Literature DB >> 889594

Aplysia bursting neurons as endogenous oscillators. I. Phase-response curves for pulsed inhibitory synaptic input.

H M Pinsker.   

Abstract

1. The left upper quadrant bursting neurons in the abdominal ganglion of Aplysia are isochronous, nonlinear oscillators. Transmembrane current and temperature are parameters of the bursting oscillator. 2. The phase-response curve (PRC) for pulsed inhibitory synaptic input from an interneuron describes the phase shift produced by synaptic input at different phases of the burst cycle. 3. The characteristic shape of the PRC consists of two linear functions that intersect at the point in the cycle where the burst of spikes ends. Whether the net effect of the synaptic input at a given phase is phase advance or phase delay depends on 1) the number of spikes inhibited, and 2) the duration of the inhibition relative to the duration of the free-run period. 4. The shape of the PRC remains constant when a stepwise change in a parameter is introduced, when the duration of the synaptic input is increased, when the fast component of the IPSP is blocked, and when a long hyperpolarizing pulse is used to mimic the slow IPSP. 5. The shape of the PRC is changed when short hyperpolarizing pulses or antidromic action potentials are used and when only the pacemaker oscillation is present in the bursting neuron. 6. Therefore, the synaptic modulation of the bursting rhythm is determined by the voltage change produced by the IPSP and its inhibition of spikes in the bursting neuron.

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Year:  1977        PMID: 889594     DOI: 10.1152/jn.1977.40.3.527

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


  34 in total

1.  Dynamics from a time series: can we extract the phase resetting curve from a time series?

Authors:  S A Oprisan; V Thirumalai; C C Canavier
Journal:  Biophys J       Date:  2003-05       Impact factor: 4.033

2.  The functional consequences of changes in the strength and duration of synaptic inputs to oscillatory neurons.

Authors:  Astrid A Prinz; Vatsala Thirumalai; Eve Marder
Journal:  J Neurosci       Date:  2003-02-01       Impact factor: 6.167

Review 3.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

4.  Differential effects of conductances on the phase resetting curve of a bursting neuronal oscillator.

Authors:  Wafa Soofi; Astrid A Prinz
Journal:  J Comput Neurosci       Date:  2015-04-03       Impact factor: 1.621

5.  Phase resetting curves and oscillatory stability in interneurons of rat somatosensory cortex.

Authors:  T Tateno; H P C Robinson
Journal:  Biophys J       Date:  2007-01-15       Impact factor: 4.033

6.  Frequency regulation of a slow rhythm by a fast periodic input.

Authors:  F Nadim; Y Manor; M P Nusbaum; E Marder
Journal:  J Neurosci       Date:  1998-07-01       Impact factor: 6.167

Review 7.  Variability, compensation, and modulation in neurons and circuits.

Authors:  Eve Marder
Journal:  Proc Natl Acad Sci U S A       Date:  2011-03-07       Impact factor: 11.205

8.  Dissection and reduction of a modeled bursting neuron.

Authors:  R J Butera; J W Clark; J H Byrne
Journal:  J Comput Neurosci       Date:  1996-09       Impact factor: 1.621

9.  Conditional dendritic oscillators in a lobster mechanoreceptor neurone.

Authors:  D Combes; J Simmers; M Moulins
Journal:  J Physiol       Date:  1997-02-15       Impact factor: 5.182

10.  Phase sensitivity and entrainment in a modeled bursting neuron.

Authors:  S S Demir; R J Butera; A A DeFranceschi; J W Clark; J H Byrne
Journal:  Biophys J       Date:  1997-02       Impact factor: 4.033

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