Reconstructing cerebellar granule layer evoked LFP using convolution (ReConv) (Diwakar et al. 2011)


The model allows reconstruction of evoked local field potentials as seen in the cerebellar granular layer. The approach uses a detailed model of cerebellar granule neuron to generate data traces and then uses a "ReConv" or jittered repetitive convolution technique to reproduce post-synaptic local field potentials in the granular layer. The algorithm was used to generate both in vitro and in vivo evoked LFP and reflected the changes seen during LTP and LTD, when such changes were induced in the underlying neurons by modulating release probability of synapses and sodium channel regulated intrinsic excitability of the cells.

Model Type: Neuron or other electrically excitable cell; Extracellular

Cell Type(s): Cerebellum interneuron granule GLU cell

Currents: I K; I M; I K,Ca; I Sodium; I Calcium; I Cl, leak

Receptors: GabaA; AMPA; NMDA

Model Concept(s): Extracellular Fields; Evoked LFP

Simulation Environment: NEURON; MATLAB; Octave

Implementer(s): Diwakar, Shyam [shyam at amrita.edu]

References:

Diwakar S, Lombardo P, Solinas S, Naldi G, D'Angelo E. (2011). Local field potential modeling predicts dense activation in cerebellar granule cells clusters under LTP and LTD control. PloS one. 6 [PubMed]


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