Online courses directory (423)
What makes living things tick?. Homeostasis. A Voyage to Mars: Bone Loss in Space. Bread Mold Kills Bacteria.
This course provides an introduction to the chemistry of biological, inorganic, and organic molecules. The emphasis is o
Provides a comprehensive introduction to key issues and findings in object recognition in experimental, neural, computational, and applied domains. Emphasizes the problem of representation, exploring the issue of how 3-D objects should be encoded so as to efficiently recognize them from 2-D images. Second half focuses on face recognition, an ecologically important instance of the general object recognition problem. Describes experimental studies of human face recognition performance and recent attempts to mimic this ability in artificial computational systems.
Parkinson's disease (PD) is a chronic, progressive, degenerative disease of the brain that produces movement disorders and deficits in executive functions, working memory, visuospatial functions, and internal control of attention. It is named after James Parkinson (1755-1824), the English neurologist who described the first case.
This six-week summer workshop explored different aspects of PD, including clinical characteristics, structural neuroimaging, neuropathology, genetics, and cognitive function (mental status, cognitive control processes, working memory, and long-term declarative memory). The workshop did not take up the topics of motor control, nondeclarative memory, or treatment.
Probability theory captures a number of essential characteristics of human cognition, including aspects of perception, reasoning, belief revision, and learning. Expressions of degree of belief were used in language long before people began codifying the laws of probability theory. This course explores the history and debates over codifying the laws of probability, how probability theory applies to specific cognitive processes, how it relates to the human understanding of causality, and how new computational approaches to causal modeling provide a framework for understanding human probabilistic reasoning.
This class is suitable for advanced undergraduates or graduate students specializing in cognitive science, artificial intelligence, and related fields.
This course covers central topics in language processing, including: the structure of language; sentence, discourse, and morphological processing; storage and access of words in the mental dictionary; speech processing; the relationship between the computational resources available in working memory and the language processing mechanism; and ambiguity resolution. The course also considers computational modeling, including connectionist models; the relationship between language and thought; and issues in language acquisition including critical period phenomena, the acquisition of speech, and the acquisition of words. Experimental methodologies such as self-paced reading, eye-tracking, cross-modal priming, and neural imaging methods are also examined.
This series of research talks by members of the Department of Brain and Cognitive Sciences introduces students to different approaches to the study of the brain and mind.
Topics include:
- From Neurons to Neural Networks
- Prefrontal Cortex and the Neural Basis of Cognitive Control
- Hippocampal Memory Formation and the Role of Sleep
- The Formation of Internal Modes for Learning Motor Skills
- Look and See: How the Brain Selects Objects and Directs the Eyes
- How the Brain Wires Itself
