Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses

Neuron, Journal Year: 2023, Volume and Issue: 111(18), P. 2918 - 2928.e8

Published: Sept. 1, 2023

Predictive processing postulates the existence of prediction error neurons in cortex. Neurons with both negative and positive response properties have been identified layer 2/3 visual cortex, but whether they correspond to transcriptionally defined subpopulations is unclear. Here we used activity-dependent, photoconvertible marker CaMPARI2 tag mouse cortex during stimuli behaviors designed evoke errors. We performed single-cell RNA-sequencing on these populations found that previously annotated Adamts2 Rrad transcriptional cell types were enriched when photolabeling drive or responses, respectively. Finally, validated results functionally by designing artificial promoters for use AAV vectors express genetically encoded calcium indicators. Thus, distinct can be targeted using exhibit distinguishable responses.

Language: Английский

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Synaptic architecture of leg and wing premotor control networks in Drosophila

Nature, Journal Year: 2024, Volume and Issue: 631(8020), P. 369 - 377

Published: June 26, 2024

Language: Английский

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Neuronal parts list and wiring diagram for a visual system

Nature, Journal Year: 2024, Volume and Issue: 634(8032), P. 166 - 180

Published: Oct. 2, 2024

Language: Английский

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Cooperative thalamocortical circuit mechanism for sensory prediction errors

Nature, Journal Year: 2024, Volume and Issue: 633(8029), P. 398 - 406

Published: Aug. 28, 2024

Abstract The brain functions as a prediction machine, utilizing an internal model of the world to anticipate sensations and outcomes our actions. Discrepancies between expected actual events, referred errors, are leveraged update guide attention towards unexpected events 1–10 . Despite importance prediction-error signals for various neural computations across brain, surprisingly little is known about circuit mechanisms responsible their implementation. Here we describe thalamocortical disinhibitory that required generating sensory in mouse primary visual cortex (V1). We show violating animals’ predictions by stimulus preferentially boosts responses layer 2/3 V1 neurons most selective stimulus. Prediction errors specifically amplify input, rather than representing non-specific surprise or difference how input deviates from animal’s predictions. This amplification implemented cooperative mechanism requiring thalamic pulvinar cortical vasoactive-intestinal-peptide-expressing (VIP) inhibitory interneurons. In response VIP inhibit specific subpopulation somatostatin-expressing interneurons gate excitatory V1, resulting pulvinar-driven stimulus-selective V1. Therefore, prioritizes unpredicted information selectively increasing salience features through synergistic interaction neocortical circuits.

Language: Английский

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Functional connectomics reveals general wiring rule in mouse visual cortex

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: March 14, 2023

Understanding the relationship between circuit connectivity and function is crucial for uncovering how brain implements computation. In mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited within V1, leaving much unknown about broader rules. this study, we leverage millimeter-scale MICrONS dataset analyze synaptic functional of individual across cortical layers areas. Our results reveal that responses preferentially connected both areas — including feedback connections suggesting universality ‘like-to-like’ hierarchy. Using a validated digital twin model, separated neuronal tuning into feature (what respond to) spatial (receptive field location) components. We found only component predicts fine-scale connections, beyond what could explained by physical proximity axons dendrites. also higher-order rule where postsynaptic neuron cohorts downstream presynaptic cells show greater similarity than predicted pairwise like-to-like rule. Notably, recurrent neural networks (RNNs) trained on simple classification task develop patterns mirroring rules, magnitude those in data. Lesion these RNNs disrupting has significantly impact performance compared lesions random connections. These findings suggest principles may play role sensory processing learning, highlighting shared biological artificial systems.

Language: Английский

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Emergence of co-tuning in inhibitory neurons as a network phenomenon mediated by randomness, correlations, and homeostatic plasticity

Science Advances, Journal Year: 2024, Volume and Issue: 10(12)

Published: March 20, 2024

Cortical excitatory neurons show clear tuning to stimulus features, but the properties of inhibitory interneurons are ambiguous. While have been considered be largely untuned, some studies that parvalbumin-expressing (PV) do feature selectivity and participate in co-tuned subnetworks with pyramidal neurons. In this study, we first use mean-field theory demonstrate a combination homeostatic plasticity governing synaptic dynamics connections from PV neurons, heterogeneity postsynaptic potentials impinge on shared correlated input layer 4 results functional structural self-organization subnetworks. Second, emerges more clearly at network level, i.e., population-level measures identify co-tuning not evident pairwise individual-level measures. Finally, such can enhance stability cost reduced selectivity.

Language: Английский

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Functional connectomics spanning multiple areas of mouse visual cortex

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2021, Volume and Issue: unknown

Published: July 29, 2021

Abstract To understand the brain we must relate neurons’ functional responses to circuit architecture that shapes them. Here, present a large connectomics dataset with dense calcium imaging of millimeter scale volume. We recorded activity from approximately 75,000 neurons in primary visual cortex (VISp) and three higher areas (VISrl, VISal VISlm) an awake mouse viewing natural movies synthetic stimuli. The data were co-registered volumetric electron microscopy (EM) reconstruction containing more than 200,000 cells 0.5 billion synapses. Subsequent proofreading subset this volume yielded reconstructions include complete dendritic trees as well local inter-areal axonal projections map up thousands cell-to-cell connections per neuron. release open-access resource scientific community including set tools facilitate retrieval downstream analysis. In accompanying papers describe our findings using provide comprehensive structural characterization cortical cell types 1–3 most detailed synaptic level connectivity diagram column date 2 , uncovering unique cell-type specific inhibitory motifs can be linked gene expression 4 . Functionally, identify new computational principles how information is integrated across space 5 characterize novel neuronal invariances 6 bring structure function together decipher general principle wires excitatory within 7, 8

Language: Английский

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CAVE: Connectome Annotation Versioning Engine

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: July 28, 2023

Abstract Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need be able concurrently create new annotations correct errors the automated by proofreading. In large datasets, every proofreading edit relabels cell identities of millions voxels thousands like synapses. For analysis, require immediate reproducible access this constantly changing expanding data landscape. Here, we present Connectome Annotation Versioning Engine (CAVE), a for connectome analysis up-to petascale (∼1mm 3 ) while annotating is ongoing. segmentation, CAVE provides distributed continuous versioning reconstructions. Annotations defined locations such that they can quickly assigned underlying segment enables fast queries CAVE’s arbitrary time points. supports schematized, extensible annotations, so researchers readily design novel annotation types. already used many connectomics including largest available date.

Language: Английский

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Synaptic architecture of leg and wing premotor control networks inDrosophila

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: May 31, 2023

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles. MN activity coordinated complex premotor networks that allow individual muscles contribute many different behaviors. Here, we use connectomics analyze wiring logic circuits controlling

Language: Английский

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Neuronal “parts list” and wiring diagram for a visual system

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Oct. 13, 2023

A catalog of neuronal cell types has often been called a "parts list" the brain, and regarded as prerequisite for understanding brain function. In optic lobe

Language: Английский

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