Literature DB >> 2310783

Reticular activation and the dynamics of neuronal networks.

J J Wright1.   

Abstract

It is postulated that during arousal the cortical system is driven by a spatially and temporally noisy signal arising from non-specific reticulo-cortical pathways. An elementary unit of cortical neuroanatomy is assumed, which permits non-linear dynamics to be represented by stochastic linear equations. Under these assumptions the resonant modes of the system of cortical dendrites approach thermodynamic equilibrium. Specific sensory signals perturb the dendritic system about equilibrium, generate low frequency, linear, non-dispersive waves corresponding to the EEG, which in turn regulate action potential sequences, and instantiate internal inputs to the dendritic field. A large and distributed memory capacity in axo-synaptic couplings, resistance to interference between functionally separate logical operations, and a very large next-state function set emerge as properties of the network. The model is able to explain the close association of the EEG with cognition, the channel of low capacity corresponding to the field of immediate attention, the low overall correlation of action potentials with EEG, and specificity of action potentials in some neurons during particular cognitive activity. Predictions made from hypothesis include features of thermal equilibrium in EEG (determinable by autoregression) and expectation that the cortical evoked response can be accounted for as the response to a sensory impulse of specific time characteristics.

Mesh:

Year:  1990        PMID: 2310783     DOI: 10.1007/bf00201443

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  30 in total

1.  The limbic system ("visceral brain") and emotional behavior.

Authors:  P D MACLEAN
Journal:  AMA Arch Neurol Psychiatry       Date:  1955-02

2.  EEG alpha map series: brain micro-states by space-oriented adaptive segmentation.

Authors:  D Lehmann; H Ozaki; I Pal
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1987-09

3.  Discovering order in chaos: stable self-organization of neural recognition codes.

Authors:  G A Carpenter; S Grossberg
Journal:  Ann N Y Acad Sci       Date:  1987       Impact factor: 5.691

4.  Computing with neural circuits: a model.

Authors:  J J Hopfield; D W Tank
Journal:  Science       Date:  1986-08-08       Impact factor: 47.728

Review 5.  Catecholamine theories of reward: a critical review.

Authors:  R A Wise
Journal:  Brain Res       Date:  1978-08-25       Impact factor: 3.252

6.  Model of brain rhythmic activity. The alpha-rhythm of the thalamus.

Authors:  F H Lopes da Silva; A Hoeks; H Smits; L H Zetterberg
Journal:  Kybernetik       Date:  1974-05-31

7.  Structural organization of nonspecific thalamic nuclei and their projection toward cortex.

Authors:  M E Scheibel; A B Scheibel
Journal:  Brain Res       Date:  1967-09       Impact factor: 3.252

8.  Simulation of chaotic EEG patterns with a dynamic model of the olfactory system.

Authors:  W J Freeman
Journal:  Biol Cybern       Date:  1987       Impact factor: 2.086

Review 9.  The auditory evoked potential in the rat--a review.

Authors:  N A Shaw
Journal:  Prog Neurobiol       Date:  1988       Impact factor: 11.685

10.  Mental phenomena as changes of state in a finite-state machine.

Authors:  R R Kydd; J J Wright
Journal:  Aust N Z J Psychiatry       Date:  1986-06       Impact factor: 5.744

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  6 in total

1.  Non-linear and linear forecasting of the EEG time series.

Authors:  K J Blinowska; M Malinowski
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

2.  The estimation of the Kolmogorov entropy from a time series and its limitations when performed on EEG.

Authors:  R M Dünki
Journal:  Bull Math Biol       Date:  1991       Impact factor: 1.758

3.  Autoregression models of EEG. Results compared with expectations for a multilinear near-equilibrium biophysical process.

Authors:  J J Wright; R R Kydd; A A Sergejew
Journal:  Biol Cybern       Date:  1990       Impact factor: 2.086

4.  Inverse filter computation of the neural impulse giving rise to the auditory evoked potential.

Authors:  J J Wright; A A Sergejew; H G Stampfer
Journal:  Brain Topogr       Date:  1990       Impact factor: 3.020

5.  Simulation of electrocortical waves.

Authors:  J J Wright; D T Liley
Journal:  Biol Cybern       Date:  1995       Impact factor: 2.086

6.  An attractor-based complexity measurement for Boolean recurrent neural networks.

Authors:  Jérémie Cabessa; Alessandro E P Villa
Journal:  PLoS One       Date:  2014-04-11       Impact factor: 3.240

  6 in total

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