bioRxiv Subject Collection: Neuroscience's Journal

Delineating neural contributions to electroencephalogram-based speech decoding
Speech Brain-computer interfaces (BCIs) have emerged as a pivotal technology in facilitating communication for individuals with speech impairments. Utilizing electroencephalography (EEG) for noninvasive speech BCIs offers an accessible and affordable solution, potentially benefiting a broader audience. However, EEG-based speech decoding remains controversial especially for overt speech, due to difficulties in separating speech-related neural activities from myoelectric potential artifacts generated during articulation. Here we aim to delineate the extent of the neural contributions by employing Explainable AI techniques to a convolutional neural network predicting spoken words based on signals obtained by ultra-high-density (uhd)-EEG. We found that electrode-wise contributions to the decoding cannot be explained by their mutual information with electromyography (EMG). Furthermore, contributing periods of speech to EEG-based decoding are distinct from those to decoding solely relying on EMG. In contrast, there are significant overlaps in signal timings contributing to EEG-based decoding, regardless of vocal conditions such as overt or covert speech. Notably, the denoising process successfully enhanced the decoding contribution from electrodes within speech-related brain areas for all speech conditions. Altogether, our findings support the idea that, with appropriate preprocessing, EEG becomes a valuable tool for decoding spoken words based on underlying neural activities.

Noradrenergic modulation of stress induced catecholamine release: Opposing influence of FG7142 and yohimbine
In humans, loss aversion is sensitive to stress, and patients with neurological or psychiatric illnesses are particularly vulnerable to the detrimental effects of stress that lead to suboptimal life-altering choices. The basolateral amygdala (BLA) and nucleus accumbens (NAc) are stress sensitive brain areas that alter extracellular levels of norepinephrine (NE) and dopamine (DA), respectively. However, the dynamics of neurotransmitter release in these brain regions during stress has not been systematically explored. We used pharmacology and fiber photometric analysis to elucidate the impact of stress, DA and NE on brain activity during decision making behavior. Long-Evans rats were trained on an operant touchscreen decision-making task in which they chose between a safe stimulus that delivered a certain 50ul sucrose, or a risky stimulus that delivered either a loss (10ul sucrose 75% of the time) or win (170ul sucrose 25% of the time). Stress, induced by an inverse GABAA agonist, FG7142, biased rats decisions towards safety due to increased loss sensitivity. The aversion to loss was blocked with co-treatment of the alpha 2A receptor antagonist, yohimbine. We also captured the rapid dynamic properties of stress induced changes in NE and DA release in the BLA and NAc, respectively. We discovered that these dynamics could be modulated with systemic injections of yohimbine by altering stress induced catecholamine release to optimize decision strategy and motivational state.

An unbiased method to partition diverse neuronal responses into functional ensembles reveals interpretable population dynamics during innate social behavior
In neuroscience, understanding how single-neuron firing contributes to distributed neural ensembles is crucial. Traditional methods of analysis have been limited to descriptions of whole population activity, or, when analyzing individual neurons, criteria for response categorization varied significantly across experiments. Current methods lack scalability for large datasets, fail to capture temporal changes and rely on parametric assumptions. There's a need for a robust, scalable, and non-parametric functional clustering approach to capture interpretable dynamics. To address this challenge, we developed a model-based, statistical framework for unsupervised clustering of multiple time series datasets that exhibit nonlinear dynamics into an a-priori-unknown number of parameterized ensembles called Functional Encoding Units (FEUs). FEU outperforms existing techniques in accuracy and benchmark scores. Here, we apply this FEU formalism to single-unit recordings collected during social behaviors in rodents and primates and demonstrate its hypothesis-generating and testing capacities. This novel pipeline serves as an analytic bridge, translating neural ensemble codes across model systems.

Extensive MEG time-series phenotyping unveils neural markers predictive of age
Understanding the evolving dynamics of the brain throughout life is pivotal for anticipating and evaluating individual health. While previous research has described age effects on spectral properties of neural signals, it remains unclear which ones are most indicative of age-related processes. This study addresses this gap by analyzing resting-state data obtained from magnetoencephalography in 350 adults (18-88 years). We employed advanced time-series analysis at the brain region level and machine learning to predict age. While traditional spectral features achieved low to moderate accuracy, over a hundred novel time-series features proved superior. Notably, temporal autocorrelation emerged as the most robust predictor of age. Distinct patterns of autocorrelation within the visual and temporal cortex were most informative, offering a versatile measure of age-related signal changes for comprehensive health assessments based on brain activity.

Paradoxical replay can protect contextual task representations from destructive interference when experience is unbalanced
Experience replay is a powerful mechanism to learn efficiently from limited experience. Despite several decades of compelling experimental results, the factors that determine which experiences are selected for replay remain unclear. A particular challenge for current theories is that on tasks that feature unbalanced experience, rats paradoxically replay the less-experienced trajectory. To understand why, we simulated a feedforward neural network with two regimes: rich learning (structured representations tailored to task demands) and lazy learning (unstructured, task-agnostic representations). Rich, but not lazy, representations degraded following unbalanced experience, an effect that could be reversed with paradoxical replay. To test if this computational principle can account for the experimental data, we examined the relationship between paradoxical replay and learned task representations in the rat hippocampus. Strikingly, we found a strong association between the richness of learned task representations and the paradoxicality of replay. Taken together, these results suggest that paradoxical replay specifically serves to protect rich representations from the destructive effects of unbalanced experience, and more generally demonstrate a novel interaction between the nature of task representations and the function of replay in artificial and biological systems.

3-nitrotyrosine shortens axons of a non-dopaminergic neuron by inhibiting mitochondrial motility
3-nitrotyrosine (3-NT), a byproduct of oxidative/nitrosative stress, is implicated in age-related neurodegenerative disorders. Existing literature indicates that free 3-NT becomes integrated into the carboxy-terminal domain of -tubulin through the tyrosination/detyrosination cycle. Independently of this integration, 3-NT has been linked to the cell death of dopaminergic neurons. Given the critical role of tyrosination/detyrosination in governing axonal morphology and function, the substitution of tyrosine with 3-NT in this process may potentially disrupt axonal homeostasis, although this aspect remains underexplored. In this study, we examined the impact of 3-NT on the axons of cerebellar granule neurons, representing non-dopaminergic neurons. Our observations revealed axonal shortening, which correlated with the incorporation of 3-NT into -tubulin. Importantly, this axonal effect was observed prior to the onset of cellular death. Furthermore, 3-NT was found to diminish mitochondrial motility within the axon, resulting in a subsequent reduction in mitochondrial membrane potential. The suppression of syntaphilin, a protein responsible for anchoring mitochondria to microtubules, reversed the 3-NT-induced decrease in mitochondrial motility, consequently restoring axonal elongation. These findings underscore the inhibitory role of 3-NT in axonal elongation by impeding mitochondrial movement, implying its potential involvement in axonal dysfunction within non-dopaminergic neurons.

Mouse α-synuclein fibrils are structurally and functionally distinct from human fibrils associated with Lewy body diseases
The intricate process of -synuclein aggregation and fibrillization hold pivotal roles in Parkinson's disease (PD) and multiple system atrophy (MSA). While mouse -synuclein can fibrillize in vitro, whether these fibrils commonly used in research to induce this process or form can reproduce structures in the human brain remains unknown. Here we report the first atomic structure of mouse -synuclein fibrils, which was solved in parallel by two independent teams. The structure shows striking similarity to MSA-amplified and PD-associated E46K fibrils. However, mouse -synuclein fibrils display altered packing arrangements, reduced hydrophobicity, heightened fragmentation sensitivity, and evoke only weak immunological responses. Furthermore, mouse -synuclein fibrils exhibit exacerbated pathological spread in neurons and humanized -synuclein mice. These findings provide new insights into the structural underpinnings of -synuclein pathogenicity and emphasize a need to reassess the role of mouse -synuclein fibrils in the development of related diagnostic probes and therapeutic interventions.

Prediction of pathological subthalamic nucleus beta burst occurrence in Parkinson's disease
The cortico-basal ganglia network in Parkinson's disease (PD) is characterised by the emergence of transient episodes of exaggerated beta frequency oscillatory synchrony known as bursts. Although beta bursts of prolonged duration and amplitude are well recognised to have a detrimental effect on motor function in PD, the neurophysiological mechanisms leading to burst initiation remain poorly understood. Related to this is the question of whether there exist features of basal ganglia activity which can reliably predict the onset of beta bursts. Current state-of-the-art adaptive Deep Brain Stimulation (aDBS) algorithms for PD involve the reactive delivery of stimulation following burst detection and are unable to stimulate proactively so as to prevent burst onset. The discovery of a predictive biomarker would allow for such proactive stimulation, thereby offering further potential for improvements in both the efficacy and side effect profile of aDBS. Here we use deep neural networks to address the hypothesis that beta bursts can be predicted from invasive subthalamic nucleus (STN) recordings in PD patients. We developed a neural network which was able to predict bursts 31.6ms prior to their onset, with a high sensitivity and a low false positive rate (mean performance metrics: sensitivity = 84.8%, precision = 91.5%, area under precision recall curve = 0.87 and false positive rate = 7.6 per minute). Furthermore, by considering data segments that our network labelled as being predictive, we show that a dip in the beta amplitude (a fall followed by a subsequent rise) is a predictive biomarker for subsequent burst occurrence. Our findings demonstrate proof-of-principle for the feasibility of beta burst prediction and inform the development of a new type of intelligent DBS approach with the capability of stimulating proactively to prevent beta burst occurrence.

Ability to monitor deviations of own movement without visual feedback
How conscious sensations of movement relates to signals essential for movement control remains under investigation. This question is typically investigated using visuomotor tasks, in which sensation of movement is disturbed by conflicting visual feedback. The present study uses metacognitive judgements to investigate conscious access to movement signals, unchallenged by visual signals, in an index finger force task. We found that some participants can correctly assign metacognitive judgements (MCJs) to their own force, suggesting that participants do indeed have metacognitive access to sensorimotor signals. We found no correlation between metacognitive access to sensorimotor signal and variance in motor performance. Further, we found that in this purely sensorimotor task, internal focus of attention reduces variability in force compared to external focus of attention. Our results indicate that not only is it possible to access sensorimotor information, it is also possible to use focus of attention to reduce variability in force performance.

Student-teacher inter-brain coupling causally predict academic achievement over semesters
Student-teacher interactions are fundamental to educational success. Leveraging advancements in hyperscanning technology, this study employs longitudinal EEG data to examine the causal effects of student-teacher inter-brain coupling on academic achievements. The findings indicate that enhanced coupling in the high-beta frequency band can positively predict improved academic performance in both Chinese and math subjects. Our analysis also suggests that student-teacher coupling has a unique and significant predictive advantage for Chinese achievement compared to inter-brain coupling among students. This study underscores the causal impact of student-teacher inter-brain coupling on learning based on robust evidence from real classroom settings, confirming its ecological validity.

Intracranial neurophysiological correlates of rumination
Rumination is a transdiagnostic psychological process that plays a prominent role in many common psychiatric disorders, albeit its neurophysiological basis remains elusive. Existing neuroimaging studies have highlighted the precuneus and hippocampus as two essential brain regions in rumination's neural underpinnings. Here, we examined the intracranial electroencephalogram (iEEG) recordings from 21 patients with epilepsy during a naturalistic, continuous, active rumination state and measured the slow frequency (1-8 Hz) and high gamma (70-150 Hz) band oscillation powers. We observed enhanced slow frequency power in the precuneus and reduced high gamma power in the hippocampus during the rumination condition compared to the control condition. The hippocampal high gamma power reduction was associated with the self-reported reflection tendency. Our findings provided the first empirical evidence of the neurophysiological underpinnings of rumination and implicated a precuneus-hippocampus coupling across neural oscillation bands during an active rumination state.

Neural correlates of rapid familiarization to novel taste
The gustatory cortex (GC) plays a pivotal role in taste perception, with neural ensemble responses reflecting taste quality and influencing behavior. Recent work, however, has shown that GC taste responses change across sessions of novel taste exposure in taste-naive rats. Here, we use single-trial analyses to explore changes in the cortical taste-code on the scale of individual trials. Contrary to the traditional view of taste perception as innate, our findings suggest rapid, experience-dependent changes in GC responses during initial taste exposure trials. Specifically, we find that early responses to novel taste are less "stereotyped" and encode taste identity less reliably compared to later responses. These changes underscore the dynamic nature of sensory processing and provides novel insights into the real-time dynamics of sensory processing across novel-taste familiarization.

Mechanical Properties of White Matter Tracts in Aging Assessed via Anisotropic MR Elastography
Magnetic resonance elastography (MRE) is a promising neuroimaging technique to probe tissue microstructure, which has revealed widespread softening with loss of structural integrity in the aging brain. Traditional MRE approaches assume mechanical isotropy. However, white matter is known to be anisotropic from aligned, myelinated axonal bundles, which can lead to uncertainty in mechanical property estimates in these areas when using isotropic MRE. Recent advances in anisotropic MRE now allow for estimation of shear and tensile anisotropy, along with substrate shear modulus, in white matter tracts. The objective of this study was to investigate age-related differences in anisotropic mechanical properties in human brain white matter tracts for the first time. Anisotropic mechanical properties in all tracts were found to be significantly lower in older adults compared to young adults, with average property differences ranging between 0.028-0.107 for shear anisotropy and between 0.139-0.347 for tensile anisotropy. Stiffness perpendicular to the axonal fiber direction was also significantly lower in older age, but only in certain tracts. When compared with fractional anisotropy measures from diffusion tensor imaging, we found that anisotropic MRE measures provided additional, complementary information in describing differences between the white matter integrity of young and older populations. Anisotropic MRE provides a new tool for studying white matter structural integrity in aging and neurodegeneration.

USP14 regulates pS129 α-synuclein levels and oxidative stress in human SH-SY5Y dopaminergic cells
Ubiquitin specific protease-14 (USP14) is critical for controlling protein homeostasis disturbed in human disorders like Parkinson's disease (PD). Here we investigated the role of USP14 in regulating proteasome and autophagy pathways, and their influence on -synuclein (-syn) degradation. Data showed that -syn and phosphorylated serine129 -syn (pS129 -syn) were elevated in USP14 gene deleted SH-SY5Y dopaminergic cells with concomitant reduction in proteasome activity. Inhibition of proteasomes using MG132 particularly elevated pS129 -syn in these cells, but the levels were not influenced by inhibiting autophagy using chloroquine. In contrast, autophagy and the CLEAR (Coordinated Lysosomal Expression and Regulation) pathways were elevated in USP14 lacking cells with an upregulation of the transcription factor TFEB. USP14-ablated cells also exhibited increases in reactive oxidative species (ROS) and elongation of mitochondria. The addition of N-Acetylcysteine amide (NACA) to counteract oxidative stress, reduced pS129 -syn and -syn levels in USP14 deficient cells. Phospho-proteomic analyses revealed that USP14 is phosphorylated at S143 affecting its function and structure as shown by molecular modeling, and protein interaction studies. Re-expression of wild-type and the phospho-mimetic S143D-USP14 mutant decreased ROS, pS129 -syn, and -syn in USP14 lacking cells. These results demonstrate that pS129 -syn levels are sensitive to oxidative stress in SH-SY5Y dopaminergic cells. USP14 by stimulating the proteasome activity and reducing oxidative stress is a promising factor for targeting -syn and its pathogenic variants in PD.

Phylogeny of neocortical-hippocampal projections provides insight in the nature of human memory
Throughout mammalian evolution, the hippocampal region, unlike the neocortex, largely preserved its cytoarchitectural organization and its role in mnemonic functions. This contrast raises the possibility that the hippocampal region receives different types of cortical input across species, which may be reflected in species-specific memory-related differences. To test this hypothesis, we examined differences in unimodal and transmodal cortical input to the hippocampal region in the rat, marmoset, macaque and human. Our results demonstrate that unlike unimodal cortical input, transmodal cortical input to the hippocampal region was selectively preserved during mammalian evolution. These findings suggest that memory-related processes in different species likely operate on different types of sensory information. Our observations provide a comparative anatomical framework elucidating the process of dimensionality reduction underlying the formation of human memory.

Discovery and characterization of stereodefined PMO-gapmers targeting tau
Antisense oligonucleotides (ASOs) are an important class of therapeutics to treat genetic diseases, and expansion of this modality to neurodegenerative disorders has been an active area of research. To realize chronic administration of ASO therapeutics to treat neurogenerative diseases, new chemical modifications improving activity and safety profile are still needed. Furthermore, it is highly desirable to develop a single stereopure ASO with defined activity and safety profile to avoid any efficacy and safety concerns due to the batch-to-batch variation in the composition of diastereomers. Herein, a stereopure PMO-gapmer was developed as a new construct to improve safety and stability by installing charge-neutral PMOs at the wing region and by fully controlling phosphorus stereochemistries. The developed stereopure PMO-gapmer construct was applied to the discovery of ASO candidates for the reduction of microtubule-associated protein tau (MAPT, tau). Sequence screening targeting MAPT followed by screening of optimal phosphorus stereochemistry identified stereopure development candidates. While evaluating the stereopure PMO-gapmers, we observed a dramatic difference in safety profile among stereoisomers in which only one phosphorus stereochemistry differs. These results further highlight the benefits of developing stereopure ASOs as safe and well-characterized candidates for clinical studies.

Dataset factors influencing age-related changes in brain structure and function in neurodevelopmental conditions
With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets, and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (cortical thickness and surface area; N=1,579) and function (resting-state functional connectivity strength; N=1,792) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental network (POND) and the Healthy Brain Network (HBN). We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For cortical surface area, the patterns of differences were associated with intelligence, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling forage effects in analyses.

Limited cognitive resources reduce the language predictability benefit across the adult lifespan
In everyday communication, humans predict upcoming language seemingly effortlessly. However, it remains unclear to what extent the formation of such predictions taxes executive resources. Our study set out to investigate how a limitation of executive resources impacts natural language prediction on multiple timescales in a novel dual-task paradigm, and how this impact is modulated by age. Participants (N = 175; 18-85 years) read short newspaper articles, presented word by word in varying font colours. This self-paced reading task was either performed in isolation or paired with a competing n-back task (1-back or 2-back) on the words' font colour. We measured word-level reading time and block-level reading comprehension as well as n-back performance. To quantify word predictability, we estimated word surprisal on four distinct timescales (i.e., context lengths ranging from words to paragraphs) using a large language model. Under high cognitive load, adults aged 60 and over benefited most from high word predictability. Our results show that independent of timescale, higher cognitive load diminishes the benefits of high word predictability on reading time, suggesting language predictions draw on executive resources.

A TRANSLAMINAR SPACETIME CODE SUPPORTS TOUCH-EVOKED TRAVELING WAVES
Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked cortical traveling waves and their underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a variable late wave that lasted hundreds of milliseconds post-stimulus. Strikingly, late-wave dynamics were modulated by stimulus value and correlated with task performance. Mechanistically, the late wave component was i) modulated by motor feedback, ii) complemented by a sparse ensemble pattern across layer 2/3, which a balanced-state network model reconciled via inhibitory stabilization, and iii) aligned to regenerative Layer-5 apical dendritic Ca2+ events. Our results reveal a translaminar spacetime pattern organized by cortical feedback in the sensory cortex that supports touch-evoked traveling waves.

Selective agonism of GPR34 stimulates microglial uptake and clearance of amyloid β fibrils
Microglia, the primary immune cells of the central nervous system, play a crucial role in maintaining brain homeostasis through phagocytosis of various substrates, including amyloid-{beta} (A{beta}) fibrils, a hallmark of Alzheimer disease (AD) pathology. However, the molecular mechanisms regulating microglial A{beta} uptake remain poorly understood. Here, we identified GPR34, a Gi/o-coupled receptor highly expressed in microglia, as a novel regulator of fibrillar A{beta} phagocytosis. Treatment with a selective GPR34 agonist, M1, specifically enhanced uptake of A{beta} fibrils, but not its monomer or oligomer, in both mouse and human microglia. Mechanistically, M1 reduced intracellular cAMP levels, which inversely correlated with A{beta} uptake activity. Importantly, a single intrahippocampal injection of M1 in an AD mouse model significantly increased microglial A{beta} uptake in vivo. Furthermore, single-nucleus RNA-sequencing analysis of Japanese AD patient samples revealed a significant reduction of GPR34 expression in microglia from AD patients compared to controls. We also observed an age-dependent decline in microglial GPR34 expression in both human and mouse datasets, suggesting a potential contribution of GPR34 downregulation to age-related A{beta} accumulation and AD risk. Collectively, our findings identify GPR34 as a promising target for modulating microglial A{beta} clearance and highlight the therapeutic potential of GPR34 agonists in AD.

Single cell RNA sequencing reveals immunomodulatory mechanism of stem cell factor and granulocyte colony-stimulating factor treatment in the brains of aged APP/PS1 mice
Alzheimers disease leads to progressive neurodegeneration and dementia. Alzheimers disease primarily affects older adults with neuropathological changes including amyloid beta deposition, neuroinflammation, and neurodegeneration. We have previously demonstrated that systemic treatment with stem cell factor, SCF, and granulocyte colony stimulating factor, GCSF, reduces amyloid beta load, increases amyloid beta uptake by activated microglia and macrophages, reduces neuroinflammation, and restores dendrites and synapses in the brains of aged APP-PS1 mice. However, the mechanisms underlying SCF-GCSF-enhanced brain repair in aged APP-PS1 mice remain unclear. This study used a transcriptomic approach to explore the mechanisms by which SCF-GCSF treatment alters the functions of microglia and macrophages in the brains of 28-month-old APP-PS1 mice. After 5-day injections of SCF-GCSF, single-cell RNA sequencing was performed on CD11b positive microglia and macrophages isolated from the brain. Flow cytometry was used for identifying CD11b positive microglia and macrophages in the brain. Both transcriptional profiling and flow cytometry data demonstrated dramatic increases in the population of macrophages in the brain following SCF-GCSF treatment. SCF-GCSF treatment robustly increased the transcription of genes implicated in activated immune cells, including gene sets that regulate inflammatory processes and cell migration. SCF-GCSF treatment also increased a cell population coexpressing microglial and macrophage marker genes. This cell cluster aligned with a disease-associated microglial profile linked with amyloid beta restriction and phagocytosis. S100a8 and S100a9 were the most robustly enhanced genes in both microglial and macrophage clusters following SCF-GCSF treatment. Furthermore, the topmost genes differentially expressed after SCF-GCSF treatment were largely upregulated in S100a8-9 positive microglia and macrophages, suggesting a largely well-conserved transcriptional profile related to SCF-GCSF treatment in cerebral immune cells. This S100a8-9-associated transcriptional profile contained genes related to pro- and anti-inflammatory responses, neuroprotection, and amyloid beta plaque inhibition or clearance. This study sheds new light on the cellular and molecular mechanisms of SCF-GCSF-mitigated Alzheimers disease neuropathology in the aged brain.

Reward perseveration is shaped by GABAA-mediated dopamine pauses
Extinction learning is an essential form of cognitive flexibility, which enables obsolete reward associations to be discarded. Its downregulation can lead to perseveration, a symptom seen in several neuropsychiatric disorders. This balance is regulated by dopamine from VTADA (ventral tegmental area dopamine) neurons, which in turn are largely controlled by GABA (gamma amino-butyric acid) synapses. However, the causal relationship of these circuit elements to extinction and perseveration remain incompletely understood. Here, we employ an innovative drug targeting technology, DART (drug acutely restricted by tethering), to selectively block GABAA receptors on VTADA neurons as mice engage in Pavlovian learning. DART eliminated GABAA mediated pauses; brief decrements in VTADA activity canonically thought to drive extinction learning. However, contrary to the hypothesis that blocking VTADA pauses should eliminate extinction learning, we observed the opposite: accelerated extinction learning. Specifically, DART eliminated the naturally occurring perseveration seen in half of control mice. We saw no impact on Pavlovian conditioning, nor on other aspects of VTADA neural firing. These findings challenge canonical theories, recasting GABAA-mediated VTADA pauses from presumed facilitators of extinction to drivers of perseveration. More broadly, this study showcases the merits of targeted synaptic pharmacology, while hinting at circuit interventions for pathological perseveration.

Cell type- and layer-specific plasticity of olfactory bulb interneurons following olfactory sensory neuron ablation
Lifelong neurogenesis endows the mouse olfactory system with a capacity for regeneration that is unique in the mammalian nervous system. Throughout life, olfactory sensory neurons (OSNs) are generated from olfactory epithelium (OE) stem cells in the nose, while the subventricular zone generates neuroblasts that migrate to the olfactory bulb (OB) and differentiate into multiple populations of inhibitory interneurons. Methimazole (MMZ) selectively ablates OSNs, but OE neurogenesis enables OSN repopulation and gradual recovery of OSN input to the OB within six weeks. However, it is not known how OB interneurons are affected by this loss and subsequent regeneration of OSN input following MMZ treatment. We found that dopaminergic neuron density was significantly reduced 7-14 days post-MMZ but recovered substantially at 35 days. The density of parvalbumin-expressing interneurons was unaffected by MMZ; however, their soma size was significantly reduced at 7-14 days post-MMZ, recovering by 35 days. Surprisingly, we found a transient increase in the density of calretinin-expressing neurons in the glomerular and external plexiform layers, but not the granule cell layer, 7 days post- MMZ. This could not be accounted for by increased neurogenesis but may result from increased calretinin expression. At subsequent time points, calretinin neurons in all three layers showed reduced density at 14 days but recovered to baseline by 35 days. Together, our data demonstrate cell type- and layer-specific changes in OB interneuron density and morphology after MMZ treatment, providing new insight into the range of plasticity mechanisms employed by OB circuits during loss and regeneration of sensory input.

Hypergraph Cortical Cytoarchitectonic Parcellation with Multimodal Canine Brain Atlas
Brain atlases are vital tools in exploring the brain structure-function relationship. The burgeoning cross-species atlases have significantly accelerated our understanding of human brain development, evolution, function, and diseases. However, the existing coarse-grained macroscopic canine brain atlases greatly constrain their utility as an animal model for neurocognition research. Finer-grained brain atlas and partitions are crucial for decoding brain spatial heterogeneity and topology at different scales. Therefore, we conduct macroscopic and microscopic brain imaging to construct an interactive online dataset of multimodal canine brain atlas. Additionally, we develop a pioneering method for cortical cytoarchitectonic partitioning based on hypergraph learning. By integrating high-dimensional cytoarchitectonic features and spatial connections between cortical columns, the method leads to fine-grained partitioning patterns. This innovative approach aims to decode the biological heterogeneity of cortical microstructures, contributing to the structural annotation of canine atlas as well as public human brain atlases. The study not only offers valuable resources but also presents a novel zonation approach to investigate the cellular organization pattern and topology of the cortex.

A meta reinforcement learning account of behavioral adaptation to volatility in recurrent neural networks
Natural environments often exhibit various degrees of volatility, ranging from slowly changing to rapidly changing contingencies. How learners adapt to changing environments is a central issue in both reinforcement learning theory and psychology. For example, learners may adapt to changes in volatility by increasing learning if volatility increases, and reducing it if volatility decreases. Computational neuroscience and neural network modeling work suggests that this adaptive capacity may result from a meta-reinforcement learning process (implemented for example in the prefrontal cortex), where past experience endows the system with the capacity to rapidly adapt to environmental conditions in new situations. Here we provide direct evidence for a meta-reinforcement learning account of adaptation to environmental volatility. Recurrent neural networks (RNNs) were trained on a restless four-armed bandit reinforcement learning problem under three different training regimes (low volatility training only, medium volatility training only, or meta-volatility training across a range of volatilities). We show that, in contrast to RNNs trained in the low volatility regime, RNNs trained under the medium or meta-volatility regimes exhibited a superior adaption to environmental volatility. This was reflected in a better performance, and computational modeling of the networks behavior revealed a more adaptive adjustment of learning and exploration to varying levels of volatility during test. Results extend the meta-RL account to volatility adaptation and confirm past experience as a crucial factor of adaptive decision-making.

A Mutation in Tmem135 Causes Progressive Sensorineural Hearing Loss
Transmembrane protein 135 (TMEM135) is a 52 kDa protein with five predicted transmembrane domains that is highly conserved across species. Previous studies have shown that TMEM135 is involved in mitochondrial dynamics, thermogenesis, and lipid metabolism in multiple tissues; however, its role in the inner ear or the auditory system is unknown. We investigated the function of TMEM135 in hearing using wild-type (WT) and Tmem135FUN025/FUN025 (FUN025) mutant mice on a CBA/CaJ background, a normal-hearing mouse strain. Although FUN025 mice displayed normal auditory brainstem response (ABR) at 1 month, we observed significantly elevated ABR thresholds at 8, 16, and 64 kHz by 3 months, which progressed to profound hearing loss by 12 months. Consistent with our auditory testing, 13-month-old FUN025 mice exhibited a severe loss of outer hair cells and spiral ganglion neurons in the cochlea. Our results using BaseScope in situ hybridization indicate that TMEM135 is expressed in the inner hair cells, outer hair cells, and supporting cells. Together, these results demonstrate that the FUN025 mutation in Tmem135 causes progressive sensorineural hearing loss, and suggest that TMEM135 is crucial for maintaining key cochlear cell types and normal sensory function in the aging cochlea.

Spatial modulation of facial expression: enhanced recognition of faces behind the observer
Our ability to recognize facial expressions is crucial for understanding others' emotions and facilitating smooth communication. Numerous studies have explored how we perceive these cues, considering factors such as health, social signals and personality traits. However, most of this research involves observers facing a monitor and assessing facial stimuli presented directly in front of them. Real-life scenarios offer more diverse spatial dynamics, such as conversing with someone at a table or glancing back at a passerby. Thus, faces behind the observer might trigger heightened recognition, akin to reacting swiftly to a perceived threat. Herein, we demonstrate that facial expression recognition is influenced by spatial relationships, i.e., faces in front of versus behind the observer. Participants judged the expressions of faces appearing in front of or behind them in virtual space. The findings of three experiments reveal an enhanced level of recognition for faces behind the participant. Interestingly, this effect varies with emotional valence; anger is amplified merely by the presence of a face behind the observer, while happiness requires actively turning to the rear for enhancement to occur. These findings suggest a biological instinct for perceiving threats behind us, potentially influencing subsequent actions. Hence, spatial relationships may modulate facial expression recognition.

A mismatch between striatal cholinergic pauses and dopaminergic reward prediction errors
Movement, motivation and reward-related learning depend strongly on striatal dopamine and acetylcholine. These neuromodulators each regulate the other, and disturbances to their coordinated signals contribute to human disorders ranging from Parkinson's Disease to depression and addiction. Pauses in the firing of cholinergic interneurons (CINs) are thought to coincide with pulses in dopamine release that encode reward prediction errors (RPEs), together shaping synaptic plasticity and thereby learning. However, such models are based upon recordings from unidentified neurons, and do not incorporate the distinct characteristics of striatal subregions. Here we compare the firing of identified, individual CINs to dopamine release as unrestrained rats performed a probabilistic decision-making task. The relationships between CIN spiking, dopamine release, and behavior varied strongly by subregion. In dorsal-lateral striatum a Go! cue evoked burst-pause CIN spiking, quickly followed by a very brief (~150ms) dopamine pulse that was unrelated to RPE. In dorsal-medial striatum the same cue evoked only a CIN pause; this pause was curtailed by a movement-selective rebound in firing. Finally in ventral striatum a reward cue evoked slower, RPE-coding increases in both dopamine and CIN firing, without any distinct pause. Our results demonstrate a spatial and temporal dissociation between CIN pauses and dopamine RPE signals, and will inform new models of striatal microcircuits and their contributions to behavior.

FAM19A5 Deficiency Mitigates the Aβ Plaque Burden and Improves Cognition in Mouse Models of Alzheimer's Disease
FAM19A5, a novel secretory protein highly expressed in the brain, is potentially associated with the progression of Alzheimer's disease (AD). However, its role in the AD brain remains unclear. Here, we investigated the potential function of FAM19A5 in the context of AD. We generated APP/PS1 mice with partial FAM19A5 deficiency, termed APP/PS1/FAM19A5LacZ+/-. Compared to control APP/PS1 mice, APP/PS1/FAM19A5LacZ+/- mice exhibited significantly lower A{beta} plaque density, suggesting that FAM19A5 reduction mitigates A{beta} plaque formation. Notably, FAM19A5 partial depletion also prolonged the lifespan of APP/PS1 mice. To further explore the therapeutic potential of FAM19A5 targeting, we developed an anti-FAM19A5 antibody. Administration of this antibody to APP/PS1 mice significantly improved their performance in the novel object recognition test, demonstrating enhanced cognitive function. This effect was reproduced in 5XFAD mice, a model of early-onset AD with rapid A{beta} accumulation. Additionally, anti-FAM19A5 antibody treatment in 5XFAD mice led to increased spontaneous alternation behavior in the Y-maze test, indicating improved spatial working memory. These findings suggest that anti-FAM19A5 antibodies may be a promising therapeutic strategy for AD by reducing A{beta} plaques and improving cognitive function.

Cntnap2 loss drives striatal neuron hyperexcitability and behavioral inflexibility
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by two major diagnostic criteria - persistent deficits in social communication and interaction, and the presence of restricted, repetitive patterns of behavior (RRBs). Evidence from both human and animal model studies of ASD suggest that alteration of striatal circuits, which mediate motor learning, action selection, and habit formation, may contribute to the manifestation of RRBs. CNTNAP2 is a syndromic ASD risk gene, and loss of function of Cntnap2 in mice is associated with RRBs. How loss of Cntnap2 impacts striatal neuron function is largely unknown. In this study, we utilized Cntnap2-/- mice to test whether altered striatal neuron activity contributes to aberrant motor behaviors relevant to ASD. We find that Cntnap2-/- mice exhibit increased cortical drive of striatal projection neurons (SPNs), with the most pronounced effects in direct pathway SPNs. This enhanced drive is likely due to increased intrinsic excitability of SPNs, which make them more responsive to cortical inputs. We also find that Cntnap2-/- mice exhibit spontaneous repetitive behaviors, increased motor routine learning, and cognitive inflexibility. Increased corticostriatal drive, in particular of the direct pathway, may contribute to the acquisition of repetitive, inflexible behaviors in Cntnap2 mice.

Nothing but lies: improving the validity of neural predictors of deception
Deception is a universal human behavior. Yet longstanding skepticism about the validity of measures used to understand the biological mechanisms underlying deceptive behavior has relegated such studies to the scientific periphery. Here we address these fundamental questions by applying novel machine learning methods and functional neuroimaging to signaling games capturing motivated deception in human participants. First, we develop an approach to test for the presence of confounding processes and thereby validate past skepticism by showing that much of the predictive power of neural predictors trained on deception data comes from confounding processes. Second, we show that the presence of confounding signals need not be fatal, and we improve the validity of our neural predictor via a novel machine learning procedure that identifies and removes these confounding signals. Together, these findings point to a scientific approach for studying a neglected class of behavior, with important methodological and societal implications.

Myosin VI controls localization of Golgi satellites at active presynaptic boutons
Neurons, as long-living non-dividing cells with complex morphology, depend on highly elaborate secretory trafficking system which ensures the constant delivery, removal and recycling of proteins and membranes. Previously, we have shown that simplified Golgi-related structures called Golgi satellites (GS), distinct from the somatic Golgi complex, are present in dendrites of primary hippocampal neurons and are involved in glycosylation and local forward trafficking of membrane proteins. However, whether GS are also targeted to axons of principal neurons have not been explored. Here, we investigate the subcellular distribution of GS in adult hippocampal neurons and discover that mobile and stationary GS are present along the entire axonal length, extending to the distal tips of the growth cone. Live imaging experiments revealed that neuronal firing modulates the switch between long range transport mediated by kinesin and dynein and stalling. We found that GS frequently pause or stop at pre-synaptic sites in activity-dependent manner. This behavior depends on the actin cytoskeleton and the actin-based motor protein myosin VI. Overall, our study demonstrates that neuronal activity can dynamically regulate the positioning of GS in the axon, shedding light on the intricate mechanisms underlying organelle trafficking in neurons.

Neurocomputational Mechanisms Underlying Maladaptive Self-Belief Formation in Depression
A core symptom of major depression is maladaptive self-beliefs. These are perpetuated by negatively biased feedback processing. Understanding the neurocomputational mechanisms of biased belief updating may help to counteract maladaptive beliefs. The present study uses functional neuroimaging to examine neural activity associated with prediction error-based learning in depression and healthy controls. We hypothesized that increasing symptom burden is associated with negatively biased self-belief formation and altered neural tracking of social feedback. Results showed that a higher symptom burden was associated with forming more negative self-beliefs and more positive beliefs about others. This bias was driven by reduced learning from positive prediction errors in depression. Neural reactivity of the insula showed increased tracking of more negative self-related prediction errors. The interplay of increased neural responsiveness to negative feedback and reduced learning from positive feedback may contribute to the persistence of maladaptive self-beliefs and, thus, the maintenance of depression.

O-GalNAc glycans enrich in white matter tracts and regulate nodes of Ranvier
Protein O-glycosylation is a critical modification in the brain, as genetic variants in the pathway are associated with both common and severe neuropsychiatric phenotypes. However, little is known about the most abundant type of O-glycan in the mammalian brain, which are O-GalNAc linked. Here, we determined the spatial localization, protein carriers, and cellular function of O-GalNAc glycans in mouse brain. We observed striking spatial enrichment of O-GalNAc glycans in white matter tracts and at nodes of Ranvier. Glycoproteomic analysis revealed that more than half of the identified O-GalNAc glycans were present on chondroitin sulfate proteoglycans termed lecticans, and display both domain enrichment and site-specific heterogeneity. Though genetic ablation in a single cell type failed to replicate the severe phenotypes seen in congenital disorders, inhibition of O-GalNAc synthesis in neurons reduced binding of Siglec-4, a known regulator neurite growth, and shortened the length of nodes of Ranvier. This work highlights a new function of O-GalNAc glycans in the brain and will inform future studies on their role in development and disease.

Deciphering the ferroptosis pathways in dorsal root ganglia of Friedreich ataxia models. The role of LKB1/AMPK, KEAP1, and GSK3beta in the impairment of the NRF2 response
Friedreich ataxia (FA) is a rare neurodegenerative disease caused by decreased levels of the mitochondrial protein frataxin. Frataxin has been related in iron homeostasis, energy metabolism, and oxidative stress. Ferroptosis has recently been shown to be involved in FA cellular degeneration; however, its role in dorsal root ganglion (DRG) sensory neurons, the cells that are affected the most and the earliest, is mostly unknown. In this study, we used primary cultures of frataxin-deficient DRG neurons as well as DRG from the FXNI151F mouse model to study ferroptosis and its regulatory pathways. A lack of frataxin induced upregulation of transferrin receptor 1 and decreased ferritin and mitochondrial iron accumulation, a source of oxidative stress. However, there was impaired activation of NRF2, a key transcription factor involved in the antioxidant response pathway. Decreased total and nuclear NRF2 explains the downregulation of both SLC7A11 (a member of the system Xc, which transports cystine required for glutathione synthesis) and glutathione peroxidase 4, responsible for increased lipid peroxidation, the main markers of ferroptosis. Such dysregulation could be due to the increase in KEAP1 and pGSK3beta (Tyr216), which promote cytosolic localization and degradation of NRF2. Moreover, there was a deficiency in the LKB1/AMPK pathway, which would also impair NRF2 activity. AMPK acts as a positive regulator of NRF2 and it is activated by the upstream kinase LKB1. The levels of LKB1 were reduced when frataxin decreased, in agreement with reduced pAMPK (Thr172), the active form of AMPK. SIRT1, a known activator of LKB1, was also reduced when frataxin decreased. In conclusion, this study demonstrated that frataxin deficiency in DRG neurons disrupts iron homeostasis and the intricate regulation of molecular pathways affecting NRF2 activation and the cellular response to oxidative stress, leading to ferroptosis.