Vanadium Dioxide Circuits Emulate Neurological Disorders
Abstract
Information in the central nervous system (CNS) is conducted via electrical signals known as action potentials and is encoded in time. Several neurological disorders including depression, Attention Deficit Hyperactivity Disorder (ADHD), originate in faulty brain signaling frequencies. Here, we present a Hodgkin-Huxley model analog for a strongly correlated VO2 artificial neuron system that undergoes an electrically-driven insulator-metal transition. We demonstrate that tuning of the insulating phase resistance in VO2 threshold switch circuits can enable direct mimicry of neuronal origins of disorders in the CNS. The results introduce use of circuits based on quantum materials as complementary to model animal studies for neuroscience, especially when precise measurements of local electrical properties or competing parallel paths for conduction in complex neural circuits can be a challenge to identify onset of breakdown or diagnose early symptoms of disease.
- Authors:
-
- Argonne National Lab. (ANL), Argonne, IL (United States). Center for Nanoscale Materials; Univ. of Chicago, IL (United States). Inst. for Molecular Engineering
- Purdue Univ., West Lafayette, IN (United States). School of Materials Engineering, and School of Electrical and Computer Engineering
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF); (NSF); Semiconductor Research Corporation (SRC)
- OSTI Identifier:
- 1490214
- Grant/Contract Number:
- AC02-06CH11357
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Frontiers in Neuroscience (Online)
- Additional Journal Information:
- Journal Name: Frontiers in Neuroscience (Online); Journal Volume: 12; Journal ID: ISSN 1662-453X
- Publisher:
- Frontiers Research Foundation
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; Hodgkin-Huxley model; VO2; artificial neurons; central nervous system diseases; strongly correlated systems
Citation Formats
Lin, Jianqiang, Guha, Supratik, and Ramanathan, Shriram. Vanadium Dioxide Circuits Emulate Neurological Disorders. United States: N. p., 2018.
Web. doi:10.3389/fnins.2018.00856.
Lin, Jianqiang, Guha, Supratik, & Ramanathan, Shriram. Vanadium Dioxide Circuits Emulate Neurological Disorders. United States. https://doi.org/10.3389/fnins.2018.00856
Lin, Jianqiang, Guha, Supratik, and Ramanathan, Shriram. Fri .
"Vanadium Dioxide Circuits Emulate Neurological Disorders". United States. https://doi.org/10.3389/fnins.2018.00856. https://www.osti.gov/servlets/purl/1490214.
@article{osti_1490214,
title = {Vanadium Dioxide Circuits Emulate Neurological Disorders},
author = {Lin, Jianqiang and Guha, Supratik and Ramanathan, Shriram},
abstractNote = {Information in the central nervous system (CNS) is conducted via electrical signals known as action potentials and is encoded in time. Several neurological disorders including depression, Attention Deficit Hyperactivity Disorder (ADHD), originate in faulty brain signaling frequencies. Here, we present a Hodgkin-Huxley model analog for a strongly correlated VO2 artificial neuron system that undergoes an electrically-driven insulator-metal transition. We demonstrate that tuning of the insulating phase resistance in VO2 threshold switch circuits can enable direct mimicry of neuronal origins of disorders in the CNS. The results introduce use of circuits based on quantum materials as complementary to model animal studies for neuroscience, especially when precise measurements of local electrical properties or competing parallel paths for conduction in complex neural circuits can be a challenge to identify onset of breakdown or diagnose early symptoms of disease.},
doi = {10.3389/fnins.2018.00856},
journal = {Frontiers in Neuroscience (Online)},
number = ,
volume = 12,
place = {United States},
year = {Fri Nov 30 00:00:00 EST 2018},
month = {Fri Nov 30 00:00:00 EST 2018}
}
Web of Science
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