ArticleFrontiers in neuroscience2018
Structural Plasticity on the SpiNNaker Many-Core Neuromorphic System.
Article in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Building a realistic, scalable memory model with independent engrams using a homeostatic mechanism.Frontiers in neuroinformatics · 2024Article
- Optoelectronic intelligence.Applied physics letters · 2021Article
- Neuromorphic Stereo Vision: A Survey of Bio-Inspired Sensors and Algorithms.Frontiers in neurorobotics · 2019Review
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4 authors.
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Abstract
The structural organization of cortical areas is not random, with topographic maps commonplace in sensory processing centers. This topographical organization allows optimal wiring between neurons, multimodal sensory integration, and performs input dimensionality reduction. In this work, a model of topographic map formation is implemented on the SpiNNaker neuromorphic platform, running in realtime using point neurons, and making use of both synaptic rewiring and spike-timing dependent plasticity (STDP). In agreement with Bamford et al. (2010), we demonstrate that synaptic rewiring refines an initially rough topographic map over and beyond the ability of STDP, and that input selectivity learnt through STDP is embedded into the network connectivity through rewiring. Moreover, we show the presented model can be used to generate topographic maps between layers of neurons with minimal initial connectivity, and stabilize mappings which would otherwise be unstable through the inclusion of lateral inhibition.
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