Literature DB >> 9573404

Computational models of neuromodulation.

J M Fellous1, C Linster.   

Abstract

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

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Year:  1998        PMID: 9573404     DOI: 10.1162/089976698300017476

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  19 in total

1.  A computational model of mechanisms controlling experience-dependent reorganization of representational maps in auditory cortex.

Authors:  E Mercado; C E Myers; M A Gluck
Journal:  Cogn Affect Behav Neurosci       Date:  2001-03       Impact factor: 3.282

Review 2.  Beyond the wiring diagram: signalling through complex neuromodulator networks.

Authors:  Vladimir Brezina
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-08-12       Impact factor: 6.237

3.  A positive feedback at the cellular level promotes robustness and modulation at the circuit level.

Authors:  Julie Dethier; Guillaume Drion; Alessio Franci; Rodolphe Sepulchre
Journal:  J Neurophysiol       Date:  2015-08-26       Impact factor: 2.714

4.  Offline reactivation of experience-dependent neuronal firing patterns in the rat ventral tegmental area.

Authors:  José L Valdés; Bruce L McNaughton; Jean-Marc Fellous
Journal:  J Neurophysiol       Date:  2015-06-24       Impact factor: 2.714

5.  Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology.

Authors:  Hirenkumar K Makadia; Warren D Anderson; Dirk Fey; Thomas Sauter; James S Schwaber; Rajanikanth Vadigepalli
Journal:  Biophys J       Date:  2015-01-06       Impact factor: 4.033

6.  Spiking neural circuits with dendritic stimulus processors : encoding, decoding, and identification in reproducing kernel Hilbert spaces.

Authors:  Aurel A Lazar; Yevgeniy B Slutskiy
Journal:  J Comput Neurosci       Date:  2014-09-02       Impact factor: 1.621

7.  Comparative study of chemical neuroanatomy of the olfactory neuropil in mouse, honey bee, and human.

Authors:  Irina Sinakevitch; George R Bjorklund; Jason M Newbern; Richard C Gerkin; Brian H Smith
Journal:  Biol Cybern       Date:  2017-08-29       Impact factor: 2.086

Review 8.  Modeling nicotinic neuromodulation from global functional and network levels to nAChR based mechanisms.

Authors:  Michael Graupner; Boris Gutkin
Journal:  Acta Pharmacol Sin       Date:  2009-06       Impact factor: 6.150

9.  Functional neuromodulation of chemosensation in vertebrates.

Authors:  Christiane Linster; Alfredo Fontanini
Journal:  Curr Opin Neurobiol       Date:  2014-06-24       Impact factor: 6.627

10.  Synaptic background noise controls the input/output characteristics of single cells in an in vitro model of in vivo activity.

Authors:  J-M Fellous; M Rudolph; A Destexhe; T J Sejnowski
Journal:  Neuroscience       Date:  2003       Impact factor: 3.590

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