homeostasis

A Robust Event-Driven Approach to Always-on Object Recognition
We propose a neuromimetic architecture able to perform always-on pattern recognition. To achieve this, we extended an existing …
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Learning heterogeneous delays of spiking neurons for motion detection
How to efficiently make use of time in neural computations? ⏱️ With @laurentperrinet we developed a model of spiking neuron including, in addition to synaptic weights, synaptic delays. https://t.co/eztnd5CUMn Come see this work on Tuesday morning at #FENS2022 poster n° 547 🪩
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Decoding spiking motifs using neurons with heterogeneous delays
The response of a biological neuron depends largely on the precise timing of presynaptic spikes that reach the basal dendritic tree. …
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Learning heterogeneous delays of Spiking Neurons for motion detection
During the #CVPR2022-#NeuroVision workshop about « What can computer vision learn from visual neuroscience? », @A_Grismaldi will talk today about « Learning hetero-synaptic delays of Spiking Neurons for motion detection » shows how to learn spike motifs !
Last updated on May 20, 2022
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From event-based computations to a bio-plausible Spiking Neural Network
We propose a neuromimetic online classifier for always-on digit recognition. To achieve this, we extend an existing event-based …
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A homeostatic gain control mechanism to improve event-driven object recognition
We propose a neuromimetic architecture able to perform pattern recognition. To achieve this, we extended the existing event-based …
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A robust bio-inspired approach to event-driven object recognition
We propose a neuromimetic architecture able to perform online pattern recognition. To achieve this, we extended the existing …
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An adaptive homeostatic algorithm for the unsupervised learning of visual features
The formation of structure in the visual system, that is, of the connections between cells within neural populations, is by large an …
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Role of homeostasis in learning sparse representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the …
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Role of homeostasis in learning sparse representations