On the estimation of population-specific synaptic currents from laminar multielectrode recordings

• Main Authors: Sergey L Gratiy, Anna eDevor, Gaute T Einevoll, Anders M Dale
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2011-12-01
• Series: Frontiers in Neuroinformatics
• Subjects: local field potential; cortical column; synaptic activity; inverse problem; Current Source Density; extracellular potential
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fninf.2011.00032/full

Multielectrode array recordings of extracellular electrical field potentials along the depth axis of the cerebral cortex is an up-and-coming approach for investigating activity of cortical neuronal circuits. The low-frequency band of extracellular potential, i.e., the local field potential (LFP), is assumed to reflect the synaptic activity and can be used to extract the current source density (CSD) profile. However, physiological interpretation of CSD profiles is uncertain because the analysis does not disambiguate synaptic inputs from passive return currents. Here we present a novel mathematical framework for identifying excited neuronal populations and for separating synaptic input currents from return currents based on LFP recordings. This involves a combination of the linear forward model, which predicts population-specific laminar LFP in response to sinusoidal synaptic inputs applied at different locations along the population cells having realistic morphologies and the linear inverse model, which reconstructs laminar profiles of synaptic inputs from the Fourier spectrum of the laminar LFP data based on the forward prediction. The model allows reconstruction of synaptic input profiles on a spatial scale comparable to known anatomical organization of synaptic projections within a cortical column. Assuming spatial correlation of synaptic inputs within individual populations, the model decomposes the columnar LFP into population-specific contributions. Constraining the solution with a priori knowledge of the spatial distribution of synaptic connectivity further allows prediction of active projections from the composite LFP profile. This modeling framework successfully delineates the main relationships between the synaptic input currents and the evoked LFP and can serve as a foundation for modeling more realistic processing of active dendritic conductances.