Neuroscience Major Requirements
2024 - 2025 Catalog
Neuroscience major leading to BS degree
A major in neuroscience leading to a Bachelor of Science degree requires the completion of at least 50 credits in science and mathematics, including 42 or more credits from the following:
- Basic Science Core (4 courses): BIOL 111/113, BIOL 220 or BIOL 230 (or BIOL 211S); BIOL 201 or CBSC 250, and CHEM 110
- Neuroscience Core (2 courses): CBSC 111; NEUR 120/121
- Electives (5 courses): Completion of at least five additional courses selected from the following categories. Students must take a minimum of one course from each sub-discipline.
- Cellular and Molecular Neuroscience: BIOL 220, 230 (or BIOL 211S), 250, 280; CBSC 256; CHEM 341; NEUR 395
- Computational Neuroscience: BIOL 185, 187, 282, 302; CBSC 240; CSCI 257 (or BIOL 357), 230, 252, 256, 315; NEUR 396
- Systems Neuroscience: BIOL 255, 275, 283, 360, 362, 397; CBSC 253, 257; ENGN 267 (BIOL 267); NEUR 397
- Cognitive and Behavioral Neuroscience: BIOL 243; CBSC 252, 254, 255, 259; PHIL 282, 375; NEUR 398
- Research Practicum: Four credits chosen from the following: CBSC 353, 354, 355, 359; NEUR 401, 403, 421, 422, 423, 442, 453, 493 and, when appropriate, CBSC 398, 399
- Capstone: Submission of the Neuroscience e-portfolio.
Note: A limit of 12 credits in research practicum courses (NEUR 400s,420s,440s,450s,490s, and CBSC 350s and CBSC 350/390s) is allowable toward a degree.
- Basic Science Core (4 courses):
- BIOL 111 - Fundamentals of Biology
FDR SL Lab Science Distribution Credits 3 Prerequisite CHEM 110 and first year standing. Upper division students must request an eligibility override Corequisite BIOL 113 - Biology Laboratory An intensive investigation of scientific thought and communication applied to topics that vary among sections and terms. Specific subjects, chosen from within the scope of modern biological investigation according to the expertise of individual instructors, are examined in the context of major concepts such as evolution, regulation, growth, and metabolism. Suitable for First-Years interested in pursuing a major in biology, neuroscience or environmental studies or the pre-health curriculum. This course, and its companion laboratory (BIOL 113), are prerequisites for all higher level biology courses.
and
- BIOL 113 - Biology Laboratory
FDR SL Lab Science Distribution Credits 1 Prerequisite CHEM 110 and first year standing. Upper division students must request an eligibility override Corequisite BIOL 111 - Fundamentals of Biology A laboratory course to accompany BIOL 111. Students are trained in basic techniques of biological research by demonstrations and investigatory exercises, including data analysis and scientific communication. Limited seating available for sophomores, juniors, and seniors. All students should contact the Biology department, for consent as soon as the class schedule is available and before registration begins.
- BIOL 220 - Genetics
FDR SL Lab Science Distribution Credits 3 Prerequisite BIOL 111, 113, and either sophomore or junior class standing A study of the three main branches of modern genetics: 1) Mendelian genetics, the study of the transmission of traits from one generation to the next; 2) molecular genetics, a study of the chemical structure of genes and how they operate at the molecular level; and 3) population genetics, the study of the variation of genes between and within populations. This course is a prerequisite to most 300-level courses in biology.
or
- BIOL 230 - Cell Biology
Credits 3 Prerequisite BIOL 111, BIOL 113, and at least sophomore class standing This course will focus on understanding the components of a cell, the internal organization of a cell, how they move, how they function, how they respond to cues from their external environment, and the limits of our current knowledge. Lecture topics will include the internal organization of a cell, structure and function of DNA, RNA and proteins, membrane and cytoskeleton structure function, protein sorting, membrane transport, cell cycle and cell-cycle control, cell signaling and communication, and cell death.
or
- BIOL 211S - Cell Biology at St. Andrews
Credits 3 Prerequisite instructor consent Lecture and lab work are intermingled in this course that introduces the structure and function of the cell and sub-cellular organelles. as well as prokaryotic and eukaryotic cells. The diversity and development of different cell types within multicellular organisms is also discussed. Taught at the University of St. Andrews in Scotland with final grade assigned by W&L biology faculty.
- BIOL 201 - Statistics for Biology and Medicine
Credits 3 Prerequisite BIOL 111, 113, and either a Biology major, Neuroscience major, or Data Science minor This course examines the principles of statistics and experimental design for biological and medical research. The focus is on the practical and conceptual aspects of statistics, rather than mathematical derivations. Students completing this class will be able to read and understand research papers, to design realistic experiments, and to carry out their own statistical analyses using computer packages.
or
- CBSC 250 - Statistics and Research Design
Credits 4 Prerequisite any CBSC course and at least sophomore class standing Students learn about the design and analysis of psychological research, with particular emphasis on experimentation. Students learn statistical inference appropriate for hypothesis testing, and they use standard statistical packages to analyze data. Laboratory course.
- CHEM 110 - General Chemistry
FDR SL Lab Science Distribution Credits 4 This is a foundational course for those pursuing upper-level chemistry and biochemistry. Fundamental vocabulary, concepts, and principles that appear throughout the chemistry and biochemistry curriculum are introduced. Topics include basic chemistry calculations, quantum mechanics in chemistry, molecular structure, chemical thermodynamics, and chemical kinetics. In addition, a range of spectroscopic methods including UV-Vis, Atomic Absorption, and XRF are employed in the laboratory. While no previous knowledge of chemistry is required, some background is advantageous. Laboratory course with fee.
- Neuroscience Core (2 courses):
- CBSC 111 - Brain and Behavior
FDR SC Science, Math, CS Distribution Credits 3 An introduction to behavioral neuroscience, including the physiological bases of sensation, learning and memory, motivation, cognition, and abnormal behavior.
- NEUR 120 - Introduction to Neuroscience
FDR SC Science, Math, CS Distribution Credits 3 Prerequisite CBSC 110 or CBSC 111 Corequisite NEUR 121 - Introduction to Neuroscience Workshop An introduction to neuroscience emphasizing the molecular organization, chemistry, and physiology of the neuron; how neurons are organized into functional circuits; and how these functional circuits process information and control both normal and abnormal behavior.
and
- NEUR 121 - Introduction to Neuroscience Workshop
Credits 1 Corequisite NEUR 120 - Introduction to Neuroscience Training in the basic fundamental skills needed tor a career in the neurosciences. Prospective majors 1) learn fundamental oral presentation skills critically needed for a career in the biosciences; 2) learn to lead a discussion with an emphasis on critical analysis of primary research articles; 3) acquire a conceptual toolbox and theoretical understanding of current neuroscience techniques; 4) develop a digital portfolio of their academic work and research; and 5) learn about current neuroscience lab research opportunities at W&L.
- Electives:
- Cellular and Molecular Neuroscience
- BIOL 220 - Genetics
FDR SL Lab Science Distribution Credits 3 Prerequisite BIOL 111, 113, and either sophomore or junior class standing A study of the three main branches of modern genetics: 1) Mendelian genetics, the study of the transmission of traits from one generation to the next; 2) molecular genetics, a study of the chemical structure of genes and how they operate at the molecular level; and 3) population genetics, the study of the variation of genes between and within populations. This course is a prerequisite to most 300-level courses in biology.
- BIOL 230 - Cell Biology
Credits 3 Prerequisite BIOL 111, BIOL 113, and at least sophomore class standing This course will focus on understanding the components of a cell, the internal organization of a cell, how they move, how they function, how they respond to cues from their external environment, and the limits of our current knowledge. Lecture topics will include the internal organization of a cell, structure and function of DNA, RNA and proteins, membrane and cytoskeleton structure function, protein sorting, membrane transport, cell cycle and cell-cycle control, cell signaling and communication, and cell death.
or
- BIOL 211S - Cell Biology at St. Andrews
Credits 3 Prerequisite instructor consent Lecture and lab work are intermingled in this course that introduces the structure and function of the cell and sub-cellular organelles. as well as prokaryotic and eukaryotic cells. The diversity and development of different cell types within multicellular organisms is also discussed. Taught at the University of St. Andrews in Scotland with final grade assigned by W&L biology faculty.
- BIOL 250 - Vertebrate Endocrinology
Credits 3 Prerequisite BIOL 111, BIOL 113, and either a Biology major, Neuroscience major, Integrated Engineering - Biology track major, Biochemistry major, or Chemistry major This course provides an introduction to the scientific study of the endocrine system, including exploration of chemoregulatory mechanisms in vertebrates and examination of biochemical, cellular, and physiological aspects of hormone action. In-class exercises focus on developing written and verbal scientific communication skills, as well as in-depth analysis of primary literature.
- BIOL 280 - Neural Imaging
Credits 4 Prerequisite BIOL 220 This course examines how the architecture of specific types of neurons affect the neuron's ability to receive, process, and transmit synaptic information. In particular, the course examines how some of the important molecular growth and differentiation cues (e.g., growth factors) can transmit signals important for axon growth and survival of developing and mature neurons. Topics may include neurogenesis, axonal pathfinding, synaptogenesis, and regeneration. Students will conduct original research in the laboratory and acquire skills with various imaging techniques and analytical tools.
- BIOL 365 - Developmental Biology
Credits 4 Prerequisite BIOL 220 and at least junior class standing An examination of the goals, practices, and accomplishments of contemporary developmental biology. Topics include gametogenesis, fertilization, cleavage, gastrulation, organogenesis, genetic control of cell differentiation, transgenic procedures, cloning, embryo manipulation, and stem cells. Lectures, discussions of the developmental literature, and electronic media are utilized. Laboratory sessions focus on experimental manipulations of early invertebrate and vertebrate embryos and emphasize student-designed research projects. Laboratory course.
- CHEM 341 - Biochemistry I
Credits 3 Prerequisite CHEM 242 A study of the structure, function, biosynthesis and breakdown of biomolecules, including amino acids, carbohydrates, and lipids. Enzymes, biological membranes and membrane transport, signal transduction, and regulation of metabolism are studied in greater detail.
- NEUR 395 - Special Topics in Cellular and Molecular Neuroscience
Credits 1-3 A seminar designed to provide an advanced student with a broader knowledge of the field of cellular and molecular neuroscience. Specific topics will vary and depend upon instructor availability. May be repeated for credit if the topics are different.
- BIOL 220 - Genetics
- Computational Neuroscience
- BIOL 185 - Data Science: Visualizing and Exploring Big Data
Credits 3 We live in the era of big data. Major discoveries in science and medicine are being made by exploring large datasets in novel ways using computational tools. The challenge in the biomedical sciences is the same as in Silicon Valley: knowing what computational tools are right for a project and where to get started when exploring large data sets. In this course, students learn to use R, a popular open-source programming language and data analysis environment, to interactively explore data. Case studies are drawn from across the sciences and medicine. Topics include data visualization, machine learning, image analysis, geospatial analysis, and statistical inference on large data sets. We also emphasize best practices in coding, data handling, and adherence to the principles of reproducible research. No prior programming experience required. Fulfills the computer science requirement for biology and neuroscience majors.
- BIOL 187 - Introduction to Data Science in Python
Credits 4 Prerequisite BIOL 111, 113, and either a Biology major, Neuroscience major, or Data Science minor In this era of data science, major discoveries in science and medicine are being made by exploring datasets in novel ways using computational tools. The challenge in the biomedical sciences is the same as in Silicon Valley: knowing what computational tools are right for a project and where to get started when exploring large data sets. In this course, students learn to use Python, a popular open-source programming language and Jupyter Notebook data-analysis environment, to explore data interactively. Case studies are drawn from across the sciences and medicine. Topics include data visualization, physiological modeling, image analysis, and statistical inference on large data sets. We also emphasize best practices in coding, data handling, and adherence to the principles of reproducible research. No prior programming experience required.
- BIOL 282 - Modeling and Simulations in Public Health
FDR SL Lab Science Distribution Credits 4 Prerequisite MATH 101 Where are infections spreading? How many people will be affected? What are some different ways to stop the spread of an epidemic? These are questions that all of us ask during an outbreak or emergency. In a process known as modeling, scientists analyze data using complex mathematical methods to provide answers to these and other questions during an emergency response. Models provide the foresight that can help decision-makers better prepare for the future. In this course you will learn how to develop a simple mathematical models using data. You will learn basic epidemiological concepts, computational data analysis tools and relevant mathematical techniques to integrate existing data into the model and generate relevant predictions. In an open-ended project, you and several of your classmates will develop a model and recommendation about potential public health threat. No prior programming experience required - you will learn to use Python, a popular open-source programming language and Jupyter Notebook data analysis environment, to interactively explore data. Laboratory course.
- BIOL 302 - Modern Computational Biostatistics
Credits 3 Prerequisite BIOL 201 or CBSC 250 or permission of instructor Traditional approaches for statistical inference are based on methods developed in the pre-computer era. In most scientific fields, these methods are being replaced by more flexible and powerful methods based on computation. In this class, we will use regression-based methods to build statistical models, compare multiple models, and test models with data. We will start with linear regression, then move to mixed (random effects) models, then to hierarchical Bayesian models. The last section of the course will be an independent project; this can be based on data that a student has already collected or developed as a new project using publicly available data in a field of interest.
- CSCI 257 - A Walk Through the Ages: Using Artificial Intelligence to Understand the Evolution of Exercise
Credits 4 Prerequisite BIOL 187 or CSCI 111 Exercise leaves us healthier and happier, yet many of us struggle to get enough physical activity. Why it is so hard to hit the gym? Our biology and evolutionary past might play a role in our reluctance to undertake physical activity. In this course, students will learn how to quantify the amount of physical activity using wearable exercise trackers. We will collect data on different types of activities in different environments and physiological conditions. Using machine learning tools, we will develop a unique classifier that will predict the environmental/physiological setting based on the data. We will go through the processes of experimental design, data extraction, data preprocessing, data modeling and finally, data interpretation. These aspects of the course will culminate in a course project which will require students to build a model that represents the exercise data gathered.
or
- BIOL 357 - A Walk Through the Ages: Using Artificial Intelligence to Understand the Evolution of Exercise
Credits 4 Prerequisite BIOL 187 or CSCI 111 Exercise leaves us healthier and happier, yet many of us struggle to get enough physical activity. Why it is so hard to hit the gym? Our biology and evolutionary past might play a role in our reluctance to undertake physical activity. In this course, students will learn how to quantify the amount of physical activity using wearable exercise trackers. We will collect data on different types of activities in different environments and physiological conditions. Using machine learning tools, we will develop a unique classifier that will predict the environmental/physiological setting based on the data. We will go through the processes of experimental design, data extraction, data preprocessing, data modeling and finally, data interpretation. These aspects of the course will culminate in a course project which will require students to build a model that represents the exercise data gathered.
- CSCI 230 - Introduction to Machine Learning and Big Data
Credits 3 Prerequisite CSCI 112 This course is an intermediate-level computer science course that gives an overview of machine learning algorithms, concepts, and applications. We will begin with an understanding of how to systematically extract and prepare data for these types of models. We will explore common machine learning models such as linear regression, logistic regression, support vector machines, k-nearest neighbors, random forest, hidden Markov models, Bayesian networks, and others. Students will be exposed to how to train and evaluate the quality of their models. This evaluation includes a thorough investigation into whether the models present bias and what techniques can be employed to mitigate these limitations.
- CSCI 252 - Neuromorphic Computing
Credits 3 Prerequisite CSCI 112 An overview of computational methods inspired by the nervous systems of animals. Topics include philosophical foundations of neuromorphic computing, fundamental mathematical concepts, Hopfield nets, Kohonen's Self-Organizing Map, Sparse Distributed Memory, Latent Semantic Analysis, Tensor Products, and current neuromorphic hardware. Readings come from both popular textbooks and the scholarly literature. A major focus of the course is on writing programs to implement and apply the concepts and algorithms studied in the course.
- CSCI 256 - Modeling and Simulation
Credits 3 Prerequisite CSCI 112 Standard practices and applications of modeling and simulation. We explore ways to model complex systems that incorporate disciplines of biology, chemistry, and physics. Students learn critical-thinking skills when reading, comprehending, and analyzing real-world systems that they then create models for. Readings are supplemented by projects which reflect scenarios where modeling and simulation would be useful. Students are evaluated on a series of coding projects, class discussion, weekly quizzes, and exams measuring the ability to identify opportunities for application and to simulate models and their environments. A final project focuses on an open-modeling opportunity in biology, chemistry, or physics
- CSCI 315 - Artificial Intelligence
Credits 3 Prerequisite CSCI 209 Basic concepts of heuristic search, game playing, natural language processing, and intelligent systems, with a focus on writing programs in these areas. Course combines a discussion of philosophical issues with hands-on problem solving.
- BIOL 185 - Data Science: Visualizing and Exploring Big Data
- Systems Neuroscience
- BIOL 255 - Reproductive Physiology
Credits 3 Prerequisite BIOL 111 and BIOL 113 An examination of sex as a biological phenomenon with consideration of the genetic (chromosomal), embryological, endocrine, and neurological bases of sexual development, differentiation, and identity.
- BIOL 275 - Food for Thought
Credits 3 Prerequisite BIOL 111 and BIOL 113 This course utilizes problem-based learning to investigate nutrition and metabolism, as well as to the neural and hormonal regulation of feeding behavior. Through the use of primary literature and service-learning experiences, students develop an understanding of the experimental tools used in basic and applied nutritional sciences research. Because nutrition directly relates to many health care and quality-of-life issues at the forefront of modern society, this course also examines popular literature on food-related topics.
- BIOL 283 - Pregnancy: A KISS in Time?
Credits 4 Prerequisite BIOL 111 and BIOL 113 Kisspeptin (KISS) is a neuropeptide that controls reproductive maturation and function. Its adequate secretion is essential for correct reproductive function and successful pregnancy. Recent experimental studies have shown that KISS may act as a central integrator for other reproductive hormones and neuropeptides. For example, KISS stimulates release of the hormone prolactin (PRL), which helps to maintain pregnancy and prepare the body for lactation. In this class ,students determine the role that KISS plays in successful pregnancy using computational modeling. Students experience the world of computational modeling in neuroendocrinology by working in teams to investigate and extend an existing model for hormonal interaction between KISS and PRL in pregnancy in rats. The model will be used to generate experimentally tested predictions. No programming experience required; all necessary skills and training are provided as a set of tutorials.
- BIOL 360 - Experimental Neurophysiology
Credits 4 Prerequisite BIOL 220 An in-depth exploration of the theory and techniques of cellular neurophysiology. Labs utilize extracellular and intracellular recording techniques to explore motor neuron and sensory receptor firing properties and to examine the ionic basis for resting and action potentials and synaptic transmission. Laboratory course.
- BIOL 362 - Animal Physiology
Credits 4 Prerequisite BIOL 220 and at least junior class standing A comparative study of functional processes of animals, primarily vertebrates, and their environmental interactions. Laboratory emphasis is on functional adaptations and the use of physiological instrumentation in measuring functional processes. Laboratory course.
- BIOL 397 - Neuroendocrinology
Credits 3 Prerequisite BIOL 220 and at least junior class standing The study of the interaction between the nervous system and the endocrine system, with special reference to regulation and communication in the mammal. Topics may include neuroendocrine regulation of development, the role of the adrenal axis in stress, metabolic regulation of reproduction, or biological rhythms. May be repeated for degree credit if the topics are different.
- ENGN 267 - Bioengineering and Bioinspired Design
FDR SC Science, Math, CS Distribution Credits 3 Prerequisite PHYS 112 Same as BIOL 267. This course integrates biology, physics, engineering, and quantitative methods to study how an animal's physiology is optimized to perform a critical function, as well as how these biological systems inspire new technologies. The first half of this course focuses on integrative case studies, such as: How does a gecko lizard leap 30 m from the forest floor and survive the landing unscathed; Why are conch shells fracture resistant and how are they inspiring the next generation of protective gear? How is the mantis shrimp eye guiding the next revolution in optical data storage technology? The second half of the course is project based: student teams develop their own bioinspired systems. This course is intended for students interested in working on problems at the boundary of biology and physics/engineering and is appropriate for those who have more experience in one field than the other.
(BIOL 267)
- BIOL 255 - Reproductive Physiology
- Cognitive and Behavioral Neuroscience
- BIOL 243 - Animal Behavior
Credits 4 Prerequisite BIOL 111 and BIOL 113 An introduction to the scientific study of animal behavior, including exploration of the evolutionary basis of behavior and examination of how animals choose mates, defend territories, find food, and avoid predators. Field and laboratory exercises focus on testing hypotheses through experiments with a variety of animals, including fish, amphibians, birds, and humans. Laboratory course.
- CBSC 314 - Attention
Credits 3 Prerequisite CBSC 110, CBSC 111, or CBSC 112; and either BIOL 201 or CBSC 250 An examination of the theories and mechanisms associated with attentional processes. Topics include: selective attention, divided attention, inhibition, working memory, and the application of these processes in human/machine interfaces. The functioning of the above processes in abnormal patient populations is also examined.
- PHIL 282 - Philosophy of Biology
FDR HU Humanities Distribution Credits 3 An examination of philosophical issues raised by biology, with an emphasis on current evolutionary theory. Topics include the structure of the theory of evolution by natural selection, an examination of the concepts of fitness and adaptation, the role of teleological explanation in biology, reductionism, the nature of biological species, individuality, levels of selection, and sociobiology.
- PHIL 375 - Philosophy of Mind
FDR HU Humanities Distribution Credits 3 An investigation and assessment of the relation between the mental and the physical, including such theories as dualism, identity theory, functionalism, eliminativism, neurocomputationalism, and extended/embodied mind. We will investigate the evolution of minds, the relation of language to mind and culture, and the possibility of artificial and non-human minds.
- BIOL 243 - Animal Behavior
- Research Practicum:
- CBSC 353 - Advanced Methods in Systems Neuroscience Research
Credits 3 Prerequisite instructor consent Directed research on a variety of topics in systems neuroscience. May be repeated for credit.
- CBSC 354 - Advanced Methods in Attention Research
Credits 3 Prerequisite instructor consent Directed research on a variety of topics in attention and memory. May be repeated for degree credit.
- CBSC 355 - Advanced Methods in Cognitive Neuroscience Research
Credits 3 Prerequisite instructor consent Directed research on a variety of topics in human neuropsychology. May be repeated for degree credit.
- CBSC 359 - Advanced Methods in Cognition and Emotion Research
Credits 3 Prerequisite instructor consent Directed research on a variety of topics in cognition and emotion. May be repeated for degree credit.
- NEUR 401 - Directed Individual Study
Credits 1 Prerequisite instructor consent This seminar involves independent reading and/or research. Students are expected to prepare a detailed research proposal based on their independent work. May be repeated for degree credit if the topics are different.
- NEUR 403 - Directed Individual Study
Credits 3 Prerequisite instructor consent This seminar involves independent reading and/or research. Students are expected to prepare a detailed research proposal based on their independent work.
- NEUR 421 - Directed Independent Research
Credits 1 Prerequisite instructor consent Each student conducts primary research in partnership with a neuroscience faculty member by prior mutual agreement. Consult with individual faculty for a description of current research areas. This course may be repeated for credit.
- NEUR 422 - Directed Individual Research
Credits 2 Prerequisite instructor consent Each student conducts primary research in partnership with a neuroscience faculty member by prior mutual agreement. Consult with individual faculty for a description of current research areas.
- NEUR 423 - Directed Individual Research
Credits 3 Prerequisite instructor consent Each student conducts primary research in partnership with a neuroscience faculty member by prior mutual agreement. Consult with individual faculty for a description of current research areas.
- NEUR 442 - Honors Thesis Proposal
Credits 2 Prerequisite instructor consent Writing a proposal for honors thesis research, including a clear statement of the problem being studied, a literature review, and a feasible, detailed plan for the research.
- NEUR 453 - Neuroscience Internship
Credits 3 Prerequisite instructor consent This course provides students an opportunity to engage in scholarly and professional development though external placements in research laboratory, clinical, or business settings where neuroscientific content is a focus of daily work activity.
- NEUR 493 - Honors Thesis
Credits 3 Prerequisite NEUR 442 Individual conference.
and when appropriate,
- CBSC 399 - Advanced Research Methods in Cognitive and Behavioral Science
Credits 3 Directed research on an area of current interest in the fields of cognitive and behavioral science. May be repeated for degree credit if the topics are different.
- Capstone
Completion of at least five additional courses selected from the following categories. Students must take a minimum of one course from each sub-discipline.
Four credits chosen from the following:
Submission of the Neuroscience e-portfolio.