Mixed selectivity: Cellular computations for complexity

Neuron, Journal Year: 2024, Volume and Issue: 112(14), P. 2289 - 2303

Published: May 9, 2024

The property of mixed selectivity has been discussed at a computational level and offers strategy to maximize power by adding versatility the functional role each neuron. Here, we offer biologically grounded implementational-level mechanistic explanation for in neural circuits. We define pure, linear, nonlinear discuss how these response properties can be obtained simple Neurons that respond multiple, statistically independent variables display selectivity. If their activity expressed as weighted sum, then they exhibit linear selectivity; otherwise, Neural representations based on diverse are high dimensional; hence, confer enormous flexibility downstream readout circuit. However, circuit cannot possibly encode all possible mixtures simultaneously, this would require combinatorially large number neurons. Gating mechanisms like oscillations neuromodulation solve problem dynamically selecting which transmitted readout.

Language: Английский

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The homogenous hippocampus: How hippocampal cells process available and potential goals

Progress in Neurobiology, Journal Year: 2024, Volume and Issue: 240, P. 102653 - 102653

Published: July 2, 2024

We present here a view of the firing patterns hippocampal cells that is contrary, both functionally and anatomically, to conventional wisdom. argue hippocampus responds efference copies goals encoded elsewhere; it uses these detect resolve conflict or interference between in general. While can involve space, do not encode spatial (or other special types of) memory, as such. also transverse circuits operate an essentially homogeneous way along its length. The apparently different functions parts (e.g. memory retrieval versus anxiety) result from (situational/motivational) inputs on which those perform same fundamental computational operations. On this view, key role iterative adjustment, via Papez-like circuits, synaptic weights cell assemblies elsewhere.

Language: Английский

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Abstract representations emerge in human hippocampal neurons during inference

Nature, Journal Year: 2024, Volume and Issue: 632(8026), P. 841 - 849

Published: Aug. 14, 2024

Humans have the remarkable cognitive capacity to rapidly adapt changing environments. Central this is ability form high-level, abstract representations that take advantage of regularities in world support generalization1. However, little known about how these are encoded populations neurons, they emerge through learning and relate behaviour2,3. Here we characterized representational geometry neurons (single units) recorded hippocampus, amygdala, medial frontal cortex ventral temporal neurosurgical patients performing an inferential reasoning task. We found only neural formed hippocampus simultaneously encode several task variables abstract, or disentangled, format. This uniquely observed after learn perform inference, consists disentangled directly observable discovered latent variables. Learning inference by trial error verbal instructions led formation hippocampal with similar geometric properties. The relation between format behaviour suggests geometries important for complex cognition. A which participants learned whose properties reflected structure task, indicating

Language: Английский

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Nonlinear manifolds underlie neural population activity during behaviour

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

Published: July 19, 2023

There is rich variety in the activity of single neurons recorded during behaviour. Yet, these diverse neuron responses can be well described by relatively few patterns neural co-modulation. The study such low-dimensional structure population has provided important insights into how brain generates Virtually all studies have used linear dimensionality reduction techniques to estimate population-wide co-modulation patterns, constraining them a flat “neural manifold”. Here, we hypothesised that since nonlinear and make thousands distributed recurrent connections likely amplify nonlinearities, manifolds should intrinsically nonlinear. Combining recordings from monkey, mouse, human motor cortex, mouse striatum, show that: 1) are nonlinear; 2) their nonlinearity becomes more evident complex tasks require varied patterns; 3) manifold varies across architecturally distinct regions. Simulations using network models confirmed proposed relationship between circuit connectivity nonlinearity, including differences Thus, underlying generation behaviour inherently nonlinear, properly accounting for nonlinearities will critical as neuroscientists move towards studying numerous regions involved increasingly naturalistic behaviours.

Language: Английский

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Temporal multiplexing of perception and memory codes in IT cortex

Nature, Journal Year: 2024, Volume and Issue: 629(8013), P. 861 - 868

Published: May 15, 2024

Abstract A central assumption of neuroscience is that long-term memories are represented by the same brain areas encode sensory stimuli 1 . Neurons in inferotemporal (IT) cortex represent percept visual objects using a distributed axis code 2–4 Whether and how IT neural population represents memory remains unclear. Here we examined familiar faces encoded anterior medial face patch (AM), perirhinal (PR) temporal pole (TP). In AM PR observed encoding for rotated relative to unfamiliar at long latency; TP this memory-related rotation was much weaker. Contrary previous claims, response magnitude versus not stable indicator familiarity any 5–11 The mechanism underlying change likely intrinsic cortex, because inactivation did affect dynamics AM. Overall, our results suggest distinct long-latency code, explaining cell can both faces.

Language: Английский

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Computational role of structure in neural activity and connectivity

Trends in Cognitive Sciences, Journal Year: 2024, Volume and Issue: 28(7), P. 677 - 690

Published: March 28, 2024

Language: Английский

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Dynamic and stable hippocampal representations of social identity and reward expectation support associative social memory in male mice

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: May 5, 2023

Abstract Recognizing an individual and retrieving updating the value information assigned to are fundamental abilities for establishing social relationships. To understand neural mechanisms underlying association between identity reward value, we developed Go-NoGo discrimination paradigms that required male subject mice distinguish familiar based on their individually unique characteristics associate them with availability. We found could discriminate conspecifics through a brief nose-to-nose investigation, this ability depended dorsal hippocampus. Two-photon calcium imaging revealed CA1 hippocampal neurons represented expectation during social, but not non-social tasks, these activities were maintained over days regardless of associated mouse. Furthermore, dynamically changing subset discriminated high accuracy. Our findings suggest neuronal in provide possible substrates associative memory.

Language: Английский

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Social representation

Nature reviews. Neuroscience, Journal Year: 2024, Volume and Issue: 25(4), P. 210 - 210

Published: March 4, 2024

Language: Английский

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Neural representational geometries reflect behavioral differences in monkeys and recurrent neural networks

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Aug. 1, 2024

Abstract Animals likely use a variety of strategies to solve laboratory tasks. Traditionally, combined analysis behavioral and neural recording data across subjects employing different may obscure important signals give confusing results. Hence, it is essential develop techniques that can infer strategy at the single-subject level. We analyzed an experiment in which two male monkeys performed visually cued rule-based task. The their performance shows no indication they used strategy. However, when we examined geometry stimulus representations state space activities recorded dorsolateral prefrontal cortex, found striking differences between monkeys. Our purely results induced us reanalyze behavior. new showed representational are associated with reaction times, revealing were unaware of. All these analyses suggest using strategies. Finally, recurrent network models trained perform same task, show correlate amount training, suggesting possible explanation for observed differences.

Language: Английский

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Semi-orthogonal subspaces for value mediate a binding and generalization trade-off

Nature Neuroscience, Journal Year: 2024, Volume and Issue: 27(11), P. 2218 - 2230

Published: Sept. 17, 2024

Language: Английский

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