Multi-scale spiking network model of human cerebral cortex DOI Creative Commons
Jari Pronold, Alexander van Meegen, Renan O. Shimoura

et al.

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(10)

Published: Oct. 1, 2024

Abstract Although the structure of cortical networks provides necessary substrate for their neuronal activity, alone does not suffice to understand activity. Leveraging increasing availability human data, we developed a multi-scale, spiking network model cortex investigate relationship between and dynamics. In this model, each area in one hemisphere Desikan–Killiany parcellation is represented by $1\,\mathrm{mm^{2}}$ column with layered structure. The aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, diffusion tensor imaging, into coherent framework. It predicts activity on all scales from single-neuron area-level functional connectivity. We compared electrophysiological resting-state magnetic resonance imaging (fMRI) data. This comparison reveals that can reproduce aspects both statistics fMRI correlations if inter-areal connections are sufficiently strong. Furthermore, study propagation single-spike perturbation macroscopic fluctuations through network. open-source serves as an integrative platform further refinements future silico studies structure, dynamics, function.

Language: Английский

Local connectivity and synaptic dynamics in mouse and human neocortex DOI
Luke Campagnola, Stephanie C. Seeman, Thomas Chartrand

et al.

Science, Journal Year: 2022, Volume and Issue: 375(6585)

Published: March 10, 2022

We present a unique, extensive, and open synaptic physiology analysis platform dataset. Through its application, we reveal principles that relate cell type to properties intralaminar circuit organization in the mouse human cortex. The dynamics of excitatory synapses align with postsynaptic subclass, whereas inhibitory synapse partly presynaptic subclass but considerable overlap. Synaptic are heterogeneous most subclass-to-subclass connections. two main axes heterogeneity strength variability. Cell subclasses divide along variability axis, axis accounts for substantial within subclass. In cortex, excitatory-to-excitatory distinct from those cortex vary depth across layers 2 3.

Language: Английский

Citations

270
The quest for multiscale brain modeling DOI
Egidio D’Angelo, Viktor Jirsa

Trends in Neurosciences, Journal Year: 2022, Volume and Issue: 45(10), P. 777 - 790

Published: July 27, 2022

Language: Английский

Citations

104
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware DOI
A. Ravishankar Rao, Philipp Plank, Andreas Wild

et al.

Nature Machine Intelligence, Journal Year: 2022, Volume and Issue: 4(5), P. 467 - 479

Published: May 19, 2022

Language: Английский

Citations

82
The logic of recurrent circuits in the primary visual cortex DOI Creative Commons
Ian Antón Oldenburg, William D. Hendricks, Gregory Handy

et al.

Nature Neuroscience, Journal Year: 2024, Volume and Issue: 27(1), P. 137 - 147

Published: Jan. 1, 2024

Abstract Recurrent cortical activity sculpts visual perception by refining, amplifying or suppressing input. However, the rules that govern influence of recurrent remain enigmatic. We used ensemble-specific two-photon optogenetics in mouse cortex to isolate impact from external found spatial arrangement and feature preference stimulated ensemble neighboring neurons jointly determine net effect activity. Photoactivation these ensembles drives suppression all cells beyond 30 µm but uniformly activation closer similarly tuned cells. In nonsimilarly cells, compact, cotuned drive suppression, while diffuse, activation. Computational modeling suggests highly local excitatory connectivity selective convergence onto inhibitory explain effects. Our findings reveal a straightforward logic which space their on

Language: Английский

Citations

37
A disinhibitory circuit mechanism explains a general principle of peak performance during mid-level arousal DOI Creative Commons
Lola Beerendonk, Jorge F. Mejías, Stijn A. Nuiten

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(5)

Published: Jan. 26, 2024

Perceptual decision-making is highly dependent on the momentary arousal state of brain, which fluctuates over time a scale hours, minutes, and even seconds. The textbook relationship between task performance captured by an inverted U-shape, as put forward in Yerkes–Dodson law. This law suggests optimal at moderate levels impaired low or high levels. However, despite its popularity, evidence for this humans mixed best. Here, we use pupil-indexed data from various perceptual tasks to provide converging U-shaped spontaneous fluctuations across different decision types (discrimination, detection) sensory modalities (visual, auditory). To further understand relationship, built neurobiologically plausible mechanistic model show that it possible reproduce our findings incorporating two interneurons are both modulated signal. architecture produces dynamical regimes under influence arousal: one regime increases with another decreases arousal, together forming arousal–performance relationship. We conclude general robust property processing. It might be brought about act disinhibitory pathway neural populations encode available used decision.

Language: Английский

Citations

22
A Disinhibitory Circuit for Contextual Modulation in Primary Visual Cortex DOI Creative Commons
Andreas Keller, Mario Dipoppa, Morgane Roth

et al.

Neuron, Journal Year: 2020, Volume and Issue: 108(6), P. 1181 - 1193.e8

Published: Dec. 1, 2020

Language: Английский

Citations

118
Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex DOI Creative Commons
Eric Lee, Hymavathy Balasubramanian, Alexandra Tsolias

et al.

eLife, Journal Year: 2021, Volume and Issue: 10

Published: Aug. 6, 2021

Cortical circuits are thought to contain a large number of cell types that coordinate produce behavior. Current in vivo methods rely on clustering specified features extracellular waveforms identify putative types, but these capture only small amount variation. Here, we develop new method (

Language: Английский

Citations

66
Modernizing the NEURON Simulator for Sustainability, Portability, and Performance DOI Creative Commons
Omar Awile, Pramod Kumbhar,

Nicolas Cornu

et al.

Frontiers in Neuroinformatics, Journal Year: 2022, Volume and Issue: 16

Published: June 27, 2022

The need for reproducible, credible, multiscale biological modeling has led to the development of standardized simulation platforms, such as widely-used NEURON environment computational neuroscience. Developing and maintaining over several decades required attention competing needs backwards compatibility, evolving computer architectures, addition new scales physical processes, accessibility users, efficiency flexibility specialists. In order meet these challenges, we have now substantially modernized NEURON, providing continuous integration, an improved build system release workflow, better documentation. With help a source-to-source compiler NMODL domain-specific language enhanced NEURON's ability run efficiently, via CoreNEURON engine, on variety hardware including GPUs. Through implementation optimized in-memory transfer mechanism this performance backend is made easily accessible training model-development paths from laptop workstation supercomputer cloud platform. Similarly, been able accelerate reaction-diffusion through use just-in-time compilation. We show that efforts growing developer base, simpler more robust software distribution, wider range supported integration with other scientific workflows, biophysical biochemical models.

Language: Английский

Citations

44
Cell-type-specific propagation of visual flicker DOI Creative Commons
Marius Schneider, Αθανασία Τζάνου, Cem Uran

et al.

Cell Reports, Journal Year: 2023, Volume and Issue: 42(5), P. 112492 - 112492

Published: May 1, 2023

Rhythmic flicker stimulation has gained interest as a treatment for neurodegenerative diseases and method frequency tagging neural activity. Yet, little is known about the way in which flicker-induced synchronization propagates across cortical levels impacts different cell types. Here, we use Neuropixels to record from lateral geniculate nucleus (LGN), primary visual cortex (V1), CA1 mice while presenting stimuli. LGN neurons show strong phase locking up 40 Hz, whereas substantially weaker V1 absent CA1. Laminar analyses reveal an attenuation of at Hz each processing stage. Gamma-rhythmic predominantly entrains fast-spiking interneurons. Optotagging experiments that these correspond either parvalbumin (PV+) or narrow-waveform somatostatin (Sst+) neurons. A computational model can explain observed differences based on neurons' capacitative low-pass filtering properties. In summary, propagation synchronized activity its effect distinct types strongly depend frequency.

Language: Английский

Citations

38
Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortex DOI Creative Commons
Atle E. Rimehaug, A. Stasik, Espen Hagen

et al.

eLife, Journal Year: 2023, Volume and Issue: 12

Published: July 24, 2023

Local field potential (LFP) recordings reflect the dynamics of current source density (CSD) in brain tissue. The synaptic, cellular, and circuit contributions to sinks sources are ill-understood. We investigated these mouse primary visual cortex using public Neuropixels a detailed model based on simulating Hodgkin-Huxley >50,000 neurons belonging 17 cell types. simultaneously captured spiking CSD responses demonstrated two-way dissociation: firing rates altered with minor effects pattern by adjusting synaptic weights, is placement dendrites. describe how thalamocortical inputs recurrent connections sculpt specific early response, whereas cortical feedback crucially alters them later stages. These results establish quantitative links between macroscopic measurements (LFP/CSD) microscopic biophysics-based understanding neuron show that analysis provides powerful constraints for modeling beyond those from considering spikes.

Language: Английский

Citations

30