Concept

Modèles du neurone biologique

Publications associées (26)

A striatal circuit balances learned fear in the presence and absence of sensory cues

Ralf Schneggenburger, Olexiy Kochubey, Michael Kintscher

During fear learning, defensive behaviors like freezing need to be finely balanced in the presence or absence of threat-predicting cues (conditioned stimulus, CS). Nevertheless, the circuits underlying such balancing are largely unknown. Here, we investiga ...

eLIFE SCIENCES PUBL LTD2023

Molecular reconstruction and simulation of the Neuron-Glia-Vasculature system

Polina Shichkova

The outstanding information processing capacity of the brain relies on numerous molecular mechanisms. It is an extremely energy-expensive function, which involves specialization and collaboration of different cell types. A common framework to study the com ...

EPFL2023

Structure-function coupling increases during interictal spikes in temporal lobe epilepsy: A graph signal processing study

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Patric Hagmann

Objective: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). ...

ELSEVIER IRELAND LTD2023

A universal workflow for creation, validation and generalization of detailed neuronal models

Henry Markram, Srikanth Ramaswamy, Mustafa Anil Tuncel, Werner Alfons Hilda Van Geit, Alexis Arnaudon, Christian Andreas Rössert, Maria Reva, Tanguy Pierre Louis Damart, Darshan Mandge

Detailed single neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools are dedicated to the reproduction of a small set of specific ...

Cambridge2023

Taming neuronal noise with large networks

Valentin Marc Schmutz

How does reliable computation emerge from networks of noisy neurons? While individual neurons are intrinsically noisy, the collective dynamics of populations of neurons taken as a whole can be almost deterministic, supporting the hypothesis that, in the br ...

EPFL2022

Approximating Relu Networks By Single-Spike Computation

Wulfram Gerstner, Stanislaw Andrzej Wozniak, Ana Stanojevic, Evangelos Eleftheriou, Giovanni Cherubini, Angeliki Pantazi

Developing energy-saving neural network models is a topic of rapidly increasing interest in the artificial intelligence community. Spiking neural networks (SNNs) are biologically inspired models that strive to leverage the energy efficiency stemming from a ...

IEEE2022