A central problem in Neuroscience is understanding how the neocortical microcircuit encodes stimuli for perceptual decisions. Theoretical models of cortical networks are mathematically convenient tools that have produced deep insights into cortical computation principles. Yet, their lack of realism does not allow to fully probe the role of the cortex’ biological diversity in shaping sensory representations for perceptual discrimination. We addressed these questions using an extensively validated biophysically detailed model of the rat’s S1 neocortical column. The model comprises 30,190 morphologically detailed neurons, spanning all six cortical layers and receiving inputs from simulated thalamic fibers. It captures the biological diversity in 60 morphological and 11 electrical neuron types and features realistic synaptic connectivity and short-term plasticity. We simulated the microcircuit’s responses to whisker deflections in 360 orientations, by injecting currents into distinct groups of thalamic fibers. We then linked individual neuron’s orientation tuning to the geometry and discrimination capacity of the evoked neural manifold. We found that neurons contribute differently to discrimination capacity based on type and layer.