bioRxiv Subject Collection: Neuroscience's Journal

Consolidation of sequential experience into a deep generative network explains human memory, prediction and planning
The consolidation of sequential experience is thought to enable efficient schema-based reconstruction of the past and prediction of the future, but the mechanism is unknown. Here, we present a computational model in which sequences are rapidly encoded in the hippocampus and replayed to train a neocortical deep generative network to predict the next item in each sequence. This is simulated using generative pre-trained transformers (GPTs), a variety of large language model. As well as capturing the gist of specific episodes, the neocortical network extracts statistical patterns that generalise to new situations. This model explains human performance on statistical learning and structural inference tasks, and accounts for gist or schema-based distortions in memories of narratives. It also shows how recent memory can contribute to inference and planning, capturing hippocampal and neocortical interactions as 'retrieval-augmented generation', in which specific memories retrieved from the hippocampus provide the context in working memory for prediction using the 'general knowledge' of the neocortical network. Furthermore, it shows how hippocampal traces could combine gist and detail for efficient encoding. The model suggests how episodic, semantic and working memory interact in the consolidation, (re)construction and planning of sequential experience.

ASD-ASSOCIATED CNTNAP2 VARIANTS DISRUPT NEURONAL ARBORIZATION THROUGH IMPAIRED REGULATION BY ECTODOMAIN SHEDDING
Ectodomain shedding (ES) is a process by which a protease cleaves the extracellular portion of membrane-bound proteins, releasing soluble fragments that influence diverse cellular functions. ES is critical in neurodevelopment, plasticity, and neurodegenerative disorders, such as Alzheimer's disease, and has recently been implicated in neurodevelopmental conditions, including autism spectrum disorders (ASD). Contactin-associated protein-like 2 (CNTNAP2) is an adhesion molecule regulated by ES, releasing a soluble ectodomain (sCNTNAP2) that enhances neuronal synchrony. CNTNAP2 is implicated in ASD, schizophrenia, and cortical dysplasia focal epilepsy syndrome (CDFE) and it is known to regulate neuronal arborization, as well as dendritic spine maturation and maintenance. However, little is known about how neuroplasticity impacts ES or the role of CNTNAP2 ES in dendritic arborization. Here, we show that the brain sheddome is enriched in shed ectodomains that regulate neuronal projections, and that its molecular and functional composition is modulated by sensory deprivation in a sex dependent manner, with a decrease in sCNTNAP2 levels observed only in male mice. Furthermore, we demonstrate that sCNTNAP2 promotes dendritic arborization, while ASD-associated CNTNAP2 variants present reduced sCNTNAP2 levels in culture and decreased neuronal branching. Together, these findings underscore the role of ES in neuroplasticity and ASD and reveal how CNTNAP2 genetic variations disrupt its regulation by ES, leading to altered dendritic branching.

The Fly Disco: Hardware and software for optogenetics and fine-grained fly behavior analysis
In the fruit fly, Drosophila melanogaster, connectome data and genetic tools provide a unique opportunity to study complex behaviors including navigation, mating, aggression, and grooming in an organism with a tractable nervous system of 140,000 neurons. Here we present the Fly Disco, a flexible system for high quality video collection, optogenetic manipulation, and fine-grained behavioral analysis of freely walking and socializing fruit fly groups. The data collection hardware and software automates the collection of videos synced to programmable optogenetic stimuli. Key pipeline features include behavioral analysis based on trajectories of 21 keypoints and optogenetic-specific summary statistics and data visualization. We created the multifly dataset for pose estimation that includes 9701 examples enriched in complex behaviors. All hardware designs, software, and the multifly dataset are freely available.

Age and amyloidβ-dependent initiation of neurofibrillary tau tangles: an improved mouse model of Alzheimers disease without mutations in MAPT.
Introducing heterozygous humanized tau to AppNL-F/NL-F knock-in mice results in the first mouse model of Alzheimers disease in which age and amyloid{beta} pathology interact to initiate neurofibrillary tau tangle pathology, not dependent on mutations in MAPT. Gradual progression from amyloid{beta} to tau pathology in NLFTaum/h mice opens possibilities for understanding processes precipitating clinical stages of Alzheimers disease and development of translatable therapies to prevent the onset of tau pathology.

Nucleus accumbens D2-expressing neurons: Balancing reward and licking disruption through rhythmic optogenetic stimulation
Dopamine D1 receptor-expressing neurons in the nucleus accumbens (NAc) are known to be critical for processing reward and regulating food intake. However, the role of D2-expressing neurons in this region remains less understood. This study employed optogenetic manipulations to investigate the role of NAc D2-expressing neurons in reward processing and sucrose consumption. Optogenetic activation of these neurons decreased sucrose preference (at 20 Hz), disrupted licking patterns (particularly at 8 and 20 Hz), and increased self-stimulation. Conversely, synchronizing stimulation with the animal's licking rhythm mitigated licking disruption and even increased sucrose intake, suggesting a rewarding effect. Furthermore, 20 Hz stimulation (but not 8 Hz) induced place preference in a real-time place preference (RTPP) test, establishing a long-lasting spatial reward memory. In contrast, inhibiting D2 neurons produced a negative hedonic state, although not reaching a complete aversion, influencing food choices in specific contexts. For instance, while the RTPP test per se was not sensitive enough to observe place aversion when mice could choose between consuming a high-fat diet (HFD) pellet in a context associated with or without inhibition of D2 neurons, they preferred to consume HFD on the non-inhibited side. This suggests that the palatability of HFD can unmask (but also overshadow) the negative hedonic state associated with D2 neuron inhibition. A negative reinforcement paradigm further confirmed the active avoidance behavior induced by D2 neuron inhibition. In conclusion, NAc D2 neuron inhibition induces a negative hedonic state, while activation has a dual effect; it is rewarding yet disrupts licking behavior, highlighting its complex role in reward and consummatory behavior. Importantly, self-paced stimulation entrained to licking rhythms offers a more physiologically relevant approach to brain activation

Pharmacological depletion of microglia protects against alcohol-induced corticolimbic neurodegeneration during intoxication in male rats
Excessive alcohol use damages the brain, especially corticolimbic regions such as the hippocampus and rhinal cortices, leading to learning and memory problems. While neuroimmune reactivity is hypothesized to underly alcohol-induced damage, direct evidence of the causative role of microglia, brain-resident immune cells, in this process is lacking. Here, we depleted microglia using PLX5622 (PLX), a CSF1R inhibitor commonly used in mice, but rarely in rats, and assessed cell death following binge-like alcohol exposure in male rats. Eleven days of PLX treatment depleted microglia >90%. Further, PLX treatment prevented alcohol-induced neuronal death in the hippocampus and rhinal cortices, as the number of FluoroJade-B-positive cells (dying neurons) was reduced to control diet levels. This study provides direct evidence that alcohol-induced microglial reactivity is neurotoxic in male rats. Improved understanding of alcohol-microglia interactions is essential for developing therapeutics that suppress pro-cytotoxic and/or amplify protective microglia activity to relieve alcohol-related damage.

MINT: a toolbox for the analysis of multivariate neural information coding and transmission
Information theory has deeply influenced the conceptualization of brain information processing and is a mainstream framework for analyzing how neural networks in the brain process information to generate behavior. Information theory tools have been initially conceived and used to study how information about sensory variables is encoded by the activity of small neural populations. However, recent multivariate information theoretic advances have enabled addressing how information is exchanged across areas and used to inform behavior. Moreover, its integration with dimensionality-reduction techniques has enabled addressing information encoding and communication by the activity of large neural populations or many brain areas, as recorded by multichannel activity measurements in functional imaging and electrophysiology. Here, we provide a Multivariate Information in Neuroscience Toolbox (MINT) that combines these new methods with statistical tools for robust estimation from limited-size empirical datasets. We demonstrate the capabilities of MINT by applying it to both simulated and real neural data recorded with electrophysiology or calcium imaging, but all MINT functions are equally applicable to other brain-activity measurement modalities. We highlight the synergistic opportunities that combining its methods afford for reverse engineering of specific information processing and flow between neural populations or areas, and for discovering how information processing functions emerge from interactions between neurons or areas. MINT works on Linux, Windows and macOS operating systems, is written in MATLAB (requires MATLAB version 2018b or newer) and depends on 5 native MATLAB toolboxes. The calculation of one possible way to compute information redundancy requires the installation and compilation of C files (made available by us also as pre-compiled files). MINT is freely available at https://github.com/panzerilab/MINT with DOI 10.5281/zenodo.13998526 and operates under a GNU GPLv3 license.

A global dopaminergic learning rate enables adaptive foraging across many options
In natural environments, animals must efficiently allocate their choices across multiple concurrently available resources when foraging, a complex decision-making process not fully captured by existing models. To understand how rodents learn to navigate this challenge we developed a novel paradigm in which untrained, water-restricted mice were free to sample from six options rewarded at a range of deterministic intervals and positioned around the walls of a large (~2m) arena. Mice exhibited rapid learning, matching their choices to integrated reward ratios across six options within the first session. A reinforcement learning model with separate states for staying or leaving an option and a dynamic, global learning rate was able to accurately reproduce mouse learning and decision-making. Fiber photometry recordings revealed that dopamine in the nucleus accumbens core (NAcC), but not dorsomedial striatum (DMS), more closely reflected the global learning rate than local error-based updating. Altogether, our results provide insight into the neural substrate of a learning algorithm that allows mice to rapidly exploit multiple options when foraging in large spatial environments.

Repetitive magnetic stimulation induces plasticity of excitatory synapses through cooperative pre- and postsynaptic activity.
Transcranial magnetic stimulation (TMS) is a widely used non-invasive technique in research and clinical settings. Despite its success, the cellular and molecular mechanisms underlying TMS-induced changes in the brain remain incompletely understood. Current protocols are largely heuristic, based on system-level observations. This study employed in vitro repetitive magnetic stimulation (rMS) in mouse brain tissue cultures, combined with computational modeling to develop an experimentally validated approach for predicting TMS effects. Unlike electrical or optogenetic stimulation, rTMS uniquely enhances plasticity by activating both pre- and postsynaptic neurons, with brain-derived neurotrophic factor (BDNF) playing a crucial role. Our simulations accurately predicted the frequency-dependent effects of rTMS, providing a critical step towards developing robust, validated tools that will enhance the precision and effectiveness of TMS applications across both research and clinical settings.

F2,6BP restores mitochondrial genome integrity in Huntingtons Disease
Several reports have indicated that impaired mitochondrial function contributes to the development and progression of Huntingtons disease (HD). Mitochondrial genome damage, particularly DNA strand breaks (SBs), is a potential cause for its compromised functionality. We have recently demonstrated that the activity of polynucleotide kinase 3-phosphatase (PNKP), a critical DNA end-processing enzyme, is significantly reduced in the nuclear extract of HD patients due to lower level of a metabolite fructose-2,6 bisphosphate (F2,6BP), a biosynthetic product of 6-phosphofructo-2-kinase fructose-2,6-bisphosphatase 3 (PFKFB3), leading to persistent DNA SBs with 3-phosphate termini, refractory to subsequent steps for repair completion. PNKP also plays a pivotal role in maintaining mitochondrial genome integrity. In this report, we provide evidence that both PFKFB3 and F2,6BP, an allosteric modulator of glycolysis, are also present in the mitochondria. Notably, the level of F2,6BP, a cofactor of PNKP, is significantly decreased due to the degradation of PFKFB3 in the mitochondrial extract of HD patients brain. PNKP activity is thus severely decreased in the mitochondrial extract; however, addition of F2,6BP restored PNKP activity. Moreover, supplementation of F2,6BP in HD mouse striatal neuronal cells restored mitochondrial genome integrity and partially restored mitochondrial membrane potential and prevented pathogenic aggregate formation. We observed similar restoration of mitochondrial genome integrity in HD drosophila supplemented with F2,6BP. Our findings, therefore, suggest that F2,6BP or its structural analog hold promise as a therapeutic for restoring both nuclear and mitochondrial genome integrity and thereby of organismal health.

Volume conductor models for magnetospinography
The recent development of small, wearable, magnetic field sensors allow for the investigation of biomagnetic fields with a flexibility previously unavailable. We test models to describe how current flow in the spinal cord and thorax gives rise to measurable magnetic fields outside the torso. We compare various open-access volume conductor models, in order to select the most parsimonious and accurate descriptor of the magnetic fields due to source current in the spinal cord. We find that fields produced due to current flow along the superior-inferior axis of the cord are relatively insensitive to the choice of volume conductor model. However, fields produced by current flow in predominantly left-right or anterior-posterior direction are significantly attenuated by the presence of bone in the forward model. Furthermore, volume conductors with bone demonstrate larger differences in field topographies for nearby sources compared to bone-free models. These findings suggest that precise modelling of spinal cord location and surrounding vertebrae will be important a-priori knowledge going forward.

A modiolar-pillar gradient in auditory-nerve dendritic length: a novel post-synaptic contribution to dynamic range?
Auditory-nerve fibers (ANFs) from a given cochlear region can vary in threshold sensitivity by up to 60 dB, corresponding to a 1000-fold difference in stimulus level, although each fiber innervates a single inner hair cell (IHC) via a single synapse. ANFs with high-thresholds also have low spontaneous rates (SRs) and synapse on the side of the IHC closer to the modiolus, whereas the low-threshold, high-SR fibers synapse on the side closer to the pillar cells. Prior biophysical work has identified modiolar-pillar differences in both pre- and post-synaptic properties, but a comprehensive explanation for the wide range of sensitivities remains elusive. Here, in guinea pigs, we used immunostaining for several neuronal markers, including Caspr, a key protein in nodes of Ranvier, to reveal a novel modiolar-pillar gradient in the location of the first ANF heminodes, presumed to be the site of the spike generator, just outside the sensory epithelium. Along the cochlea, from apex to base, the unmyelinated terminal dendrites of modiolar ANFs were 2 - 4 times longer than those of pillar ANFs. This modiolar-pillar gradient in dendritic length, coupled with the 2 - 4 fold smaller caliber of modiolar dendrites seen in prior single-fiber labeling studies, suggests there could be a large difference in the number of length constants between the synapse and the spike initiation zone for low- vs high-SR fibers. The resultant differences in attenuation of post-synaptic potentials propagating along these unmyelinated dendrites could be a key contributor to the observed range of threshold sensitivities among ANFs.

Brain-wide population activity during reaching integrates action-mediated goal expectation
Large scale recordings have revealed that neurons encoding motor and non-motor variables are highly distributed across the brain. While these neurons generate population level dynamics during spontaneous behavior, it remains unclear how these latent subspaces relate to the simultaneous motor and cognitive demands during ongoing goal-directed behavior. Here, we show that continuously anticipated action outcome, in addition to movement, drives ubiquitous latent dynamics during goal-directed movements. We used multiple Neuropixels probes to simultaneously record spiking activity from cortical and subcortical regions during a reaching task in head-fixed mice. Task-related population dynamics covaried within a common latent subspace across regions and was conserved across recording days and animals. These latent dynamics preceded movement onset and were modulated by reach distance and reward availability. Furthermore, their temporal progression continuously scaled with the timing of reward consumption and their activity decreased afterwards, despite ongoing stereotypical re-reaches. Our findings thus provide evidence for a brain-wide latent subspace for continuous representation of action-mediated proximity to goal, which could provide the basis for ubiquitous temporal difference learning based on predicted action outcome.

Flow parsing as causal source separation: A computational model for concurrent retrieval of object and self-motion information from optic flow
Optic flow, the retinal pattern of motion that is experience during self-motion contains information about one's direction of heading. If the visual scene contains other moving objects optic flow becomes a combination of self-motion and independent object motion. The global pattern due to self-motion is locally confounded, and the locally restricted object flow is the sum of components due to these different causal sources of motion. Nonetheless, humans are able to retrieve information from such flow accurately, including the direction of heading and the scene-relative motion of an object. One way to handle such complex flow is flow parsing, a process speculated to allow the brain's sensitivity to optic flow to separate the causal sources of retinal motion in information due to self-motion and information due to object motion. In a computational model that retrieves object and self-motion information from optic flow, we implemented such a process of causal separation based on heading likelihood maps, whose distributions indicate the consistency of parts of the flow with self-motion alone. The flow parsing allows for concurrent estimation of heading, the detection and localization of and independently moving object, and the estimation of scene-relative motion of that object. We developed a paradigm that allows the model to perform all the different estimations while systematically varying how the object contributes to the flow field. Simulations of that paradigm showed that the model replicates many aspects of human performance, including the dependence of heading estimation on object speed and how different object movements bias that estimation. Regarding object detection and motion estimation, the model's results fit human behavioral data, the latter even for flow of reduced quality.

Perisomatic Synaptic Targeting by Cholecystokinin-Basket Interneurons through NrCAM and Ankyrin B
The perisomatic region of cortical pyramidal neurons (PNs) integrates local and long-range inputs and regulates firing.This domain receives GABAergic inputs from cholecystokinin (CCK)- and parvalbumin (PV)-expressing basket cells (BCs) but how synaptic contacts are established is unclear. Neuron-glial related cell adhesion molecule (NrCAM) is a homophilic transmembrane protein that binds the scaffold protein Ankyrin B. Here we show that NrCAM and Ankyrin B mediate perisomatic synaptic contact between CCK-BCs and PNs in mouse prefrontal cortex (PFC). Immunolabeling of CCK-BC terminals for vesicular glutamate transporter-3 (VGlut3) or vesicular glutamate transporter (VGAT) revealed a significant decrease in CCK-BC synaptic puncta on PN soma in NrCAM-null mice, however no decrease in PV-BC puncta, or cell loss. VGlut3+ CCK-BC puncta were also decreased by Ankyrin B deletion from PNs in Nex1Cre-ERT2:Ank2flox/flox:EGFP mice. A novel CCK-BC reporter mouse expressing tdTomato (tdT) at the Synuclein-{gamma} (Sncg) locus showed NCAM localized to presynaptic Sncg+ CCK-BCs, as well as to postsynaptic PN soma of WT mice. Results implicate NrCAM homophilic interactions and Ankyrin B binding with development of inhibitory connectivity between CCK-BCs and excitatory neurons of the PFC.

Mechanical load conditions the spectrin network to `run-on' proteolysis and promotes early onset neurodegeneration
The correct homeostasis of the neuronal cytoskeleton and its dynamics is important for health and disease. Forces constantly act on the neurons in our body, leading to subtle axonal deformations and length changes. The spectrin cytoskeleton is known as a key player that protects neurons against mechanical damage. How the spectrin cytoskeleton changes with age and how it influences mechanoprotection in aging animals is not well understood. Using an interdisciplinary approach, we show that age causes a loss of proprioception during the first few days of adulthood in Caenorhabditis (C.) elegans via spectrin unfolding, loss of mechanical tension and degradation of the spectrin cytoskeleton. Guided by a proteomic screen to identify potential spectrin binding partners, we found that this early-onset neurodegeneration can be suppressed in clp-1 Calpain mutants and by targeted expression of an engineered chaperone derived from human alphaB-crystallin. Our data suggest that the spectrin cytoskeleton is sensitized to proteolytic damage by calcium-sensitive proteases when mechanical stresses conspires with high-calcium concentrations as in proprioceptive signaling. These results may have implications for the etiology of diseases in which high calcium dynamics and mechanical stress coincide.

Systematic effects of retinotopic biases and category selectivity across human occipitotemporal cortex
The organization of human visual cortex has traditionally been studied using two different methods: retinotopic mapping and category-selectivity mapping. Retinotopic mapping has identified a large number of systematic maps of the visual field, while category-selectivity mapping has identified clusters of neural populations that reliably respond more strongly to specific image categories such as objects, faces, scenes and body parts compared to other categories. While early investigations seemed to suggest that these two organizing principles were largely separated in the brain, with retinotopic maps in posterior visual cortex and category-selective regions in anterior visual cortex, recent work shows that category-selective regions overlap with retinotopic maps, giving rise to spatial visual field biases within these regions. Here, we collected fMRI responses whilst performing both retinotopic and category mapping within the same participants, allowing detailed comparison of neural tuning for space and category at the single voxel level. We use these data to evaluate two previous proposals of how retinotopic biases relate to category-selectivity: 1) complementary quadrant biases (upper vs. lower contralateral visual field) inherited from early visual cortex explain the presence of paired regions selective for the same category across lateral and ventral occipitotemporal cortex (lOTC, vOTC); and 2) eccentricity biases (center vs. periphery of the visual field) explain the presence of selectivity for different categories, specifically differentiating face- versus scene-selectivity within the ventral surface. Confirming and extending previous findings for a comprehensive set of face-, scene-, object, and place-selective regions of interest, we provide robust evidence that category-selective regions do not sample visual space uniformly, exhibiting systematic biases towards either the upper or lower field (all category regions) and center vs. periphery (face vs. place regions). Consistent with 1), we find that quadrant biases differ systematically between lateral and ventral OTC, with lateral regions showing systematic lower field biases and ventral regions showing upper field biases, differentiating regions selective for the same category in terms of their spatial bias. However, contrary to 2), we find that eccentricity tuning does not strongly predict the strength of face- or scene category-selectivity in a given voxel. Specifically, highly face-selective voxels are not solely confined to the fovea, and while most scene-selective voxels show peripheral tuning, highly scene-selective voxels actually show strong foveal tuning, particularly in anterior medial-ventral cortex. Collectively, these results demonstrate that spatial biases in category-selective cortex are widespread and robust, whilst also suggesting there is no simple relation between spatial tuning and category-selectivity.

Predicting neuronal firing from calcium imaging using a control theoretic approach
Two-photon calcium imaging has become a powerful tool to explore the functions of neurons and the connectivity of their circuitry. Frequently, fluorescent calcium indicators are taken as a direct measure of neuronal activity. These indicators, however, are slow relative to behavior, obscuring functional relationships between an animal's movements and the true neuronal activity. As a consequence, the firing rate of a neuron is a more meaningful metric. Converting calcium imaging data to the firing of a neuron is nontrivial. State of the art methods depend largely on neural networks or non-mechanistic processes, which may yield acceptable correlations between calcium dynamics and the frequency at which a neuron fires, but do not illuminate the underlying chemical exchanges within the neuron or require significant data to be trained on. Leveraging modeling frameworks from chemical reaction networks (CRN) coupled with modern control architectures, a new algorithm is presented based off of fully deterministic ordinary differential equations (ODEs). This framework utilizes model predictive control to challenge state of the art correlation scores while retaining the interpretability that comes inherent with a model. Moreover, these computations can be done in real time, thus enabling online experimentation informed by neuronal firing rates. To demonstrate the use cases of this architecture, it is tested on a ground truth dataset courtesy of the spikefinder challenge. Finally, the predictive power of the methodology put forward here is underscored by demonstrating its ability to aid in the creation of novel indicators utilized in two-photon imaging.

Multi-omics analysis in mouse primary cortical neurons reveals complex positive and negative biological interactions between constituent compounds in Centella asiatica
Background: A water extract of the Ayurvedic plant Centella asiatica (CAW) improves cognitive function in mouse models of aging and Alzheimers disease, and affects dendritic arborization, mitochondrial activity and oxidative stress in mouse primary neurons. Triterpenes (TT) and caffeoylquinic acids (CQA) are constituents associated with these bioactivities of CAW although little is known about how interactions between these compounds contribute to the plants therapeutic benefit. Methods: Mouse primary cortical neurons were treated with CAW, or equivalent concentrations of four TT combined, eight CQA combined, or these twelve compounds combined (TTCQA). Treatment effects on the cell transcriptome (18,491 genes) and metabolome (192 metabolites) relative to vehicle control were evaluated using RNAseq and metabolomic analyses respectively. Results: Extensive differentially expressed genes (DEGs) were seen with all treatments, as well as evidence of interactions between compounds. Notably many DEGs seen with TT treatment were not observed in the TTCQA condition, possibly suggesting CQA reduced the effects of TT. Moreover, additional gene activity seen with CAW as compared to TTCQA indicate the presence of additional compounds in CAW that further modulate TTCQA interactions. Weighted Gene Correlation Network Analysis (WGCNA) identified 4 gene co-expression modules altered by treatments that were associated with extracellular matrix organization, fatty acid metabolism, cellular response to stress and stimuli, and immune function. Compound interaction patterns were seen at the eigengene level in these modules. Interestingly, in metabolomics analysis, the TTCQA treatment saw the highest number of changes in individual metabolites (20), followed by CQA (15), then TT (8) and finally CAW (3). WGCNA analysis found two metabolomics modules with significant eigenmetabolite differences for TT and CQA, and possible compound interactions at this level. Conclusions: Four gene expression modules and two metabolite modules were altered by the four types of treatments applied. This methodology demonstrated the existence of both negative and positive interactions between TT, CQA and additional compounds found in CAW on the transcriptome and metabolome of mouse primary cortical neurons.

Modulating Neurotoxic Effects of Prenatal Chlorpyrifos Exposure Through Probiotic and Vitamin D Gestational Supplementation: Unexpected Effects on Neurodevelopment and Sociability
Autism is a neurodevelopmental disorder characterized by impairments in sociability and communication. Prenatal exposure to Chlorpyrifos has been associated with autism-like behaviors in preclinical models. Interest has grown in the gut-brain axis and the role of microbiota modulation through dietetic supplementation to reduce this ASD-like phenotype. This study examines the effects of prenatal CPF exposure in Wistar Rats and assesses the potential of gestational probiotic and vitamin D supplementation to mitigate these effects in offspring. CPF exposure significantly impaired sociability in adolescence, and supplementation did not reverse these deficits. However, in control animals, supplementation induced neurodevelopmental changes, including alterations in metabolic status, the pattern of expression of ASD-related genes, the regulation of oxytocin and vasopressin receptors, and the GABAergic system in the brain. Additionally, supplementation accelerated overall development, increased ultrasonic vocalization emission and modified the typical responses to social novelty. CPF exposure blocked most of these effects at both behavioral and molecular levels. While supplementation did not block CPF-induced impairments, CPF exposure altered the observed effects of supplementation in controls, possibly indicating shared molecular mechanisms. These findings highlight the need for further research into the safety of probiotic and vitamin D supplementation during pregnancy.

dArc1 controls sugar reward valuation in Drosophila melanogaster
The Arc genes, which include Drosophila Arc1 and Arc2 (dArc), evolved from Ty3 retrotransposons and encode proteins that form virus-like capsids. These capsids enable a novel form of intercellular communication by transferring RNAs between cells. However, the specific neuronal circuits and brain processes Arc intercellular signaling regulates remain unknown. Here, we show that loss of both dArc genes in Drosophila melanogaster enhances associative learning in an appetitive conditioning paradigm, where flies associate an odor with sugar rewards. This increased learning performance arises from an increased valuation of sugar rewards: unlike wild-type flies, dArc-/- flies form abnormally strong associations even when the sugar reward is small or has no caloric value. We found that the gamma5-dopaminergic neurons of the protocerebral anterior medial (PAM) cluster, which encode the positive valence of sugar rewards, show heightened activity in response to sucrose in dArc-/- flies. We further show that the learning phenotype of dArc-/- flies depends on the formation of capsids, underscoring a direct role for capsid-mediated Arc signaling in sugar valuation. Our findings establish dArc genes as critical regulators of reward valuation in D. melanogaster, acting through a non-cell autonomous mechanism that relies on capsid-mediated communication between cells.

Chimeric music reveals an interaction of pitch and time in electrophysiological signatures of music encoding
Pitch and time are the essential dimensions defining musical melody. Recent electrophysiological studies have explored the neural encoding of musical pitch and time by leveraging probabilistic models of their sequences, but few have studied how the features might interact. This study examines these interactions by introducing "chimeric music," which pairs two distinct melodies, and exchanges their pitch contours and note onset-times to create two new melodies, thereby distorting musical pattern while maintaining the marginal statistics of the original pieces' pitch and temporal sequences. Through this manipulation, we aimed to dissect the music processing and the interaction between pitch and time. Employing the temporal response function (TRF) framework, we analyzed the neural encoding of melodic expectation and musical downbeats in participants with varying levels of musical training. Our findings revealed differences in the encoding of melodic expectation between original and chimeric stimuli in both dimensions, with a significant impact of musical experience. This suggests that the structural violation due to decoupling the pitch and temporal structure affect expectation processing. In our analysis of downbeat encoding, we found an enhanced neural response when participants heard a note that aligned with the downbeat during music listening. In chimeric music, responses to downbeats were larger when the note was also a downbeat in the original music that provided the pitch sequence, indicating an effect of pitch structure on beat perception. This study advances our understanding of the neural underpinnings of music, emphasizing the significance of pitch-time interaction in the neural encoding of music.

Suppression of Huntington's Disease Somatic Instability by Transcriptional Repression and Direct CAG Repeat Binding
Huntington's disease (HD) arises from a CAG expansion in the huntingtin (HTT) gene beyond a critical threshold. A major thrust of current HD therapeutic development is lowering levels of mutant HTT mRNA (mHTT) and protein (mHTT) with the aim of reducing the toxicity of these product(s). Human genetic data also support a key role for somatic instability (SI) in HTT's CAG repeat -- whereby it lengthens with age in specific somatic cell types -- as a key driver of age of motor dysfunction onset. Thus, an attractive HD therapy would address both mHTT toxicity and SI, but to date the relationship between SI and HTT lowering remains unexplored. Here, we investigated multiple therapeutically-relevant HTT-lowering modalities to establish the relationship between HTT lowering and SI in HD knock-in mice. We find that repressing transcription of mutant Htt (mHtt) provides robust protection from SI, using diverse genetic and pharmacological approaches (antisense oligonucleotides, CRISPR-Cas9 genome editing, the Lac repressor, and virally delivered zinc finger transcriptional repressor proteins, ZFPs). However, we find that small interfering RNA (siRNA), a potent HTT-lowering treatment, lowers HTT levels without influencing SI and that SI is also normal in mice lacking 50% of total HTT levels, suggesting HTT levels, per se, do not modulate SI in trans. Remarkably, modified ZFPs that bind the mHtt locus, but lack a repressive domain, robustly protect from SI, despite not reducing HTT mRNA or protein levels. These results have important therapeutic implications in HD, as they suggest that DNA-targeted HTT-lowering treatments may have significant advantages compared to other HTT-lowering approaches, and that interaction of a DNA-binding protein and HTT's CAG repeats may provide protection from SI while sparing HTT expression.

Antigen-Specific T Cell Receptor Discovery for Treating Progressive Multifocal Leukoencephalopathy
Background: Progressive multifocal leukoencephalopathy (PML) is a frequently fatal disease of the central nervous system caused by JC virus (JCV). Survival is dependent on early diagnosis and ability to re-establish anti-viral T cell immunity. Adoptive transfer of polyomavirus-specific T cells has shown promise; however, there are no readily available HLA-matched anti-viral T cells to facilitate rapid treatment. Objective: Identify epitopes of the JCV major capsid protein VP1 that elicit an immune response in the context of human leukocyte antigen allele A*02:01 (HLA-A2) and isolate cognate T cell receptors (TCRs) from healthy donors. Evaluate individual VP1-specific TCRs for their capacity to be expressed in T cells and clear JCV in vitro. Methods: PBMCs from HLA-A2+ healthy donors were stimulated with peptide libraries tiled across the JCV VP1 protein. Multiple rounds of stimulation were performed to identify the antigens that induced the largest expansion and CD8+ T cell response (measured as INFg;, TNFa;, CD137, and CD69 expression). High-affinity, antigen-specific CD8+ T cells were isolated based on intensity of tetramer binding for downstream single-cell TCR sequencing. Candidate TCRs were selected based on tetramer binding affinity and activation assays. Promising TCRs were introduced into the T cell genome via viral transduction for in vitro validation including peptide-pulsed K562 cells and astrocyte cells, and JCV-infected astrocytes. Results: Four conserved JCV VP1 epitopes (amino acids 100-108, 251-259, 253-262, and 274-283) presented by HLA-A2 were identified. VP1(100-108) consistently elicited the highest level of IFNg; production from multiple donors and this peptide is in a highly conserved region of VP1. We next identified fourteen high avidity TCRs specific for VP1(100-108). When virally transduced into primary human T cells, seven of these TCRs demonstrated specific binding to VP1(100-108):HLA-A2 tetramers, and four showed increased IFNg; response when incubated with peptide. Primary CD8+ T cells expressing two of these TCRs cleared both HLA-A2 positive K562 cells and HLA-A2 positive SVG astrocyte cell line presenting exogenously added VP1 peptide at a range of E:T ratios. In addition, both TCR-transduced T cell populations effectively lysed JCV-infected astrocytes. Conclusions: We identified JCV VP1 epitopes that are immunogenic in the context of HLA-A2 MHC-I, including epitopes that have not been previously described. The VP1(100-108) epitope was used to isolate HLA-A2-restricted TCRs. When cloned into primary human CD8+ T cells, these TCRs recognized VP1 (100-108)-presenting targets, and the transduced T cells conferred cytotoxic activity and eliminated K562 and astrocyte cells displaying the VP1(100-108) peptide and not sham peptide, as well as JCV-infected astrocytes. Taken together, these data suggest that JCV VP1-specific TCRs could be appealing therapeutics for HLA-A2+ individuals with PML in whom intrinsic T cell immunity cannot be rescued.

A consensus definition for deep layer 6 excitatory neurons in mouse neocortex
To understand neocortical function, we must first define its cell types. Recent studies indicate that neurons in the deepest cortical layer play roles in mediating thalamocortical interactions and modulating brain state and are implicated in neuropsychiatric disease. However, understanding the functions of deep layer 6 (L6b) neurons has been hampered by the lack of agreed upon definitions for these cell types. We compared commonly used methods for defining L6b neurons, including molecular, transcriptional and morphological approaches as well as transgenic mouse lines, and identified a core population of L6b neurons. This population does not innervate sensory thalamus, unlike layer 6 corticothalamic neurons (L6CThNs) in more superficial layer 6. Rather, single L6b neurons project ipsilaterally between cortical areas. Although L6b neurons undergo early developmental changes, we found that their intrinsic electrophysiological properties were stable after the first postnatal week. Our results provide a consensus definition for L6b neurons, enabling comparisons across studies.

Corticonigral projections recruit substantia nigra pars lateralis dopaminergic neurons for auditory threat memories
Dopaminergic neurons (DANs) in the lateral substantia nigra project to the tail of striatum (TS), which is involved in threat conditioning. Auditory cortex also contributes to threatening behaviors, but whether it directly interacts with midbrain DANs and how these interactions might influence threat conditioning remain unclear. Here, functional mapping revealed robust excitatory input from auditory and temporal association cortexes to substantia nigra pars lateralis (SNL) DANs, but not to pars compacta (SNc) DANs. SNL DANs exhibited unique firing patterns, with irregular pacemaking and higher maximal firing, reflecting different channel complements than SNc DANs. Behaviorally, inhibiting cortex to SNL projections impaired memory retrieval during auditory threat conditioning. Thus, we demonstrate robust corticonigral projections to SNL DANs, contrasting with previous observations of sparse cortical input to substantia nigra DANs. These findings distinguish SNL DANs from other nigral populations, highlighting their role in threatening behaviors and expanding knowledge of cortex to midbrain interactions.

EEG connectome-based predictive modeling of nonverbal intelligence level in healthy subjects
Intelligence is increasingly recognized as a critical factor in successful behavioral and emotional regulation. Neuroimaging techniques coupled with machine learning algorithms have proven to be valuable tools for uncovering the neural foundations of individual cognitive abilities. Nevertheless, current electroencephalograph (EEG) studies primarily focus on classification tasks to predict the intelligence category of subjects (e.g., high, medium, or low intelligence), rather than providing quantitative intelligence level forecasts. Furthermore, the outcomes obtained are significantly impacted by the specific data processing pipeline chosen, which could potentially compromise result generalizability. In this study, we implemented a connectome-based predictive modeling approach on high-density resting state EEG data from healthy participants to predict their nonverbal intelligence level. This method was applied to three independently collected datasets (N = 255) with different functional connectivity methods, parcellation atlases, threshold p-values and curve fitting orders used to ensure the reliability of the findings. We found that the prediction accuracy expressed in terms of R2 varied significantly depending on the processing pipeline configuration, ranging from negative R2 values up to 0.27. The most consistent results across datasets were found in the alpha frequency band. Furthermore, we employed a computational lesioning approach to identify the valuable edges that made the most significant contribution to predicting intelligence. This analysis highlighted the crucial role of frontal and parietal regions in complex cognitive computations. Overall, these findings support and expand upon previous research, underscoring the close relationship between alpha rhythm characteristics and cognitive functions and emphasizing the critical consideration of method selection in result evaluation.