In ferret visual cortex, spontaneous activity before eye-opening is organised into large-scale, modular patterns in the absence of long-range projections. This correlated activity reveals endogenous networks that predict aspects of future orientation selectivity. Previous modelling works have shown that the long-range correlations observed in these networks can arise from locally connected neurons through multi-synaptic interactions. Here we seek to map the structure of cortical lateral interactions through localised perturbations in vivo.We first constructed a rectified recurrent neural network model of strongly coupled excitatory and inhibitory units with effective local heterogeneous Mexican hat connections, finding that perturbing a small region of inhibitory neurons exerts a spatially extended influence on the activity pattern. Notably, the strength of influence depends on stimulation location, and can be predicted from stimulation site’s overlap with the leading spontaneous principal components.To test these predictions, we virally expressed GCaMP6s in excitatory neurons and Chrimson-ST in inhibitory neurons in layer 2/3 of young ferret V1, allowing us to optogenetically activate small regions of inhibitory neurons and simultaneously record widefield calcium activity. In line with model predictions, local optogenetic inhibitory perturbations propagate through the entire network and induce a reorganisation of activity far away from stimulation sites. The degree of disruption can be predicted, and the perturbed activity space only partially overlaps with spontaneous activity space, suggesting a different activity manifold with local disruption.Our results are consistent with the presence of strongly coupled networks in early cortex, and demonstrate that network behaviour is an emergent property.