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Simple Neuron Models and Adaptation

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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

Controlling morpho-electrophysiological variability of neurons with detailed biophysical models

Henry Markram, Werner Alfons Hilda Van Geit, Lida Kanari, Alexis Arnaudon, Maria Reva, Mickael Maurice Zbili

Variability is a universal feature among biological units such as neuronal cells as they enable a robust encoding of a high volume of information in neuronal circuits and prevent hyper synchronizations such as epileptic seizures. While most computational s ...

2023

On a Finite-Size Neuronal Population Equation

Tilo Schwalger, Valentin Marc Schmutz, Eva Löcherbach

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

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

In this work, we investigate the intrinsic cycle-to-cycle variations in a spiking temperature-sensitive neuron, based on the resistive switching of a Vanadium dioxide (VO2) two-terminal device. We study how this phenomenon impacts the spike rate jitter, an ...

New York2023

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

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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 ...

2022

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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 ...

PUBLIC LIBRARY SCIENCE2021

Spike frequency adaptation supports network computations on temporally dispersed information

Anand Subramoney

For solving tasks such as recognizing a song, answering a question, or inverting a sequence of symbols, cortical microcircuits need to integrate and manipulate information that was dispersed over time during the preceding seconds. Creating biologically rea ...

ELIFE SCIENCES PUBLICATIONS LTD2021