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Introducing the Dendrify framework for incorporating dendrites to spiking neural networks

Biology

Introducing the Dendrify framework for incorporating dendrites to spiking neural networks

M. Pagkalos, S. Chavlis, et al.

Discover how Dendrify, an innovative Python package developed by Michalis Pagkalos, Spyridon Chavlis, and Panayiota Poirazi, enhances our understanding of spiking neural networks by incorporating the vital role of dendrites. This exciting research makes it possible to explore dendritic contributions efficiently while advancing neuromorphic systems.

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Playback language: English
Abstract
Spiking neural networks (SNNs) are widely used for understanding brain functions and neuromorphic computing, but often ignore dendrites' computational capabilities. Dendrify, an open-source Python package based on Brian 2, generates reduced compartmental neuron models with biologically relevant dendritic and synaptic properties. This bridges the gap between efficient but simplistic SNNs and computationally expensive detailed models, allowing exploration of dendritic contributions to network-level functions and advancing neuromorphic systems.
Publisher
Nature Communications
Published On
Jan 10, 2023
Authors
Michalis Pagkalos, Spyridon Chavlis, Panayiota Poirazi
Tags
Spiking Neural Networks
Dendrites
Computational Models
Dendrify
Neuromorphic Computing
Brain Functions
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