Regulation of circuit organization and function through inhibitory synaptic plasticity

Trends in Neurosciences, Год журнала: 2022, Номер 45(12), С. 884 - 898

Опубликована: Окт. 28, 2022

Язык: Английский

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

Neuron, Год журнала: 2023, Номер 111(18), С. 2918 - 2928.e8

Опубликована: Сен. 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.

Язык: Английский

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Neural learning rules for generating flexible predictions and computing the successor representation

eLife, Год журнала: 2023, Номер 12

Опубликована: Март 16, 2023

The predictive nature of the hippocampus is thought to be useful for memory-guided cognitive behaviors. Inspired by reinforcement learning literature, this notion has been formalized as a map called successor representation (SR). SR captures number observations about hippocampal activity. However, algorithm does not provide neural mechanism how such representations arise. Here, we show dynamics recurrent network naturally calculate when synaptic weights match transition probability matrix. Interestingly, horizon can flexibly modulated simply changing gain. We derive simple, biologically plausible rules learn in network. test our model with realistic inputs and data recorded during random foraging. Taken together, results suggest that more accessible circuits than previously support broad range functions.

Язык: Английский

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Prediction-error signals in anterior cingulate cortex drive task-switching

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Авг. 17, 2024

Task-switching is a fundamental cognitive ability that allows animals to update their knowledge of current rules or contexts. Detecting discrepancies between predicted and observed events essential for this process. However, little known about how the brain computes prediction-errors whether neural prediction-error signals are causally related task-switching behaviours. Here we trained mice use switch, in single trial, responding same stimuli using two distinct rules. Optogenetic silencing un-silencing, together with widefield two-photon calcium imaging revealed anterior cingulate cortex (ACC) was specifically required rapid task-switching, but only when it exhibited signals. These were projection-target dependent larger preceding successful behavioural transitions. An all-optical approach disinhibitory interneuron circuit computation. results reveal mechanism computing transitioning states.

Язык: Английский

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Mechanisms for survival: vagal control of goal-directed behavior

Trends in Cognitive Sciences, Год журнала: 2023, Номер 28(3), С. 237 - 251

Опубликована: Ноя. 29, 2023

Язык: Английский

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Simple synaptic modulations implement diverse novelty computations

Cell Reports, Год журнала: 2024, Номер 43(5), С. 114188 - 114188

Опубликована: Май 1, 2024

Detecting novelty is ethologically useful for an organism's survival. Recent experiments characterize how different types of over timescales from seconds to weeks are reflected in the activity excitatory and inhibitory neuron types. Here, we introduce a learning mechanism, familiarity-modulated synapses (FMSs), consisting multiplicative modulations dependent on presynaptic or pre/postsynaptic activity. With FMSs, network responses that encode emerge under unsupervised continual minimal connectivity constraints. Implementing FMSs within experimentally constrained model visual cortical circuit, demonstrate generalizability by simultaneously fitting absolute, contextual, omission effects. Our also reproduces functional diversity cell subpopulations, leading testable predictions about synaptic dynamics can produce both population-level heterogeneous individual signals. Altogether, our findings simple plasticity mechanisms circuit structure qualitatively distinct complex responses.

Язык: Английский

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Layer-specific control of inhibition by NDNF interneurons

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(4)

Опубликована: Янв. 22, 2025

Neuronal processing of external sensory input is shaped by internally generated top–down information. In the neocortex, projections primarily target layer 1, which contains NDNF (neuron-derived neurotrophic factor)-expressing interneurons and dendrites pyramidal cells. Here, we investigate hypothesis that shape cortical computations in an unconventional, layer-specific way, exerting presynaptic inhibition on synapses 1 while leaving deeper layers unaffected. We first confirm experimentally auditory cortex, from somatostatin-expressing (SOM) onto neurons are indeed modulated ambient Gamma-aminobutyric acid (GABA). Shifting to a computational model, then show this mechanism introduces distinct mutual motif between synaptic outputs SOM interneurons. This can control way competition for dendritic cells different timescales. thereby information flow redistributing fast slow timescales gating sources inhibition.

Язык: Английский

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TreeCN: Time Series Prediction With the Tree Convolutional Network for Traffic Prediction

IEEE Transactions on Intelligent Transportation Systems, Год журнала: 2023, Номер 25(5), С. 3751 - 3766

Опубликована: Окт. 27, 2023

The complexity of traffic scenarios, the spatial-temporal feature correlations pose higher challenges for prediction research. Traffic model is an essential method in this research field, primarily focusing on capturing features among nodes and their neighboring nodes. However, existing methods lack comprehensive consideration directional hierarchical They are mostly applicable to scenarios with random uniform distribution nodes, but not suitable more complex small-scale aggregation scenarios. Therefore, study proposes Tree Convolutional Network (TreeCN), a tree-based structure. data design TreeCN focus relationships represented by plane tree matrix constructed as spatial matrix. TreeCN, full convolution network, performs bottom-up structure complete task node capturing. In study, thoroughly compared statistical, machine learning, deep learning time series prediction. experimental results show that only well also exhibits outstanding effect distribution. Moreover, adheres principles Graph Networks (GCN) can further capture them. This expected make new handle improve accuracy.

Язык: Английский

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Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain

NeuroImage, Год журнала: 2024, Номер 295, С. 120658 - 120658

Опубликована: Май 28, 2024

The human brain is characterized by interacting large-scale functional networks fueled glucose metabolism. Since former studies could not sufficiently clarify how these connections shape metabolism, we aimed to provide a neurophysiologically-based approach.

Язык: Английский

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A layered microcircuit model of somatosensory cortex with three interneuron types and cell-type-specific short-term plasticity

Cerebral Cortex, Год журнала: 2024, Номер 34(9)

Опубликована: Сен. 1, 2024

Abstract Three major types of GABAergic interneurons, parvalbumin-, somatostatin-, and vasoactive intestinal peptide-expressing (PV, SOM, VIP) cells, play critical but distinct roles in the cortical microcircuitry. Their specific electrophysiology connectivity shape their inhibitory functions. To study network dynamics signal processing to these cell cerebral cortex, we developed a multi-layer model incorporating biologically realistic interneuron parameters from rodent somatosensory cortex. The is fitted vivo data on cell-type-specific population firing rates. With protocol stimulation, responses when activating different neuron are examined. reproduces experimentally observed effects PV SOM cells disinhibitory effect VIP excitatory cells. We further create version short-term synaptic plasticity (STP). While ongoing activity with without STP similar, modulates Exc, presumably by changing dominant pathways. slight adjustments, also sensory recorded vivo. Our provides predictions involving can serve explore computational interneurons

Язык: Английский

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