Modeling granular layer local field potential using single neuron and network based approaches to predict LTP/LTD in extracellular recordings

Nimshitha Abdulmanaph (1) , Harilal Parasuraman (1) , Bipin Nair (1) , Shyam Diwakar (1)

1 School of Biotechnology

Local field potentials (LFPs) are recorded as waveforms of extracellular activity that arise from complex interactions of spatial distribution of current sources, time dynamics, spatial distribution of dipoles apart underlying conductive properties of the extracellular medium. We reconstructed granular layer post-synaptic LFP by two different approaches in order to test and parameterize the molecular mechanisms of cellular function with network properties. In the first, we used a single granule neuron as a model kernel for reconstructing population activity. The second approach consisted using a detailed network model. LTP and LTD could regulate the spatiotemporal pattern of granular layer responses to mossy fibre inputs. The effect of changes in synaptic release probability and modulation in intrinsic excitability of granule cell on LFP was studied. The study revealed cellular function was represented in LFP wave revealing the activity of underlying neurons. Changes to cell during LTP and LTD were reflected by LFP wave as an indicator of the function of granule neurons as spatial pattern generators. Both modeling approaches generated LFP in vitro [16] and in vivo [17] waveforms as reported in experiments.

Mots clés: Others; Plasticity and functional specialization; Information coding; Biophysical models

Domaines: Neurosciences [q-bio.NC]; Neurosciences

Nimshitha Abdulmanaph, Harilal Parasuraman, Bipin Nair, Shyam Diwakar. Modeling granular layer local field potential using single neuron and network based approaches to predict LTP/LTD in extracellular recordings. Cinquième conférence plénière française de Neurosciences Computationnelles, "Neurocomp'10", Aug 2010, Lyon, France. ⟨hal-00553410⟩