Literature DB >> 12853443

Neuromuscular modulation in Aplysia. I. Dynamic model.

Vladimir Brezina1, Irina V Orekhova, Klaudiusz R Weiss.   

Abstract

Many physiological systems are regulated by complex networks of modulatory actions. Here we use mathematical modeling and complementary experiments to study the dynamic behavior of such a network in the accessory radula closer (ARC) neuromuscular system of Aplysia. The ARC muscle participates in several types of rhythmic consummatory feeding behavior. The muscle's motor neurons release acetylcholine to produce basal contractions, but also modulatory peptide cotransmitters that, through multiple cellular effects, shape the contractions to meet behavioral demands. We construct a dynamic model of the modulatory network and examine its operation as the motor neurons fire in realistic patterns that change gradually over an hour-long meal and abruptly with switches between the different feeding behaviors. The modulatory effects have very disparate dynamical time scales. Some react to the motor neuron firing only over many cycles of the behavior, but one key effect is fast enough to respond to each individual cycle. Switches between the behaviors are therefore followed by rapid relaxations along some modulatory dimensions but not others. The trajectory of the modulatory state is a transient throughout the meal, ranging widely over regions of the modulatory space not accessible in the steady state. There is a pronounced history-dependency: the modulatory state associated with a cycle of a particular behavior depends on when that cycle occurs and what behaviors preceded it. On average, nevertheless, each behavior is associated with a different modulatory state. In the following companion study, we add a model of the neuromuscular transform to reconstruct and evaluate the actual modulated contraction shapes.

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Year:  2003        PMID: 12853443     DOI: 10.1152/jn.01091.2002

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  9 in total

Review 1.  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

2.  Temperature compensation of neuromuscular modulation in aplysia.

Authors:  Yuriy Zhurov; Vladimir Brezina
Journal:  J Neurophysiol       Date:  2005-06-08       Impact factor: 2.714

3.  Variability of motoneuron activation and the modulation of force production in a postural reflex of the hermit crab abdomen.

Authors:  Jacob L Krans; William D Chapple
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2005-07-01       Impact factor: 1.836

4.  Functional penetration of variability of motor neuron spike timing through a modulated neuromuscular system.

Authors:  Vladimir Brezina
Journal:  Neurocomputing       Date:  2007-06       Impact factor: 5.719

5.  Cycle-to-cycle variability as an optimal behavioral strategy.

Authors:  Vladimir Brezina; Alex Proekt; Klaudiusz R Weiss
Journal:  Neurocomputing       Date:  2006-06-01       Impact factor: 5.719

6.  AMGSEFLamide, a member of a broadly conserved peptide family, modulates multiple neural networks in Homarus americanus.

Authors:  Patsy S Dickinson; Evyn S Dickinson; Emily R Oleisky; Cindy D Rivera; Meredith E Stanhope; Elizabeth A Stemmler; J Joe Hull; Andrew E Christie
Journal:  J Exp Biol       Date:  2019-01-18       Impact factor: 3.312

Review 7.  State dependence of network output: modeling and experiments.

Authors:  Farzan Nadim; Vladimir Brezina; Alain Destexhe; Christiane Linster
Journal:  J Neurosci       Date:  2008-11-12       Impact factor: 6.167

8.  Comodulation of h- and Na+/K+ Pump Currents Expands the Range of Functional Bursting in a Central Pattern Generator by Navigating between Dysfunctional Regimes.

Authors:  Parker J Ellingson; William H Barnett; Daniel Kueh; Alex Vargas; Ronald L Calabrese; Gennady S Cymbalyuk
Journal:  J Neurosci       Date:  2021-06-08       Impact factor: 6.167

9.  Predicting adaptive behavior in the environment from central nervous system dynamics.

Authors:  Alex Proekt; Jane Wong; Yuriy Zhurov; Nataliya Kozlova; Klaudiusz R Weiss; Vladimir Brezina
Journal:  PLoS One       Date:  2008-11-07       Impact factor: 3.240

  9 in total

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