Journal of Computational Neuroscience

, Volume 33, Issue 2, pp 323–339 | Cite as

Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model

  • Elena Phoka
  • Mark Wildie
  • Simon R. Schultz
  • Mauricio Barahona
Article

Abstract

Experimental evidence suggests that spontaneous neuronal activity may shape and be shaped by sensory experience. However, we lack information on how sensory experience modulates the underlying synaptic dynamics and how such modulation influences the response of the network to future events. Here we study whether spike-timing-dependent plasticity (STDP) can mediate sensory-induced modifications in the spontaneous dynamics of a new large-scale model of layers II, III and IV of the rodent barrel cortex. Our model incorporates significant physiological detail, including the types of neurons present, the probabilities and delays of connections, and the STDP profiles at each excitatory synapse. We stimulated the neuronal network with a protocol of repeated sensory inputs resembling those generated by the protraction-retraction motion of whiskers when rodents explore their environment, and studied the changes in network dynamics. By applying dimensionality reduction techniques to the synaptic weight space, we show that the initial spontaneous state is modified by each repetition of the stimulus and that this reverberation of the sensory experience induces long-term, structured modifications in the synaptic weight space. The post-stimulus spontaneous state encodes a memory of the stimulus presented, since a different dynamical response is observed when the network is presented with shuffled stimuli. These results suggest that repeated exposure to the same sensory experience could induce long-term circuitry modifications via ‘Hebbian’ STDP plasticity.

Keywords

Barrel cortex Spontaneous dynamics STDP Large-scale model 

Notes

Acknowledgements

We would like to thank Rasmus Petersen for kindly providing us with the thalamic data and Borislav Vangelov for his help with the implementation of the Gaussian Process Regression analysis. This work was supported by a BBSRC DTA studentship (EP), EPSRC grant EP/E002331/1 (SRS), EPSRC grant EP/E049451/1 (MB) and by the EPSRC Support Fund.

Supplementary material

10827_2012_388_MOESM1_ESM.mpv (43.6 mb)
Movie S1Visualization of neuronal activity in barrel cortical layers II, III and IV (left panel) from 30-120 seconds. Each neuron is represented as a dot (color coding as in Fig. 1A) and active synapses are shown as red lines connecting the pre- with post-synaptic neurons. The sensory stimulation epochs are shown as black blocks at the bottom of the panel. The high-dimensional synaptic weight state vector is followed in reduced dimensional space using MDS (right panel). Each dot represents the neuronal ensemble synaptic activity sampled every 100 milliseconds (color-coding as in Fig. 3C). (MPV 43.6 MB)
10827_2012_388_MOESM2_ESM.pdf (293 kb)
(PDF 292 KB)

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Elena Phoka
    • 1
    • 2
  • Mark Wildie
    • 3
  • Simon R. Schultz
    • 1
  • Mauricio Barahona
    • 2
  1. 1.Department of BioengineeringImperial College LondonLondonUK
  2. 2.Department of MathematicsImperial College LondonLondonUK
  3. 3.Department of ComputingImperial College LondonLondonUK

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