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Abstract:
A fundamental challenge in neuroscience is to understand the cellular and circuit mechanisms underlying the receptive fields of neurons in sensory cortices. Despite
steady progress in the analysis of cortical circuits, current models cannot explain the origin of broad receptive fields in L5 thick-tufted pyramidal neurons (L5tt), a major
cortical output cell type. We therefore developed a reverse-engineering approach to create anatomically and functionally realistic models of neurons in rat vibrissal cortex (vS1). Based on in vivo receptive field measurements, 3D reconstruction of neuron morphologies, and integration of neurons into an average model of the circuitry of vS1, we constrained simulations to reveal the source of broad receptive fields of L5tt. First, recorded and reconstructed neurons were registered to their location in an average model of vS1 and we determined the number and subcellular distribution of thalamocortical and
intracortical synaptic inputs to each neuron. Next, neurons were turned into biophysically detailed compartmental models. Finally, we activated presynaptic neurons based on spike probabilities measured in vivo. Without optimization of the experimentally constrained parameters, the simulated spiking responses of these models to biologically realistic
spatiotemporal synaptic input patterns after touch of the principal whisker (PW) or different surround whiskers (SuW) matched in vivo measurements. We found that the response of L5tt is composed of two phases. The first phase is driven by input from thalamus and L6 (PW deflection) or solely by L6 (SuW deflection), while the second phase reflects recurrent intracortical activity. This new model of the spread of sensory-evoked excitation in cortex explains previous contradicting observations and suggests cell type-specific computations in cortical circuits. For example, L6 neurons may act as differential input detectors, while L5tt integrate sensory input across time
and space.
