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A Theory of Rate Coding Control by Intrinsic Plasticity Effects

Overview of attention for article published in PLoS Computational Biology, January 2012
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Article details
Title
A Theory of Rate Coding Control by Intrinsic Plasticity Effects
Published in
PLoS Computational Biology, January 2012
DOI 10.1371/journal.pcbi.1002349
Pubmed ID
Authors
Abstract

Intrinsic plasticity (IP) is a ubiquitous activity-dependent process regulating neuronal excitability and a cellular correlate of behavioral learning and neuronal homeostasis. Because IP is induced rapidly and maintained long-term, it likely represents a major determinant of adaptive collective neuronal dynamics. However, assessing the exact impact of IP has remained elusive. Indeed, it is extremely difficult disentangling the complex non-linear interaction between IP effects, by which conductance changes alter neuronal activity, and IP rules, whereby activity modifies conductance via signaling pathways. Moreover, the two major IP effects on firing rate, threshold and gain modulation, remain unknown in their very mechanisms. Here, using extensive simulations and sensitivity analysis of Hodgkin-Huxley models, we show that threshold and gain modulation are accounted for by maximal conductance plasticity of conductance that situate in two separate domains of the parameter space corresponding to sub- and supra-threshold conductance (i.e. activating below or above the spike onset threshold potential). Analyzing equivalent integrate-and-fire models, we provide formal expressions of sensitivities relating to conductance parameters, unraveling unprecedented mechanisms governing IP effects. Our results generalize to the IP of other conductance parameters and allow strong inference for calcium-gated conductance, yielding a general picture that accounts for a large repertoire of experimental observations. The expressions we provide can be combined with IP rules in rate or spiking models, offering a general framework to systematically assess the computational consequences of IP of pharmacologically identified conductance with both fine grain description and mathematical tractability. We provide an example of such IP loop model addressing the important issue of the homeostatic regulation of spontaneous discharge. Because we do not formulate any assumptions on modification rules, the present theory is also relevant to other neural processes involving excitability changes, such as neuromodulation, development, aging and neural disorders.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 3 5%
Germany 3 5%
France 2 4%
United States 1 2%
Japan 1 2%
Unknown 47 82%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 17 30%
Researcher 13 23%
Professor 6 11%
Other 3 5%
Student > Bachelor 3 5%
Other 8 14%
Unknown 7 12%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 20 35%
Neuroscience 10 18%
Computer Science 5 9%
Physics and Astronomy 5 9%
Medicine and Dentistry 4 7%
Other 6 11%
Unknown 7 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 January 2012.
All research outputs
#18,985,932
of 27,521,156 outputs
Outputs from PLoS Computational Biology
#7,745
of 9,341 outputs
Outputs of similar age
#184,056
of 259,926 outputs
Outputs of similar age from PLoS Computational Biology
#73
of 118 outputs
Altmetric has tracked 27,521,156 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,341 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.4. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 259,926 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.