Neuroscience

Acquaints non-science majors with classical and modern neuroscience. Lectures will give an overview at levels ranging from molecular signaling to cognitive science with a focus on the neuroscience of everyday life, from the general (love, memory, and personality) to the particular (jet lag, autism, and weight loss). The laboratory will offer hands-on experience in recording signals from single neurons, examining neural structures, and analysis of whole-brain functional brain imaging data. Two 90-minute lectures, one laboratory.

This is a survey course in neurobiology which takes a mechanistic and reductionist perspective to cover important topics in the field, including the physiological basis of neural excitability, sensory and motor processing, learning and memory, and neuropsychiatric diseases.

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. Two 90-minute lectures, one precept

This course is an integrative treatment of memory in humans and animals. We explore working memory (our ability to actively maintain thoughts in the face of distraction), episodic memory (our ability to remember previously experienced events), and semantic memory (our ability to learn and remember the meanings of stimuli). In studying how the brain gives rise to different kinds of memory, we consider evidence from behavioral experiments, neuroscientific experiments (neuroimaging, electrophysiology, and lesion studies), and computational models. Two lectures, one preceptorial. Prerequisite: 255 or 259, or instructor's permission.

A fundamental goal of cognitive neuroscience is to understand how psychological functions such as attention, memory, language, and decision making arise from computations performed by assemblies of neurons in the brain. This course will provide an introduction to the use of connectionist models (also known as neural network or parallel distributed processing models) as a tool for exploring how psychological functions are implemented in the brain, and how they go awry in patients with brain damage. Prerequisite: instructor's permission. Two 90-minute lectures, one laboratory.

A survey of the unique behaviors of different animal species and how they are mediated by specialized brain circuits. Topics include, for example, monogamy in voles, face recognition in primates, sex- and role-change in fish, and predation by bats. The role of evolutionary and developmental constraints on neural circuit construction will be a key underlying theme. Prerequisites: 258 or 259. One three-hour seminar.

A survey of fundamental principles in neurobiology at the biophysical, cellular, and system levels. Lectures will address the basis of the action potential, synaptic transmission and plasticity, local circuit computation, sensory physiology, and motor control. Prerequisites: MOL 214 or MOL 215, PSY 258, PHY 103-104, and MAT 103-104, or permission of instructor. Two 90-minute lectures, one preceptorial.

This course focuses on clinical depression as a model topic for scientific discourse. Depression is a subject of growing individual and societal importance, and it is an ideal topic because it intersects such a broad range of issues. Our work will emphasize a neurobiological approach, with topics ranging from the molecular to the clinical. Prerequisites: 208 or 258, or EEB 211, or MOL 214, and instructor's permission. One three-hour seminar.

Introduction to the biophysics of nerve cells and synapses, and the mathematics of neural networks. How can networks of neurons compute? How do we model and analyze data from neuroscientific experiments? Data from experiments running at Princeton will be used as examples (e.g., blowfly visual system, hippocampal slice, rodent prefrontal cortex). Each topic will have a lecture and a computer laboratory component. Prerequisite: MOL 410, or elementary knowledge of linear algebra, differential equations, probability, and basic programming ability, or permission of the instructor. Two 90 minute lectures, one laboratory.

In this course, we will explore the diverse and complex interactions between the brain and the immune system from the perspective of current, cutting-edge research papers. In particular, we will focus on the molecular mechanisms of these interactions and their role in brain development and function as well as their potential contributions to specific neurological disorders, including autism. In the process, students will learn to read, critically evaluate, and explain in presentations the content of articles from the primary literature. Prerequisites: MOL 214/215.

A survey of modern neuroscience in lecture format combining theoretical and computational/quantitative approaches. Topics include cellular neurophysiology, neuroanatomy, neural circuits and dynamics, neural development and plasticity, sensory systems, genetic model systems, and molecular neuroscience. This is one-half of a double-credit core course required of all Neuroscience Ph.D. students.

This lab course complements NEU 501A and introduces students to the variety of techniques and concepts used in modern neuroscience, from the point of view of experimental and computational/quantitative approaches. Topics will include synaptic transmission, fluorescent and viral tracers, patch clamp recording in brain slices, optogenetic methods to control neural activity, and computational modeling approaches. In-lab lectures give students the background necessary to understand the scientific content of the labs, but the emphasis is on the labs themselves. Second half of a double-credit core course required of all NEU Ph.D. students.

A survey of modern neuroscience in lecture format combining theoretical and computational/quantitative approaches. Topics include systems and cognitive neuroscience, perception and attention, learning and behavior, memory, executive function/decision-making, motor control and sequential actions. Diseases of the nervous system are considered. This is one-half of a double-credit core course required of all Neuroscience Ph.D. students.

This lab course complements NEU 502A and introduces students to the variety of techniques and concepts used in modern neuroscience, from the point of view of experimental and computational/quantitative approaches. Topics include electrophysiological recording, functional magnetic resonance imaging, psychophysics, and computational modeling. In-lab lectures give students the background necessary to understand the scientific content of the labs, but the emphasis is on the labs themselves. Second half of a double-credit core course required of all Neuroscience Ph.D. students.

How do seemingly simple organisms generate complex behaviors? Course will explore our current understanding of the genetic and neural basis for animal behavior, with an emphasis on cutting-edge research and model systems that are amenable to genetic manipulation. Each week students will discuss a new behavior with a focus on the underlying mechanisms; students will also lead discussions of primary literature. The goal of this course is to provide required background knowledge and critical thinking skills to move beyond the published literature to proposing original experiments. This effort will culminate in a final paper from each student.

An advanced seminar that reflects current research on the brain and behavior. Research by seminar participants and articles from the literature are discussed.

An introduction to the biophysics of nerve cells and synapses, the mathematical description of neural networks, and how neurons represent information. This course surveys computational modeling and data analysis methods for neuroscience and parallels some topics from 549, but from a computational perspective. Topics include representation of visual information, spatial navigation, short-term memory, and decision-making. Two 90 minute lectures, one laboratory. Lectures in common with MOL 437. Graduate students carry out and write up an in-depth semester-long project. Prerequisite: 410, or elementary knowledge of linear algebra.

This is a graduate-level lecture course covering statistical reasoning and techniques for neuroscience. The focus is on, 1. the foundations of statistical inference (probability theory, linear algebra, and statistical models); 2. hierarchical (mixed effect) general linear models as a framework for both classic techniques and modern extensions; 3. other contemporary methods relevant to neuroscience (including nonparametric and Monte Carlo techniques, Bayesian approaches, and estimating models by maximizing likelihood). There is emphasis on practical exercises with computation using R, and on example applications to neuroscientific data.

Examination of issues in the responsible conduct of scientific research, including the definition of scientific misconduct, mentoring, authorship, peer review, grant practices, use of humans and of animals as subjects, ownership of data, and conflict of interest. Class will consist primarily of the discussion of cases. Required of all first and second year graduate students in the Department of Psychology. Open to other graduate students.

Full-time research internship at a host institution, to perform scholarly research relevant to student's dissertation work. Research objectives are determined by advisor in conjunction with outside host. A mid-semester progress review and a final paper are required. Enrollment limited to post-generals students for up to two semesters. Special rules apply to international students regarding CPT/OPT use.