The properties of stimulus categorization exhibited by neurons in the owl OTid account well for behavioral deficits in monkeys following the inactivation of the intermediate and deep layers of the superior colliculus (Lovejoy and Krauzlis, 2010, McPeek and Keller, 2004 and Nummela and Krauzlis, 2010). In monkeys performing stimulus selection tasks, focal inactivation of the portion of the superior colliculus representing the target stimulus causes an impairment in their ability to select
an oddball target or a spatially cued target among distracters, an impairment that increases dramatically as the distracting stimuli become more similar to the target stimulus. These studies indicate that the midbrain network performs computations that are essential for reliable find more competitive stimulus selection, especially
when competing stimuli are of similar strength. A neural computation that is fundamental to stimulus competition in the OTid is the suppression of responses to an RF stimulus by stimuli located outside the RF. Such “surround suppression” is observed in many brain areas across many species (Allman et al., 1985). Unlike interactions that occur among stimuli within the RF (such as crossorientation suppression in the visual cortex; Freeman et al., 2002), surround suppression is thought to be mediated by lateral inhibition and, often, by feedforward lateral inhibition (Blakemore and Tobin, 1972, Bolzon et al., 2009, Cisek and Kalaska, 2010, Hartline et al., 1956, Kuffler, 1953, Olsen et al., 2010 and Yang and Wu, 1991). click here Anatomical evidence from the avian midbrain network supports lateral inhibition as underlying global suppression in the OTid as well (Figure 1; Wang et al., 2004). Specifically, a
midbrain GABAergic nucleus, the nucleus isthmi pars magnocellularis (Imc), receives focal input from neurons with dendrites in the retinorecipient layers of the optic tectum and sends broad projections to neurons in the multimodal and motor layers of the optic tectum, the OTid. Through the use of this basic feedforward lateral inhibitory circuit as a starting point, we employ a first principles approach to address enough neural computations that underlie flexible categorization in the OTid. We show that feedforward lateral inhibition, a circuit motif at the heart of most models of selection for attention or action (Cisek and Kalaska, 2010 and Lee et al., 1999), cannot account for categorization that is flexible. However, a simple modification—introducing reciprocal inhibition between feedforward lateral inhibitory channels—successfully achieves flexible categorization. The key additional computation that achieves adaptive boundary flexibility in categorization is lateral inhibition that is dependent on relative stimulus strength.