A neuromorphic model of olfactory processing and sparse coding in the Drosophila larva brain

2021 | journal article; research paper

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​A neuromorphic model of olfactory processing and sparse coding in the Drosophila larva brain​
Jürgensen, A.-M.; Khalili, A.; Chicca, E.; Indiveri, G. & Nawrot, M. P. ​ (2021) 
Neuromorphic Computing and Engineering1(2) art. 024008​.​ DOI: https://doi.org/10.1088/2634-4386/ac3ba6 

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Authors
Jürgensen, Anna-Maria; Khalili, Afshin; Chicca, Elisabetta; Indiveri, Giacomo; Nawrot, Martin Paul 
Abstract
Animal nervous systems are highly efficient in processing sensory input. The neuromorphic computing paradigm aims at the hardware implementation of neural network computations to support novel solutions for building brain-inspired computing systems. Here, we take inspiration from sensory processing in the nervous system of the fruit fly larva. With its strongly limited computational resources of <200 neurons and <1.000 synapses the larval olfactory pathway employs fundamental computations to transform broadly tuned receptor input at the periphery into an energy efficient sparse code in the central brain. We show how this approach allows us to achieve sparse coding and increased separability of stimulus patterns in a spiking neural network, validated with both software simulation and hardware emulation on mixed-signal real-time neuromorphic hardware. We verify that feedback inhibition is the central motif to support sparseness in the spatial domain, across the neuron population, while the combination of spike frequency adaptation and feedback inhibition determines sparseness in the temporal domain. Our experiments demonstrate that such small, biologically realistic neural networks, efficiently implemented on neuromorphic hardware, can achieve parallel processing and efficient encoding of sensory input at full temporal resolution.
Issue Date
2021
Journal
Neuromorphic Computing and Engineering 
Project
FOR 2705: Dissection of a Brain Circuit: Structure, Plasticity and Behavioral Function of the Drosophila Mushroom Body 
FOR 2705 | TP 4: From molecular computation to adaptive behavior: Across level modeling of memory computation in the mushroom bodies 
Working Group
RG Nawrot 
ISSN
2634-4386
Language
English

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