Feb. 17, 11:45, Wei Ji Ma. Optimality and Probabilistic Computation in Visual Categorization

Roles of attention and reward in perceptual learning

Takeo Watanabe, Boston University

 Perceptual learning (PL) is defined as a long-term performance improvement on a perceptual task as a result of perceptual experience and is regarded as a manifestation of plasticity in perceptual system (Yotsumoto, Watanabe & Sasaki, 2008, Neuron). In spite of the prevalence of PL research, how PL occurs has yet to be entirely clarified. We have conducted research concerning what determines PL. First, in spite of the prevailing dogma that PL occurs only for stimulus features to which voluntary attention is directed (task-relevant PL), we found that PL occurs for features that were task-irrelevant and subthreshold (Watanabe, Nanez & Sasaki, 2001, Nature; Watanabe et al, 2002, Nature Neuroscience) (task-irrelevant PL) and further that learning of those task-irrelevant features depends upon the subjects' engagement in the main task (Seitz & Watanabe, 2003, Nature; Seitz et al, 2005, Current Biology). Furthermore, we have found that pairing task-irrelevant features with rewards is key to task-irrelevant PL (Seitz, Kim & Watanabe, 2009, Neuron). These results suggest that PL occurs as a result of interactions between reinforcement signals and bottom-up stimulus signals (Seitz & Watanabe, 2005, TICS). At the same time, results of an fMRI study indicate that while the lateral prefrontal cortex (LPFC) detects and suppresses suprathreshold signals, it fails to detect and thus to suppress subthreshold signals.  This leads to the paradoxical effect that a signal that is below, but close to, one's discrimination threshold ends up being stronger than suprathreshold signals (Tsushima, Sasaki & Watanabe, 2006, Science).  We have confirmed this mechanism by showing that task-irrelevant learning occurs only when a presented feature is under and close to the threshold (Seitz, Tsushima & Watanabe, 2008, Current Biology). From all of these results, we have concluded that while attention enhances task-relevant feature signals and suppresses task-irrelevant feature signals, leading only to task-relevant PL, reinforcement signals enhance both task-relevant and task-irrelevant feature signals, leading to both task-relevant and task-irrelevant PL (Sasaki, Nanez & Watanabe, 2010, Nature Reviews Neuroscience).