Feed-forward inhibition as a buffer of the neuronal input-output relation

Neuronal processing depends on the input-output (I/O) relation between the frequency of synaptic stimulation and the resultant axonal firing rate. The all-or-none properties of spike generation and active membrane mechanisms can make the neuronal I/O relation very steep. The ensuing nearly bimodal b...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 106; no. 42; pp. 18004 - 18009
Main Authors Ferrante, Michele, Migliore, Michele, Ascoli, Giorgio A
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 20.10.2009
National Acad Sciences
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ISSN0027-8424
1091-6490
1091-6490
DOI10.1073/pnas.0904784106

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Summary:Neuronal processing depends on the input-output (I/O) relation between the frequency of synaptic stimulation and the resultant axonal firing rate. The all-or-none properties of spike generation and active membrane mechanisms can make the neuronal I/O relation very steep. The ensuing nearly bimodal behavior may severely limit information coding, as minimal input fluctuations within the expected natural variability could cause neuronal output to jump between quiescence and maximum firing rate. Here, using biophysically and anatomically realistic computational models of individual neurons, we demonstrate that feed-forward inhibition, a ubiquitous mechanism in which inhibitory interneurons and their target cells are activated by the same excitatory input, can change a steeply sigmoid I/O curve into a double-sigmoid typical of buffer systems. The addition of an intermediate plateau stabilizes the spiking response over a broad dynamic range of input frequency, ensuring robust integration of noisy synaptic signals. Both the buffered firing rate and its input firing range can be independently and extensively modulated by biologically plausible changes in the weight and number of excitatory synapses on the feed-forward interneuron. By providing a soft switch between essentially digital and analog rate-code, this continuous control of the circuit I/O could dramatically increase the computational power of neuronal integration.
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Author contributions: M.F., M.M., and G.A.A. designed research, performed research, analyzed data, and wrote the paper.
Edited by Charles F. Stevens, The Salk Institute for Biological Studies, La Jolla, CA, and approved September 4, 2009
ISSN:0027-8424
1091-6490
1091-6490
DOI:10.1073/pnas.0904784106