Emulating Dendritic Computing Paradigms on Analog Neuromorphic Hardware. (1st May 2022)

• Record Type: Journal Article
• Authors: Kaiser, Jakob; Billaudelle, Sebastian; Müller, Eric; Tetzlaff, Christian; Schemmel, Johannes; Schmitt, Sebastian
• Is Part Of: Neuroscience. Volume 489(2022)
• Page Start: 290
• Page End: 300
• Publication Date: 2022-05-01
• Subjects: multi-compartmental models -- accelerated technology -- physical model -- mixed-signal neuromorphic -- AdEx neuron model; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2021.08.013
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: Emulating neuron dynamics 1000 times faster on neuromorphic hardware than in biology. Implementation of user-defined neuron morphologies. Dendritic spikes in form of sodium-like spikes and plateau potentials. Bidirectional current flow between compartments allows replication of BAC firing. Abstract: BrainScaleS-2 is an accelerated and highly configurable neuromorphic system with physical models of neurons and synapses. Beyond networks of spiking point neurons, it allows for the implementation of user-defined neuron morphologies. Both passive propagation of electric signals between compartments as well as dendritic spikes and plateau potentials can be emulated. In this paper, three multi-compartment neuron morphologies are chosen to demonstrate passive propagation of postsynaptic potentials, spatio-temporal coincidence detection of synaptic inputs in a dendritic branch, and the replication of the BAC burst firing mechanism found in layer 5 pyramidal neurons of the neocortex.