  Mechanisms underlying the emergence of orientation selectivity in the primary
visual cortex are highly debated. Here we study the contribution of
inhibition-dominated random recurrent networks to orientation selectivity, and
more generally to sensory processing. By simulating and analyzing large-scale
networks of spiking neurons, we investigate tuning amplification and contrast
invariance of orientation selectivity in these networks. In particular, we show
how selective attenuation of the common mode and amplification of the
modulation component take place in these networks. Selective attenuation of the
baseline, which is governed by the exceptional eigenvalue of the connectivity
matrix, removes the unspecific, redundant signal component and ensures the
invariance of selectivity across different contrasts. Selective amplification
of modulation, which is governed by the operating regime of the network and
depends on the strength of coupling, amplifies the informative signal component
and thus increases the signal-to-noise ratio. Here, we perform a mean-field
analysis which accounts for this process.
