TY - JOUR
T1 - The activity phase of postsynaptic neurons in a simplified rhythmic network
AU - Bose, Amitabha
AU - Manor, Yair
AU - Nadim, Farzan
N1 - Funding Information:
We thank Timothy Lewis for helpful discussions. This work was supported in part by NSF DMS-0315862 (AB), ISF 314/99-1 (YM), BSF 2001-039 (YM, FN) and NIMH 60605-01 (FN).
PY - 2004
Y1 - 2004
N2 - Many inhibitory rhythmic networks produce activity in a range of frequencies. The relative phase of activity between neurons in these networks is often a determinant of the network output. This relative phase is determined by the interaction between synaptic inputs to the neurons and their intrinsic properties. We show, in a simplified network consisting of an oscillator inhibiting a follower neuron, how the interaction between synaptic depression and a transient potassium current in the follower neuron determines the activity phase of this neuron. We derive a mathematical expression to determine at what phase of the oscillation the follower neuron becomes active. This expression can be used to understand which parameters determine the phase of activity of the follower as the frequency of the oscillator is changed. We show that in the presence of synaptic depression, there can be three distinct frequency intervals, in which the phase of the follower neuron is determined by different sets of parameters. Alternatively, when the synapse is not depressing, only one set of parameters determines the phase of activity at all frequencies.
AB - Many inhibitory rhythmic networks produce activity in a range of frequencies. The relative phase of activity between neurons in these networks is often a determinant of the network output. This relative phase is determined by the interaction between synaptic inputs to the neurons and their intrinsic properties. We show, in a simplified network consisting of an oscillator inhibiting a follower neuron, how the interaction between synaptic depression and a transient potassium current in the follower neuron determines the activity phase of this neuron. We derive a mathematical expression to determine at what phase of the oscillation the follower neuron becomes active. This expression can be used to understand which parameters determine the phase of activity of the follower as the frequency of the oscillator is changed. We show that in the presence of synaptic depression, there can be three distinct frequency intervals, in which the phase of the follower neuron is determined by different sets of parameters. Alternatively, when the synapse is not depressing, only one set of parameters determines the phase of activity at all frequencies.
KW - A-current
KW - Central pattern generator
KW - Phase maintenance
KW - Synaptic depression
UR - https://www.scopus.com/pages/publications/4344636927
UR - https://www.scopus.com/inward/citedby.url?scp=4344636927&partnerID=8YFLogxK
U2 - 10.1023/B:JCNS.0000037685.71759.1a
DO - 10.1023/B:JCNS.0000037685.71759.1a
M3 - Article
C2 - 15306742
AN - SCOPUS:4344636927
SN - 0929-5313
VL - 17
SP - 245
EP - 261
JO - Journal of Computational Neuroscience
JF - Journal of Computational Neuroscience
IS - 2
ER -