Conference Presentation (After Call)

FZJ-2024-01347

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Bio-inspired sequence learning mechanisms and their implementation in a memristive neuromorphic hardware

Bouhadjar, Y. (Corresponding author)FZJ* ; Siegel, S.FZJ* ; Diesmann, M.FZJ* ; Waser, R.FZJ* ; Neftci, E.FZJ* ; Wouters, D. J. ; Tetzlaff, T.FZJ*

2023

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Please use a persistent id in citations: doi:10.34734/FZJ-2024-01347

Abstract: We present a sequence learning model that explains how biological networks learn to predict upcoming elements, signal non-anticipated events, and recall sequences in response to a cue signal. The model accounts for anatomical and electrophysiological properties of cortical neuronal circuits and learns complex sequences in an unsupervised manner using known biological plasticity and homeostatic control mechanisms. We further investigate the feasibility of implementing the sequence learning model on dedicated hardware mimicking brain properties, specifically focusing on memristive crossbar arrays. Finally, we apply the model to sequence classification and anomaly detection in streams of real-world data, and discuss the role of dendritic branches for the sequence learning capacity.

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Contributing Institute(s):

1. Computational and Systems Neuroscience (INM-6)
2. Computational and Systems Neuroscience (IAS-6)
3. Jara-Institut Brain structure-function relationships (INM-10)
4. Elektronische Materialien (PGI-7)
5. JARA Institut Green IT (PGI-10)
6. Neuromorphic Software Eco System (PGI-15)

Research Program(s):

1. 574 - Theory, modelling and simulation (POF3-574) (POF3-574)
2. 5232 - Computational Principles (POF4-523) (POF4-523)
3. 5234 - Emerging NC Architectures (POF4-523) (POF4-523)
4. Advanced Computing Architectures (aca_20190115) (aca_20190115)
5. HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) (785907)
6. HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539) (945539)
7. DFG project 491111487 - Open-Access-Publikationskosten / 2022 - 2024 / Forschungszentrum Jülich (OAPKFZJ) (491111487) (491111487)

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Database coverage:
; ; ; BIOSIS Previews ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Ebsco Academic Search ; IF < 5 ; JCR ; PubMed Central ; SCOPUS ; Web of Science Core Collection

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