One main thread of my research uses fMRI and cortical-surface-based methods to map multiple visual, auditory, somatosensory, and motor areas in the human brain and to make high-resolution cross-subject average flat maps. The internal structure of these small cortical areas (typically only 1 cm wide) are uncovered through the use of phase-encoded methods for retinotopy, tonotopy, and somatotopy and cortical surface reconstruction methods my laboratory first introduced, refined, and distributed over a decade ago.
Recently, we have turned to investigate higher order maps such as the head-centred visual maps found in the multisensory ventral intraparietal area, VIP. A much larger proportion of the human cortex contains sensory and motor maps than was originally suspected. High resolution cross subject averaging is achieved by non-linear cortical-surface-based morphing driven by sulcal boundaries. This research is tightly integrated with earlier detailed microelectrode studies of retinotopic maps in non-human primates and other animals. I am also interested in the relationship between these sensory and motor maps and higher level cognition.
A major new direction in my laboratory has been to combine high-resolution mapping with cognitive experiments (e.g., on the comprehension of physical metaphors for time such as “the holidays are approaching”) in individual subjects to determine exactly how these small sensory and motor maps are deployed in different higher level cognitive tasks. In particular, I am interested in how these maps have been modified from those in non-human primates in order to support peculiarly human cognitive abilities like language. At a lower level of organization, I have studied how individual neurons code features of visual scenes in different visual areas using reverse-correlation methods and have computationally modeled how successive layers of more and more complex filters might be learned by example using Hebbian learning rules.
Finally, I have a long-standing interest in the architecture of natural and artificial symbol-using systems. This more philosophical project focusses on the architecture and origin of the two canonical naturally-occurring code-using systems: DNA for protein synthesis, and speech (or sign) streams for the peculiarly human comprehension of linguistic discourse. The code-using system in cells is better understood than language and can be used as an analogical source system for thinking about how the neural underpinnings of language might have evolved.
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