Neurobiology and Behavior under Rich Stimulation

The primary goal of this conference is to bring together neuroscientists, psychologists, theorists and engineers who are seeking to understand the structure of natural signals and how biological systems encode and process these complex stimuli under natural conditions.

Why organize a conference around natural signals? Traditionally, neuroscientists and psychologists have used relatively simple, "controlled" stimuli -- sine-wave gratings, pure tones, spots, clicks, taps or periodic skin vibrations -- to probe the response properties of sensory neurons and characterize perceptual abilities. This approach has been fairly successful at elucidating information processing at early stages of sensory processing. But in the cerebral cortex, where processing is highly nonlinear and subject to recurrent computation in the form of feedback from other cortical neurons, this approach appears to be of limited utility. Neurons in the cortex are presumably encoding certain spatiotemporal patterns from the input stream, but it is difficult to discover these by simply probing one element at a time in some reduced space in the absence of context and behavior. It is reasonable, therefore, to turn to the sort of inputs that the system was designed to process. An interdisciplinary field that has emerged in recent years focuses on a set of interrelated questions: What are the forms of structure that tend to occur in the environment; how do we characterize these mathematically/statistically? How is this structure encoded and represented by neurons in the brain? How does the interaction of the organism with the environment shape and alter sensory encoding? How might sensory processing adjust to meet the needs of specific tasks? How can this understanding be used to enhance artificial stimuli or restore lost processing capability? Addressing these issues requires not only drawing upon the methods of neurophysiology, neuroethology and psychophysics, but also developing mathematical theories and building computational models. This field is highly interdisciplinary in nature and participants in this conference often combine several of these methodologies and cover a wide variety of biological systems.