Global Arc

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.

This seminar focuses on the recent explosion of interest in understanding the neural basis of valuation and decision making, and the resulting marriage between the formal rigor of economics and the empirical basis of psychology and neuroscience, termed "neuroeconomics". We will approach the question of how the brain makes economic decisions from multiple perspectives, drawing on theoretical, behavioral, and neural data from economics, psychology, and neurobiology. Major topics include: decision under risk and uncertainty; the role of learning in evaluating options; choice mechanisms; and multiplayer interactions and social decision making.

The brain is more than a mere collection of its constituent parts. In this class we aim to understand how neurons interact together in local circuits and distributed brain dynamics to perform behaviorally relevant functions. The class will be organized into modules, which are selected to cover most of the major divisions of the brain. For most modules, we will first discuss a simpler circuit/system for which detailed mechanistic models and concrete ideas about function are known. Then, we will go on to discuss more complex systems, which are related to the simpler system.

Neurodevelopmental disorders,autism spectrum disorders, attention deficit/hyperactivity disorder, developmental dyslexia and dyspraxia, affect approximately 1 in 6 children and present major challenges. We will discuss the neural basis, clinical symptoms and interventional strategies of major neurodevelopmental conditions. Students will have the opportunity to engage in hands-on experience with children afflicted with dyslexia and ASD through observational studies performed in special education schools. The course is aimed at premeds, NEU concentrators, teacher prep program, and students with an interest in clinical applications.

This course will provide an overview of the major epigenetic mechanisms of gene regulation and the research tools that are used to study epigenetic modifications in different model systems, including humans. We will explore various topics in molecular and behavioral neuroscience including: developmental sensitive periods during for epigenome disruption by environmental factors, the role of epigenetic mechanisms in the dynamic regulation of adult brain function, epigenetic dysregulation in psychiatric disorders, and the controversial hypothesis that environmentally-induced epigenetic modifications can be heritable.

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.

Computational psychiatry is an emerging field of research that strives to leverage recent discoveries in the computational basis of high-level cognitive functions in order to understand, diagnose, and treat mental illness. Psychiatry is the only field of medicine where there are currently no laboratory tests, due in part to a lack of understanding what is the biological basis of symptoms. Computational theories of the brain's mechanisms for evaluation and decision may provide a foundation for such an understanding, and tasks measuring their function can offer objective measures. This seminar will discuss recent findings in this field.

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.

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.