A major challenge in studying mammalian brain functions is to understand how information is encoded in the electrical activity of neurons. The current project aims to understand processing of visual information with a combination of experimental and computational approaches. Novel features of this project include the use of multielectrode recording of neural activity and natural scenes as visual inputs. Several computational analyses will be carried out concurrently with the physiological experiments to address information coding in the early visual pathway. In the first part of the project, the investigators will use several decoding techniques to reconstruct natural scenes from recorded ensemble neural responses. These decoding studies will provide a critical test of various computational models of visual coding. Because of the relatively simple response properties of their visual neurons, the decoding study will first be carried out in the visual thalamus. To understand the mechanisms of visual coding, it is also crucial to understand what features of visual inputs are encoded at different stages of the visual pathway. Therefore in the second part of the project, the investigators will systematically characterize the features of visual inputs that are represented by the responses of primary visual cortical neurons. Such studies may reveal nonlinear coding properties of cortical neurons that have eluded earlier analyses. Taken together, the results from the proposed studies are likely to provide new insights into the general principles of sensory coding. Successful implementation of these research plans will also create an exciting environment for encouraging early involvement of undergraduate students into basic research, for in depth training of graduate students in neuroscience, and for preparing postdoctoral fellows for an independent research career.
