Perceptual Learning Of Object Shape

Recognition of objects is accomplished through the use of cues that depend on internal representations of familiar shapes. We used a paradigm of perceptual learning during visual search to explore what features human observers use to identify objects. Human subjects were trained to search for a target object embedded in an array of distractors, until their performance improved from chance levels to over 80% of trials in an object specific manner. We determined the role of specific object components in the recognition of the object as a whole by measuring the transfer of learning from the trained object to other objects sharing components with it. Depending on the geometric relationship of the trained object with untrained objects, transfer to untrained objects was observed. Novel objects that shared a component with the trained object were identified at much higher levels than those that did not, and this could be used as an indicator of which features of the object were important for recognition. Training on an object transferred to the less complex components of the object when these components were embedded in an array of distractors of similar complexity. There was transfer to the different components of object, regardless of how well they distinguish the object from distractors. These results suggest that objects are not represented in a holistic manner during learning, but that their individual components are encoded. Transfer between objects was not complete, and occurred for more than one component, suggesting that a joint involvement of multiple components was necessary for full performance. The sequence of this learning indicated a possible underlying mechanism of the learning. Subjects improved first in a single quadrant of the visual field, and the improvement then spread out sequentially to the other quadrants. This location specificity of the improvement suggests that, with training, encoding information about object shape occurs in early, retinotopically mapped cortical areas. fMRI work suggests that the learning of novel objects in this manner involves a reciprocal switch between two cortical networks, one that involves the normally object-sensitive regions of LOC, and one that involves the temporal and parietal cortices