Abstract
Previous research examining perceptual expertise shows that experience alters sensory processing, including in visual cortical areas. There is also evidence that neural processing of non-face objects of expertise interferes with the processing of faces in experts (Gauthier & Curby, 2005). However, the emergence of visuo-cortical competition during early object learning has not yet been examined. The present investigations used steady state visual evoked potential (ssVEP) frequency tagging while adults (n= 24) viewed novel objects superimposed with human faces before and after a brief expertise training period. Faces served as comparison stimuli, given their ability to engage expertise-related brain regions without training. The novel objects were generated to represent exemplars of two species, based on distinctive physical characteristics. In the training phase, participants learned to distinguish exemplars of Species 1 from exemplars of Species 2. They also completed a forced choice gender discrimination task for the faces, to keep exposure to faces and objects comparable. During the pre- and post-training phases, pictures of human faces and pictures of novel objects were periodically and rapidly turned on and off at unique temporal rates (5/sec or 6/sec) against a Brownian noise background. Competition between the overlapping stimuli was quantified in the EEG frequency domain before and after training. ssVEP data were projected to a distributed source space using an L2 (minimum) norm estimation with Tikhonov-philips regularization (lambda = 0.01), and competition between faces and objects compared (before vs after training) using permutation-controlled mass univariate t-tests. Results showed that after a short expertise training period, trained objects attained a competitive advantage over faces, selectively in left and right occipitotemporal cortex, and in prefrontal cortical areas. These findings show task-relevant modulation of visuo-cortical regions during learning and suggest that neural processing of faces and objects are not functionally independent and are flexibly modulated during learning.