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Complexity and performance in simple neuron models

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Nonlinear microscopy for temporally and spatially resolved label-free imaging of living cells

Marie Eve Pascale Didier

The human brain consists of approximately a hundred billion of neurons that communicate through a unique series of biochemical and electrical processes. When neuronal networks are solicited, electrochemical processes happen involving millions of cells with ...

EPFL2018

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Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal memb ...

PUBLIC LIBRARY SCIENCE2018

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

Wulfram Gerstner, Tilo Schwalger, Moritz Deger

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacti ...

Public Library of Science2017

On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs

Joao Emanuel Felipe Gerhard, Moritz Deger

Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational ...

Public Library of Science2017

Prospective Coding by Spiking Neurons

Johanni Michael Brea, Walter Senn

Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learnin ...

Public Library of Science2016

The ability to control and modulate the action potential firing in neurons represents a powerful tool for neuroscience research and clinical applications. While neuronal excitation has been achieved with many tools, including electrical and optical stimula ...

2016

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The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong i ...

Public Library of Science2016

Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue

Daniel Keller

Recorded potentials in the extracellular space (ECS) of the brain is a standard measure of population activity in neural tissue. Computational models that simulate the relationship between the ECS potential and its underlying neurophysiological processes a ...

Public Library of Science2016

Cell-type- and activity-dependent extracellular correlates of intracellular spiking

Henry Markram, Rodrigo de Campos Perin, Constantinos Anastassiou

Despite decades of extracellular action potential (EAP) recordings monitoring brain activity, the biophysical origin and inherent variability of these signals remains enigmatic. We performed whole-cell patch recordings of excitatory and inhibitory neurons ...

American Physiological Society2015

Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models

Wulfram Gerstner, Richard Naud, Skander Mensi, Christian Antonio Pozzorini, Olivier Richard Hagens

Single-neuron models are useful not only for studying the emergent properties of neural circuits in large-scale simulations, but also for extracting and summarizing in a principled way the information contained in electrophysiological recordings. Here we d ...

Public Library of Science2015