Non-linearity of spatial integration varies across layers of primary visual cortex

The receptive field (RF) of visual cortical neurons is highly dynamic and context-dependent, shaped by both the spatial and temporal properties of stimuli and the complex architecture of cortical circuits. While classical RF mapping through extracellular recordings reveals only the area triggering spiking responses, intracellular recordings reveal a much broader region of subthreshold synaptic input. We investigated how neurons in different cortical layers integrate visual input across space, with a focus on the linearity of spatial summation. Using intracellular recordings, we found that supragranular complex cells integrate input in a highly sublinear manner, in contrast to infragranular complex cells and simple cells, which exhibited near-linear summation. To understand the underlying mechanisms, we employed a large-scale recurrent spiking model of cat primary visual cortex (V1). Modeling results point to the differential patterning of long-range horizontal connections--particularly their targeting of excitatory versus inhibitory neurons--as a potential source of the observed layer-specific integration properties. These findings suggest that RFs emerge from interaction of feedforward, horizontal, and possibly feedback inputs, that are continuous in space, challenging the conventional notions of fixed spatial RF boundaries in early visual processing. O_LIThe properties of receptive fields (RF) of neurons in the primary visual cortex (V1) are not static but change depending on spatiotemporal properties of visual stimulus. C_LIO_LITo study spatial integration of visual information by V1 neurons in a RF independent way, we made intracellular recordings across the cat V1 in response to drifting gratings confined to either circular apertures of variable diameters (disks), or in annuli with fixed outer diameters and variable inner diameters (rings). C_LIO_LIWe find that supragranular complex cells integrate input in a sublinear manner, whereas infragranular complex cells and simple cells exhibit near-linear summation. C_LIO_LIOur large-scale recurrent spiking model shows that these differences between supragranular and infragranular complex cells can be explained by laminar differences in horizontal connectivity properties. C_LIO_LIThese results highlight the substantial differences in spatial integration of visual information at different stages of visual processing C_LI