Second half of intensive survey of brain and behavioral studies for first-year graduate students. Topics include: perception, attention, working memory, recognition and recall, categorization, language, and thought. Topics covered from behavioral, computational, and neural perspectives.
This class is the second half of an intensive survey of cognitive science for first-year graduate students. Topics include visual perception, language, memory, cognitive architecture, learning, reasoning, decision-making, and cognitive development. Topics covered are from behavioral, computational, and neural perspectives.
An introduction to human information processing and learning; topics include the nature of mental representation and processing; the architecture of memory; pattern recognition; attention; imagery and mental codes; concepts and prototypes; reasoning and problem solving.
This course will introduce you to cognitive psychology. Memory, along with attention, perception, language, and decision making, are among the most prominent topics within this broad and diverse field. Upon successful completion of this course, students will be able to: Identify underlying theoretical considerations in the field of cognitive psychology; Describe the historical context in which cognitive psychology emerged as a field; Define cognitive psychology as is was historically defined and is now defined; Identify the main academic fields and other subdisciplines of psychology to which cognitive psychology is tied; Describe the main findings in the primary areas of scientific research within cognitive psychology; Compare and contrast the theories associated within the primary areas of scientific research in cognitive psychology (e.g., models of memory, attention, etc.). (Psychology 206)
Principles of supervisory control and telerobotics. Different levels of automation are discussed, as well as the allocation of roles and authority between humans and machines. Human-vehicle interface design in highly automated systems. Decision aiding. Tradeoffs between human control and human monitoring. Automated alerting systems and human intervention in automatic operation. Enhanced human interface technologies such as virtual presence. Performance, optimization, and social implications of the human-automation system. Examples from aerospace, ground, and undersea vehicles, robotics, and industrial systems. Human Supervisory Control of Automated Systems discusses elements of the interactions between humans and machines. These elements include: assignment of roles and authority; tradeoffs between human control and human monitoring; and human intervention in automatic processes. Further topics comprise: performance, optimization and social implications of the system; enhanced human interfaces; decision aiding; and automated alterting systems. Topics refer to applications in aerospace, industrial and transportation systems.
This course explores the social relevance of neuroscience, considering how emerging areas of brain research at once reflect and reshape social attitudes and agendas. Topics include brain imaging and popular media; neuroscience of empathy, trust, and moral reasoning; new fields of neuroeconomics and neuromarketing; ethical implications of neurotechnologies such as cognitive enhancement pharmaceuticals; neuroscience in the courtroom; and neuroscientific recasting of social problems such as addiction and violence. Guest lectures by neuroscientists, class discussion, and weekly readings in neuroscience, popular media, and science studies.
What are the circuits, mechanisms and representations that permit the recognition of a visual scene from just one glance? In this one-day seminar on Scene Understanding, speakers from a variety of disciplines -- neurophysiology, cognitive neuroscience, visual cognition, computational neuroscience and computer vision -- will address a range of topics related to scene recognition, including natural image categorization, contextual effects on object recognition, and the role of attention in scene understanding and visual art. The goal is to encourage exchanges between researchers of all fields of brain sciences in the burgeoning field of scene understanding.
" Our conjoint participation in the 9.70 learning system places us in a consensually-shared social situation. (All of the foregoing words are important. Do you understand their meaning in this context?) We will endeavor to organize ourselves into a community of discourse that approximates (albeit in an altogether partial way) a meaningful, real-world research enterprise: Like all scientific communities, we will work with limited resources. Unlike "real" scientific communities, ours will operate under the constraint of predetermined project duration and contractually agreed-upon limits in the amount of time and effort to be contributed to it by the individual participants. Toward this end, we randomly divide the membership of the class – at the outset — into subsystems – study groups — intended to operate interdependently with others while each remains together as a stable subsystem for the duration of the term, unless or until the participants determine otherwise. This approach creates a "level playing field." The coursework will provide everyone with first hand opportunities to experience and to exchange ideas about what it means to scientifically investigate (experimentally/experientially) the subject before us on individual, small group and large group levels."
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