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Cortical cell assemblies and their underlying connectivity: an in silico study

Publications associées (40)

Cortical cell assemblies and their underlying connectivity: An in silico study

Michael Reimann, András Ecker, Sirio Bolaños Puchet, James Bryden Isbister, Daniela Egas Santander

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to these assemblies rema ...

2024

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

Long-term plasticity induces sparse and specific synaptic changes in a biophysically detailed cortical model

Eilif Benjamin Muller, Michael Reimann, James Gonzalo King, Marwan Muhammad Ahmed Abdellah, Pramod Shivaji Kumbhar, András Ecker, Sirio Bolaños Puchet, James Bryden Isbister, Daniela Egas Santander, Jorge Blanco Alonso, Giuseppe Chindemi, Ioannis Magkanaris

Synaptic plasticity underlies the brain’s ability to learn and adapt. This process is often studied in small groups of neurons in vitro or indirectly through its effects on behavior in vivo. Due to the limitations of available experimental techniques, inve ...

2023

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

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

In recent years, large-scale computational models of the cortex have emerged as a powerful way to study the multi-scale mechanisms of neural processing. However, due to computational costs and difficulty of parameterization, detailed biophysical reconstruc ...

2023

Plasticity of sensory representations in the posterior insular cortex during fear learning

Denys Osypenko

Aversively-motivated associative learning allows animals to avoid harm and thus ensures survival. Aversive learning can be studied by the fear learning paradigm, in which an innocuous sensory stimulus like a tone (conditioned stimulus, CS), acquires a nega ...

EPFL2023

Label-Free Long-Term Methods for Live Cell Imaging of Neurons: New Opportunities

Georg Fantner, Zahra Ayar Dulabi, Samuel Mendes Leitão

Time-lapse light microscopy combined with in vitro neuronal cultures has provided a significant contribution to the field of Developmental Neuroscience. The establishment of the neuronal polarity, i.e., formation of axons and dendrites, key structures resp ...

MDPI2023

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

Tilo Schwalger, Valentin Marc Schmutz

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal rep ...

PUBLIC LIBRARY SCIENCE2022

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

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Voltage-sensitive dye imaging (VSDI) is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but with effective resolution limits that confound interpretation. To address this limitation, we developed an in ...

NATURE RESEARCH2021

In Silico Voltage-Sensitive Dye Imaging: A Model-Based Approach for Bridging Scales of Cortical Activity

Taylor Howard Newton

An understanding of how microscale voltage fluctuations interact to shape mesoscale cortical information processing is lacking. Voltage-sensitive dye imaging (VSDI) is a powerful technique for interrogating membrane potential dynamics in assemblies of cort ...

EPFL2019

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