Neuromorphic dendritic network computation with silent synapses for visual motion perception
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- Title
- Neuromorphic dendritic network computation with silent synapses for visual motion perception
- Authors
- BAEK, EUNHYE; Sen Song; BAEK, CHANG KI; Zhao Rong; Luping Shi; Carlo Vittorio Cannistraci
- Date Issued
- 2024-06
- Publisher
- NATURE PUBLISHING GROUP
- Abstract
- Neuromorphic technologies typically employ a point neuron model, neglecting the spatiotemporal nature of neuronal computation. Dendritic morphology and synaptic organization are structurally tailored for spatiotemporal information processing, such as visual perception. Here we report a neuromorphic computational model that integrates synaptic organization with dendritic tree-like morphology. Based on the physics of multigate silicon nanowire transistors with ion-doped sol–gel films, our model—termed dendristor—performs dendritic computation at the device and neural-circuit level. The dendristor offers the bioplausible nonlinear integration of excitatory/inhibitory synaptic inputs and silent synapses with diverse spatial distribution dependency, emulating direction selectivity, which is the feature that reacts to signal direction on the dendrite. We also develop a neuromorphic dendritic neural circuit—a network of interconnected dendritic neurons—that serves as a building block for the design of a multilayer network system that emulates three-dimensional spatial motion perception in the retina. © The Author(s), under exclusive licence to Springer Nature Limited 2024.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/124157
- DOI
- 10.1038/s41928-024-01171-7
- Article Type
- Article
- Citation
- Nature Electronics, 2024-06
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- There are no files associated with this item.
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