This course is required for all the other courses offered in Neuroscience and Behavior. The course introduces students to the anatomy and physiology of the nervous system. The topics include the biological structure of the nervous system and its different cell types, the basis of the action potential, principles of neurotransmission, neuronal basis of behavior, sleep/wake cycles, and basic aspects of clinical neuroscience.
This course provides a hands-on introduction to techniques commonly used in current neurobiological research. Topics covered will include neuroanatomy, neurophysiology, and invertebrate animal behavioral genetics. Participation in this course involves dissection of sheep brains and experimentation with invertebrate animals.
This course is for students interested in learning how to conduct scientific research. They will learn how to (i) design well-controlled experiments and identify “quack” science; (ii) organize, summarize and illustrate data, (iii) analyze different types of data; and (iv) interpret the results of statistical tests.
Computational neuroscience is an exciting, constantly evolving subfield in neuroscience that brings together theories and ideas from many different areas in STEM such as physics, chemistry, math, computer science, and psychology. Through the exploration of computational models of neuronal and neural network activity, students will be introduced to a handful of quantitative STEM concepts that intersect with neuroscience. Before beginning this course students are expected to know about the action potential and synaptic transmission (see prerequisites). In this course, we will connect those biological phenomena to quantitative STEM concepts and then to computational models in Matlab. This course is designed for Neuroscience and Biology majors who want to take their first steps towards mathematical and computational models of the brain. Students interested in the computational track for the Neuroscience major should consider taking this course. By the end of this course students will be able to:
● Identify the scope of a neuroscience model and determine what it can and cannot tell us.
● Compare models and select an appropriate model for a given scientific question from among the models covered in this course.
● Make connections from the action potential and synaptic transmission to quantitative concepts from other STEM disciplines.
● Design, construct, and implement computational neuroscience models of neurons and neural networks using Matlab.
This course can be worth 1 to 4 credits (each credit is equivalent to approximately three hours of work per week) and requires a Barnard faculty as a mentor who has to provide written approval. The course entails a scholarly component; for this, a research report is required by the end of the term. The research report can take the form that best suits the nature of the project. The course will be taken for a letter grade, regardless of whether the student chooses 1, 2, 3, or 4 credits.
Prerequisites: BC1001 and BC1128/1129 Developmental (lab and lecture taken together) or BC1129 (only lecture). Or permission of the instructor. Enrollment limited to 15 students. Analysis of human development during the fetal period and early infancy. Review of effects of environmental factors on perinatal perceptual, cognitive, sensory-motor, and neurobehavioral capacities, with emphasis on critical conditions involved in both normal and abnormal brain development. Other topics include acute and long term effects of toxic exposures (stress, smoking, and alcohol) during pregnancy, and interaction of genes and the environment in shaping the developing brain of high-risk infants, including premature infants and those at risk for Sudden Infant Death Syndrome.
By the end of this course you'll understand some of the canonical principles underlying how brains encode information. You'll become familiar with the most influential frameworks and models for describing the encoding and transfer of information in the brain and you'll dive into the paradigms that generate or motivate these coding frameworks. Prerequisites: Introduction to Neuroscience (NSBV BC 1001) and either Systems and Behavioral neuroscience (NSBV BC 3001), or a Stats course (NSBV BC2002, PSYC BC1101, PSYC UN1610, STAT UN1101, STAT UN1201), or a computer science course (such as any of the following: COMS BC1016+lab COMS BC1017, COMS W1001, COMS W1002, COMS W1004), or any bioengineering course, or permission of the instructor. Students will complete a brief survey during registration to determine whether they meet the prerequisites.
Prerequisites: BC1001 and one of the following: Neurobiology, Behavioral Neuroscience, Fundamentals of Neuropsychology, or permission of the instructor. Enrollment limited to 20 students. Recent advancements in neuroscience raise profound ethical questions. Neuroethics integrates neuroscience, philosophy, and ethics in an attempt to address these issues. Reviews current debated topics relevant to the brain, cognition, and behavior. Bioethical and philosophical principles will be applied allowing students to develop skill in ethical analysis.
This course is a seminar designed to enhance students understanding of the methods used in primary research to inform how we study and understand the neural basis of both normative and pathological behavior in humans through the use of model systems. Through this course students will read and discuss primary research papers, debate the merits, limitations, and applicability of various approaches for advancing our understanding of the human condition, gain skills in presentation of scientific data, and a richer understanding of the scientific process. Topics covered will include the study of depression, anxiety, aging, memory, evolution, developmental disorders, and genetics (among others).
Perception is often taken as the most striking proof of something factual: when we perceive something, we interpret it as real. In this seminar we will challenge this assumption by taking into consideration states of altered perception, wherein the brain creates perceptual experiences that do not correspond to sensory input. Specifically, we will review a number of experiments showing changes in brain activity accompanying illusions, hallucinations, and dreaming across sensory modalities (i.e., vision, hearing, touch), and in both clinical and non-clinical populations. We will examine the similarities and differences between these states of altered perception both at the level of phenomenology and underlying biological mechanisms, specifically focusing on neural oscillations. Using the latest research findings in clinical, cognitive, and computational neuroscience, this seminar offers a great opportunity to learn more about how the brain creates perceptual experiences and why sometimes we perceive something that isn’t real.
Educational neuroscience is an emerging interdisciplinary effort to integrate neural, developmental, and behavioral research methods and findings with educational theory and practice. We will begin with an overview of the neurobiological basis of learning and memory, followed by a systematic investigation of five key cognitive processes: emotion, attention, motivation, decision-making, and sleep, examining how each contributes to learning. Our evidence-based exploration will confront both the challenges and opportunities in creating a productive, symbiotic partnership between neuroscience and education.
Neuroscience research commonly generates datasets that are increasingly complex and large. Open science and data sharing platforms have emerged across a wide range of neuroscience disciplines, laying the foundation for a transformation in the way scientists share, analyze, and reuse immense amounts of data collected in laboratories around the world. This class is designed to introduce students to several open source databases that span multiple investigative levels of neuroscience research. Students will utilize the datasets to conduct individual research projects.
Prerequisites: Open to senior Neuroscience and Behavior majors. Permission of the instructor. This is a year-long course. By the end of the spring semester program planning period during junior year, majors should identify the lab they will be working in during their senior year. Discussion and conferences on a research project culminate in a written and oral senior thesis. Each project must be supervised by a scientist working at Barnard or at another local institution. Successful completion of the seminar substitutes for the major examination.