bioRxiv Subject Collection: Neuroscience's Journal

Influence of contextual exposure on memory strength and precision for inhibitory avoidance in male and female rats
Aversive associative learning paradigms such as inhibitory avoidance (IA) are frequently used to examine episodic-like memories in rodents. In IA, rodents learn to associate a context with a footshock, followed by testing for memory strength in the original training context and for memory precision in a similar yet distinct neutral context. The present work assessed the effects of different contextual exposure procedures on memory strength and precision in IA at both recent and remote time points using male and female Long-Evans rats. An initial experiment found that rats kept in the lit (non-shock) compartment of the IA apparatus for 60 s during training, as opposed to 10 s, displayed enhanced memory strength, with discrimination between both chambers at the recent retention test and generalization at the remote retention test. Subsequent experiments investigated the effects of contextual pre-exposure the day before training. The results indicate that pre-exposure to the neutral context promoted generalization without altering memory strength compared to the first experiment. In contrast, pre-exposure to the aversive chamber promoted discrimination and enhanced memory strength. Notably, the different procedures yielded similar effects in both sexes. However, the results also indicate an overall pattern of greater contextual discrimination in females compared to males. These findings provide evidence for how different contextual exposures influence the degree of encoding at the time of training and a behavioral foundation for future studies examining the neurobiological mechanisms underlying memory strength and precision in IA, while highlighting the importance of using both sexes in initial behavioral work.

The Good, the Bad, and the Ugly: Segmentation-Based Quality Control of Structural Magnetic Resonance Images
The processing and analysis of magnetic resonance images is highly dependent on the quality of the input data, and systematic differences in quality can consequently lead to loss of sensitivity or biased results. However, varying image properties due to different scanners and acquisition protocols, as well as subject-specific image interferences, such as motion artifacts, can be incorporated in the analysis. A reliable assessment of image quality is therefore essential to identify critical outliers that may bias results. Here we present a quality assessment for structural (T1-weighted) images using tissue classification. We introduce multiple useful image quality measures, standardize them into quality scales and combine them into an integrated structural image quality rating to facilitate the interpretation and fast identification of outliers with (motion) artifacts. The reliability and robustness of the measures are evaluated using synthetic and real datasets. Our study results demonstrate that the proposed measures are robust to simulated segmentation problems and variables of interest such as cortical atrophy, age, sex, brain size and severe disease-related changes, and might facilitate the separation of motion artifacts based on within-protocol deviations. The quality control framework presents a simple but powerful tool for the use in research and clinical settings.

Dissecting the sublexical route for reading: Frontal and parietal networks support learned orthography-to-phonology mappings
Oral reading relies on lexical and sublexical processes with distinct neural mechanisms. Damage within the sublexical system causes phonological alexia, a blanket diagnosis describing acquired deficits in reading unfamiliar words. Improving the precision of alexia diagnosis requires understanding the neurocognitive basis of specific reading subprocesses. This study investigated the neural correlates of sublexical reading in 64 adults with chronic left-hemisphere stroke (LHS), focusing on lesions that impair the use of learned orthography-to-phonology (OP) mappings to read new words. Participants read aloud real words and three types of pseudowords varying in the number of plausible OP mappings at the level of the orthographic body: zero mappings (0M), one mapping (1M), and multiple mappings (MM). LHS participants exhibited phonological reading deficits with an exaggerated lexicality effect compared to 71 neurotypical controls. Across both groups, pseudowords with learned OP mappings were read more accurately than those without. Voxelwise and connectome-based lesion-symptom mapping revealed that relative lexical reading deficits were associated with lateral temporal lesions, while sublexical reading deficits were associated with lesions or disconnections of the left inferior frontal (IFG), supramarginal, and pre/postcentral gyri. Applying learned OP mappings relied on anterior IFG and frontoparietal connections, while resolving multiple plausible OP mappings relied on intraparietal connections. These results underscore the role of learned mutigraphemic OP mappings in sublexical reading, and demonstrate that disruptions of different sublexical reading subprocesses result in subtly different deficit patterns. Dissecting the neurocognitive basis of reading subprocesses may improve the precision of alexia diagnosis and point to new treatments.

Reading fluency development is predicted by cortical latency
The development of fluent literacy skills from childhood to adolescence is strongly constrained by the temporal dynamics of word recognition. Capturing the neural basis of these subtle timing changes in word recognition has remained challenging with EEG measures that lack reliability at the individual subject level. Here, we leverage phase information from Steady-State Visual Evoked Potentials (SSVEPs) to derive precise and reliable temporal dynamics of neural signatures underlying visual word form recognition at the individual level and examine their relationship to reading fluency and comprehension. Typically developing readers (N = 68), aged 8-15 years, viewed a stream of four-character stimulus strings presented at 3 Hz. Significant SSVEP signals emerged for nearly all participants. Signals at 3, 6, and 9 Hz harmonics exhibited a phase pattern consistent with a delay model, indicating a mean latency of approximately 170 milliseconds. Individual variations in latencies demonstrated (a) high internal consistency (R = .94); (b) stability across variations in letter string forms (familiar words, nonwords with familiar letters, nonwords with unfamiliar pseudo-characters); (c) a linear relationship with age; and most remarkably, (d) a predictive relationship with individual variation in reading fluency and reading comprehension. These results establish SSVEP visual word form latency as a promising approach for investigating the neural basis of reading development, paving the way for future translational applications in education and offering potential solutions to broader societal challenges in promoting population-level reading fluency.

Spatial and molecular insights into microglial roles in cerebellar aging
Aging induces region-specific functional decline across the brain. The cerebellum, critical for motor coordination and cognitive function, undergoes significant structural and functional changes with age. The molecular mechanisms driving cerebellar aging, particularly the role of cerebellar glia, including microglia, remain poorly understood. Here, we used single-nuclei RNA sequencing (snRNA-seq), microglial bulk RNA-seq, and multiplexed error-robust fluorescence in situ hybridization (MERFISH) to characterize transcriptional changes associated with cellular aging in the mouse cerebellum. We discovered that microglia exhibited the most pronounced age-related changes of all cell types and that their transcriptional signatures pointed to enhanced neuroprotective immune activation and reduced lipid-droplet accumulation compared to hippocampal microglia. Furthermore, cerebellar microglia in aged mice, compared to young mice, were found in closer proximity to granule cells. This relationship was characterized using the newly defined neuron-associated microglia score, which captures proximity-dependent transcriptional changes and suggests a novel microglial responsiveness. These findings underscore the unique adaptations of the cerebellum during aging and its potential resilience to Alzheimers disease (AD) related pathology, providing crucial insight into region-specific mechanisms that may shape disease susceptibility.

The astrocyte Fabp7 gene regulates diurnal seizure threshold and activity-dependent gene expression in mice
Epileptic seizures are often influenced by time-of-day and changes in vigilance state, yet the molecular and cellular mechanisms underpinning these associations remain poorly understood. Astrocytes, a pivotal type of glial cell, play a critical role in modulating neuronal excitability and circadian rhythms, and they express Fatty Acid Binding Protein 7 (Fabp7), a molecule vital for sleep regulation, lipid signaling, and gene transcription. This study investigates the role of Fabp7 in determining time-of-day dependent seizure susceptibility. We assessed electroshock seizure thresholds in male C57/BL6N wild-type (WT) and Fabp7 knockout (KO) mice. Results demonstrated that, compared to WT mice, Fabp7 KO mice displayed significantly elevated general and maximal electroshock seizure thresholds (GEST and MEST) during the dark phase, but not during the light phase. To explore the impact of Fabp7 on activity-dependent gene expression during seizures, we conducted RNA sequencing (RNA-seq) on cortical and hippocampal tissues from WT and Fabp7 KO mice following MEST and SHAM procedures during the dark period. While immediate early genes (IEGs) showed considerable differential expression between WT-MEST and WT-SHAM, this expression was absent in Fabp7 KO-MEST compared to Fabp7 KO-SHAM. Gene ontology analyses revealed significant overlaps between the WT-MEST:WT-SHAM and Fabp7 KO-SHAM:WT-SHAM comparisons, indicating that the basal mRNA expression profiles in Fabp7 KO brains resemble those of WT brains in a post-ictal state. Collectively, these findings suggest that Fabp7 is a key regulator of time-of-day dependent neural excitability and that astrocyte-mediated signaling pathways involving Fabp7 interact with neuronal activity to influence gene expression in response to seizures.

Mapping the ISR Landscape in Cognitive Disorders via single-cell multi-omics
Persistent activation of the integrated stress response (ISR) is a major driver of cognitive decline in both neurodevelopmental and neurodegenerative disorders. Using a new mouse model (Ppp1r15bR658C mice) that mimics the persistent ISR activation and cognitive decline observed in humans, we generated the first single-cell ISR atlas of the brain. By integrating single-cell RNA-seq and single-cell ATAC-seq with proteomics, we discovered that distinct brain cell types respond differently to persistent ISR activation and elicit cell-type-specific ISR programs. Interestingly, chromatin accessibility analyses revealed that the ISR downstream factor ATF4 is a key ISR effector in GABAergic neurons, while AP-1 (JUNB) is implicated in glutamatergic neurons. More importantly, selective deletion of ATF4 in GABAergic neurons, but not in glutamatergic neurons, impacts ISR-mediated cognitive decline in Ppp1r15bR658C mice, demonstrating that different neuronal subtypes rely on unique ISR downstream effectors to regulate mnemonic processes. Furthermore, we defined a comprehensive molecular signature of persistent ISR activation, which we showed could serve as a biomarker for cognitive dysfunction across neurodevelopmental, neurodegenerative disorders and normal aging. This multi-omic framework provides a key platform for exploring and validating new scientific hypotheses, significantly advancing our understanding of ISR-related brain disorders.

Revealing the mechanisms underlying latent learning with successor representations
Latent learning experiments were critical in shaping Tolman's cognitive map theory. In a spatial navigation task, latent learning means that animals acquire knowledge of their environment through exploration, without explicit reinforcements. Animals pre-exposed in this way perform better on a subsequent learning task than those that were not. This learning enhancement is dependent on the specific design of the pre-exposure phase. Here, we investigate latent learning and its modulation using computational modeling based on the deep successor representation (DSR), a recent model for cognitive map formation. Our results confirm experimental observations in that exploration aligned with the future reward location significantly improves reward learning compared to random or no exploration. This effect generalizes across different action selection strategies. We show that these performance differences follow from the spatial information encoded in the structure of the DSR acquired in the pre-exposure phase. In summary, this study sheds light on the mechanisms underlying latent learning and how such learning shapes cognitive maps, impacting their effectiveness in goal-directed spatial tasks.

EEG reveals online monitoring mechanisms of speech production
Speaking involves the orchestration of multiple speech muscles while actively monitoring sensory consequences through auditory and somatosensory feedback. A mistuned sensorimotor mechanism may disrupt the normal integration of motor and auditory brain systems in several developmental and acquired motor speech disorders, including stuttering, speech apraxia, speech sound disorders and dysarthria. Electroencephalography (EEG) provides a non-invasive measure of online neural activity with potential to assess (deficiencies in) sensorimotor integration during speech production. However, the relation between EEG and continuous speech output remains poorly characterized. Here, we investigate prediction of auditory speech output using multivariate EEG patterns under three levels of auditory masking. A decoding analysis was employed in combination with a lag-based approach that allowed studying predictions based on instantaneous EEG-speech relations, and their involvement in feedforward and feedback processes. For all masking conditions, we found consistent decoding in instantaneous lags and speech feedback lags, but not in feedforward lags. Furthermore, the level of auditory masking modulated decoding in both the instantaneous and feedback lags. Our results provide insights of neural monitoring during online speech production and offer a window to further study the dysfunction latent in motor speech disorders that may help in optimizing brain-informed therapies for speech fluency.

MICROGLIAL EXTRACELLULAR VESICLES MEDIATE C1Q DEPOSITION AT THE PRE-SYNAPSE AND PROMOTE SYNAPTIC PRUNING
C1q is released by microglia, localizes on weak synapses and acts as a tag for microglial synaptic pruning. However, how C1q tags synapses during the pruning period remains to be fully elucidated. Here, we report that C1q is delivered by microglia to pre-synaptic sites that externalize phosphatidylserine through extracellular vesicles. Using approaches to increase or reduce vesicles production in microglia, by C9orf72 knock out or pharmacological inhibition respectively, we provided mechanistic evidence linking extracellular vesicle release to pre-synaptic remodelling in neuron-microglia cultures. In C9orf72 knockout mice, we confirmed larger production of microglial extracellular vesicles, and showed augmented C1q presynaptic deposition associated with enhanced engulfment by microglia in the early postnatal hippocampus. Finally, we provide evidence that microglia physiologically release more vesicles during the period of postnatal circuit refinement. These findings implicate abnormal release of microglial extracellular vesicles in both neurodevelopmental and age-related disorders characterized by dysregulated microglia-mediated synaptic pruning.

Profiling local translatomes and RNA binding proteins of somatosensory neuronsreveals specializations of individual axons
Individual neurons have one or more axons that often extend long distances and traverse multiple microenvironments. However, it is not known how the composition of individual axons is established or locally modulated to enable neuronal function and plasticity. Here, we use spatial translatomics to identify local axonal translatomes in anatomically and functionally specialized neurons in the dorsal root ganglia (DRG). DRG neurons extend long central and peripheral axons in opposite directions and distinct microenvironments to enable somatosensation. Using Translating Ribosome Affinity Purification and RNA sequencing, we generated a comprehensive resource of mRNAs preferentially translated within each axon. Locally translated proteins include pain receptors, ion channels, and translational machinery, which establish distinct electrophysiologic properties and regenerative capacities for each axon. We identify RNA-binding proteins associated with sorting and transporting functionally related mRNAs. These findings provide resources for addressing how axonal translation shapes the spatial organization of neurons and enables subcellular neuroplasticity.

Parietal cortex is recruited by frontal and cingulate areas to support action monitoring and updating during stopping
Recent evidence indicates that the intraparietal sulcus (IPS) may play a causal role in action stopping, potentially representing a novel neuromodulation target for inhibitory control dysfunctions. Here, we leverage intracranial recordings in human subjects to establish the timing and directionality of information flow between IPS and prefrontal and cingulate regions during action stopping. Prior to successful inhibition, information flows primarily from the inferior frontal gyrus (IFG), a critical inhibitory control node, to IPS. In contrast, during stopping errors the communication between IPS and IFG is lacking, and IPS is engaged by posterior cingulate cortex, an area outside of the classical inhibition network and typically associated with default mode. Anterior cingulate and orbitofrontal cortex also display performance-dependent connectivity with IPS. Our functional connectivity results provide direct electrophysiological evidence that IPS is recruited by frontal and anterior cingulate areas to support action plan monitoring/updating, and by posterior cingulate during control failures.

Human brain cell-type-specific aging clocks based on single-nuclei transcriptomics
Aging is the primary risk factor for most neurodegenerative diseases, yet the cell-type-specific progression of brain aging remains poorly understood. Here, we developed human cell-type-specific transcriptomic aging clocks using high-quality single-nucleus RNA sequencing data from post mortem human prefrontal cortex tissue of 31 donors aged 18-94 years, encompassing 73,941 high-quality nuclei. We observed distinct transcriptomic changes across major cell types, including upregulation of inflammatory response genes in microglia from older samples. Aging clocks trained on each major cell type accurately predicted chronological age and remained robust in independent single-nucleus RNA-sequencing datasets, underscoring their broad applicability. These findings demonstrate the feasibility of cell-type-specific transcriptomic clocks to measure biological aging in the human brain and highlight potential mechanisms of selective vulnerability in neurodegenerative diseases. We anticipate these clocks will serve as a basis for further studies in other brain regions and more diverse populations, ultimately advancing our understanding of age-related neurodegenerative processes at the single-cell level.

Atypical functional connectome in congenitally blind humans
The cortex is organized along macroscale structural and functional gradients that extend from unimodal to transmodal association areas and from somatosensory to visual regions. It has not been tested whether this organization represents an intrinsic neuro-architecture immune to sensory experience or depends on sensory input. Here, we conducted connectome gradient analyses using resting-state functional Magnetic Resonance Imaging in congenitally blind individuals and sighted controls. In both groups, we observed a principal gradient (G1) extending from unimodal to transmodal, a second gradient (G2) spanning from somatosensory to visual, and a third gradient (G3) separating the frontoparietal network from the rest of the brain. Our findings indicate that the macroscale organization of the cortex develops largely independently of sensory experience. However, in blind individuals, the sensorimotor network was more distanced from the visual network (G2), while the visual network was more integrated with transmodal (G1) and frontoparietal (G3) networks. In blind individuals, the hierarchical organization within the early visual cortex was altered, the structure-function coupling in visual and temporal areas was reduced, and functional similarity between V1 center and periphery disappeared. These results suggest a critical role of sensory input in shaping the macroscale functional and structural organization of the brain.

Reduced harmonic complexity of brain parenchymal cardiovascular pulse waveforms in Alzheimer's disease
Alzheimer's disease (AD) is characterized by specific neuropathologies, and is associated with arterial wall {beta}-amyloid accumulations, which lead to radiologically detectable amplitude increases and variable propagation speed of cardiovascular impulses in brain. In this study, we developed a fast frequency domain imaging method know as relative harmonic power of magnetic resonance encephalography (MREGRHP), aiming to investigate the configuration of the cardiovascular impulses independently of the mean magnetic resonance signal intensity and physiological impulse amplitude. In the initial analyses in healthy controls, we found that a wide 0.8 - 5Hz bandpass produced the most physiologically realistic cardiovascular waveforms. Whereas the data recorded in cerebrospinal fluid (CSF) from flip angle (FA) of 25{degrees} yielded up to 7-fold higher cardiac signal intensity as compared to FA of 5{degrees}, within the brain tissue recordings with FA of 5{degrees} were markedly more sensitive to cardiac waveform. We detected arterial impulses originating from major arteries and extending into the surrounding brain parenchyma, with simultaneous dampening of amplitude as a function of distance from source. Finally, we compared MREGRHP results in 34 AD patients (mean age: 60.7{+/-}4.7 years; 53% female) against 29 controls (mean age: 56.9{+/-}7.9 years; 66% female). We show that the harmonic power of cardiovascular brain pulses is significantly reduced in cortical frontoparietal areas of AD patients, indicating monotonous impulse patterns colocalizing with the previously reported areas of increased impulse propagation speed. In conclusion, the MREGRHP offers a fast Fourier transform (FFT)-based method to non-invasively quantify and locate human arterial blood vessel wall pathology.

Examining Alzheimer's Disease Modifiable Risk Factors: Impact of Physical Activity and Diet on Neuroanatomy and Behaviour in Mice
Dementia, a global public health challenge, is significantly influenced by lifestyle factors such as obesity. This study examines the impact of obesity and intervention approaches -physical exercise, a low-fat diet, or both- on brain structure in a triple-transgenic mouse model of Alzheimer's disease (3xTgAD) and wild-type mice fed a high-fat diet. Volumetric and deformation-based morphometry analyses showed significant neuroanatomical differences related to genotype and a high-fat diet, particularly affecting the hippocampus and cerebellum. Diet and exercise interventions partially mitigate these effects. Volume changes were correlated with behavioural data, producing a unique brain-behaviour signature tied to intervention-driven neuroanatomy improvements. This pattern was correlated with gene expression patterns, identifying modules of genes related to metabolic processes such as glucose homeostasis and fatty acid transportation. Overall, interventions promote changes that seem to counteract some of the effects of a high-fat diet, influencing biological processes that support brain health.

Local cues enable classification of image patches as surfaces, object boundaries, or illumination changes
To correctly parse the visual scene, one must detect edges and determine their underlying cause. Previous work has demonstrated that image-computable neural networks trained to differentiate natural shadow and occlusion edges exhibited sensitivity to boundary sharpness and texture differences. Although these models showed a strong correlation with human performance on an edge classification task, this previous study did not directly investigate whether humans actually make use of boundary sharpness and texture cues when classifying edges as shadows or occlusions. Here we directly investigated this using synthetic image patch stimuli formed by quilting together two different natural textures, allowing us to parametrically manipulate boundary sharpness, texture modulation, and luminance modulation. In a series of initial training experiments, observers were trained to correctly identify the cause of natural image patches taken from one of three categories (occlusion, shadow, uniform texture). In a subsequent series of test experiments, these same observers then classified 5 sets of synthetic boundary images defined by varying boundary sharpness, luminance modulation, and texture modulation cues using a set of novel parametric stimuli. These three visual cues exhibited strong interactions to determine categorization probabilities. For sharp edges, increasing luminance modulation made it less likely the patch would be classified as a texture and more likely it would be classified as an occlusion, whereas for blurred edges, increasing luminance modulation made it more likely the patch would be classified as a shadow. Boundary sharpness had a profound effect, so that in the presence of luminance modulation increasing sharpness decreased the likelihood of classification as a shadow and increased the likelihood of classification as an occlusion. Texture modulation had little effect on categorization, except in the case of a sharp boundary with zero luminance modulation. Results were consistent across all 5 stimulus sets, showing these effects are not due to the idiosyncrasies of the particular texture pairs. Human performance was found to be well explained by a simple linear multinomial logistic regression model defined on luminance, texture and sharpness cues, with slightly improved performance for a more complicated nonlinear model taking multiplicative parameter combinations into account. Our results demonstrate that human observers make use of the same cues as our previous machine learning models when detecting edges and determining their cause, helping us to better understand the neural and perceptual mechanisms of scene parsing.

Shapley Fields Reveal Chemotopic Organization in the Mouse Olfactory Bulb Across Diverse Chemical Feature Sets
Representations of chemical features in the neural activity of the olfactory bulb (OB) are not well-understood, unlike the neural code for stimuli of the other sensory modalities. This is because the space of olfactory stimuli lacks a natural coordinate system, and this significantly complicates characterizing neural receptive fields (tuning curves), analogous to those in the other sensory modalities. The degree to which olfactory tuning is spatially organized across the OB, often referred to as chemotopy, is also not well-understood. To advance our understanding of these aspects of olfactory coding, we introduce an interpretable method of Shapley fields, as an olfactory analog of retinotopic receptive fields. Shapley fields are spatial distributions of chemical feature importance for the tuning of OB glomeruli. We used this tool to investigate chemotopy in the OB with diverse sets of chemical features using widefield epifluorescence recordings of the mouse dorsal OB in response to stimuli across a wide range of the chemical space. We found that Shapley fields reveal a weak chemotopic organization of the chemical feature sensitivity of dorsal OB glomeruli. This organization was consistent across animals and mostly agreed across very different chemical feature sets: (i) the expert-curated PubChem database features and (ii) features derived from a Graph Neural Network trained on human olfactory perceptual tasks. Moreover, we found that the principal components of the Shapley fields often corresponded to single commonly accepted chemical classification groups, that therefore could be "recovered" from the neural activity in the mouse OB. Our findings suggest that Shapley fields may serve as a chemical feature-agnostic method for investigating olfactory perception.

Smart Dura: a functional artificial dura for multimodal neural recording and modulation
A multi-modal neural interface capable of long-term recording and stimulation is essential for advancing brain monitoring and developing targeted therapeutics. Among the traditional electrophysiological methods, micro-electrocorticography (ECoG) is appealing for chronic applications because it provides a good compromise between invasiveness and high-resolution neural recording. When combining ECoG with optical technologies, such as calcium imaging and optogenetics, this multi-modal approach enables the simultaneous collection of neural activity from individual neurons and the ability to perform cell-specific manipulation. While previous efforts have focused on multi-modal interfaces for small animal models, scaling these technologies to larger brains, of primates, remains challenging. In this paper, we present a multi-modal neural interface, named Smart Dura, a functional version of the commonly used artificial dura with integrated electrophysiological electrodes for large cortical area coverage for the NHP brain. The Smart Dura is fabricated using a novel thin-film microfabrication process to monolithically integrate a micron-scale electrode array into a soft, flexible, and transparent substrate with high-density electrodes (up to 256 electrodes) while providing matched mechanical compliance with the native tissue and achieving high optical transparency (exceeding 97%). Our in vivo experiments demonstrate electrophysiological recording capabilities combined with neuromodulation, as well as optical transparency via multiphoton imaging. This work paves the way toward a chronic neural interface that can provide large-scale, bidirectional interfacing for multimodal and closed-loop neuromodulation capabilities to study cortical brain activity in non-human primates, with the potential for translation to humans.

Transcranial ultrasonic stimulation of central thalamus reduces arousal in healthy volunteers
We present the first causal evidence in healthy humans linking central thalamus to vigilance and pulvinar to visuospatial attention using low-intensity transcranial focused ultrasound stimulation (tFUS). In a within-subjects, counterbalanced design, 27 healthy volunteers completed the Psychomotor Vigilance Task (PVT), a measure of vigilance, and the Egly Driver Task (EDT), which assesses visuospatial attention, before and after central thalamus, pulvinar, and sham sonication with tFUS. Central thalamic sonication significantly impaired performance on both tasks in a manner consistent with decreases in arousal. Pulvinar sonication resulted in more subtle effects consistent with a selective disruption of visuospatial attention. Specifically, participants were less responsive to visual stimuli presented in the visual field contralateral to the targeted pulvinar. These results demonstrate that tFUS can elicit measurable behavioral changes in healthy volunteers and underscores its potential as a high-resolution tool for noninvasive brain mapping, capable of differentiating functional contributions of adjacent thalamic nuclei only millimeters apart.

Rewiring an olfactory circuit by altering the combinatorial code of cell-surface proteins
Proper brain function requires the precise assembly of neural circuits during development. Despite the identification of many cell-surface proteins (CSPs) that help guide axons to their targets, it remains largely unknown how multiple CSPs work together to assemble a functional circuit. Here, we used synaptic partner matching in the Drosophila olfactory circuit to address this question. By systematically altering the combination of differentially expressed CSPs in a single olfactory receptor neuron (ORN) type, which senses a male pheromone that inhibits male-male courtship, we switched its connection from its endogenous postsynaptic projection neuron (PN) type nearly completely to a new PN type that promotes courtship. To achieve this switch, we deduced a combinatorial code including CSPs that mediate both attractive and repulsive interactions between synaptic partners. The anatomical switch changed the odor response of the new PN partner and markedly increased male-male courtship. We generalized three manipulation strategies from this rewiring to successfully rewire a second ORN type to multiple distinct PN types. This work demonstrates that manipulating a small set of CSPs is sufficient to respecify synaptic connections, paving ways to explore how neural systems evolve through changes of circuit connectivity.

Harnessing the Evolution of Proteostasis Networks to Reverse Cognitive Dysfunction
The integrated stress response (ISR) is a highly conserved network essential for maintaining cellular homeostasis and cognitive function. Here, we investigated how persistent ISR activation impacts cognitive performance, primarily focusing on a PPP1R15BR658C genetic variant associated with intellectual disability. By generating a novel mouse model that mimics this human condition, we revealed that this variant destabilizes the PPP1R15B-PP1 phosphatase complex, resulting in chronic ISR activation, impaired protein synthesis, and deficits in long-term memory. Importantly, we found that the cognitive and synaptic deficits in Ppp1r15bR658C mice are directly due to ISR activation. Leveraging insights from evolutionary biology, we characterized DP71L, a viral orthologue of PPP1R15B, through detailed molecular and structural analyses, uncovering its mechanism of action as a potent pan-ISR inhibitor. Remarkably, we found that DP71L not only buffers cognitive decline associated with a wide array of conditions, including Down syndrome, Alzheimer disease and aging, but also enhances long-term synaptic plasticity and memory in healthy mice. These findings highlight the promise of utilizing evolutionary insight to inform innovative therapeutic strategies.

Shifted balance between ventral striatal prodynorphin and proenkephalin biases development of cocaine place avoidance
Evidence from human self-report and rodent models indicate cocaine can induce a negative affective state marked by panic and anxiety, which may reduce future cocaine use or promote co-use with opiates. Dynorphin-mediated signaling within the striatum is associated with negative affect following cocaine withdrawal and stress-induced cocaine seeking. Here, we used a trace conditioning procedure to first establish the optimum parameters to capture this transient cocaine negative affective state in wild type mice, then we investigated striatal opioid peptides as a substrate mediating cocaine conditioned place avoidance (CPA). Previous reports indicate that trace conditioning, where drug administration occurs after removal from the conditioning chamber, results in CPA to ethanol, nicotine, and amphetamine. We tested different cocaine doses, conditioning session lengths, and apparatus types, to determine which combination yields the best cocaine CPA. Cocaine CPA was moderately larger at the highest cocaine dose (25 mg/kg), but this did not generalize across apparatus types and the effect was transient, thus data were collapsed across all parameters. Cocaine conditioning scores were variable, but also became more polarized across conditioning, with approximately equal proportions developing preference and avoidance. We then correlated cocaine CPA with striatal gene expression levels of the opioid peptides enkephalin (Penk) and dynorphin (Pdyn) using qPCR. Cocaine CPA was correlated with low Pdyn levels and a low Pdyn:Penk ratio in the ventral, but not dorsal, striatum. Consistent with this, mice with higher striatal Pdyn relative to Penk were more resistant to developing cocaine CPA compared to littermate controls. This approach revealed a subset of subjects sensitive to the aversive state immediately following cocaine administration. Our findings suggest striatal dynorphin has opposing roles in mediating the aversion associated with acute cocaine intoxication versus cocaine withdrawal.

Repulsive interactions instruct synaptic partner matching in an olfactory circuit
Neurons exhibit extraordinary precision in selecting synaptic partners. Whereas cell-surface proteins (CSPs) mediating attractive interactions between developing axons and dendrites have been shown to instruct synaptic partner matching, it is less clear the degree to which repulsive interactions play a role. Here, using a genetic screen guided by single cell transcriptomes, we identified three CSP pairs--Toll2-Ptp10D, Fili-Kek1, and Hbs/Sns-Kirre--in mediating repulsive interactions between non-partner olfactory receptor neuron (ORN) axons and projection neuron (PN) dendrites in the developing Drosophila olfactory circuit. Each CSP pair exhibits inverse expression patterns in the select PN-ORN partners. Loss of each CSP in ORNs led to similar synaptic partner matching deficits as the loss of its partner CSP in PNs, and mistargeting phenotypes caused by overexpressing one CSP could be suppressed by loss of its partner CSP. Each CSP pair is also differentially expressed in other brain regions. Together, our data reveal that multiple repulsive CSP pairs work together to ensure precise synaptic partner matching during development by preventing neurons from forming connections with non-cognate partners.

Laterality and interhemispheric integration in the larval Drosophila olfactory system
All animals with bilateral symmetry must integrate the sensory input from the left and right sides of their bodies to make coherent perceptual decisions. In Drosophila larvae, connectomic evidence suggests that olfactory signals from the two sides of the head are initially processed independently (as in the mammalian olfactory system) before being combined in the central brain. By pairing volumetric calcium imaging in intact larvae with microfluidic odor delivery and targeted laser ablation at the sensory periphery, we have mapped the propagation of olfactory signals between the two brain hemispheres, across successive layers of the larval olfactory system. This approach implicates the mushroom body (MB) as a key substrate for interhemispheric integration of odor representations. Whereas the two larval MBs appear to process odors largely independently at the level of their intrinsic neurons (Kenyon cells), the modulatory neurons of the MB show strongly symmetrized responses to asymmetric olfactory stimuli. Nevertheless, odor responses in some MB output neurons (MBONs), up to 5 synapses downstream from the sensory periphery, preserve information about stimulus laterality. Moreover, we show that asymmetric activation of these MBONs can modulate the animals turning behavior in a side-biased manner. These findings suggest that the deeply lateralized architecture of the larval olfactory system balances the need for interhemispheric integration with the advantages of parallel sensory processing.

Biologically realistic mean field model of spiking neural networks with fast and slow inhibitory synapses
We present a mean field model for a spiking neural network of excitatory and inhibitory neurons with fast GABAA and nonlinear slow GABAB inhibitory conductance-based synapses. This mean field model can predict the spontaneous and evoked response of the network to external stimulation in asynchronous irregular regimes. The model displays theta oscillations for sufficiently strong GABAB conductance. Optogenetic activation of interneurons and an increase of GABAB conductance caused opposite effects on the emergence of gamma oscillations in the model. In agreement with direct numerical simulations of neural networks and experimental data, the mean field model predicts that an increase of GABAB conductance reduces gamma oscillations. Furthermore, the slow dynamics of GABAB synapses regulates the appearance and duration of transient gamma oscillations, namely gamma bursts, in the mean field model. Finally, we show that nonlinear GABAB synapses play a major role to stabilize the network from the emergence of epileptic seizures.

Temporal Propagation of Neural State Boundaries in Naturalistic Context
Our senses receive a continuous stream of complex information, which we segment into discrete events. Previous research has related such events to neural states: temporally and regionally specific stable patterns of brain activity. The aim of this paper was to investigate whether there was evidence for top-down or bottom-up propagation of neural state boundaries. To do so, we used intracranial measurements with high temporal resolution while subjects were watching a movie. As this is the first study of neural states in intracranial data in the context of event segmentation, we also investigated whether known properties of neural states could be replicated. The neural state boundaries indeed aligned with stimulus features and between brain areas. Importantly, we found evidence for top-down propagation of neural state boundaries at the onsets and offsets of clauses. Interestingly, we did not observe a consistent top-down or bottom-up propagation in general across all timepoints, suggesting that neural state boundaries could propagate in both a top-down and bottom-up manner, with the direction depending on the stimulus input at that moment. Taken together, our findings provide new insights on how neural state boundaries are shared across brain regions and strengthen the foundation of studying neural states in electrophysiology.

Dynamically rich states in balanced networks induced by single-neuron dynamics
Network states with rich dynamics and highly variable firing rates of individual neurons are prominent in experimental observations and thought to benefit complex information processing and learning. Such states have been proposed to arise from properties of network coupling, like a strong connectivity or slow synaptic dynamics. Here, we identify an alternative mechanism based on weak synaptic coupling and intrinsic cellular dynamics. We show that a switch in the cellular excitability class of action-potential generation (via a switch in the underlying mathematical bifurcation), further amplified by recurrent interactions, results in super-Poissonian spiking variability in random balanced networks. Information encoding is shifted to higher frequency bands and collective chaos in the network is enhanced when intrinsic cellular dynamics follow a saddle homoclinic orbit (HOM) bifurcation. The robust effect links the biophysics of individual neurons to collective dynamics of large random networks, highlighting the relevance of single-cell dynamics for computation in physiological and artificial networks.

Metaplastic priming enables non-ionotropic NMDA receptor-mediated synaptic depotentiation in the hippocampus
The reversal of learning-induced synaptic potentiation through depotentiation is thought to underlie forgetting and can be influenced by prior synaptic activity. Here, we evaluated how such metaplastic alterations manifest at the synaptic level. In hippocampal slices obtained from male and female mice, we artificially induced long-term potentiation (LTP) using either a temporally spaced or compressed stimulation pattern. Using a combination of electrophysiology and protein quantification approaches, we found divergent molecular pathways recruited during depotentiation of spaced and compressed LTP. Depotentiation of both forms of LTP required glutamatergic activation of the NMDA receptor (NMDAR). However, only depotentiation of spaced LTP required ionotropic NMDAR signaling, while ion flux-independent, or non-ionotropic, NMDAR signaling was necessary and sufficient for depotentiation of compressed LTP. Downstream of NMDAR signaling, AMPA receptor phosphorylation was also differentially modified during depotentiation of spaced and compressed LTP. Finally, we found that spaced but not compressed depotentiation required synaptic Arc. Together, our results reveal that the temporal pattern of prior LTP induction exerts a metaplastic influence on the molecular pathways recruited during the induction and expression of depotentiation. Our findings have important implications for the regulation of both physiological and pathological forgetting.

Significance statementSynaptic depotentiation, the reversal of learning-associated synaptic potentiation, is an important mechanism of forgetting. This study uncovers how prior synaptic activity modifies the molecular mechanisms underlying depotentiation in the hippocampus in a metaplastic manner. We reveal that the mechanisms of NMDA-receptor depotentiation depend on the temporal spacing of long-term potentiation (LTP) induction. Specifically, we show that non-ionotropic NMDA receptor signaling is necessary and sufficient for the depotentiation of LTP induced using temporally compressed but not spaced patterned activity. Further, depotentiation of spaced and compressed LTP are associated with distinct downstream signaling pathways and AMPA receptor phosphorylation states during depotentiation. Our results illuminate fundamental mechanisms that govern plasticity associated with forgetting, with implications for memory preservation in disease states.