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Frequency modulation of large oscillatory neural networks

Francis wyffels UGent, Jiwen Li, Tim Waegeman, Benjamin Schrauwen and Herbert Jaeger (2014) BIOLOGICAL CYBERNETICS. 108(2). p.145-157
abstract
Dynamical systems which generate periodic signals are of interest as models of biological central pattern generators and in a number of robotic applications. A basic functionality that is required in both biological modelling and robotics is frequency modulation. This leads to the question of whether there are generic mechanisms to control the frequency of neural oscillators. Here we describe why this objective is of a different nature, and more difficult to achieve, than modulating other oscillation characteristics (like amplitude, offset, signal shape). We propose a generic way to solve this task which makes use of a simple linear controller. It rests on the insight that there is a bidirectional dependency between the frequency of an oscillation and geometric properties of the neural oscillator's phase portrait. By controlling the geometry of the neural state orbits, it is possible to control the frequency on the condition that the state space can be shaped such that it can be pushed easily to any frequency.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
ADAPTATION, Frequency modulation, BEHAVIORS, CIRCUITS, MODELS, ROBOT, Reservoir computing, Pattern generators, CENTRAL PATTERN GENERATORS, WALKING, LOCOMOTION
journal title
BIOLOGICAL CYBERNETICS
Biol. Cybern.
volume
108
issue
2
pages
145 - 157
Web of Science type
Article
Web of Science id
000333201000003
JCR category
COMPUTER SCIENCE, CYBERNETICS
JCR impact factor
1.713 (2014)
JCR rank
8/24 (2014)
JCR quartile
2 (2014)
ISSN
0340-1200
DOI
10.1007/s00422-013-0584-0
project
AMARSI (Adaptive Modular Architecture for Rich Motor Skills)
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
4292780
handle
http://hdl.handle.net/1854/LU-4292780
date created
2014-02-17 09:33:37
date last changed
2016-12-19 15:38:32
@article{4292780,
  abstract     = {Dynamical systems which generate periodic signals are of interest as models of biological central pattern generators and in a number of robotic applications. A basic functionality that is required in both biological modelling and robotics is frequency modulation. This leads to the question of whether there are generic mechanisms to control the frequency of neural oscillators. Here we describe why this objective is of a different nature, and more difficult to achieve, than modulating other oscillation characteristics (like amplitude, offset, signal shape). We propose a generic way to solve this task which makes use of a simple linear controller. It rests on the insight that there is a bidirectional dependency between the frequency of an oscillation and geometric properties of the neural oscillator's phase portrait. By controlling the geometry of the neural state orbits, it is possible to control the frequency on the condition that the state space can be shaped such that it can be pushed easily to any frequency.},
  author       = {wyffels, Francis and Li, Jiwen and Waegeman, Tim and Schrauwen, Benjamin and Jaeger, Herbert},
  issn         = {0340-1200},
  journal      = {BIOLOGICAL CYBERNETICS},
  keyword      = {ADAPTATION,Frequency modulation,BEHAVIORS,CIRCUITS,MODELS,ROBOT,Reservoir computing,Pattern generators,CENTRAL PATTERN GENERATORS,WALKING,LOCOMOTION},
  language     = {eng},
  number       = {2},
  pages        = {145--157},
  title        = {Frequency modulation of large oscillatory neural networks},
  url          = {http://dx.doi.org/10.1007/s00422-013-0584-0},
  volume       = {108},
  year         = {2014},
}

Chicago
wyffels, Francis, Jiwen Li, Tim Waegeman, Benjamin Schrauwen, and Herbert Jaeger. 2014. “Frequency Modulation of Large Oscillatory Neural Networks.” Biological Cybernetics 108 (2): 145–157.
APA
wyffels, F., Li, J., Waegeman, T., Schrauwen, B., & Jaeger, H. (2014). Frequency modulation of large oscillatory neural networks. BIOLOGICAL CYBERNETICS, 108(2), 145–157.
Vancouver
1.
wyffels F, Li J, Waegeman T, Schrauwen B, Jaeger H. Frequency modulation of large oscillatory neural networks. BIOLOGICAL CYBERNETICS. 2014;108(2):145–57.
MLA
wyffels, Francis, Jiwen Li, Tim Waegeman, et al. “Frequency Modulation of Large Oscillatory Neural Networks.” BIOLOGICAL CYBERNETICS 108.2 (2014): 145–157. Print.