Stimulus-dependent spiking and bursting behavior in memsensor circuits: experiment and wave digital modeling

Abstract Biological information processing pathways in neuron assemblies rely on spike activity, encoding information in the time domain, and operating the highly parallel network at an outstanding robustness and efficiency. One particularly important aspect is the distributed, local pre-processing effectively converting stimulus-induced signals to action potentials, temporally encoding analog information. The field of brain-inspired electronics strives to adapt concepts of information processing in neural networks, e.g., stimulus detection and processing being intertwined. As such, stimulus-modulated resistive switching in memristive devices attracts an increasing attention. This work reports on a three-component memsensor circuit, featuring a UV-sensor, a memristive device with diffusive switching characteristics and a capacitor. Upon application of a DC bias, complex, stimulus-dependent spiking and brain-inspired bursting can be observed, as experimentally showcased using combination of a microstructured, tetrapodal ZnO sensor and a Au/SiO x N y /Ag cross-point memristive device. The experimental findings are corroborated by a wave digital model, which successfully replicates both types of behavior and outlines the relation of temporal variation of switching thresholds to the occurrence of bursting activity. Graphical abstract

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Publication Details

Journal
The European Physical Journal B
Published
2024-09-01
DOI
https://doi.org/10.1140/epjb/s10051-024-00770-9
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.21

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article

Stimulus-dependent spiking and bursting behavior in memsensor circuits: experiment and wave digital modeling

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1 citations
The European Physical Journal B
Advanced Memory and Neural Computing
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article

Stimulus-dependent spiking and bursting behavior in memsensor circuits: experiment and wave digital modeling

Roshani Madurawala, Franz Faupel, Rohit Gupta, Sören Kaps, Alexander Vahl, Karlheinz Ochs, Thomas Strunskus, Sebastian Jenderny, Rainer Adelung
article en
1 citations

Abstract

Abstract Biological information processing pathways in neuron assemblies rely on spike activity, encoding information in the time domain, and operating the highly parallel network at an outstanding robustness and efficiency. One particularly important aspect is the distributed, local pre-processing effectively converting stimulus-induced signals to action potentials, temporally encoding analog information. The field of brain-inspired electronics strives to adapt concepts of information processing in neural networks, e.g., stimulus detection and processing being intertwined. As such, stimulus-modulated resistive switching in memristive devices attracts an increasing attention. This work reports on a three-component memsensor circuit, featuring a UV-sensor, a memristive device with diffusive switching characteristics and a capacitor. Upon application of a DC bias, complex, stimulus-dependent spiking and brain-inspired bursting can be observed, as experimentally showcased using combination of a microstructured, tetrapodal ZnO sensor and a Au/SiO x N y /Ag cross-point memristive device. The experimental findings are corroborated by a wave digital model, which successfully replicates both types of behavior and outlines the relation of temporal variation of switching thresholds to the occurrence of bursting activity. Graphical abstract

The European Physical Journal BVol. 97(9)
Hochschule für Angewandte Wissenschaften Kiel (DE), Christian-Albrechts-Universität zu Kiel (DE), Leibniz Institute for Plasma Science and Technology (DE), Ruhr University Bochum (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 48%
Advanced Memory and Neural Computing
0.21
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