Theory of optimal balance predicts and explains the amplitude and decaytime of synaptic inhibition

Collection with item attached
2017
Item details URL
http://open-repository.kisti.re.kr/cube/handle/open_repository/486174.do
DOI
10.1038/ncomms14566
Title
Theory of optimal balance predicts and explains the amplitude and decaytime of synaptic inhibition
Description
We thank Larry Trussell, Gary Westbrook, Mike Wehr and Gerard Borst forhelpful discussions. Research was supported by a grant to C.D.F. fromthe National Research Foundation of Korea (2015-R1A2A2A01004185).
abstract
Synaptic inhibition counterbalances excitation, but it is not known what constitutes optimal inhibition. We previously proposed that perfect balance is achieved when the peak of an excitatory postsynaptic potential (EPSP) is exactly at spike threshold, so that the slightest variation in excitation determines whether a spike is generated. Using simulations, we show that the optimal inhibitory postsynaptic conductance (IPSG) increases in amplitude and decay rate as synaptic excitation increases from 1 to 800 Hz. As further proposed by theory, we show that optimal IPSG parameters can be learned through anti-Hebbian rules. Finally, we compare our theoretical optima to published experimental data from 21 types of neurons, in which rates of synaptic excitation and IPSG decay times vary by factors of about 100 (5-600 Hz) and 50 (1-50 ms), respectively. From an infinite range of possible decay times, theory predicted experimental decay times within less than a factor of 2. Across a distinct set of 15 types of neuron recorded in vivo, theory predicted the amplitude of synaptic inhibition within a factor of 1.7. Thus, the theory can explain biophysical quantities from first principles.
provenance
Made available in Cube on 2018-09-28T16:00:31Z (GMT). No. of bitstreams: 0
language
English
author
Kim, Jaekyung K.
Fiorillo, Christopher D.
accessioned
2018-09-28T16:00:31Z
available
2018-09-28T16:00:31Z
issued
2017
citation
NATURE COMMUNICATIONS(8)
issn
2041-1723
uri
http://open-repository.kisti.re.kr/cube/handle/open_repository/486174.do
Funder
교육부
Funding Program
BK21플러스사업(0.5)
Project ID
1345273950
Jurisdiction
Rep.of Korea
Project Name
Biomedical Convergence Techonology
rights
openAccess
type
article


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