bioRxiv Subject Collection: Neuroscience's Journal

Errors of attention adaptively warp spatial memory
Adaptation is the process by which we adjust internal models of the body, world, and mind in response to sensory feedback. While adaptation is studied extensively in the context of motor control, there is limited evidence that cognitive functions such as working memory are subject to the same error-driven adaptive control mechanism. To examine the possibility that working memory representations undergo adaptation, we had participants perform a task that interleaved a perceptual discrimination task and a spatial working memory task. Perceptual discrimination trials (85% of trials) presented an initial peripheral cue to exogenously capture attention, immediately followed by a displaced target stimulus. This sequence of events served to repeatedly induce a covert attentional allocation error. Interleaved spatial working memory trials (15% of trials) presented a stimulus at a pseudorandom peripheral location followed by a delay interval. On half of the working memory trials, the stimulus was surreptitiously presented at the same location as the initial attentional cue. We found that as attentional errors accumulated over the course of the experiment, participants' working memory recall shifted in the direction of the attentional error. The magnitude of this shift was proportional to the number of induced errors. Recall performance rapidly recovered following the offset of error trials. Multiple control experiments ruled out alternative explanations for these results such as oculomotor confounds and attentional biases unrelated to error. These findings indicate that the computational mechanisms governing the adaptive control of motor commands appear to similarly serve to adjust and calibrate memory processes.

Hematopoietic growth factors Regulate Entry of Monocytes into the Adult Brain via Chemokine Receptor CCR5
Monocytes are circulating macrophage precursors and are generated from bone marrow hematopoietic stem cells. In the adults, monocytes continuously replenish cerebral border-associated macrophages under a physiological condition. Monocytes also rapidly infiltrate into the brain in the settings of pathological conditions. The mechanisms of recruiting monocyte-derived macrophages into the brain under pathological conditions have been extensively studied. However, it remains unclear how monocytes enter the brain for renewal of border-associated macrophages under the physiological condition. Using both in vitro and in vivo approaches, this study reveals that the combination of two hematopoietic growth factors, stem cell factor, SCF, and granulocyte colony stimulating factor, GCSF, complementarily and synergistically enhances adhesion of monocytes to cerebral endothelial cells in a dose dependent manner. Cysteine-cysteine chemokine receptor 5, CCR5, in brain endothelial cells, but not cell adhesion molecules mediating neuroinflammation related infiltration of monocyte derived macrophages, modulates the SCF-GCSF-enhanced monocyte-endothelial cell adhesion. Blocking CCR5 or genetically deleting CCR5 reduces monocyte-endothelial cell adhesion induced by SCF-GCSF. SCF-GCSF-enhanced recruitment of bone marrow-derived monocytes-macrophages in cerebral perivascular space is also reduced in adult CCR5 knockout mice. This study demonstrates the contribution of SCF and GCSF in regulating the entry of monocytes into the adult brain to replenish perivascular macrophages.

Sensorimotor faculties bias perceptual decision-making
Decision-making is a deliberate process that seemingly evolves under our own volition. Yet, research on embodied cognition has demonstrated that higher-order cognitive processes may be influenced, in unexpected ways, by properties of motor and sensory and systems. Here we tested whether and how simple decisions are influenced by handedness and by asymmetries in the auditory system. Right- and left- handed participants perform an auditory decision task. In the task, subjects decided whether they heard more click sounds in the right ear or in the left ear, and pressed a key with either their right or left index finger, according to an instructed stimulus-key assignment (congruent or reversed). On some trials, there was no stimulus and subjects could choose either of the responses freely. When subjects chose freely, their choices were substantially governed by their handedness: Left-handed subjects were significantly biased to make the leftward choice, whereas right-handed subjects showed a substantial rightward bias. When the choice was governed by the sensory stimulus, subjects showed a rightward choice bias under the congruent key assignment, but this effect reversed to a leftward choice bias under the reversed key assignment. This result indicates a bias towards deciding that there were more clicks presented to the right ear. Together, our findings demonstrate that human choices can be considerably influenced by properties of motor and sensory systems.

Differential effects of aging and epilepsy in discriminating and reactivating memories
Pattern separation and pattern completion are distinct neurocognitive processes involved in encoding and retrieval of memories. However, there is currently no robust behavioural task in humans to measure both processes within the same paradigm. We describe the Memory Pinhole task, a novel paradigm which offers a distinct measure of each process, applied to healthy young, healthy older and people with epilepsy. Both pattern separation and pattern completion are observed in healthy younger individuals. A pattern completion deficit is seen in people with epilepsy, while the healthy older cohort show a deficit in pattern separation. To understand the neural mechanisms, we simulated human performance using an auto-associative neural network. Modelling indicated that disruption in different neuronal populations could explain the distinct memory profiles observed in ageing and epilepsy. These results demonstrate that pattern separation and pattern completion are distinct processes that can be measured from a single behavioural task and are differentially affected by ageing and epilepsy.

Concurrent predictive and prospective strategies in a simple visuomotor task
Interception, a fundamental visuomotor skill for activities such as driving and sports, involves two main strategies: predictive, anticipating the target's trajectory, and prospective, actively tracking and adjusting movement. Experimentally controlled factors could potentially influence the relative usage of these strategies. We designed a visuomotor task to probe the relationship between target predictability and interception strategies. We manipulated stimulus predictability through controlled adjustments of external forces, altering the target's trajectory. We also manipulated the availability of perceptual information by introducing spatial occlusion at specific parts of the visual field. Our observations indicate that decreased target variability promoted predictive interception, whereas increased variability prompted a shift toward prospective strategies. Notably, hand-catching trajectories exhibited increased curvature in response to changes in target variability, whereas eye trajectories displayed a relatively consistent curvature across trials. Similarly, heightened target variability resulted in delayed onset of hand movements while showing no discernible alterations in the onset of eye movements. Thus, gaze position was a poor predictor of hand position, highlighting distinct adaptive patterns for hand and eye movements in response to task unpredictability. Finally, participants exhibited consistent interception strategies within and across sessions, highlighting their differences and preferences for predictive or prospective strategies. These results reveal a dynamic interplay between target predictability and interception, suggesting a flexible combination of both approaches. Examining how humans integrate sensory information, plan, and execute movements provides a unique opportunity to characterize predictive and prospective interception strategies in dynamic, real-world scenarios.

Rapid modulation of striatal cholinergic interneurons and dopamine release by satellite astrocytes
Astrocytes are increasingly thought to have underestimated and important roles in modulating neuronal circuits. Astrocytes in striatum can regulate dopamine transmission by governing the extracellular tone of axonal neuromodulators, including GABA and adenosine. However, here we reveal that striatal astrocytes occupy a cell type-specific anatomical and functional relationship with cholinergic interneurons (ChIs), through which they rapidly excite ChIs and govern dopamine release via nicotinic acetylcholine receptors on subsecond timescales. We identify that ChI somata are in unexpectedly close proximity to astrocyte somata, in mouse and human, forming a soma-to-soma satellite-like configuration not typically observed for other striatal neurons. Transient depolarization of astrocytes in mouse striatum reversibly regulated ChI excitability by decreasing extracellular calcium. These findings reveal a privileged satellite astrocyte-interneuron interaction for striatal ChIs operating on subsecond timescales via regulation of extracellular calcium dynamics to shape downstream striatal circuit activity and dopamine signaling.

MEA-seqX: High-resolution Profiling of Large-scale Electrophysiological and Transcriptional Network Dynamics
Concepts of brain function imply congruence and mutual causal influence between molecular events and neuronal activity. Decoding entangled information from concurrent molecular and electrophysiological network events demands innovative methodology bridging scales and modalities. Our MEA-seqX platform, integrating high-density microelectrode arrays, spatial transcriptomics, optical imaging, and advanced computational strategies, enables the simultaneous recording and analysis of molecular and electrical network activities at the level of individual cells. Applied to a mouse hippocampal model of experience-dependent plasticity, MEA-seqX unveiled massively enhanced nested dynamics between transcription and function. Graph-theoretic analysis revealed an increase in densely connected bimodal hubs, marking the first observation of coordinated spatiotemporal dynamics in hippocampal circuitry at both molecular and functional levels. This platform also identified different cell types based on their distinct bimodal profiles. Machine-learning algorithms accurately predicted network-wide electrophysiological features from spatial gene expression, demonstrating a previously inaccessible convergence across modalities, time, and scales.

Linking heartbeats with the cortical network dynamics involved in self-other distinction during affective touch.
Research on interoception has revealed the role of heartbeats in shaping our perceptual awareness and embodying a first-person perspective. These heartbeat dynamics exhibit distinct responses to various types of affective touch. We advanced that those dynamics are directly associated to the brain activity that allow self-other distinction. In our study encompassing self and social affective touch, we employed a method to quantify the distinct couplings of temporal patterns in cardiac sympathetic and parasympathetic activities with brain connectivity. Our findings revealed that social touch led to an increase in the coupling between specific brain networks and parasympathetic/vagal activity, particularly in the alpha, beta, and gamma bands. Conversely, as social touch progressed, we observed a decrease in the coupling between brain networks and sympathetic dynamics across a broad frequency range. These results show how heartbeat dynamics are intertwined with brain organization and provide fresh evidence on the neurophysiological mechanisms of affective touch.

Benefits of spaced learning are predicted by re-encoding of past experience in ventromedial prefrontal cortex
More than a century of research shows that spaced learning improves long-term memory. Yet, there remains debate concerning why. A major limitation to resolving theoretical debates is the lack of evidence for how neural representations change as a function of spacing. Here, leveraging a massive-scale 7T human fMRI dataset, we tracked neural representations and behavioral expressions of memory as participants viewed thousands of natural scene images that repeated at lags ranging from seconds to many months. We show that spaced learning increases the similarity of human ventromedial prefrontal cortex representations across stimulus encounters and, critically, these increases parallel and predict the behavioral benefits of spacing. Additionally, we show that these spacing benefits critically depend on remembering and, in turn, 're-encoding' past experience. Collectively, our findings provide fundamental insight into how spaced learning influences neural representations and why spacing is beneficial.

Test Retest Reliability of Meta Analytic Networks During Naturalistic Viewing
Functional connectivity analyses have given considerable insights into human brain function and organization. As research moves towards clinical application, test-retest reliability has become a main focus of the field. So far, the majority of studies have relied on resting-state paradigms to examine brain connectivity, based on its low demand and ease of implementation. However, the reliability of resting-state measures is mostly moderate, potentially due to its unconstrained nature. Recently, naturalistic viewing paradigms have gained popularity because they probe the human brain under more ecologically valid conditions, thereby possibly increasing reliability. Therefore, we here compared the reliability of graph metrics extracted from resting-state and naturalistic viewing in functional networks, across two sessions. We show that naturalistic viewing can increase reliability over resting-state, but that its effect varies between stimuli and networks. Furthermore, we demonstrate that the effect of naturalistic viewing differs between two cohorts with Asian and European cultural backgrounds. Taken together, our study encourages the use of naturalistic viewing to increase reliability, but emphasizes the need to carefully select the appropriate stimulus and network for the respective research question.

An anesthetized rat assay for evaluating the effects of organophosphate-based compounds and countermeasures on intracranial EEG and respiratory rate.
The development of medical countermeasures (MCMs) against organophosphate (OP) induced poisoning is of substantial importance. Use of conventional therapeutics is complicated by off-target effects and restricted penetration of the blood-brain barrier (BBB). Therefore, a concerted effort is underway to discover improved acetylcholinesterase (AChE) reactivators, muscarinic acetylcholine receptor (mAChR) antagonists, and other countermeasures with broader spectrum activity and enhanced CNS efficacy. We recently developed a rat brain slice assay to assess the efficacy of AChE reactivators and mAChR antagonists against the acute effects of the organophosphorus AChE inhibitor 4-nitrophenyl isopropyl methylphosphonate (NIMP) in the basolateral amygdala (BLA). Here we introduce a complimentary anesthetized animal model to evaluate the same compounds in vivo with concurrent monitoring of EEG and respiratory rate. We find that intravenous delivery of 0.5 mg/kg NIMP reliably produces seizure like activity in the BLA, with concurrent respiratory depression and eventual respiratory failure. The central effects of AChE reactivators and mAChR antagonists delivered intravenously are consistent with their expected ability to cross the BBB. Combining our previously described in vitro assay with the methods described here provides a relatively comprehensive set of preclinical tools for evaluating the efficacy of novel MCMs. Notably, using these methods potentially obviates subjecting conscious animals to cholinergic crises, which aligns with the AAALAC's 3Rs principle of refinement.

Functional Magnetic Resonance Spectroscopy of Prolonged Motor Activation using Conventional and Spectral GLM Analyses
Background: Functional MRS (fMRS) is a technique used to measure metabolic changes in response to increased neuronal activity, providing unique insights into neurotransmitter dynamics and neuroenergetics. In this study we investigate the response of lactate and glutamate levels in the motor cortex during a sustained motor task using conventional spectral fitting and explore the use of a novel analysis approach based on the application of linear modelling directly to the spectro-temporal fMRS data. Methods: fMRS data were acquired at a field strength of 3 Tesla from 23 healthy participants using a short echo-time (28ms) semi-LASER sequence. The functional task involved rhythmic hand clenching over a duration of 8 minutes and standard MRS preprocessing steps, including frequency and phase alignment, were employed. Both conventional spectral fitting and direct linear modelling were applied, and results from participant-averaged spectra and metabolite-averaged individual analyses were compared. Results: We observed a 20% increase in lactate in response to the motor task, consistent with findings at higher magnetic field strengths. However, statistical testing showed some variability between the two averaging schemes and fitting algorithms. While lactate changes were supported by the direct spectral modelling approach, smaller increases in glutamate (2%) were inconsistent. Exploratory spectral modelling identified a 4% decrease in aspartate, aligning with conventional fitting and observations from prolonged visual stimulation. Conclusion: We demonstrate that lactate dynamics in response to a prolonged motor task are observed using short-echo time semi-LASER at 3 Tesla, and that direct linear modelling of fMRS data is a useful complement to conventional analysis. Future work includes mitigating spectral confounds, such as scalp lipid contamination and lineshape drift, and further validation of our novel direct linear modelling approach through experimental and simulated datasets.

Abscisic Acid rescues behavior in adult female mice in Attention Deficit Disorder with Hyperactivity model of dopamine depletion by regulating microglia and vesicular GABA transporter
Background: Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental syndrome influenced by both genetic and environmental factors. While genetic studies have highlighted catecholamine dysfunction, emerging epidemiological evidence suggest neuroinflammation as a significant trigger. However, understanding the relative contributions of these alterations to ADHD symptomatology remains elusive. Method: This study employed 93 female Swiss mice of the ADHD dopamine deficit model. Dopaminergic lesions were induced via 6-hydroxidopamine (6-OHDA) injection on postnatal day 5. The impact of these lesions during development was examined by comparing young and adult mice (at postnatal day 21 and 90, respectively). We sought to mitigate adult symptoms through abscisic acid (ABA) administration during two-months. Postmortem analyses encompassed the evaluation of neuroinflammation (microglia morphology, NLRP3 inflammasome activation, cytokine expression) and excitatory/inhibitory (E/I) ratio in specific brain regions. Results: Neonatal dopaminergic lesions elicited hyperactivity, impulsivity, hypersensitivity increased social interaction in both one-month and three-month females and induced impaired memory in three-month mice. ABA exposure significantly ameliorated hyperactivity, impulsivity, anxiety, hypersensitivity, and social interaction alterations, but not cognitive impairment. In the anterior cingulate cortex (ACC) of one-month mice dopamine-deficit elevated IL-1{beta} and TNF-alpha; expression and reduced Arg1 mRNA levels, along with E/I imbalance. ABA intervention restored microglia morphology, IL-1beta, Arg1 expression and enhanced vGAT levels. Conclusions: This study strongly suggest that dopamine deficit induced alteration of microglia and E/I ratio underling distinct ADHD symptoms. Reinstating healthy microglia by anti-inflammatory agents in specific areas emerges as a promising strategy for managing ADHD

Investigating tissue microstructure using steady-state diffusion MRI
Diffusion MRI is a leading method to non-invasively characterise brain tissue microstructure across multiple domains and scales. Diffusion-weighted steady-state free precession (DW-SSFP) is an established imaging sequence for post-mortem MRI, addressing the challenging imaging environment of fixed tissue with short T2 and low diffusivities. However, a current limitation of DW-SSFP is signal interpretation: it is not clear what diffusion 'regime' the sequence probes and therefore its potential to characterise tissue microstructure. Building on a model of Extended Phase Graphs (EPG), I establish two alternative representations of the DW-SSFP signal in terms of (1) conventional b-values (time-independent diffusion) and (2) encoding power-spectra (time-dependent diffusion). The proposed representations provide insights into how different parameter regimes and gradient waveforms impact the diffusion properties of DW-SSFP. Using these representations, I introduce an approach to incorporate existing diffusion models into DW-SSFP without the requirement of extensive derivations. Investigations incorporating free-diffusion and tissue-relevant microscopic restrictions (cylinder of varying radius) give excellent agreement to complementary analytical models and Monte Carlo simulations. Experimentally, the time-independent representation is used to derive Tensor and proof of principle NODDI estimates in a whole human post-mortem brain. A final SNR-efficiency investigation demonstrates the theoretical potential of DW-SSFP for ultra-high field microstructural imaging.

Unexpected events modulate context signaling in VIP and excitatory cells of the visual cortex
The visual cortex plays a significant role in constructing internal models that predict incoming sensory experiences. Unexpected stimuli that violate those predictions play an important role in how neural circuits learn these internal models. The cortical inhibitory network, particularly VIP cells, is hypothesized to act as a key player in representing unexpected stimuli due to its unique anatomical connectivity motifs; however, the exact information carried by VIP neurons during unexpected events remains unclear: to what extent does VIP activity reflect stimulus-specific prediction violations vs. broad context information such as shared network dynamics that may arise from the animal's internal representations or external cues signals? To address this question, we analyzed a dataset of cell-type specific, multi-area, two-photon calcium imaging during a behavioral task collected by the Allen Institute. Mice viewed repeated familiar images, as well as unexpected omissions of such images. Using dimensionality reduction, we extracted the contribution of context to the activity of individual neurons, defined as the shared neuronal activity across brain areas that is not driven by images or omissions. We demonstrate that during omissions the activity of VIP neurons in V1 and higher visual area LM is highly influenced by context, particularly in superficial layers. Excitatory neurons across all recorded layers and areas switched from weakly modulation by context during expected images to being largely modulated by context during unexpected omission. Our results suggest that during expected images context information is suppressed to allow for external stimuli to drive neuronal activity. Conversely, during unexpected omissions, VIP neurons function as non-specific error encoders, driving cortical networks to attend to context.

POSTERIOR-SUPERIOR INSULA REPETITIVE TRANSCRANIAL MAGNETIC STIMULATION REDUCES EXPERIMENTAL TONIC PAIN AND PAIN-RELATED CORTICAL INHIBITION IN HUMANS
High frequency repetitive transcranial magnetic stimulation (rTMS) to the posterosuperior insula (PSI) may produce analgesic effects. However, the neuroplastic changes behind PSI-rTMS analgesia remain poorly understood. The present study aimed to determine whether tonic capsaicin-induced pain and cortical inhibition (indexed using TMS-electroencephalography) are modulated by PSI-rTMS. Twenty healthy volunteers (10 females) attended two sessions randomized to active or sham rTMS. Experimental pain was induced by capsaicin administered to the forearm for 90 minutes, with pain ratings collected every 5 minutes. Left PSI-rTMS was delivered (10Hz, 100 pulses per train, 15 trains) ~50 minutes post-capsaicin administration. TMS-evoked potentials (TEPs) and thermal sensitivity were assessed at baseline, during capsaicin pain prior to rTMS and after rTMS. Bayesian evidence of reduced pain scores and increased heat pain thresholds were found following active rTMS, with no changes occurring after sham rTMS. Pain (prior to active rTMS) led to an increase in the frontal negative peak ~45 ms (N45) TEP relative to baseline. Following active rTMS, there was a decrease in the N45 peak back to baseline levels. In contrast, following sham rTMS, the N45 peak was increased relative to baseline. We also found that the reduction in pain NRS scores following active vs. sham rTMS was partially mediated by decreases in the N45 peak. These findings provide evidence of the analgesic effects of PSI-rTMS and suggest that the TEP N45 peak is a potential marker and mediator of both pain and analgesia.

Transition to chaos separates learning regimes and relates to measure of consciousness in recurrent neural networks
Recurrent neural networks exhibit chaotic dynamics when the variance in their connection strengths exceed a critical value. Recent work indicates connection variance also modulates learning strategies; networks learn "rich" representations when initialized with low coupling and "lazier" solutions with larger variance. Using Watts-Strogatz networks of varying sparsity, structure, and hidden weight variance, we find that the critical coupling strength dividing chaotic from ordered dynamics also differentiates rich and lazy learning strategies. Training moves both stable and chaotic networks closer to the edge of chaos, with networks learning richer representations before the transition to chaos. In contrast, biologically realistic connectivity structures foster stability over a wide range of variances. The transition to chaos is also reflected in a measure that clinically discriminates levels of consciousness, the perturbational complexity index (PCIst). Networks with high values of PCIst exhibit stable dynamics and rich learning, suggesting a consciousness prior may promote rich learning. The results suggest a clear relationship between critical dynamics, learning regimes and complexity-based measures of consciousness.

Reducing neuronal nitric oxide synthase (nNOS) expression in the ventromedial hypothalamus (VMH) increases body weight and blood glucose levels while decreasing physical activity in female mice.
Glucose-inhibited (GI) neurons of the ventromedial hypothalamus (VMH) depend on neuronal nitric oxide synthase (nNOS) and AMP-activated protein kinase (AMPK) for activation in low glucose. The Lopez laboratory has shown that the effects of estrogen on brown fat thermogenesis and white fat browning require inhibition of VMH AMPK. This effect of estrogen was mediated by downstream lateral hypothalamus (LH) orexin neurons (1,2). We previously showed that estrogen inhibits activation of GI neurons in low glucose by inhibiting AMPK (3). Thus, we hypothesized that VMH AMPK- and nNOS-dependent GI neurons project to and inhibit orexin neurons. Estrogen inhibition of AMPK in GI neurons would then disinhibit orexin neurons and stimulate brown fat thermogenesis and white fat browning, leading to decreased body weight. To test this hypothesis, we reduced VMH nNOS expression using nNOS shRNA in female mice and measured body weight, adiposity, body temperature, white and brown fat uncoupling protein (UCP1; an index of thermogenesis and browning), locomotor activity, and blood glucose levels. Surprisingly, we saw no effect of reduced VMH nNOS expression on body temperature or UCP1. Instead, body weight and adiposity increased by 30% over 2 weeks post injection of nNOS shRNA. This was associated with increased blood glucose levels and decreased locomotor activity. We also found that VMH nNOS-GI neurons project to the LH. However, stimulation of VMH-LH projections increased excitatory glutamate input onto orexin neurons. Thus, our data do not support our original hypothesis. Excitation of orexin neurons has previously been shown to increase physical activity, leading to decreased blood glucose and body weight (4). We now hypothesize that VMH nNOS-GI neurons play a role in this latter function of orexin neurons.

Surround Suppression of Broadband Images
Visual perception is profoundly sensitive to context. Surround suppression is a well-known visual context effect in which the firing rate of a neuron is suppressed by stimulation of its extra-classical receptive field. The majority of contrast surround suppression studies exclusively use narrowband, sinusoidal grating stimuli; however, it is unclear whether the results produced by such artificial stimuli generalize to real-world, naturalistic visual experiences. To address this issue, we developed a contrast discrimination paradigm that includes both naturalistic broadband textures and narrowband grating textures. All textures were matched for first order image statistics and overall perceptual salience. We observed surround suppression across broadband textures (F(1,6)=19.01, p=.005); however, effect sizes were largest for narrowband, sinusoidal gratings (Cohen's d=1.83). Among the three broadband texture types, we observed strongest suppression for the texture with a clear dominant orientation (stratified: Cohen's d=1.29), while the textures with a more even distribution of orientation information produced weaker suppression (fibrous: Cohen's d=0.63; braided: Cohen's d=0.65). We also observed an effect of texture identity on the slope of psychometric functions (F(1.98,11.9)=7.29, p=0.01), primarily driven by smaller slopes for the texture with the most uniform distribution of orientations. Our results suggest that well-known contextual modulation effects only partially generalize to more ecologically valid stimuli.

Excitoprotective effects of conditional tau reduction in excitatory neurons and in adulthood
Tau reduction is a promising therapeutic strategy for Alzheimer's disease. In numerous models, tau reduction via genetic knockout is beneficial, at least in part due to protection against hyperexcitability and seizures, but the underlying mechanisms are unclear. Here we describe the generation and initial study of a new conditional Tauflox model to address these mechanisms. Given the protective effects of tau reduction against hyperexcitability, we compared the effects of selective tau reduction in excitatory or inhibitory neurons. Tau reduction in excitatory neurons mimicked the protective effects of global tau reduction, while tau reduction in inhibitory neurons had the opposite effect and increased seizure susceptibility. Since most prior studies used knockout mice lacking tau throughout development, we crossed Tauflox mice with inducible Cre mice and found beneficial effects of tau reduction in adulthood. Our findings support the effectiveness of tau reduction in adulthood and indicate that excitatory neurons may be a key site for its excitoprotective effects.

Activation of the proteasome 20S Core particle prevents neuronal death induced by oxygen- and glucose deprivation in cultured neurons
Neuronal damage in brain ischemia is characterized by a disassembly of the proteasome and a decrease in its activity. However, to what extent these alterations are coupled to neuronal death is controversial since proteasome inhibitors were shown to provide protection in different models of stroke in rodents. This question was addressed in the present work using cultured cerebrocortical neurons subjected to transient oxygen- and glucose-deprivation (OGD). Under the latter conditions there was a time-dependent loss in the proteasome activity, determined by cleavage of the Suc-LLVY-AMC fluorogenic substrate, and the disassembly of the proteasome, as assessed by native-polyacrylamide gel electrophoresis followed by western blot against Psma2 and Rpt6, which are components of the catalytic core and regulatory particle, respectively. Immunocytochemistry experiments against the two proteins also showed differential effects on their dendritic distribution. OGD also downregulated the protein levels of Rpt3 and Rpt10, two components of the regulatory particle, by a mechanism dependent on the activity of NMDA receptors and mediated by calpains. Activation of the proteasome activity, using an inhibitor USP14, a deubiquitinase enzyme, inhibited OGD-induced cell death, and decreased calpain activity as determined by analysis of spectrin cleavage. Similar results were obtained in the presence of two oleic amide derivatives (B12 and D3) which directly activate the 20S proteasome. Together, these results shown that calpain activation prevents neuronal death in cortical neurons subjected to OGD, suggesting that inhibition of the proteasome is a mediator of neuronal death in brain ischemia.

Meta-Reinforcement Learning reconciles surprise, value and control in the anterior cingulate cortex.
The role of the dorsal anterior cingulate cortex (dACC) in cognition is a frequently studied yet highly debated topic in neuroscience. Most authors agree that the dACC is involved in either cognitive control (e.g. voluntary inhibition of automatic responses) or monitoring (e.g. comparing expectations with outcomes, detecting errors, tracking surprise). A consensus on which theoretical perspective best explains dACC contribution to behaviour is still lacking. In a recent neuroimaging study, the experimental predictions of two prominent models formalizing the cognitive control hypothesis (Expected Value of Control, EVC) and the monitoring hypothesis (Predicted Response Outcome, PRO) have been tested using a behavioural task involving both monitoring and cognitive control mechanisms. The results indicated that of the two tested models, only the PRO model effectively predicted the dACC activity, indicating surprise tracking for performance monitoring as the key sole underlying mechanism, even when cognitive control was required by the task at hand. These findings challenged the long-standing and established cognitive control hypothesis of dACC function and opened a theory crisis: the proposed surprise-monitoring hypothesis indeed cannot account for a wide array of previous experimental findings evidencing dACC activation in tasks requiring cognitive control without involving monitoring or surprise. Here we propose a novel hypothesis on dACC function that integrates both the monitoring and the cognitive control perspective in a unifying coherent framework, based on meta-Reinforcement Learning. Our model, the Reinforcement Meta Learner (RML), optimizes cognitive control - as in control models like EVC- by meta-learning based on tracking surprise - as in monitoring models like PRO. We tested RML experimental predictions with the same behavioural task used to compare the PRO and EVC models, and showed that RML predictions on dACC activity matched PRO predictions and outperformed EVC predictions. However, crucially, the RML simultaneously accounts for both cognitive control and monitoring functions, resolving the theoretical impasse about dACC function within an integrative framework. In sum, our results suggest that dACC function can be framed as a meta-learning optimiser of cognitive control, providing an integrative perspective on its roles in cognitive control, surprise tracking, and performance monitoring.

Genetic screening and metabolomics identify glial adenosine metabolism as a therapeutic target in Parkinson's disease
Parkinson's disease (PD) is the second most common neurodegenerative disorder and lacks disease-modifying therapies. We developed a Drosophila model for identifying novel glial-based therapeutic targets for PD. Human alpha-synuclein is expressed in neurons and individual genes are independently knocked down in glia. We performed a forward genetic screen, knocking down the entire Drosophila kinome in glia in alpha-synuclein expressing flies. Among the top hits were five genes (Ak1, Ak6, Adk1, Adk2, and awd) involved in adenosine metabolism. Knockdown of each gene improved locomotor dysfunction, rescued neurodegeneration, and increased brain adenosine levels. We determined that the mechanism of neuroprotection involves adenosine itself, as opposed to a downstream metabolite. We dove deeper into the mechanism for one gene, Ak1, finding rescue of dopaminergic neuron loss, alpha-synuclein aggregation, and bioenergetic dysfunction after glial Ak1 knockdown. We performed metabolomics in Drosophila and in human PD patients, allowing us to comprehensively characterize changes in purine metabolism and identify potential biomarkers of dysfunctional adenosine metabolism in people. These experiments support glial adenosine as a novel therapeutic target in PD.

Synchronization of the prefrontal cortex with the hippocampus and posterior parietal cortex is navigation strategy-dependent during spatial learning
During goal-directed spatial learning, subjects progressively change their navigation strategies to increase their navigation efficiency, an operation supported by the medial prefrontal cortex (mPFC). However, how the mPFC may integrate relevant information in a wider memory networks involving the hippocampus (HPC) and the posterior parietal cortex (PPC) is poorly understood. We recorded local-field potential and neuronal firing simultaneously from the mPFC, HPC and PPC in mice subjected to spatial memory acquisition in the Barnes maze. During navigation trials, animals demonstrated two consecutive behavioral stages: searching and exploration. Throughout training, mice gradually switched from less efficient (non-spatial) to more efficient (spatial) goal-oriented strategies exclusively during the searching stage. 4-Hz and theta (6-12 Hz) oscillations were detected during spatial navigation in the three recorded areas associated with episodes of immobility and locomotion, respectively. The entrainment of prefrontal gamma oscillations (60-100 Hz) by hippocampal and parietal 4-Hz and theta oscillations, as well as the incidence of prefrontal gamma, was higher when mice implemented spatial strategies during the searching stage. Interestingly, 4-Hz and theta from HPC and PPC also synchronized the spike-timing of prefrontal neurons, which was maximum during spatial strategies in the searching stage. Finally, neurons recorded in the mPFC increased their task stage firing selectivity when they used spatial strategy. Altogether, these results provide evidence for the neural mechanisms underlying the prefrontal large-scale coordination with distributed neural networks during spatial learning.

Distinct representation of navigational action affordances in human behavior, brains and deep neural networks
Humans can use a variety of actions to navigate their immediate environment. To decide how to move, the brain must determine which navigational actions are afforded by the current environment. Here, we demonstrate that human visual cortex represents navigational action affordances of complex natural scenes. Behavioral annotations of possible navigational actions (e.g., walking, cycling) show that humans group environments into distinct affordance clusters using at least three separate dimensions. Representational similarity analysis of multi-voxel fMRI responses in scene-selective visual cortex regions shows that perceived affordances are represented in a manner that is only partly explained by other scene properties (e.g. contained objects), and independent of the task performed in the scanner. Visual features extracted from deep neural networks (DNNs) pretrained on a range of other visual understanding tasks fail to fully account for behavioral and neural representations of affordances. While DNN predictions of human-perceived affordances improve when training directly on affordance labels, the best human-model alignment is observed when visual DNN features are paired with rich linguistic representation in a multi-modal large-language model. These results uncover a new type of representation in the human brain that reflect action affordances independent from other scene properties.

Efficient Federated Learning for distributed NeuroImaging Data
Recent advancements in neuroimaging have led to greater data sharing among the scientific community. However, institutions frequently maintain control over their data, citing concerns related to research culture, privacy, and accountability. This creates a demand for innovative tools capable of analyzing amalgamated datasets without the need to transfer actual data between entities. To address this challenge, we propose a decentralized sparse federated learning (FL) strategy. This approach emphasizes local training of sparse models to facilitate efficient communication within such frameworks. By capitalizing on model sparsity and selectively sharing parameters between client sites during the training phase, our method significantly lowers communication overheads. This advantage becomes increasingly pronounced when dealing with larger models and accommodating the diverse resource capabilities of various sites. We demonstrate the effectiveness of our approach through the application to the Adolescent Brain Cognitive Development (ABCD) dataset.

eIF2α phosphorylation evokes dystonia-like movements with D2-receptor and cholinergic origin and abnormal neuronal connectivity
Dystonia is the 3rd most common movement disorder. Dystonia is acquired through either injury or genetic mutations, with poorly understood molecular and cellular mechanisms. Eukaryotic initiation factor alpha (eIF2) controls cell state including neuronal plasticity via protein translation control and expression of ATF4. Dysregulated eIF2 phosphorylation (eIF2-P) occurs in dystonia patients and models including DYT1, but the consequences are unknown. We increased/decreased eIF2-P and tested motor control and neuronal properties in a Drosophila model. Bidirectionally altering eIF2-P produced dystonia-like abnormal posturing and dyskinetic movements in flies. These movements were also observed with expression of the DYT1 risk allele. We identified cholinergic and D2-receptor neuroanatomical origins of these dyskinetic movements caused by genetic manipulations to dystonia molecular candidates eIF2-P, ATF4, or DYT1, with evidence for decreased cholinergic release. In vivo, increased and decreased eIF2-P increase synaptic connectivity at the NMJ with increased terminal size and bouton synaptic release sites. Long-term treatment of elevated eIF2-P with ISRIB restored adult longevity, but not performance in a motor assay. Disrupted eIF2-P signaling may alter neuronal connectivity, change synaptic release, and drive motor circuit changes in dystonia.

Precision fMRI reveals that the language network exhibits adult-like left-hemispheric lateralization by 4 years of age
Left hemisphere damage in adulthood often leads to linguistic deficits, but many cases of early damage leave linguistic processing preserved, and a functional language system can develop in the right hemisphere. To explain this early apparent equipotentiality of the two hemispheres for language, some have proposed that the language system is bilateral during early development and only becomes left-lateralized with age. We examined language lateralization using functional magnetic resonance imaging with two large pediatric cohorts (total n=273 children ages 4-16; n=107 adults). Strong, adult-level left-hemispheric lateralization (in activation volume and response magnitude) was evident by age 4. Thus, although the right hemisphere can take over language function in some cases of early brain damage, and although some features of the language system do show protracted development (magnitude of language response and strength of inter-regional correlations in the language network), the left-hemisphere bias for language is robustly present by 4 years of age.

Dissociable encoding of evolving beliefs and momentary belief updates in distinct neural decision signals
Making accurate decisions in noisy or otherwise uncertain environments requires integrating evidence over time. Using simple tasks requiring rapid evaluation of a stationary sensory feature, two human neurophysiological signals have been found to evolve with similar integration dynamics, with one (centroparietal positivity; CPP) appearing to compute the running integral and continuously feed it to the other (motor beta lateralisation; MBL). However, it remains unknown whether and how these signals serve more distinct functional roles in more complex scenarios where information arrives discontinuously and requires more computational steps to form appropriate belief updates. We employed a volatile expanded judgement task that permits dissociation of the encoding of raw sensory information in each of a series of discrete stimuli ('objective evidence'), the appropriately transformed belief updates from that information ('effective evidence'), and the evolving belief itself (accumulated evidence). Whereas MBL traced the evolving belief across stimuli, the CPP was found only to locally encode the effective evidence associated with each individual stimulus. Furthermore, fluctuations in CPP amplitude after each single stimulus could account for variability in the encoding of accumulated evidence in MBL. These results suggest a flexible computational hierarchy in which effective evidence can be computed sample-by-sample at an intermediate processing level to drive downstream belief updates for protracted decisions about discrete stimuli.

Developmental and adult striatal patterning of nociceptin ligand marks striosomal population with direct dopamine projections
Circuit influences on the midbrain dopamine system are crucial to adaptive behavior and cognition. Recent developments in the study of neuropeptide systems have enabled high-resolution investigations of the intersection of neuromodulatory signals with basal ganglia circuitry, identifying the nociceptin/orphanin FQ (N/OFQ) endogenous opioid peptide system as a prospective regulator of striatal dopamine signaling. Using a prepronociceptin-Cre reporter mouse line, we characterized highly selective striosomal patterning of Pnoc mRNA expression in mouse dorsal striatum, reflecting early developmental expression of Pnoc. In the ventral striatum, Pnoc expression was clustered across the nucleus accumbens core and medial shell, including in adult striatum. We found that PnoctdTomato reporter cells largely comprise a population of dopamine receptor D1 (Drd1) expressing medium spiny projection neurons localized in dorsal striosomes, known to be unique among striatal projections neurons for their direct innervation of midbrain dopamine neurons. These findings provide new understanding of the intersection of the N/OFQ system among basal ganglia circuits with particular implications for developmental regulation or wiring of striato-nigral circuits.

A left-lateralized dorsolateral prefrontal network for naming
The ability to connect the form and meaning of a concept, known as word retrieval, is fundamental to human communication. While various input modalities could lead to identical word retrieval, the exact neural dynamics supporting this convergence relevant to daily auditory discourse remain poorly understood. Here, we leveraged neurosurgical electrocorticographic (ECoG) recordings from 48 patients and dissociated two key language networks that highly overlap in time and space integral to word retrieval. Using unsupervised temporal clustering techniques, we found a semantic processing network located in the middle and inferior frontal gyri. This network was distinct from an articulatory planning network in the inferior frontal and precentral gyri, which was agnostic to input modalities. Functionally, we confirmed that the semantic processing network encodes word surprisal during sentence perception. Our findings characterize how humans integrate ongoing auditory semantic information over time, a critical linguistic function from passive comprehension to daily discourse.

Cortico-amygdala synaptic structural abnormalities produced by templated aggregation of α-synuclein
Parkinsons disease (PD) and Dementia with Lewy bodies (DLB) are characterized by neuronal -synuclein (-syn) inclusions termed Lewy Pathology, which are abundant in the amygdala. The basolateral amygdala (BLA), in particular, receives projections from the thalamus and cortex. These projections play a role in cognition and emotional processing, behaviors which are impaired in -synucleinopathies. To understand if and how pathologic -syn impacts the BLA requires animal models of -syn aggregation. Injection of -synuclein pre-formed fibrils (PFFs) into the striatum induces robust -synuclein aggregation in excitatory neurons in the BLA that corresponds with reduced contextual fear conditioning. At early time points after aggregate formation, cortico-amygdala excitatory transmission is abolished. The goal of this project was to determine if -syn inclusions in the BLA induce synaptic degeneration and/or morphological changes. In this study, we used C57BL/6J mice injected bilaterally with PFFs in the dorsal striatum to induce -syn aggregate formation in the BLA. A method was developed using immunofluorescence and three-dimensional reconstruction to analyze excitatory cortico-amygdala and thalamo-amygdala presynaptic terminals closely juxtaposed to postsynaptic densities. The abundance and morphology of synapses were analyzed at 6- or 12-weeks post-injection of PFFs. -Syn aggregate formation in the BLA did not cause a significant loss of synapses, but cortico-amygdala and thalamo-amygdala presynaptic terminals and postsynaptic densities with aggregates of -synuclein show increased volumes, similar to previous findings in human DLB cortex, and in non-human primate models of PD. Transmission electron microscopy showed that PFF-injected mice showed reduced intervesicular distances similar to a recent study showing phospho-serine-129 -synuclein increases synaptic vesicle clustering. Thus, pathologic -synuclein causes major alterations to synaptic architecture in the BLA, potentially contributing to behavioral impairment and amygdala dysfunction observed in synucleinopathies.

Molecular mechanisms driving divergent development of the human frontal and visual cortex during prenatal development
Key principles of structural brain organization are established very early in fetal development. The frontal cortex is an important hub for integration and control of information, and its integrity and connectivity within the wider neural system are linked to individual differences across multiple cognitive domains and neurodevelopmental conditions. Here we leveraged fetal brain transcriptomics to investigate molecular mechanisms during prenatal development that drive early differences between the two regions at the opposite poles of the physical and representational gradient of the brain - the frontal and visual cortex. We show that the frontal cortex exhibits significantly higher cumulative gene expression for pathways involved in the continued growth and maintenance of larger neurons. These pathways include the gene ontology terms of neuron development and neuronal cell body as well as glucose metabolism important in trophically supporting larger cell sizes. Whole pathways for axonal growth (axonal growth cone, microtubules, filopodia, lamellipodia) and single genes involved in circuit connectivity exhibited increased expression in the frontal cortex. In contrast, in line with the established earlier completion of neurogenesis and lower number of neurons in the anterior cortex, expression of genes involved in DNA replication was significantly lower relative to the visual cortex. We further demonstrate differential cellular composition with higher expression of marker genes for inhibitory neurons in the prenatal frontal cortex. Together, these results suggest that the cellular architecture and composition facilitates earlier connectivity in the frontal cortex which may determine its role as an integrative hub in the global brain organization.