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Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

Related publications (143)

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Of mice and men: Increased dendritic complexity gives rise to unique human networks

Henry Markram, Kathryn Hess Bellwald, Lida Kanari, Alexis Arnaudon, Ying Shi, Jay Coggan, Natali Barros Zulaica, Idan Segev, Ruth Benavides Piccione

The organizational principles that distinguish the human brain from those of other species have been a long-standing enigma in neuroscience. Here, we leverage advances in algebraic topology to uncover the structural properties of the human brain at subcell ...

bioRxiv2023

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Population equations for infinitely large networks of spiking neurons have a long tradition in theoret-ical neuroscience. In this work, we analyze a recent generalization of these equations to populations of finite size, which takes the form of a nonlinear ...

SIAM PUBLICATIONS2023

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

Data-driven whole mouse brain modeling for multi-scale simulations

Dimitri Bruno Marie Rodarie

In this thesis, we present a data-driven iterative pipeline to generate, simulate and validate point-neuron models of the whole mouse brain. The ultimate goal is to replicate close loop experiments with a virtual body in a virtual world. This pipeline was ...

EPFL2022

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

Timing is Everything

Karen Adam

In this thesis, timing is everything. In the first part, we mean this literally, as we tackle systems that encode information using timing alone. In the second part, we adopt the standard, metaphoric interpretation of this saying and show the importance of ...

EPFL2022

Methods for acute and long-term imaging of the ventral nerve cord in behaving adult Drosophila

Laura Joan Hermans

Understanding how neural circuits remodel and adapt to animal behavior is a central theme in the field of Neuroscience. One strategy to reach this goal is to repeatedly record the same animal's neural circuits and observe how they adapt when facing differe ...

EPFL2022

Mesoscopic modeling of hidden spiking neurons

Wulfram Gerstner, Shuqi Wang, Valentin Marc Schmutz

Can we use spiking neural networks (SNN) as generative models of multi-neuronal recordings, while taking into account that most neurons are unobserved? Modeling the unobserved neurons with large pools of hidden spiking neurons leads to severely underconstr ...

2022

Spatial attention enhances sensory processing of goal-relevant information and improves perceptual sensitivity. Yet, the specific neural mechanisms underlying the effects of spatial attention on performance are still contested. Here, we examine different a ...

MIT PRESS2022

A Time Encoding Approach to Training Spiking Neural Networks

Karen Adam

While Spiking Neural Networks (SNNs) have been gaining in popularity, it seems that the algorithms used to train them are not powerful enough to solve the same tasks as those tackled by classical Artificial Neural Networks (ANNs).In this paper, we provide ...

IEEE2022