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Courses taught at IIIT-D which draw partly from the group's research.

Course 1: Learning and Memory 

Course Code: PSY 306 / 506 

Semester offered: Winter

Course credits: Four (39 hours)

Course description & objectives: The course introduces the learners to the stages and mechanisms by which environmental information is learned; its flow from sensory receptors through sensory, short- term unto long- term memory, its storage and retrieval. Lectures and discussions draw from published scientific evidence mainly in the areas of behaviour, neuroimaging and neurophysiology to elucidate the organization and implementation of memory in the brain that influences various aspects of cognition. The course encourages the learners to develop analytical thinking based on analyses and understanding of experimental data towards building capacity for original ideation in this area of cognitive science . By the end, the course aims that the learners are able to...

 

  • describe historical antecedents, methods of cognitive science for studying learning and memory.

  • classify types of conditioning, learning, memory and explain their basic mechanisms.

  • deconstruct data from cognitive science experiments /studies in learning and memory to justify their results.

  • generate and articulate one experimentally testable idea in learning and memory

     Course 2: Neuroscience of Decision Making 

Course Code: PSY 307 / 507 

Semester offered: Monsoon

Course credits: Four (39 hours)

Course description & objectives: The course introduces how perception, goals, preferences, motivation of living systems guide their selection of actions and thoughts from several possible options. The course attempts at building a mechanistic understanding of the processes in the brain that support decision making and how they are flexibly updated in a dynamically changing environment. Sessions discuss relevant scientific & historical background, salient theoretical models and experimental evidence in various aspects of decision-making. An additional component involve computational analyses of experimental datasets in this field to draw inferences about brain and behaviour. The primary effort is to make neural mechanisms accessible to the learners, expose them to possible applications and encourage them to find their own avenues of interest for translating the core principles of decision neuroscience. Learners by the end of the course are expected to...

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  • describe the basic neural structures involved in decision making and their functions.

  • explain the different methods of investigating neural decision making and the rationale behind choosing the methods.

  • explain the neural basis of the salient models and concepts of decision making with the help of data from brain and behaviour.

  • utilize the aforementioned concepts to generate and articulate one experimentally testable idea in decision neuroscience.

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