NDNF interneurons in layer 1 gain-modulate whole cortical columns according to an animal’s behavioral state

Neuron, Год журнала: 2021, Номер 109(13), С. 2150 - 2164.e5

Опубликована: Май 25, 2021

Язык: Английский

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Cortical disinhibitory circuits: cell types, connectivity and function

Trends in Neurosciences, Год журнала: 2021, Номер 44(8), С. 643 - 657

Опубликована: Май 15, 2021

Язык: Английский

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Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications

Proceedings of the National Academy of Sciences, Год журнала: 2022, Номер 119(13)

Опубликована: Март 23, 2022

Significance An influential idea in neuroscience is that neural circuits do not only passively process sensory information but rather actively compare them with predictions thereof. A core element of this comparison prediction-error neurons, the activity which changes upon mismatches between actual and predicted stimuli. While it has been shown these neurons come different variants, largely unresolved how they are simultaneously formed shaped by highly interconnected networks. By using a computational model, we study circuit-level mechanisms give rise to variants neurons. Our results shed light on formation, refinement, robustness circuits, an important step toward better understanding predictive processing.

Язык: Английский

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Learning how network structure shapes decision-making for bio-inspired computing

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Май 23, 2023

Abstract To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that used to build personalized brain models for 650 Human Connectome Project participants. We found participants with higher intelligence scores took more time solve difficult problems, and slower solvers had average functional connectivity. With simulations identified mechanistic link between connectivity, intelligence, processing speed synchrony trading accuracy in dependence of excitation-inhibition balance. Reduced led decision-making circuits quickly jump conclusions, while allowed integration evidence robust working memory. Strict tests were applied ensure reproducibility generality the obtained results. Here, identify links function enable learn connectome topology from noninvasive recordings map it inter-individual differences suggesting broad utility research clinical applications.

Язык: Английский

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A primary sensory cortical interareal feedforward inhibitory circuit for tacto-visual integration

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

Опубликована: Апрель 10, 2024

Abstract Tactile sensation and vision are often both utilized for the exploration of objects that within reach though it is not known whether or how these two distinct sensory systems combine such information. Here in mice, we used a combination stereo photogrammetry 3D reconstruction whisker array, brain-wide anatomical tracing functional connectivity analysis to explore possibility tacto-visual convergence space circuitry primary visual cortex (VISp). Strikingly, find stimulation contralateral array suppresses visually evoked activity sub-region VISp whose representation closely overlaps with search space. This suppression mediated by local fast-spiking interneurons receive direct cortico-cortical input predominantly from layer 6 neurons located posterior somatosensory barrel (SSp-bfd). These data demonstrate between cortical areas multisensory object detection recognition.

Язык: Английский

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Neocortical somatostatin neuron diversity in cognition and learning

Trends in Neurosciences, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Bottom-up inputs are required for establishment of top-down connectivity onto cortical layer 1 neurogliaform cells

Neuron, Год журнала: 2021, Номер 109(21), С. 3473 - 3485.e5

Опубликована: Сен. 2, 2021

Язык: Английский

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Somatostatin and Somatostatin-Containing Interneurons—From Plasticity to Pathology

Biomolecules, Год журнала: 2022, Номер 12(2), С. 312 - 312

Опубликована: Фев. 15, 2022

Despite the obvious differences in pathophysiology of distinct neuropsychiatric diseases or neurodegenerative disorders, some them share general but pivotal mechanisms, one which is disruption excitation/inhibition balance. Such an imbalance can be generated by changes inhibitory system, very often mediated somatostatin-containing interneurons (SOM-INs). In physiology, this group interneurons, as well somatostatin itself, profoundly shapes brain activity, thus influencing behavior and plasticity; however, number, density activity SOM-INs levels are found throughout many neurological conditions, both patients animal models. Here, we (1) briefly describe somatostatinergic characterizing neuropeptide its receptors functions, physiology circuitry SOM-INs; (2) summarize effects physiological processes pathological focusing primarily on learning-induced plasticity encompassing selected neuropsychological respectively. The presented data indicate somatostatinergic-system-mediated inhibition a substantial factor mechanisms neuroplasticity, disrupted plethora pathologies.

Язык: Английский

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Layer 1 neocortex: Gating and integrating multidimensional signals

Neuron, Год журнала: 2023, Номер 112(2), С. 184 - 200

Опубликована: Окт. 31, 2023

Язык: Английский

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Cell type-specific connectome predicts distributed working memory activity in the mouse brain

eLife, Год журнала: 2024, Номер 13

Опубликована: Янв. 4, 2024

Recent advances in connectomics and neurophysiology make it possible to probe whole-brain mechanisms of cognition behavior. We developed a large-scale model the multiregional mouse brain for cardinal cognitive function called working memory, brain’s ability internally hold process information without sensory input. The is built on mesoscopic connectome data interareal cortical connections endowed with macroscopic gradient measured parvalbumin-expressing interneuron density. found that memory coding distributed yet exhibits modularity; spatial pattern mnemonic representation determined by long-range cell type-specific targeting density classes. Cell graph measures predict activity patterns core subnetwork maintenance. shows numerous attractor states, which are self-sustained internal states (each engaging distinct subset areas). This work provides framework interpret recordings during cognition, while highlighting need connectomics.

Язык: Английский

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