Brainmorphic computing: Paradigm and hardware

A brainmorphic computing (BMC) paradigm, a new framework for brain-like computing, is necessary for realizing a highly efficient and high-performance brain-specific information processing that emerged evolutionarily in the brain. The BMC paradigm should consider the tight relationship between complex structure and computation, high-dimensional integrated dynamics, embodiment, and computation through biophysical phenomena. Furthermore, a dedicated hardware, i.e., brainmorphic computing hardware (BMC-HW), is mandatory for reproducing the BMC paradigm, through which highly efficient, high-performance, and brain-like computation can be realized as a practical engineering system. It is natural and essential to employ continuous-value and continuous-time physical phenomena in BMC-HW like the brain. This study reviews the BMC paradigm and BMC-HW framework with some implementation examples, which we have developed. In addition, extensions of the BMC paradigm and BMC-HW framework to a complex spatiotemporal information processing through event-driven, continuous-value, continuous-time, asynchronous spiking neural networks are discussed, which is closer to the way the brain processes information. Furthermore, novel device and circuit technologies to realize the extended BMC paradigm are introduced.

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Publication Details

Journal
Nonlinear Theory and Its Applications IEICE
Published
2025-01-01
DOI
https://doi.org/10.1587/nolta.16.312
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Brainmorphic computing: Paradigm and hardware

Yoshihiko Horio
Nonlinear Theory and Its Applications IEICE
Advanced Memory and Neural Computing
article

Brainmorphic computing: Paradigm and hardware

Yoshihiko Horio
article en

Abstract

A brainmorphic computing (BMC) paradigm, a new framework for brain-like computing, is necessary for realizing a highly efficient and high-performance brain-specific information processing that emerged evolutionarily in the brain. The BMC paradigm should consider the tight relationship between complex structure and computation, high-dimensional integrated dynamics, embodiment, and computation through biophysical phenomena. Furthermore, a dedicated hardware, i.e., brainmorphic computing hardware (BMC-HW), is mandatory for reproducing the BMC paradigm, through which highly efficient, high-performance, and brain-like computation can be realized as a practical engineering system. It is natural and essential to employ continuous-value and continuous-time physical phenomena in BMC-HW like the brain. This study reviews the BMC paradigm and BMC-HW framework with some implementation examples, which we have developed. In addition, extensions of the BMC paradigm and BMC-HW framework to a complex spatiotemporal information processing through event-driven, continuous-value, continuous-time, asynchronous spiking neural networks are discussed, which is closer to the way the brain processes information. Furthermore, novel device and circuit technologies to realize the extended BMC paradigm are introduced.

Nonlinear Theory and Its Applications IEICEVol. 16(3)
Tohoku University (JP), Teikyo University (JP)
Openalex Percentile: Top 87%
Advanced Memory and Neural Computing
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Brainmorphic computing: Paradigm and hardware — Yoshihiko Horio · Nonlinear Theory and Its Applications IEICE (2025) | TGRS Research Map | TGRS