Fig. 1.

Inference of thalamic input and V1 recurrent connectivity weights using in vivo extracellular recordings from mouse dLGN and V1 and a network model. (A) (Top) Neurons in area V1 integrate inputs from dLGN and V1 excitatory (E) and inhibitory (I) neurons. The dLGN input, together with the strengths of connections between neurons (green), determines the response of the V1 network. (Bottom) Contrast invariance of E and I V1 neurons means that the width of orientation responses is invariant with respect to contrast. (B) Contrast invariance in V1 allows contrast responses (Top Left) and orientation tuning (Bottom Left) to be treated separately. Due to contrast invariance, the two-population SSN model used for the contrast response analysis (Top Middle) can be embedded in the extended SSN model, which reproduces V1 responses as a function of stimulus contrast and orientation (Bottom Middle). The shape of the contrast responses determines the connectivity weights to the E and I V1 populations arising from dLGN inputs, and recurrent V1 E and V1 I connections (Top Right). The orientation component of the response contains information about the relative amounts of orientation-specific inputs to a population with a particular orientation preference (Bottom Right).