Neuromorphic device architectures with global connectivity through electrolyte gating.
Open accessAbstract
Information processing in the brain takes place in a network of neurons that are connected with each other by an immense number of synapses. At the same time, neurons are immersed in a common electrochemical environment, and global parameters such as concentrations of various hormones regulate the overall network function. This computational paradigm of global regulation, also known as homeoplasticity, has important implications in the overall behaviour of large neural ensembles and is barely addressed in neuromorphic device architectures. Here, we demonstrate the global control of an array of organic devices based on poly(3,4ethylenedioxythiophene):poly(styrene sulf) that are immersed in an electrolyte, a behaviour that resembles homeoplasticity phenomena of the neural environment. We use this effect to produce behaviour that is reminiscent of the coupling between local activity and global oscillations in the biological neural networks. We further show that the electrolyte establishes complex connections between individual devices, and leverage these connections to implement coincidence detection. These results demonstrate that electrolyte gating offers significant advantages for the realization of networks of neuromorphic devices of higher complexity and with minimal hardwired connectivity.
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There is currently a consensus that neurons and synapses constitute the fundamental electrochemical processing units of the human brain.
“However, there is currently a consensus that neurons and synapses constitute the fundamental electrochemical processing units of the human brain”
From Human Brain/Cloud Interface (2019) · cites this paper as Gkoupidenis et al., 2017
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- Authors
- Gkoupidenis, P., Koutsouras, D. A., & Malliaras, G. G.
- Corresponding author
- Malliaras, George G.
- Venue
- Nature Communications
- Published
- 2017-05-17
- Volume
- 8
- Issue
- 1
- Pages
- 15448-15448
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC5442355
- OpenAlex
- W2614342775
- Cited by
- 353
- References
- 48
- Citations by year
- 2026: 28 · 2025: 34 · 2024: 32 · 2023: 44 · 2022: 49 · 2021: 60 · 2020: 41 · 2019: 35 · 2018: 28 · 2017: 2
- FWCI
- 12.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Cambridge University Engineering Department Publications Database (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- University of Southampton
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Materials Science › Polymers and Plastics › Conducting polymers and applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- neuromorphic hardware, electrolyte gating, organic field-effect transistors, PEDOT:PSS, global connectivity, coincidence detection, neural oscillations, organic electronics, neuromorphic networks
- MeSH terms
- Brain, Electrolytes, Models, Neurological, Nerve Net, Neurons, Polystyrenes, Synapses, Thiophenes, Neural Networks, Computer, Microtechnology
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