This study presents a computational model of orientation selectivity in cat visual cortical simple cells, demonstrating that local intracortical excitation, rather than traditional models of intracortical inhibition or thalamocortical convergence, is the primary source of orientation selectivity. The model, based on a 1:4 scale representation of layer IV of cat primary visual cortex, shows that sharp orientation tuning arises from recurrent cortical excitation, even in the presence of strong iso-orientation inhibition and weak cross-orientation inhibition. The model reproduces experimental findings, including sharp orientation tuning that is independent of stimulus contrast and persists even when ON-type subfields are silenced. It also provides a unified explanation for conflicting experimental results regarding the role of inhibition in orientation selectivity, suggesting that intracortical inhibition acts nonspecifically and indirectly to maintain neuronal selectivity by balancing strong intracortical excitation at the columnar level. The model incorporates detailed simulations of retinal, lateral geniculate, and cortical circuits, including the generation of orientation selectivity through recurrent excitation and the effects of various inhibitory and excitatory inputs. It demonstrates that cortical excitation is the primary driver of sharp orientation tuning, with recurrent excitation amplifying weak thalamic orientation biases. The model also shows that orientation tuning is an emergent property of the cortical feedback circuitry, with sharp tuning resulting from the interaction between cortical excitation and inhibition. The model's results align with experimental findings, including the contrast-invariance of orientation tuning and the robustness of orientation selectivity despite weak thalamocortical inputs. The study highlights the importance of recurrent excitation in generating sharp orientation selectivity and provides a framework for understanding the neural mechanisms underlying visual cortical processing.This study presents a computational model of orientation selectivity in cat visual cortical simple cells, demonstrating that local intracortical excitation, rather than traditional models of intracortical inhibition or thalamocortical convergence, is the primary source of orientation selectivity. The model, based on a 1:4 scale representation of layer IV of cat primary visual cortex, shows that sharp orientation tuning arises from recurrent cortical excitation, even in the presence of strong iso-orientation inhibition and weak cross-orientation inhibition. The model reproduces experimental findings, including sharp orientation tuning that is independent of stimulus contrast and persists even when ON-type subfields are silenced. It also provides a unified explanation for conflicting experimental results regarding the role of inhibition in orientation selectivity, suggesting that intracortical inhibition acts nonspecifically and indirectly to maintain neuronal selectivity by balancing strong intracortical excitation at the columnar level. The model incorporates detailed simulations of retinal, lateral geniculate, and cortical circuits, including the generation of orientation selectivity through recurrent excitation and the effects of various inhibitory and excitatory inputs. It demonstrates that cortical excitation is the primary driver of sharp orientation tuning, with recurrent excitation amplifying weak thalamic orientation biases. The model also shows that orientation tuning is an emergent property of the cortical feedback circuitry, with sharp tuning resulting from the interaction between cortical excitation and inhibition. The model's results align with experimental findings, including the contrast-invariance of orientation tuning and the robustness of orientation selectivity despite weak thalamocortical inputs. The study highlights the importance of recurrent excitation in generating sharp orientation selectivity and provides a framework for understanding the neural mechanisms underlying visual cortical processing.