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Dataset for Real-time encoding and compression of neuronal spikes by metal-oxide memristor

Dataset for Real-time encoding and compression of neuronal spikes by metal-oxide memristor
Dataset for Real-time encoding and compression of neuronal spikes by metal-oxide memristor
Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here, we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multielectrode array, demonstrating the technology’s potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces.
University of Southampton
Gupta, Isha
11f9ea1a-e38a-45d4-930d-96ac78b3d734
Serb, Alexantrou
30f5ec26-f51d-42b3-85fd-0325a27a792c
Khiat, Ali
bf549ddd-5356-4a7d-9c12-eb6c0d904050
Prodromakis, Themistoklis
d58c9c10-9d25-4d22-b155-06c8437acfbf
Vassanelli, Stefano
105761d3-6b9b-47ec-a07b-97ad4ef8bd6c
Zeitler, Ralf
0d1ed289-e01f-4ccf-979b-febc9fa22dc2
Gupta, Isha
11f9ea1a-e38a-45d4-930d-96ac78b3d734
Serb, Alexantrou
30f5ec26-f51d-42b3-85fd-0325a27a792c
Khiat, Ali
bf549ddd-5356-4a7d-9c12-eb6c0d904050
Prodromakis, Themistoklis
d58c9c10-9d25-4d22-b155-06c8437acfbf
Vassanelli, Stefano
105761d3-6b9b-47ec-a07b-97ad4ef8bd6c
Zeitler, Ralf
0d1ed289-e01f-4ccf-979b-febc9fa22dc2

Gupta, Isha, Serb, Alexantrou, Khiat, Ali, Prodromakis, Themistoklis, Vassanelli, Stefano and Zeitler, Ralf (2016) Dataset for Real-time encoding and compression of neuronal spikes by metal-oxide memristor. University of Southampton doi:10.5258/SOTON/400411 [Dataset]

Record type: Dataset

Abstract

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here, we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multielectrode array, demonstrating the technology’s potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces.

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More information

Published date: 2016
Organisations: Electronics & Computer Science, Nanoelectronics and Nanotechnology
Projects:
Reliably unreliable nanotechnologies
Funded by: UNSPECIFIED (EP/K017829/1)
2 September 2013 to 1 September 2018
Real neurons-nanoelectronics Architecture with Memristive Plasticity (RAMP)
Funded by: UNSPECIFIED (612058)
1 November 2013 to 31 October 2016

Identifiers

Local EPrints ID: 400411
URI: http://eprints.soton.ac.uk/id/eprint/400411
PURE UUID: 1a4b66df-d123-40c7-9ca2-96d164cbf62e
ORCID for Themistoklis Prodromakis: ORCID iD orcid.org/0000-0002-6267-6909

Catalogue record

Date deposited: 14 Sep 2016 12:50
Last modified: 04 Nov 2023 15:08

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Contributors

Creator: Isha Gupta
Creator: Alexantrou Serb
Creator: Ali Khiat
Creator: Themistoklis Prodromakis ORCID iD
Creator: Stefano Vassanelli
Creator: Ralf Zeitler

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