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STDP in adaptive neurons gives close-to-optimal information transmission

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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

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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 ...

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Neurons receive synaptic input primarily onto their dendrites. While we know much about the electrical properties of dendrites in rodents, we have only just started to describe their properties in the human brain. Here, we investigate the capacity of human ...

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MDPI2022

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Wulfram Gerstner, Tilo Schwalger, Valentin Marc Schmutz

Coarse-graining microscopic models of biological neural networks to obtain mesoscopic models of neural activities is an essential step towards multi-scale models of the brain. Here, we extend a recent theory for mesoscopic population dynamics with static s ...

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ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2020

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Neurons process information through spatiotemporal integration of synaptic input. Synaptic transmission between any given pair of neurons is typically a dynamic process with presynaptic action potentials (APs) evoking depressing or facilitating postsynapti ...

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The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedfo ...

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Neuromorphic systems provide biologically inspired methods of computing, alternative to the classical von Neumann approach. In these systems, computation is performed by a network of spiking neurons controlled by the values of their synaptic weights, which ...

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