Principles of real-time computing with feedback applied to cortical microcircuit models

Wolfgang Maass, Prashant Joshi, Eduardo Sontag

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

The network topology of neurons in the brain exhibits an abundance of feedback connections, but the computational function of these feedback connections is largely unknown. We present a computational theory that characterizes the gain in computational power achieved through feedback in dynamical systems with fading memory. It implies that many such systems acquire through feedback universal computational capabilities for analog computing with a non-fading memory. In particular, we show that feedback enables such systems to process time-varying input streams in diverse ways according to rules that are implemented through internal states of the dynamical system. In contrast to previous attractor-based computational models for neural networks, these flexible internal states are high-dimensional attractors of the circuit dynamics, that still allow the circuit state to absorb new information from online input streams. In this way one arrives at novel models for working memory, integration of evidence, and reward expectation in cortical circuits. We show that they are applicable to circuits of conductance-based Hodgkin-Huxley (HH) neurons with high levels of noise that reflect experimental data on in-vivo conditions.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference
Pages835-842
Number of pages8
StatePublished - Dec 1 2005
Event2005 Annual Conference on Neural Information Processing Systems, NIPS 2005 - Vancouver, BC, Canada
Duration: Dec 5 2005Dec 8 2005

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Other

Other2005 Annual Conference on Neural Information Processing Systems, NIPS 2005
CountryCanada
CityVancouver, BC
Period12/5/0512/8/05

Fingerprint

Feedback
Networks (circuits)
Data storage equipment
Neurons
Dynamical systems
Brain
Topology
Neural networks

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

Cite this

Maass, W., Joshi, P., & Sontag, E. (2005). Principles of real-time computing with feedback applied to cortical microcircuit models. In Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference (pp. 835-842). (Advances in Neural Information Processing Systems).
Maass, Wolfgang ; Joshi, Prashant ; Sontag, Eduardo. / Principles of real-time computing with feedback applied to cortical microcircuit models. Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference. 2005. pp. 835-842 (Advances in Neural Information Processing Systems).
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Maass, W, Joshi, P & Sontag, E 2005, Principles of real-time computing with feedback applied to cortical microcircuit models. in Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference. Advances in Neural Information Processing Systems, pp. 835-842, 2005 Annual Conference on Neural Information Processing Systems, NIPS 2005, Vancouver, BC, Canada, 12/5/05.

Principles of real-time computing with feedback applied to cortical microcircuit models. / Maass, Wolfgang; Joshi, Prashant; Sontag, Eduardo.

Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference. 2005. p. 835-842 (Advances in Neural Information Processing Systems).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Maass W, Joshi P, Sontag E. Principles of real-time computing with feedback applied to cortical microcircuit models. In Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference. 2005. p. 835-842. (Advances in Neural Information Processing Systems).