One large group of faculty and students focus their research on understanding the organization and function of the visual system. Members of this group use a range of perceptual, physiological, anatomical, and computational methods to investigate the optics of the eye, signal processing in the retina and at higher levels in the visual pathway, and the mechanisms underlying the perception of color, motion, shape, and other attributes of visual images. Many investigators also study the integration of visual perception with memory and motor organization.
The Center for Visual Science, an interdisciplinary research unit to which many faculty, fellows, and students in the department belong, provides the focus for research on vision, drawing us together with scientists from the departments of Computer Science, Ophthalmology, Neurobiology and Anatomy, Neurology, and the Institute of Optics.
Brain and cognitive sciences (BCS) faculty and students study the nature of the neural, cognitive and computational systems underlying language processing and acquisition. We study how infants acquire the speech sounds, words, and structures of their native language(s), how these skills develop throughout childhood, and how adults learn new languages.
Students and postdocs in our language labs also investigate how we produce and understand spoken and written language. We ask to what extent and why languages across the world share certain properties.
Our study of the processes underlying our ability to use language involves flexible combinations of behavioral, computational, brain imaging, neuropsychological, and neurobiological methods, applied to the study of both healthy adults and those with developmental or other brain disorders. Our research also connects human language processing to neurobiological systems involved in communication and symbolic representation in both humans and animals.
The study of learning and plasticity during development cuts across domains and links those who study perception, language, and neurobiology. Faculty and students working on a variety of different systems share an interest in the mechanisms that underlie learning and plasticity, and explore these mechanisms using behavioral, computational, and neuroscientific methods.
The research ranges from investigating the development of perception and language in human infants and adults, and the acquisition of bird song in finches and sparrows, to the measurement and modeling of the neural and computational mechanisms that underlie developmental plasticity, Hebbian learning, and critical periods in the development of the brain and behavior.
Researchers in BCS explore the cognitive and neural basis of concepts and categories in order to understand the structure of information in the domains of object form and function, space and time, number and logic, action, speech, music, and semantics.
Research in this area investigates the primitive basis of conceptual representations in human infants and non-human animals, conceptual changes during child development, language-based conceptual representations in human adults, action-based representations of objects and tools, distortions in conceptual knowledge due to brain damage, and gains in conceptual processing that can be achieved by cognitive training.
BCS faculty and students explore fundamental questions regarding how the brain combines multiple sources of sensory input with prior knowledge and internal cognitive states, in order to make simple decisions. We examine how attention, working memory, and executive control processes modulate the flow of information that leads to decisions in both humans and animals. We also explore how judgments of reward and value modulate decision-making processes, and how normal functioning of these operations may be compromised in the context of drug addiction or obsessive-compulsive disorders.
Developmental studies seek to understand the information-seeking strategies of children that facilitate learning. Computational and theoretical work places an emphasis on establishing optimal or rational strategies for implementing statistical inference, and seeks to make testable predictions regarding neural correlates of decision making and top-down control.