Perisomatic ultrastructure efficiently classifies cells in mouse cortex

Nature, Год журнала: 2025, Номер 640(8058), С. 478 - 486

Опубликована: Апрель 9, 2025

Abstract Mammalian neocortex contains a highly diverse set of cell types. These types have been mapped systematically using variety molecular, electrophysiological and morphological approaches 1–4 . Each modality offers new perspectives on the variation biological processes underlying cell-type specialization. Cellular-scale electron microscopy provides dense ultrastructural examination an unbiased perspective subcellular organization brain cells, including their synaptic connectivity nanometre-scale morphology. In data that contain tens thousands neurons, most which incomplete reconstructions, identifying becomes clear challenge for analysis 5 Here, to address this challenge, we present systematic survey somatic region all cells in cubic millimetre cortex quantitative features obtained from microscopy. This demonstrates perisomatic is sufficient identify types, defined primarily basis patterns. We then describe how classification facilitates cell-type-specific characterization locating with rare patterns dataset.

Язык: Английский

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Inhibitory specificity from a connectomic census of mouse visual cortex

Nature, Год журнала: 2025, Номер 640(8058), С. 448 - 458

Опубликована: Апрель 9, 2025

Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties1. Synaptic connectivity shapes how type participates in the cortical circuit, but mapping rules at resolution distinct types remains difficult. Here we used millimetre-scale volumetric electron microscopy2 to investigate all inhibitory neurons across densely segmented population 1,352 cells spanning layers mouse visual cortex, producing wiring diagram inhibition more than 70,000 synapses. Inspired by classical neuroanatomy, classified based on targeting dendritic compartments developed an excitatory neuron classification reconstructions whole-cell maps synaptic input. Single-cell showed class disinhibitory specialist that targets basket cells. Analysis onto found widespread specificity, many interneurons exhibiting differential spatially intermingled subpopulations. Inhibitory was organized into 'motif groups', diverse sets collectively target both perisomatic same targets. Collectively, our analysis identified new organizing principles for will serve as foundation linking contemporary multimodal atlases diagram.

Язык: Английский

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Functional connectomics reveals general wiring rule in mouse visual cortex

Nature, Год журнала: 2025, Номер 640(8058), С. 459 - 469

Опубликована: Апрель 9, 2025

Abstract Understanding the relationship between circuit connectivity and function is crucial for uncovering how brain computes. In mouse primary visual cortex, excitatory neurons with similar response properties are more likely to be synaptically connected 1–8 ; however, broader rules remain unknown. Here we leverage millimetre-scale MICrONS dataset analyse synaptic functional of across cortical layers areas. Our results reveal that preferentially within areas—including feedback connections—supporting 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 proximity axons dendrites. also discovered higher-order rule whereby postsynaptic neuron cohorts downstream presynaptic cells show greater similarity than predicted pairwise like-to-like rule. Recurrent neural networks trained on simple classification task develop patterns mirror both rules, magnitudes those in data. Ablation studies these recurrent disrupting impairs performance random connections. These findings suggest principles may have role sensory processing learning, highlighting shared biological artificial systems.

Язык: Английский

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Connectomics of predicted Sst transcriptomic types in mouse visual cortex

Nature, Год журнала: 2025, Номер 640(8058), С. 497 - 505

Опубликована: Апрель 9, 2025

Neural circuit function is shaped both by the cell types that comprise and connections between them1. have previously been defined morphology2,3, electrophysiology4, transcriptomic expression5,6, connectivity7-9 or a combination of such modalities10-12. The Patch-seq technique enables characterization morphology, electrophysiology properties from individual cells13-15. These were integrated to define 28 inhibitory, morpho-electric-transcriptomic (MET) in mouse visual cortex16, which do not include synaptic connectivity. Conversely, large-scale electron microscopy (EM) morphological reconstruction near-complete description neuron's local connectivity, but does electrophysiological information. Here, we leveraged information predict transcriptomically subclass and/or MET-type inhibitory neurons within EM dataset. We further analysed Martinotti cells-a somatostatin (Sst)-positive17 type18,19-which classified successfully into Sst MET-types with distinct axon myelination output connectivity patterns. demonstrate features can be used link across experimental modalities, enabling comparison gene expression electrophysiology. observe unique rules for predicted types.

Язык: Английский

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Foundation model of neural activity predicts response to new stimulus types

Nature, Год журнала: 2025, Номер 640(8058), С. 470 - 477

Опубликована: Апрель 9, 2025

Abstract The complexity of neural circuits makes it challenging to decipher the brain’s algorithms intelligence. Recent breakthroughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding computational objectives and coding. However, is difficult for such generalize beyond their training distribution, limiting utility. emergence foundation 1 trained on vast datasets has introduced a new artificial intelligence paradigm with remarkable generalization capabilities. Here we collected large amounts activity from visual cortices multiple mice model predict neuronal responses arbitrary natural videos. This generalized minimal successfully predicted across various stimulus domains, as coherent motion noise patterns. Beyond response prediction, also anatomical cell types, dendritic features connectivity within MICrONS functional connectomics dataset 2 . Our work crucial step towards building brain. As neuroscience accumulates larger, multimodal datasets, will reveal statistical regularities, enable rapid adaptation tasks accelerate research.

Язык: Английский

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A map of neural signals and circuits traces the logic of brain computation

Nature, Год журнала: 2025, Номер 640(8058), С. 319 - 321

Опубликована: Апрель 9, 2025

Язык: Английский

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Biggest brain map ever details huge number of neurons and their activity

Nature, Год журнала: 2025, Номер unknown

Опубликована: Апрель 9, 2025

Язык: Английский

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