Amoeba-based neurocomputing with chaotic dynamics

Masashi Aono, Masahiko Hara, Kazuyuki Aihara

Research output: Contribution to journalReview article

41 Citations (Scopus)

Abstract

An amoeba that freely change its planar shape inside the stellar carrier structure on an agar plate was employed for neuralcomputing with chaotic dynamics. A neural network model with state transition represented by the amoeba's photoaviodance-based shape deformation under optical feedback control was also implemented. Optical feedback automatically is found to update illumination according to recurrent neural network dynamics while each neuron is activated or inactivated when the weighted sum of inputs from other neurons exceed a certain threshold. The symmetry-broken oscillation patterns of amoeba imply that the system operates as a logical circuit with computational university by properly altering the number of neurons, thresholds, and weights. Collectively interacting amoeba proteins are found to generate chaotic dynamics capable of amplifying intrinsic microscopic fluctuations to destabilize neural macroscopic conditions.

Original languageEnglish
Pages (from-to)69-72
Number of pages4
JournalCommunications of the ACM
Volume50
Issue number9
DOIs
Publication statusPublished - 2007 Sep 1
Externally publishedYes

Fingerprint

Chaotic Dynamics
Neurons
Optical Feedback
Optical feedback
Neuron
Network Dynamics
Recurrent neural networks
Recurrent Neural Networks
State Transition
Weighted Sums
Neural Network Model
Feedback Control
Feedback control
Illumination
Exceed
Lighting
Update
Oscillation
Fluctuations
Neural networks

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Graphics and Computer-Aided Design
  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics

Cite this

Amoeba-based neurocomputing with chaotic dynamics. / Aono, Masashi; Hara, Masahiko; Aihara, Kazuyuki.

In: Communications of the ACM, Vol. 50, No. 9, 01.09.2007, p. 69-72.

Research output: Contribution to journalReview article

Aono, Masashi ; Hara, Masahiko ; Aihara, Kazuyuki. / Amoeba-based neurocomputing with chaotic dynamics. In: Communications of the ACM. 2007 ; Vol. 50, No. 9. pp. 69-72.
@article{520195b84a58442791e03c43441be3a3,
title = "Amoeba-based neurocomputing with chaotic dynamics",
abstract = "An amoeba that freely change its planar shape inside the stellar carrier structure on an agar plate was employed for neuralcomputing with chaotic dynamics. A neural network model with state transition represented by the amoeba's photoaviodance-based shape deformation under optical feedback control was also implemented. Optical feedback automatically is found to update illumination according to recurrent neural network dynamics while each neuron is activated or inactivated when the weighted sum of inputs from other neurons exceed a certain threshold. The symmetry-broken oscillation patterns of amoeba imply that the system operates as a logical circuit with computational university by properly altering the number of neurons, thresholds, and weights. Collectively interacting amoeba proteins are found to generate chaotic dynamics capable of amplifying intrinsic microscopic fluctuations to destabilize neural macroscopic conditions.",
author = "Masashi Aono and Masahiko Hara and Kazuyuki Aihara",
year = "2007",
month = "9",
day = "1",
doi = "10.1145/1284621.1284651",
language = "English",
volume = "50",
pages = "69--72",
journal = "Communications of the ACM",
issn = "0001-0782",
publisher = "Association for Computing Machinery (ACM)",
number = "9",

}

TY - JOUR

T1 - Amoeba-based neurocomputing with chaotic dynamics

AU - Aono, Masashi

AU - Hara, Masahiko

AU - Aihara, Kazuyuki

PY - 2007/9/1

Y1 - 2007/9/1

N2 - An amoeba that freely change its planar shape inside the stellar carrier structure on an agar plate was employed for neuralcomputing with chaotic dynamics. A neural network model with state transition represented by the amoeba's photoaviodance-based shape deformation under optical feedback control was also implemented. Optical feedback automatically is found to update illumination according to recurrent neural network dynamics while each neuron is activated or inactivated when the weighted sum of inputs from other neurons exceed a certain threshold. The symmetry-broken oscillation patterns of amoeba imply that the system operates as a logical circuit with computational university by properly altering the number of neurons, thresholds, and weights. Collectively interacting amoeba proteins are found to generate chaotic dynamics capable of amplifying intrinsic microscopic fluctuations to destabilize neural macroscopic conditions.

AB - An amoeba that freely change its planar shape inside the stellar carrier structure on an agar plate was employed for neuralcomputing with chaotic dynamics. A neural network model with state transition represented by the amoeba's photoaviodance-based shape deformation under optical feedback control was also implemented. Optical feedback automatically is found to update illumination according to recurrent neural network dynamics while each neuron is activated or inactivated when the weighted sum of inputs from other neurons exceed a certain threshold. The symmetry-broken oscillation patterns of amoeba imply that the system operates as a logical circuit with computational university by properly altering the number of neurons, thresholds, and weights. Collectively interacting amoeba proteins are found to generate chaotic dynamics capable of amplifying intrinsic microscopic fluctuations to destabilize neural macroscopic conditions.

UR - http://www.scopus.com/inward/record.url?scp=34548387441&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34548387441&partnerID=8YFLogxK

U2 - 10.1145/1284621.1284651

DO - 10.1145/1284621.1284651

M3 - Review article

AN - SCOPUS:34548387441

VL - 50

SP - 69

EP - 72

JO - Communications of the ACM

JF - Communications of the ACM

SN - 0001-0782

IS - 9

ER -