This title appears in the Scientific Report :
2014
Please use the identifier:
http://hdl.handle.net/2128/9139 in citations.
Please use the identifier: http://dx.doi.org/10.3389/fncom.2014.00124 in citations.
Dynamic stability of sequential stimulus representations in adapting neuronal networks
Dynamic stability of sequential stimulus representations in adapting neuronal networks
The ability to acquire and maintain appropriate representations of time-varying, sequential stimulus events is a fundamental feature of neocortical circuits and a necessary first step towards more specialized information processing. The dynamical properties of such representations depend on the curr...
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Personal Name(s): | Duarte, Renato |
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Morrison, Abigail | |
Contributing Institute: |
Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Published in: | Frontiers in computational neuroscience, 8 (2014) 124, S. 1 - 20 |
Imprint: |
Lausanne
Frontiers Research Foundation
2014
|
DOI: |
10.3389/fncom.2014.00124 |
PubMed ID: |
25374534 |
Document Type: |
Journal Article |
Research Program: |
W2/W3 Professorinnen Programm der Helmholtzgemeinschaft (Dys-)function and Plasticity Theory, modelling and simulation (Dys-)function and Plasticity |
Link: |
Get full text OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.3389/fncom.2014.00124 in citations.
The ability to acquire and maintain appropriate representations of time-varying, sequential stimulus events is a fundamental feature of neocortical circuits and a necessary first step towards more specialized information processing. The dynamical properties of such representations depend on the current state of the circuit, which is determined primarily by the ongoing, internally generated activity, setting the ground state from which input-specific transformations emerge. Here, we begin by demonstrating that timing-dependent synaptic plasticity mechanisms have an important role to play in the active maintenance of an ongoing dynamics characterized by asynchronous and irregular firing, closely resembling cortical activity in vivo. Incoming stimuli, acting as perturbations of the local balance of excitation and inhibition, require fast adaptive responses to prevent the development of unstable activity regimes, such as those characterized by a high degree of population-wide synchrony. We establish a link between such pathological network activity, which is circumvented by the action of plasticity, and a reduced computational capacity. Additionally, we demonstrate that the action of plasticity shapes and stabilizes the transient network states exhibited in the presence of sequentially presented stimulus events, allowing the development of adequate and discernible stimulus representations. The main feature responsible for the increased discriminability of stimulus-driven population responses in plastic networks is shown to be the decorrelating action of inhibitory plasticity and the consequent maintenance of the asynchronous irregular dynamic regime both for ongoing activity and stimulus-driven responses, whereas excitatory plasticity is shown to play only a marginal role. |