high-risk research on hard problems in natural and artificial systems:

  • the constraints necessary to "build" a visual system

  • better articulated models of the intermediate and high-level vision

  • the organizational princples of visual cortex

  • how vision interacts with other modalities

tools drawn from cognitive science, machine learning, computer vision, computer graphics, and large-scale neuroimaging, including fMRI, DTI, MEG, EEG

My own (crazy) thoughts about some of our recent work: The organization of knowledge within visual cortex may be best characterized as a multimodal "operating system" for learning about, representing, and processing information relevant to adaptive behaviors. Alternatively, one might argue that this organization necessarily reflects and emerges from common adaptive behaviors of humans (e.g., food selectivity emerges because humans eat frequently and so on...). However, the consistency of organization for these functional structures across individuals suggests otherwise; instead, pointing towards a core set of constraints that enable a specific higher-order knowledge structure that is inherently anchored in real-world behaviors. Exploring these ideas further will require new ways of thinking about visual cortex.