Article
Version 1
This version is not peer-reviewed
Omeprazole and Proteinoids in Neuron Models
Version 1
: Received: 4 August 2024 / Approved: 4 August 2024 / Online: 5 August 2024 (08:19:12 CEST)
How to cite: Mougkogiannis, P.; Adamatzky, A. Omeprazole and Proteinoids in Neuron Models. Preprints 2024, 2024080252. https://doi.org/10.20944/preprints202408.0252.v1 Mougkogiannis, P.; Adamatzky, A. Omeprazole and Proteinoids in Neuron Models. Preprints 2024, 2024080252. https://doi.org/10.20944/preprints202408.0252.v1
Abstract
This study examines a new approach to hybdrid neuromorphic devices by studying the impact of omeprazole-proteinoid complexes on Izhikevich neurone models. We investigate the influence of these metabolic structures on five specific patterns of neuronal firing: accommodation, chattering, triggered spiking, phasic spiking, and tonic spiking. By combining omeprazole, a proton pump inhibitor, with proteinoids, we create a unique substrate that interfaces with neuromorphic models. The Izhikevich neurone model is used because it is computationally efficient and can accurately simulate various behaviours of cortical neurones. The results of our simulations show that omeprazole-proteinoid complexes have the ability to affect neuronal dynamics in different ways. This suggests that they could be used as adjustable components in bio-inspired computer systems. We have noticed a notable alteration in the frequency of spikes, patterns of bursts, and rates of adaptation, especially in chattering and triggered spiking behaviours. The findings indicate that omeprazole-proteinoid complexes have the potential to serve as adaptable elements in neuromorphic systems, presenting novel opportunities for information processing and computation that have origins in neurobiological principles. This study makes a valuable contribution to the expanding field of biochemical neuromorphic devices and establishes a basis for the development of hybrid bio-synthetic computational systems.
Keywords
Neuromorphic computing; omeprazole; proteinoids; Izhikevich neuron model; bio-inspired computing; neuromodulation; pharmacological computing; adaptive systems; neuron firing patterns
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
