Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Neuro-informatique

Publications associées (28)

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats

Maria del Carmen Sandi Perez, Elias Georges Gebara

Social behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activit ...

Springer2024

Principles of Network Plasticity in Neocortical Microcircuits

András Ecker

Synaptic plasticity underlies our ability to learn and adapt to the constantly changing environment. The phenomenon of synapses changing their efficacy in an activity-dependent manner is often studied in small groups of neurons in vitro or indirectly throu ...

EPFL2023

Membrane potential dynamics of excitatory and inhibitory neurons in mouse barrel cortex during active whisker sensing

Carl Petersen, Sylvain Crochet, Aurélie Pala, Taro Kiritani, Célia Roxane Gasselin

Neocortical neurons can increasingly be divided into well-defined classes, but their activity patterns during quantified behavior remain to be fully determined. Here, we obtained membrane potential recordings from various classes of excitatory and inhibito ...

PUBLIC LIBRARY SCIENCE2023

Enhancement of brain atlases with region-specific coordinate systems: flatmaps and barrel column annotations

Felix Schürmann, Michael Reimann, Armando Romani, Huanxiang Lu, Sirio Bolaños Puchet, Juan Bautista Hernando Vieites, Aleksandra Zuzanna Teska

Digital brain atlases define a hierarchy of brain regions and their locations in three-dimensional space. They provide a standard coordinate system in which diverse datasets can be integrated for visualization and analysis. They also enable building of dat ...

2024

Differential Impact of Brain Network Efficiency on Poststroke Motor and Attentional Deficits

Dimitri Nestor Alice Van De Ville, Friedhelm Christoph Hummel, Gabriel Girard, Maximilian Jonas Wessel, Takuya Morishita, Elena Beanato, Philipp Johannes Koch, Andéol Geoffroy Cadic-Melchior, Philip Egger, Nathalie Heidi Meyer, Lisa Aïcha Mireille Julie Fleury, Giorgia Giulia Evangelista, Julia Brügger, Martino Bruno Armando Ceroni, Diego de Leon Rodriguez

Background:Most studies on stroke have been designed to examine one deficit in isolation; yet, survivors often have multiple deficits in different domains. While the mechanisms underlying multiple-domain deficits remain poorly understood, network-theoretic ...

2023

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

A 16-Channel Low-Power Neural Connectivity Extraction and Phase-Locked Deep Brain Stimulation SoC

Mahsa Shoaran, Uisub Shin, Cong Ding

Growing evidence suggests that phase-locked deep brain stimulation (DBS) can effectively regulate abnormal brain connectivity in neurological and psychiatric disorders. This letter therefore presents a low-power SoC with both neural connectivity extraction ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Energy-Efficient Electronic Functions Based on the Co-integration of 2D and Ferroelectric Materials

Sadegh Kamaei Bahmaei

The digital revolution has significantly transformed our world over the past decades, driven by the scaling of transistor dimensions and the exponential increase in computation power. However, as the CMOS scaling era approaches its end, the semiconductor i ...

EPFL2023

Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

Henry Markram, Felix Schürmann, Daniel Keller, Eilif Benjamin Muller, Michael Reimann, Werner Alfons Hilda Van Geit, Srikanth Ramaswamy, Matthias Wolf, James Gonzalo King, Alexis Arnaudon, András Ecker, Rajnish Ranjan, Jean-Denis Georges Emile Courcol, Armando Romani, Pramod Shivaji Kumbhar, Judit Planas Carbonell, Giuseppe Chindemi, Michael Emiel Gevaert, Christian Andreas Rössert, Fernando Joaquim Leite Pereira, Omar Awile, Mustafa Anil Tuncel, Daniela Egas Santander, James Bryden Isbister, Natali Barros Zulaica, Samuel Lieven D. Lapere, Sirio Bolaños Puchet, Maria Reva, Genrich Ivaska, Tanguy Pierre Louis Damart, Darshan Mandge, Joni Henrikki Herttuainen, Christoph Pokorny, Elvis Boci, Vishal Sood, Thomas Brice Delemontex, Aleksandra Zuzanna Teska, Polina Litvak, Alexander Dietz, Jorge Blanco Alonso, Gianluca Ficarelli, Weina Ji

Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a m ...

2024

Neuromodulation of neocortical microcircuitry: a multi-scale framework to model the effects of cholinergic release

Cristina Colangelo

Neuromodulation of neocortical microcircuits is one of the most fascinating and mysterious aspects of brain physiology. Despite over a century of research, the neuroscientific community has yet to uncover the fundamental biological organizing principles un ...

EPFL2022

A Cation Concentration Gradient Approach to Tune the Selectivity and Activity of CO2 Electroreduction

Xile Hu, Wenhao Ren

The linear scaling relationship of the binding energies of different intermediates limits the catalyst performance in CO 2 electroreduction. Here we demonstrate a cation concentration gradient strategy to promote the activity and tune the selectivity of CO ...

Wiley-VCH Verlag GmbH2022

The neocortical column as a universal template for perception and world-model learning

Mackenzie Mathis

Mackenzie Mathis highlights an essay by Vernon Mountcastle that shaped our understanding of the organization and function of the neocortex. ...

NATURE PORTFOLIO2022

The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models

Jean-Denis Georges Emile Courcol, Genrich Ivaska

In the last decades, brain modeling has been established as a fundamental tool for understanding neural mechanisms and information processing in individual cells and circuits at different scales of observation. Building data-driven brain models requires th ...

FRONTIERS MEDIA SA2022

Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies

Michael Reimann, Ran Levi, Christoph Pokorny

In motor-related brain regions, movement intention has been successfully decoded from invivo spike train by isolating a lower-dimension manifold that the high-dimensional spiking activity is constrained to. The mechanism enforcing this constraint remains u ...

PUBLIC LIBRARY SCIENCE2022

HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data

Eilif Benjamin Muller, Werner Alfons Hilda Van Geit, Armando Romani

Anatomically and biophysically detailed data-driven neuronal models have become widely used tools for understanding and predicting the behavior and function of neurons. Due to the increasing availability of experimental data from anatomical and electrophys ...

2021

Analytic performance modeling and analysis of detailed neuron simulations

Felix Schürmann, Francesco Cremonesi

Big science initiatives are trying to reconstruct and model the brain by attempting to simulate brain tissue at larger scales and with increasingly more biological detail than previously thought possible. The exponential growth of parallel computer perform ...

2020

A Neuro-Inspired Computational Model for a Visually Guided Robotic Lamprey Using Frame and Event Based Cameras

Auke Ijspeert, Alessandro Crespi, Mehmet Hasan Mutlu, Simon Lukas Hauser, Alexandre Bernardino, Mohammadreza Bayat

The computational load associated with computer vision is often prohibitive, and limits the capacity for on-board image analysis in compact mobile robots. Replicating the kind of feature detection and neural processing that animals excel at remains a chall ...

2020

First-person body view modulates the neural substrates of episodic memory and autonoetic consciousness: A functional connectivity study

Dimitri Nestor Alice Van De Ville, Olaf Blanke, Bruno Herbelin, Nathan Quentin Faivre, Thomas William Arthur Bolton, Baptiste Gauthier, Robin Mange, Lucie Bréchet, Florian Lance

Episodic memory (EM) is classically conceived as a memory for events, localized in space and time, and characterized by autonoetic consciousness (ANC) allowing to mentally travel back in time and subjectively relive an event. Building on recent evidence th ...

2020

Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience

Auke Ijspeert, Silvestro Micera, Marc-Oliver Gewaltig, Emanuele Formento, Shravan Tata Ramalingasetty

Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all ...

FRONTIERS MEDIA SA2020

An efficient analytical reduction of detailed nonlinear neuron models

Felix Schürmann, Idan Segev, Pramod Shivaji Kumbhar, Michael Emiel Gevaert

Detailed conductance-based nonlinear neuron models consisting of thousands of synapses are key for understanding of the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of these ...

Nature Research2020