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.

The Neuroscience Research Experience is designed to provide sophomore students with research experience in the labs of individual faculty members. NEU250 is intended to be a credit-bearing P/D/F course. Students will gain research experience in the laboratory of a faculty member in the Princeton Neuroscience Institute. Students are expected to work with their faculty mentor to develop a schedule that involves spending 10 hours per week engaged in research, including attending weekly research meetings and reading research papers. At the end of the semester, students will present their findings to the faculty member and research group.

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.

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.

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.

This course explores methods for recording and analyzing neural activity from populations of neurons at cellular resolution, and the scientific discoveries that such methods have enabled. Topics include methods for electrical and optical recording of large populations of neurons, as well as their application to studying neural dynamics underlying animal behavior. The course will survey seminal journal articles in the field and will provide students with hands-on practice analyzing real neural population recording datasets.

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.

Plasticity refers to the nervous system's ability to change its structure and function in response to intrinsic or extrinsic influences. Plasticity is necessary for healthy brain development and is an important player in brain damage and disease, as too little or too much can underlie the inability of the brain to effectively repair itself. This course will consider recent research into these topics exploring molecular, cellular and circuit-level mechanisms of synaptic and structural plasticity during development and adulthood, under conditions of health as well as damage and disease.

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.

This course explores the neural foundations of social cognition in natural contexts. Highly controlled lab experiments fail to capture and model the complexity of social interaction in the real world. Recent advances in artificial neural networks provide an alternative computational framework to model cognition in natural contexts. In contrast to the simplified and interpretable hypotheses we test in the lab, these models do not learn simple, human-interpretable rules or representations of the world.