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Neurobiology of Cerebral Cortex (Psy 267)

Description: This course covers the fundamental neurobiology of the cerebral cortex. The topics include the evolution of the neocortex; its macro- and micro-architecture (cortical areas, sulci and gyri, minicolumns, cells); classic and novel approaches to cortico-cortical loops; and complex-systems approaches to the neocortex as a large-scale network.
Level: Graduate
Quaters: Spring 2016

Neuroanatomy (Psy 269)

Description: This course covers the functional neuroanatomy of the human central nervous system.
Level: Graduate
Quaters: Spring 2017

Diffuse Neurocellular Systems (Psy 163SJ/594SJ)

Description: This course focuses on the cellular and molecular neurobiology of brain systems that show little regional specificity. The topics include "diffuse" neurotransmitter systems, glial cells, neuroimmunology, and other related topics. The course does not cover cognitive processes, and a background in molecular neurobiology or neuropharmacology is assumed.
Level: Upper-division Undergraduate and Graduate
Quarters: Winter 2016; Fall 2016

Neurobiology of Brain States (Psy 166)

Description: This course covers the neurobiology of complex brain states in health and disease. The unifying theme of the course is the active, top-down construction of reality in the brain. The topics include the brain's large-scale networks, Bayesian approaches to brain function, full-body illusions, wakefulness and sleep, the neurobiology of music, hallucinogens, and associated neurological disorders.
Level: Upper-division Undergraduate
Quarters: Winter 2017; Fall 2017

Complex Systems in Brain Sciences (Psy 164)

Description: Neurobiology, psychology, and social sciences study systems that are inherently complex and can't be broken down into simple parts without losing the systems' key properties. A new science, complexity theory, has revealed that the structure and behavior of such systems are often based on surprisingly simple rules. Interestingly, the brain has no intuition for this hidden simplicity. By combining basic theory and hands-on modeling in Mathematica, this course builds a deeper understanding for these systems. While no prior programming experience is required, students are expected to develop coding skills as part of the course.
Level: Upper-division Undergraduate
Quarters: Fall 2015