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Topic: dendritic nonlinearities

Seminar
1 seminar
ePoster
1 ePoster

In Biology and Computational Biology

Seminar · Computational Neuroscience

How dendrites help solve biological and machine learning problems

Yiota Poirazi · IMBB / FORTH

Fri, Apr 23, 2021 · 15:00 UTC

Dendrites are thin processes that extend from the cell body of neurons, the main computing units of the brain. The role of dendrites in complex brain functions has been investigated for several decades, yet their direct involvement in key behaviors such as for example sensory perception has only recently been established. In my presentation I will discuss how computational modelling has helped us illuminate dendritic function. I will present the main findings of a number of projects in lab dealing with dendritic nonlinearities in excitatory and inhibitory and their consequences on neuronal tun

ePoster · Computational Neuroscience

Dendritic nonlinearities and synapse type-specific input clustering enable the development of input selectivity in a wide range of settings.

Emmanouil Giannakakis, Alex Bird, Peter Jedlicka, Hermann Cuntz, Anna Levina · Bernstein Conference 2024

The importance of dendritic structures for neural computation has been recognized since the early days of neuroscience. However, it is only recently, with the increasing availability of data and advances in modelling techniques, that researchers have begun to map out the precise roles of different branching structures and synaptic distributions [1, 2]. Here, we investigate how the nonlinear integration of excitatory and inhibitory currents in dendritic branches can enhance the ability of a neuron to develop input selectivity and E/I balance via Hebbian synaptic plasticity. We model a single ra