How do genes and neural circuits encode behavior? How have genes and circuits evolved to generate the incredible diversity of behaviors we see across the animal kingdom? This course will explore these questions with emphasis on recent advances in the primary literature. Each class will focus on a specific behavior with a lecture introducing what is known about its genetic and neural basis followed by a discussion of a paper that builds on that knowledge to examine how the behavior evolves. A major goal of the class will be to learn how to critique contemporary research, generate new hypotheses, and design experiments to test those hypotheses.

Cognitive neuroscience is a young and exciting field with many questions yet to be answered. This course surveys current knowledge about the neural basis of perception, cognition and action and will comprehensively cover topics such as high-level vision, attention, memory, language, decision making, as well as their typical and atypical development. Precepts will discuss the assigned research articles, pertaining to topics covered in class with an emphasis on developing critical reading skills of scientific literature.

This course is designed to introduce undergraduate students to modern methods of analysis applied to the activity of single neurons, the synaptic connections between neurons, and the dynamics of networks of neurons underlying learning and decision making. The course will include methods for intracellular and extracellular recording of neural activity, the application of optogenetic approaches to analysis of neuronal function, and noninvasive measurement of human cognitive information processing using EEG and fMRI.

Stress has been linked to a wide range of physical and mental illnesses, yet stress is part of everyday life and most organisms respond to challenges with adaptation and recovery. This course will consider both foundational and contemporary research regarding stress effects on the body and brain with the goal of gaining an understanding of the mechanisms of both resilience to stress and stress-induced pathology. The course will be divided into three modules, each covering basic themes in stress research.

The brain is made up of billions of neurons, each sending and receiving signals from thousands of other neurons. This densely connected network of neurons gives rise to rich spatial and temporal dynamics. This course will investigate these dynamics. The course will present experimental results from systems-level neuroscience and then discuss the theoretical implications of these findings, particularly as they relate to higher-order, cognitive behaviors.

Introduction to a mathematical description of how networks of neurons can represent information and compute with it. Course will survey computational modeling and data analysis methods for neuroscience. Example topics are short-term memory and decision-making, population coding, modeling behavioral and neural data, and reinforcement learning. Classes will be a mix of lectures from the professor, and presentations of research papers by the students. Two 90 minute lectures, one laboratory. Lectures in common between NEU 437/NEU 537.

The basal ganglia is an interconnected set of brain regions involved in a wide range of essential functions, including reward-based learning, action selection and motor control. These circuits are also implicated in a wide range of neuropsychiatric diseases, including addiction and Parkinson's. How do these circuits contribute to this array of healthy and diseased functions? In this seminar, we will read and analyze modern systems and circuits neuroscience papers to address these questions.

Computers now exceed humans in many complex, real-world tasks. However, humans remain unique in the range of tasks they can perform, and the ability to generalize their knowledge to new ones. This course will consider the components and characteristics of a computational architecture needed to achieve these capabilities. Topics will span work in cognitive, brain, and computer science. Students will come away with a broad view of how these fields are informing each other, and how together they are beginning to provide an outline of the computational architecture responsible for the (still) uniquely human form of intelligence.

A survey of modern neuroscience that covers experimental and theoretical approaches to understanding how the brain works. This semester builds on 501, focusing on how the circuits and systems of the brain give rise to cognition. The course covers the neural mechanisms responsible for vision, long-term memory, sleep, motor control, habits, decision making, attention, working memory, and cognitive control. How these functions are disrupted in neurodegenerative and neuropsychiatric disorders are also covered. This is the second term of a double-credit core lecture course required of all Neuroscience Ph.D. students.

This lab course introduces students to the variety of experimental and computational techniques and concepts used in modern cognitive neuroscience. Topics include functional magnetic resonance imaging, scalp electrophysiological recording, and computational modeling. In-lab lectures provide students with the background necessary to understand the scientific content of the labs, but the emphasis is on the labs themselves, including student-designed experiments using these techniques. This is the second term of a double-credit core lab course required of all Neuroscience Ph.D. students.

Advanced seminar that reflects current research on brain and behavior.

Introduction to a mathematical description of how networks of neurons can represent information and compute with it. Course surveys computational modeling and data analysis methods for neuroscience. Example topics are short-term memory and decision-making, population coding, modeling behavioral and neural data, and reinforcement learning. Classes are a mix of lectures from the professor, and presentations of research papers by the students. Two 90 minute lectures, one laboratory. Lectures in common between NEU 437/NEU 537. Graduate students carry out a semester-long project.

This course explores the neural foundations of social cognition and social emotions. The objective is to provide a comprehensive overview of research topics relevant to the emerging field of social neuroscience. We will also discuss questions that cut across the specific topics that will be covered. Do neural systems exist that are specialized for social cognition or do the systems that participate in social cognition have more general cognitive functions? Can neuroscientific research shed new light on social cognition? How can different disciplines in neuroscience and the social sciences contribute to social neuroscience research?

We will take a modern, integrative view of animal learning phenomena from experimental psychology, analyzing them through the lens of computational models of reinforcement learning and current neuroscientific knowledge. The goal is to explore how theoretical concepts apply to every-day attempts to change people's minds, and how computational modeling is a useful framework for understanding human behavior. To maximize learning and skill acquisition, the course will include group work and class presentations, and will follow the 'teaching without grades' method, primarily motivated by progress towards your own goals, rather than by grades.

Decision-making is ubiquitous to everyday life and crucial to survival. Good choice is subject to evolutionary selection; poor choice accompanies many neurological and psychiatric disorders. But theoretical understanding of a function is needed to manipulate and measure it experimentally. Recently, this has led scientists studying choice to seek insights from economics. This course explores how humans and animals make decisions, focusing on how psychological and neural mechanisms implement, or fail to implement, economic theories of choice. We consider choice in many sorts of tasks; eg, in animal foraging and human competitive interactions.

This course will provide an introduction to the scientific study of sensation and perception, the biological and psychological processes by which we perceive and interpret the world around us. We will undertake a detailed study of the major senses (vision, audition, touch, smell, taste), using insights from a variety of disciplines (philosophy, physics, computer science, neuroscience, psychology) to examine how these senses work and why. We will begin with physical bases for perceptual information (e.g., light, sound waves) and proceed to an investigation of the structures, circuits, and mechanisms by which the brain forms sensory percepts.