohesin results in disruption of chromatin architecture at regenerative genes and severely impaired nerve regeneration. Together, these data provide an original three-dimensional chromatin map of adult sensory neurons in vivo and demonstrate a role for cohesin-dependent chromatin interactions in neuronal regeneration.

Experienced meditators show greater forward travelling cortical alpha wave strengths
Mindfulness meditation involves training attention, commonly towards the current sensory experience, with an attitude of non-judgemental awareness. Theoretical perspectives suggest meditation alters the brain's predictive processing mechanisms, increasing the synaptic gain and precision with which sensory information is processed, and reducing the generation or elaboration of higher-order beliefs. Recent research suggests that forwards and backwards travelling cortical alpha waves provide an indication of these predictive processing functions. Here, we used electroencephalography (EEG) to test whether the strength of forwards and backwards travelling cortical alpha waves differed between experienced meditators and a matched sample of non-meditators, both during an eyes-closed resting state (N = 97) and during a visual cognitive (Go/No-go) task (N = 126). Our results showed that meditators produced stronger forwards travelling cortical alpha waves compared to non-meditators, both while resting with their eyes closed and during task performance. Meditators also exhibited weaker backwards travelling cortical alpha wave strength while resting with their eyes closed. These results may be indicative of a neural mechanism underpinning enhanced attention associated with meditation practice, as well as a potential neural marker of the reductions in resting mind-wandering that are suggested to be associated with meditation practice. The results also support models of brain function that suggest attention modification can be achieved by mental training aimed at increased processing of sensory information, which might be indexed by greater strength of forwards travelling cortical alpha waves.

Characterization of β-Hydroxybutyrate as a Cell Autonomous Fuel for Active Excitatory and Inhibitory Neurons
The ketogenic diet is an effective treatment for drug-resistant epilepsy, but the therapeutic mechanisms are poorly understood. Although ketones are able to fuel the brain, it is not known whether ketones are directly metabolized by neurons on a time scale sufficiently rapid to fuel the bioenergetic demands of sustained synaptic transmission. Here, we show that nerve terminals can use the ketone {beta}-hydroxybutyrate in a cell-autonomous fashion to support neurotransmission in both excitatory and inhibitory nerve terminals and that this flexibility relies on Ca2+ dependent upregulation of mitochondrial metabolism. Using a genetically encoded ATP sensor, we show that inhibitory axons fueled by ketones sustain much higher ATP levels under steady state conditions than excitatory axons, but that the kinetics of ATP production following activity are slower when using ketones as fuel compared to lactate/pyruvate for both excitatory and inhibitory neurons.

Long term rescue of Alzheimer deficits in vivo by one-time gene-editing of App C-terminus.
Gene-editing technologies promise to create a new class of therapeutics that can achieve permanent correction with a single intervention. Besides eliminating mutant alleles in familial disease, gene-editing can also be used to favorably manipulate upstream pathophysiologic events and alter disease-course in wider patient populations, but few such feasible therapeutic avenues have been reported. Here we use CRISPR-Cas9 to edit the last exon of amyloid precursor protein (App), relevant for Alzheimer disease (AD). Our strategy effectively eliminates an endocytic (YENPTY) motif at APP C-terminus, while preserving the N-terminus and compensatory APP-homologues. This manipulation favorably alters events along the amyloid-pathway; inhibiting toxic APP-beta-cleavage fragments (including amyloid-beta; and upregulating neuroprotective APP-alpha-cleavage products. AAV-driven editing ameliorates neuropathologic, electrophysiologic, and behavioral deficits in an AD knockin mouse model. Effects persist for many months, and no abnormalities are seen in WT mice even after germline App-editing; underlining overall efficacy and safety. Pathologic alterations in the glial-transcriptome of App-KI mice, as seen by single nuclei RNA-sequencing (sNuc-Seq), are also normalized by App C-terminus editing. Our strategy takes advantage of innate transcriptional rules that render terminal exons insensitive to nonsense-decay, and the upstream manipulation is expected to be effective for all forms of AD. These studies offer a path for a one-time disease-modifying treatment for AD.

Multi-modal Spatial-modality Attentive Fusion for Studying Neurodegenerative Disorders
Multi-modal learning has emerged as a powerful technique that leverages diverse data sources to enhance learning and decision-making processes. Adapting this approach to analyzing data collected from different biological domains is intuitive, especially for studying neuropsychiatric disorders. A complex neuropsychiatric disorder like schizophrenia (SZ) can affect multiple aspects of the brain and biologies. These biological sources each present distinct yet correlated expressions of underlying physiological processes. Joint learning from these data sources can improve our understanding of the disorder. However, combining these biological sources is challenging for several reasons: (i) observations are domains-specific, leading to data being represented in dissimilar subspaces, and (ii) fused data is often noisy and high-dimensional, making it challenging to identify relevant information. To address these challenges, we propose a multi-modal artificial intelligence (AI) model with a novel fusion module inspired by a bottleneck attention module (BAM). We use deep neural networks (DNN) to learn latent space representations of the input streams. Next, we introduce a two-dimensional (spatio-modality) attention module to regulate the intermediate fusion for SZ classification. We implement spatial attention via a dilated convolutional neural network that creates large receptive fields for extracting significant contextual patterns. The resulting joint learning framework maximizes complementarity allowing us to explore the correspondence among the modalities. We test our model on a multi-modal imaging-genetic dataset and achieve an SZ prediction accuracy of 94.10% (P < 0.0001), outperforming state-of-the-art unimodal and multi-modal models for the task. Moreover, the model provides inherent interpretability that helps identify concepts significant for the neural network decision and explains the underlying physiopathology of the disorder. Results also show that functional connectivity among subcortical, sensorimotor, and cognitive control domains plays an important role in characterizing SZ. Analysis of the spatio-modality attention scores suggests that structural components like the supplementary motor area, caudate, and insula play a significant role in SZ. Biclustering the attention scores discover a multi-modal cluster that includes genes CSMD1, ATK3, MOB4, and HSPE1, all of which have been identified as relevant to schizophrenia. In summary, feature attribution appears to be especially useful for probing the transient and confined but decisive patterns of complex disorders, and it shows promise for extensive applicability in future studies.