Neuroscience Bachelor of Science Degree
In the neuroscience BS degree, you’ll learn how the brain works and apply that knowledge to develop systems for new frontiers such as advancing artificial intelligence, combating neurodegenerative diseases, and assisting those with learning disabilities.
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Specialized Track Options:
Neurobiology, Computational Neuroscience, and Behavioral Neuroscience
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Student Clubs with a Neuroscience Focus
Overview for Neuroscience BS
Why Pursue a Neuroscience Degree at RIT?
Interdisciplinary Approach: The Neuroscience degree at RIT is a collaboration between the College of Science and the Department of Psychology in the College of Liberal Arts, mixing critical coursework from both fields.
Three Dynamic Tracks: Choose from Neurobiology, Computational Neuroscience, or Behavioral Neuroscience.
Active Neuroscience Research Laboratories: Get hands-on lab experience all four years focused on comparative cognition, psychopathology, color perception, facial perception, and multisensory integration in VR/AR.
If you are drawn to questioning how we think, how we learn, and how understanding the systems in our brains can help change the world, then it’s time to consider RIT’s neuroscience BS. Major advancements in the field are expected in the coming years, and this degree in neuroscience will put you at the forefront of innovation.
BS in Neuroscience
Neuroscience is applied to a vast array of industries, including the rapidly developing field of artificial intelligence (AI). At the intersection of science, technology, and innovation, RIT is uniquely positioned to offer students a rich background in programming and computing as well as access to AI research projects to prepare for this booming field.
The study of the brain is also essential for understanding and combating neurodegenerative diseases like Alzheimer’s and Parkinson’s. Experts in neuroscience are at the forefront of treating mental illnesses and learning disabilities. With the combination of program electives and the opportunity to create your own track, you have the flexibility to design a neuroscience degree that will prepare you for admission to dental, medical, or optometry professional programs.
RIT’s Degree in Neuroscience
RIT’s flexible neuroscience BS involves the collaboration of the College of Science and the College of Liberal Arts to provide you with a multidisciplinary opportunity to study the brain while developing your background knowledge in the natural sciences, social sciences, and humanities. Graduates will be prepared for a multitude of professional careers and pre-professional programs.
Neuroscience Courses
You may choose from three track options based on your course preferences and career goals: neurobiology, computational neuroscience, and behavioral neuroscience. In addition to tracks, program electives make it possible for a double major or twin minor to be completed by students who wish to do so. The track courses and program electives allow you to expand your knowledge in intersecting subfields of neuroscience, such as biology, cognitive science, health science, psychology, and computing.
The lab requirements provide experience in the practical use of the equipment and methods used in the field of neuroscience today. This background gives graduates from this program a leg up when entering the workforce or continuing education.
Neuroscience Capstone
You will be required to participate in a two-semester Capstone in your final year of study to enhance your skills in technical communication and scientific research practices. You will research, write, and present a proposal for an independent research project.
Neuroscience BS Tracks
Neurobiology: The neurobiology track explores the branch of life sciences that deals with the anatomy, physiology, and pathology of the nervous system. Neurobiology centers around the study of nerve cells and the organization of these cells into functional circuits that process information and mediate behavior. Develop an in-depth understanding of how information is processed and stored in the brain and the molecular and cellular mechanisms underlying neural functioning.
Computational Neuroscience: The computational neuroscience track prepares students to use mathematical modeling and computer simulations together with the theories and experimentally gained knowledge of how the brain works to understand the principles that underlie perception, cognition, learning, and other processes in the nervous system. Computational neuroscience addresses the relationship between neuroscience and artificial intelligence (AI). The development of artificial neural networks was inspired by studying brain function. AI researchers aim to emulate human intelligence by building models and developing biologically-inspired architectures that can make decisions and solve problems in the same way that humans do. Artificial intelligence is also increasingly used as a research tool in neuroscience to advance our understanding of how the human brain works. For example, by analyzing data on brain activity acquired using neuroimaging techniques, machine learning is used to uncover the patterns in brain activity and link them to specific cognitive and motor actions.
Behavioral Neuroscience: The behavioral neuroscience track focuses on the relationship between behavior and behavioral science, such as psychology and neuroscience. Behavioral neuroscience examines what is happening in the brain and the behaviors, thoughts, and emotions that are associated with those processes. A range of topics are studied in this field, including learning and memory, motivation, emotion, and sensory processes.
Careers in Neuroscience
A BS in neuroscience is versatile, and you can apply your knowledge to a variety of industries. Graduates are well qualified for positions as research analysts, forensic science technicians, lab managers, neuroradiology technicians, pharmaceutical sales representatives, patient care assistants, science writers, neurotechnologists, data science specialists, and AI research associates. Those interested in advanced study can continue their education in graduate degree programs. Some typical job titles for those with advanced degrees include clinical psychologist, physician, speech-language pathologist, machine learning research scientist, occupational therapist, audiologist, AI systems engineer, public policy consultant, medical research scientist, MRI technician, lawyer, and neuroeconomist.
Pre-Health Professions Program
Medical schools and graduate programs in the health professions (such as physician assistants, physical therapy, and occupational therapy) welcome applications from students majoring in a wide range of academic programs. Acceptance into these programs requires the completion of pre-med requirements such as coursework in biological and physical sciences, a strong academic record, pertinent experiences in the field, and key intrapersonal and interpersonal capabilities. Learn more about how RIT’s Pre-Health Professions Program can help you become a competitive candidate for admission to graduate programs in the medical and health professions.
Pre-Vet Advising Program
Occupations in veterinary medicine are expected to grow three times faster than all other occupations between 2016 and 2026. If you’re interested in caring for animals, conducting research related to animal illnesses, or working with livestock in university or government settings, the Pre-Vet Advising Program can help you reach your career goals. Learn more about RIT’s personalized Pre-Vet Advising Program and how it can help you maximize your candidacy for admission to veterinary schools.
Pre-Law Advising Program
Law schools welcome applications from students majoring in a wide range of academic programs. If you are interested in pursuing law school, RIT’s Pre-Law Advising Program is designed to maximize your chances of admission to law school. The program includes personalized advising, LSAT preparation, academic counseling, and a timetable for law school admission.
Further Your Career in Neuroscience
Today’s careers require advanced degrees grounded in real-world experience. RIT’s Combined Accelerated Bachelor’s/Master’s Degrees enable you to earn both a bachelor’s and a master’s degree in as little as five years of study, all while gaining the valuable hands-on experience that comes from co-ops, internships, research, study abroad, and more.
+1 MBA: Students who enroll in a qualifying undergraduate degree have the opportunity to add an MBA to their bachelor’s degree after their first year of study, depending on their program. Learn how the +1 MBA can accelerate your learning and position you for success.
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Apply for Fall 2025
First-year students can apply for Early Decision II by Jan. 1 to get an admissions and financial aid assessment by mid-January.
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Careers and Experiential Learning
Typical Job Titles
| Research Analyst | Neurosurgeon | Neuroimaging Technician |
| Machine Learning Research Scientist | Neurotechnologist | Radiation Physicist |
| Behavioral Disorder Counselor | Social Worker | Data Science Specialist |
| Neuroeconomist | Lab Manager | Science Writer/Journalist |
| Clinical Psychologist | Artificial Intelligence Systems Engineer |
Cooperative Education
What’s different about an RIT education? It’s the career experience you gain by completing cooperative education and internships with top companies in every single industry. You’ll earn more than a degree. You’ll gain real-world career experience that sets you apart. It’s exposure–early and often–to a variety of professional work environments, career paths, and industries.
Co-ops and internships take your knowledge and turn it into know-how. Science co-ops include a range of hands-on experiences, from co-ops and internships and work in labs to undergraduate research and clinical experience in health care settings. These opportunities provide the hands-on experience that enables you to apply your scientific, math, and health care knowledge in professional settings while you make valuable connections between classwork and real-world applications.
National Labs Career Events and Recruiting
The Office of Career Services and Cooperative Education offers National Labs and federally-funded Research Centers from all research areas and sponsoring agencies a variety of options to connect with and recruit students. Students connect with employer partners to gather information on their laboratories and explore co-op, internship, research, and full-time opportunities. These national labs focus on scientific discovery, clean energy development, national security, technology advancements, and more. Recruiting events include our university-wide Fall Career Fair, on-campus and virtual interviews, information sessions, 1:1 networking with lab representatives, and a National Labs Resume Book available to all labs.
Featured Work and Profiles
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![neuroscience student working with patient]()
A Bright Future at RIT for Students Interested in Neuroscience
RIT researchers built a degree offering students a foundation in neuroscience concepts and research while taking advantage of the university’s strengths in color, imaging science, artificial...
Read More about A Bright Future at RIT for Students Interested in Neuroscience
Curriculum for 2024-2025 for Neuroscience BS
Current Students: See Curriculum Requirements
Neuroscience, BS degree, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| BIOL-123 | Introduction to Biology: Organisms and Ecosystems (General Education) This course serves as an introduction to biology for majors, focusing on the organismal, population, and ecosystem levels. Major themes include: evolution, structure and function, information flow and storage, pathways and transformations of energy and matter, and systems. The course also focuses on developing core competencies, such as applying the process of science, using quantitative reasoning, communicating, and collaborating. Small-group recitation sessions will develop study skills, introduce faculty research opportunities, and foster communication between students, peer mentors and teaching faculty. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.) Lecture 3, Recitation 1 (Fall). |
3 |
| BIOL-125 | Introduction to Biology Laboratory: Organisms and Ecosystems (General Education) This course is an introduction to laboratory work in life sciences. The laboratory work is project-based, and may involve field work as well as laboratory experiments. The course is designed to show the huge scope of biology and will encompass how some molecular biology and bioinformatics techniques connect with organismal and ecological biology. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.
Co-requisites: BIOL-123 or equivalent course.) Lab 3 (Fall). |
1 |
| BIOL-124 | Introduction to Biology: Molecules and Cells (General Education) This course serves as an introduction to biology for majors, focusing on the molecular and cellular level. Major themes include: evolution, structure and function, information flow and storage, pathways and transformations of energy and matter, and systems. The course also focuses on developing core competencies, such as applying the process of science, using quantitative reasoning, communicating, and collaborating. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.) Lecture 3 (Spring). |
3 |
| BIOL-126 | Molecules and Cells (General Education) This course is an introduction to laboratory work in life sciences. The laboratory work is project based, and the subject matter of the project(s) may vary. The course is designed to show the huge scope of biology and will encompass some molecular biology and bioinformatics techniques connect with organismal and ecological biology. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.
Co-requisites: BIOL-124 or equivalent course.) Lab 3 (Spring). |
1 |
| CHMG-141 | General & Analytical Chemistry I (General Education – Natural Science Inquiry Perspective) This is a general chemistry course for students in the life and physical sciences. College chemistry is presented as a science based on empirical evidence that is placed into the context of conceptual, visual, and mathematical models. Students will learn the concepts, symbolism, and fundamental tools of chemistry necessary to carry on a discourse in the language of chemistry. Emphasis will be placed on the relationship between atomic structure, chemical bonds, and the transformation of these bonds through chemical reactions. The fundamentals of organic chemistry are introduced throughout the course to emphasize the connection between chemistry and the other sciences. Lecture 3 (Fall, Spring, Summer). |
3 |
| CHMG-145 | General & Analytical Chemistry I Lab (General Education – Natural Science Inquiry Perspective) The course combines hands-on laboratory exercises with workshop-style problem sessions to complement the CHMG-141 lecture material. The course emphasizes laboratory techniques and data analysis skills. Topics include: gravimetric, volumetric, thermal, titration and spectrophotometric analyses, and the use of these techniques to analyze chemical reactions. (Corequisite: CHMG-141 or CHMG-131 or equivalent course.) Lab 3 (Fall, Spring, Summer). |
1 |
| CHMG-142 | General & Analytical Chemistry II (General Education – Scientific Principles Perspective) The course covers the thermodynamics and kinetics of chemical reactions. The relationship between energy and entropy change as the driving force of chemical processes is emphasized through the study of aqueous solutions. Specifically, the course takes a quantitative look at: 1) solubility equilibrium, 2) acid-base equilibrium, 3) oxidation-reduction reactions and 4) chemical kinetics. (Prerequisites: CHMG-141 or CHMG-131 or equivalent course.) Lecture 3 (Fall, Spring, Summer). |
3 |
| CHMG-146 | General & Analytical Chemistry II Lab (General Education – Scientific Principles Perspective) The course combines hands-on laboratory exercises with workshop-style problem sessions to complement the CHMG-142 lecture material. The course emphasizes the use of experiments as a tool for chemical analysis and the reporting of results in formal lab reports. Topics include the quantitative analysis of a multicomponent mixture using complexation and double endpoint titration, pH measurement, buffers and pH indicators, the kinetic study of a redox reaction, and the electrochemical analysis of oxidation reduction reactions. (Prerequisites: CHMG-131 or CHMG-141 or equivalent course.
Corequisites: CHMG-142 or equivalent course.) Lab 3 (Fall, Spring, Summer). |
1 |
| MATH-161 | Applied Calculus* (General Education – Mathematical Perspective A) This course is an introduction to the study of differential and integral calculus, including the study of functions and graphs, limits, continuity, the derivative, derivative formulas, applications of derivatives, the definite integral, the fundamental theorem of calculus, basic techniques of integral approximation, exponential and logarithmic functions, basic techniques of integration, an introduction to differential equations, and geometric series. Applications in business, management sciences, and life sciences will be included with an emphasis on manipulative skills. (Prerequisite: C- or better in MATH-101, MATH-111, MATH-131, NMTH-260, NMTH-272 or NMTH-275 or Math Placement Exam score greater than or equal to 45.) Lecture 4 (Fall, Spring). |
4 |
| PSYC-101 | Introduction to Psychology (General Education) Introduction to the field of psychology. Provides a survey of basic concepts, theories, and research methods. Topics include: thinking critically with psychological science; neuroscience and behavior; sensation and perception; learning; memory; thinking, language, and intelligence; motivation and emotion; personality; psychological disorders and therapy; and social psychology. Lecture 3 (Fall, Spring, Summer). |
3 |
| ISCH-110 | Principles of Computing (General Education) This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop step-by-step written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homework, group discussions and debates, and development of a term paper. Computer Science majors may take this course only with department approval, and may not apply these credits toward their degree requirements. Lec/Lab 3 (Fall, Spring). |
3 |
| UWRT-150 | Writing Seminar (General Education – First-Year Writing) (WI) Writing Seminar is a three-credit course limited to 19 students per section. The course is designed to develop first-year students’ proficiency in analytical and rhetorical reading and writing, and critical thinking. Students will read, understand, and interpret a variety of non-fiction texts representing different cultural perspectives and/or academic disciplines. These texts are designed to challenge students intellectually and to stimulate their writing for a variety of contexts and purposes. Through inquiry-based assignment sequences, students will develop academic research and literacy practices that will be further strengthened throughout their academic careers. Particular attention will be given to the writing process, including an emphasis on teacher-student conferencing, critical self-assessment, class discussion, peer review, formal and informal writing, research, and revision. Small class size promotes frequent student-instructor and student-student interaction. The course also emphasizes the principles of intellectual property and academic integrity for both current academic and future professional writing. Lecture 3 (Fall, Spring, Summer). |
3 |
| YOPS-10 | RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). |
0 |
General Education – Elective† |
3 | |
| Second Year | ||
| CGNS-222 | Introduction to Cognitive Neuroscience Cognition refers to mental action or processes of acquiring knowledge through the senses and through experience or thought. Neuroscience encompasses any or all of the sciences that deal with the structure and function of the nervous system and brain. This course provides the scientific foundation for the understanding of cognitive neuroscience, including neuroanatomy, neural signaling, motor control systems, the visual pathway, and research and experimental methods. Emphasis will be on Visual Neuroscience. (Prerequisites: (BIOG-101 and BIOG-102 or BIOL-101 and BIOL-102 or BIOL-121 and BIOL-122) and PSYC-101 or equivalent courses.) Lecture 3 (Fall). |
3 |
| ISCH-370 | Principles of Data Science This course builds on the principles of computing to introduce students to data analytics techniques commonly performed on digital data sets, using a variety of software tools. Students will learn what constitutes data and its associated social, ethical, and privacy concerns, common data acquisition and preparation techniques, and how to perform exploratory data analysis on real-world datasets from several domains. Common statistical and machine learning techniques, including regression, classification, clustering, and association rule mining will be covered. In addition, students will learn the importance of applying visualization for presenting and analyzing data. Students will be required to demonstrate oral and written communication skills through critical thinking homework assignments and both presenting and writing a detailed report for a project to analyze a data set of their choice. GCCIS majors may take this course only with the students’ home department approval, and may not apply these credits toward their degree requirements. (Prerequisites: CSCI-101 or ISCH-110 or equivalent course. Students in the B. Thomas Golisano College for Computing and Information Sciences are not eligible to take this class.) Lec/Lab 3 (Fall, Spring). |
3 |
| PHYS-111 | College Physics I* (General Education) This is an introductory course in algebra-based physics focusing on mechanics and waves. Topics include kinematics, planar motion, Newton’s laws, gravitation; rotational kinematics and dynamics; work and energy; momentum and impulse; conservation laws; simple harmonic motion; waves; data presentation/analysis and error propagation. The course is taught using both traditional lectures and a workshop format that integrates material traditionally found in separate lecture, recitation, and laboratory settings. Attendance at the scheduled evening sessions of this class is required for exams. There will be 2 or 3 of these evening exams during the semester. Competency in algebra, geometry and trigonometry is required. Lab 4, Lecture 2 (Fall, Spring, Summer). |
4 |
| PSYC-222 | Biopsychology Introduction to the field of behavioral neuroscience, the study of neurobiological basis of cognition and behavior. Topics include neuroanatomy and physiology, localization of function, brain injury, research methods in behavioral neuroscience, and biological basis of language, memory, emotion, conscious states, and sexual behavior, with an evolutionary perspective. (Prerequisites: PSYC-101 or PSYC-101H or completion of one (1) 200 level PSYC course.) Lecture 3 (Fall, Spring). |
3 |
| PSYC-223 | Cognitive Psychology This course examines how people perceive, learn, represent, remember and use information. Contemporary theory and research are surveyed in such areas as attention, pattern and object recognition, memory, knowledge representation, language acquisition and use, reasoning, decision making, problem solving, creativity, and intelligence. Applications in artificial intelligence and human/technology interaction may also be considered. (Prerequisites: PSYC-101 or PSYC-101H or completion of one (1) 200 level PSYC course.) Lecture 3 (Fall, Spring, Summer). |
3 |
| PSYC-255 | Behavioral Science Research Methods This course introduces the fundamentals of quantitative and qualitative research methods to equip students to understand and critically assess behavioral science research literature. Students learn about empirically-grounded approaches to knowledge, ethical issues in research, experimental and non-experimental methods, threats to validity and generalizability, general protocols for data-analysis, and standard formats for reporting research. (Pre-requisites: PSYC-101 and (STAT-145 or MATH-251) or equivalent courses.) Lecture 1 (Fall, Spring). |
3 |
| STAT-145 | Introduction to Statistics I (General Education – Mathematical Perspective B) This course introduces statistical methods of extracting meaning from data, and basic inferential statistics. Topics covered include data and data integrity, exploratory data analysis, data visualization, numeric summary measures, the normal distribution, sampling distributions, confidence intervals, and hypothesis testing. The emphasis of the course is on statistical thinking rather than computation. Statistical software is used. (Prerequisites: Any 100 level MATH course, or NMTH-260 or NMTH-272 or NMTH-275 or (NMTH-250 with a C- or better) or a Math Placement Exam score of at least 35.) Lecture 3 (Fall, Spring, Summer). |
3 |
General Education – Artistic Perspective |
3 | |
General Education – Global Perspective |
3 | |
General Education – Social Perspective |
3 | |
| Third Year | ||
| CGNS-310 | Experimental Lab Methods in Neuroscience Scientists use a wide range of laboratory methods to elucidate the function of the brain and nervous circuits in enabling behavior. This course will provide an overview of these methods, in order to allow students to understand a wide range of scientific studies and to be able to select an appropriate method for a specific research topic. For understanding human cognitive functioning such methods include neuroimaging, psychophysiology, single-cell recordings, computational modeling, and cognitive psychology and behavioral methods that use measures such as response time and decision accuracy to test theories concerning the nature of mental processes and representations. The methods employed in animal behavior research use animal models, such as rodents, drosophila, nonhuman primates, as well as stereotaxic surgeries and electrode implants. Microscopy, manipulating and visualizing neural activity, as well as genetic, cellular and molecular techniques are among the arsenal of methods used in neuroscience to achieve understanding of neural system functioning at various levels. (Prerequisites: PSYC-222 and CGNS-222 or equivalent courses.) Lec/Lab 4 (Fall). |
3 |
| CGNS-451 | Cognitive Neuroscience Seminar A Cognitive Neuroscience Seminar A is a weekly forum in which students will learn about and discuss historical and current topics in cognitive neuroscience. The course focuses on journal club discussions of papers selected by the students and faculty. It also includes oral presentations from students and faculty as well as visiting speakers from within and external to RIT. Students will prepare their own oral presentations and written assignments based on the course readings and independent research. Students will develop professional skills required for formal scientific presentations and writing. (Prerequisites: PSYC-222 and CGNS-222 or equivalent courses.) Lecture 1 (Fall). |
1 |
| CGNS-452 | Cognitive Neuroscience Seminar B Cognitive Neuroscience Seminar B is a weekly forum in which students will learn about and discuss historical and current topics in cognitive neuroscience. The course focuses on journal club discussions of papers selected by the students and faculty. It also includes oral presentations from students and faculty as well as visiting speakers from within and external to RIT. Students will prepare their own oral presentations and written assignments based on the course readings and independent research. Students will develop professional skills required for formal scientific presentations and writing. (Prerequisites: PSYC-222 and CGNS-222 or equivalent courses.) Lecture 1 (Spring). |
1 |
| CHMO-231 | Organic Chemistry I (General Education) This course is a study of the structure, nomenclature, reactions and synthesis of the following functional groups: alkanes, alkenes, alkynes. This course also introduces chemical bonding, IR and NMR spectroscopy, acid and base reactions, stereochemistry, nucleophilic substitution reactions, and alkene and alkyne reactions. In addition, the course provides an introduction to the use of mechanisms in describing and predicting organic reactions. (Prerequisites: CHMG-142 or CHMG-131 or equivalent course.
Corequisites: CHMO-235 or equivalent course.) Lecture 3 (Fall, Spring, Summer). |
3 |
| CHMO-235 | Organic Chemistry I Lab (General Education) This course trains students to perform techniques important in an organic chemistry lab. The course also covers reactions from the accompanying lecture CHMO-231. (Corequisite: CHMO-231 or equivalent course.) Lab 3 (Fall, Spring, Summer). |
1 |
General Education – Ethical Perspective |
3 | |
General Education – Immersion 1, 2 |
6 | |
Program Electives‡ |
12 | |
| Fourth Year | ||
| CGNS-501 | Neuroscience Capstone I Neuroscience has played a key role in the history of artificial intelligence (AI). The development of artificial neural networks was inspired by the knowledge gained from the study of brain functioning, with neuroscientists and psychologists, such as Donald Hebb, William McCulloch, and Geoff Hinton, contributing significantly to the establishment of the field. AI researchers aim to emulate human intelligence by building models and developing biologically-inspired architectures that can make decisions and solve problems in the same way that humans do.
At the same time, artificial intelligence is increasingly used as a research tool in neuroscience to advance our understanding of how the human brain works and to accelerate neuroscience development. For example, by analyzing the massive amounts of experimental data on brain activity acquired using neuroimaging techniques, machine learning is used to uncover the patterns in brain activity and link them to specific cognitive and motor actions. This course reviews the fundamental ideas in computational neuroscience and connects the study of the brain to the concepts and research in artificial intelligence. The list of example topics includes neural coding, the biophysics of single neurons and neuron models, neural networks, biological and computational vision, adaptation and learning, machine learning, deep convolutional networks, memory, speech and language processing, and applications of computational neuroscience and artificial intelligence. Research 3 (Fa/sp/su). |
1 |
| CGNS-502 | Neuroscience Capstone II (WI-PR) Students perform the independent research project defined in the proposal developed in COS-CGNS-501. The project is supervised by a faculty member in neuroscience program. The student submits a written paper and presents the results of the project to a public meeting. (Prerequisite: CGNS-501 or equivalent course.) Research 3 (Fa/sp/su). |
3 |
Open Electives |
12 | |
General Education – Immersion 3 |
3 | |
Program Electives‡ |
9 | |
| Total Semester Credit Hours | 121 |
|
Please see General Education Curriculum (GE) for more information.
(WI-PR) Refers to a writing intensive course within the major.
Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
* Students may take a higher course if applicable.
† For students interested in the Computational Neuroscience track, MATH-182 Calculus II is recommended for this General Education Elective.
‡ Students may choose to expand their knowledge in a specific area by selecting three program elective courses from one of the following tracks: Neurobiology, Computational Neuroscience, or Behavioral Neuroscience. They can select three courses as track courses from the table below. In some cases, with the permission of the program director and a recommendation from the academic advisor, students can define their own track that fits well with their interests and the program of study. If students choose to complete a track, 11-12 credit hours of additional program electives must be completed. If students choose not to complete a track, 21 credit hours of additional program electives must be completed. In addition to the list below, all track courses can be chosen as additional program electives.
Tracks
Neurobiology
| CGNS-401 | Neurobiology |
| CGNS-322 | Animal Vision This course explores the varied approaches to visually acquiring information employed by animals occupying aquatic and land-based environments, including lens-based, mirror, and compound eyes. Students will prepare oral presentations and written assignments based on the course readings and independent research. Students will develop the professional skills required for formal scientific presentations and writing. (Prerequisite: CGNS-222 or equivalent course.) Lecture 3 (Spring). |
| CGNS-410 | Imaging in Neuroscience his course introduces students to the fundamental principles of neuroimaging methods that are used in basic and applied neuroscientific research. Topics include history of neuroimaging as well as an overview of major neuroimaging techniques, including magnetic resonance imaging (MRI), functional MRI, diffusion tensor imaging, positron emission tomography, functional near-infrared spectroscopy, electroencephalography, and magnetoencephalography. The course will also address structural and functional neuroanatomy, basic physical principles, experimental design, statistical analysis and specific methodological principles and limitations associated with each imaging technique, as well as neuroimaging applications in studying the normal and diseased brain. (Prerequisites: CGNS-310 and (ISCH-370 or STAT-257) and (PHYS-111 and PHYS-112) or (PHYS-211 and PHYS-212) or equivalent courses.) Lec/Lab 4 (Fall or Spring). |
| Students must complete both of the courses listed below: | |
| BIOL-302 | Cell Biology This course will address the fundamental concepts of cell biology. Class discussions, assignments, and laboratory projects will 1) Explore the structure-function relationships that drive cellular processes at the molecular, cellular and tissue level. 2) Investigate the mechanisms of cellular signaling and the transmission of genetic information. 3) Examine energy transformation strategies and the biochemical pathways used for synthesis and breakdown of ATP and other important biomolecules. 4) Investigate the organizational strategies used by cells to form functional tissue and organ systems. (Prerequisites: (BIOL-206 and BIOL-216) or BIOL-201 or BIOL-202 or BIOG-240 or equivalent courses.) Lecture 3 (Spring). |
| BIOL-315 | Tissue Culture Laboratory This course will address the fundamental skills and concepts required to culture and maintain mammalian cells in culture. Laboratory discussions, assignments and projects will allow students to develop basic eukaryotic tissue culture techniques and explore tissue culture techniques in modern research and medical applications. (Prerequisites: BIOL-202 or (BIOL-206 and BIOL-216) or equivalent courses and students in BIOTECH-BS, BIOL-BS or NEURO-BS programs.
Co-requisites: BIOL 302 or equivalent course.) Lab 3 (Spring). |
Computational Neuroscience
| CGNS-421 | Neuroscience and Artificial Intelligence Neuroscience has played a key role in the history of artificial intelligence (AI). The development of artificial neural networks was inspired by the knowledge gained from the study of brain functioning, with neuroscientists and psychologists, such as Donald Hebb, William McCulloch, and Geoff Hinton, contributing significantly to the establishment of the field. AI researchers aim to emulate human intelligence by building models and developing biologically-inspired architectures that can make decisions and solve problems in the same way that humans do.
At the same time, artificial intelligence is increasingly used as a research tool in neuroscience to advance our understanding of how the human brain works and to accelerate neuroscience development. For example, by analyzing the massive amounts of experimental data on brain activity acquired using neuroimaging techniques, machine learning is used to uncover the patterns in brain activity and link them to specific cognitive and motor actions. This course reviews the fundamental ideas in computational neuroscience and connects the study of the brain to the concepts and research in artificial intelligence. The list of example topics includes neural coding, the biophysics of single neurons and neuron models, neural networks, biological and computational vision, adaptation and learning, machine learning, deep convolutional networks, memory, speech and language processing, and applications of computational neuroscience and artificial intelligence. (Prerequisites: PHYS-111 or PHYS-211 and (PHYS-111 and 112 or PHYS-211 and 212) and ISCH-110 or IMGS 180 and MATH-211 and (BIOL-124 and 126) and CGNS-222 or equivalent courses.) Lecture 3 (Spring). |
| CGNS-410 | Imaging in Neuroscience his course introduces students to the fundamental principles of neuroimaging methods that are used in basic and applied neuroscientific research. Topics include history of neuroimaging as well as an overview of major neuroimaging techniques, including magnetic resonance imaging (MRI), functional MRI, diffusion tensor imaging, positron emission tomography, functional near-infrared spectroscopy, electroencephalography, and magnetoencephalography. The course will also address structural and functional neuroanatomy, basic physical principles, experimental design, statistical analysis and specific methodological principles and limitations associated with each imaging technique, as well as neuroimaging applications in studying the normal and diseased brain. (Prerequisites: CGNS-310 and (ISCH-370 or STAT-257) and (PHYS-111 and PHYS-112) or (PHYS-211 and PHYS-212) or equivalent courses.) Lec/Lab 4 (Fall or Spring). |
| LING-581 | Natural Language Processing I This course provides theoretical foundation as well as hands-on (lab-style) practice in computational approaches for processing natural language text. The course will have relevance to various disciplines in the humanities, sciences, computational, and technical fields. We will discuss problems that involve different components of the language system (such as meaning in context and linguistic structures). Students will additionally collaborate in teams on modeling and implementing natural language processing and digital text solutions. Students will program in Python and use a variety of relevant tools. Expected: Programming skills, demonstrated via coursework or instruction approval. Lecture 3 (Spring). |
| PSYC-432 | Decision Making, Judgment, and Problem Solving This course is intended for students in the cognitive track. This course explores judgment, decision-making and problem-solving processes and focuses on the social and cognitive aspects of complex information processing. Major topics include normative, descriptive (heuristics and biases), and naturalistic approaches to decision-making, as well as selective perception, memory and hindsight biases, framing effects, social influences, group processes and human error. Models of decision-making considered include the prospect theory, expected utility theory, and Bayes’ Theorem. Problem solving will be examined from perspectives of formal, computational methods as well as intuition and creativity. Experimental methods and applications in design of systems and decision aids will receive special attention. (Prerequisites: PSYC-223 and (PSYC-251 or 0514-315, 0514-350 and 0514-400) or equivalent courses.) Lecture 3 (Biannual). |
Behavioral Neuroscience
| CGNS-410 | Imaging in Neuroscience his course introduces students to the fundamental principles of neuroimaging methods that are used in basic and applied neuroscientific research. Topics include history of neuroimaging as well as an overview of major neuroimaging techniques, including magnetic resonance imaging (MRI), functional MRI, diffusion tensor imaging, positron emission tomography, functional near-infrared spectroscopy, electroencephalography, and magnetoencephalography. The course will also address structural and functional neuroanatomy, basic physical principles, experimental design, statistical analysis and specific methodological principles and limitations associated with each imaging technique, as well as neuroimaging applications in studying the normal and diseased brain. (Prerequisites: CGNS-310 and (ISCH-370 or STAT-257) and (PHYS-111 and PHYS-112) or (PHYS-211 and PHYS-212) or equivalent courses.) Lec/Lab 4 (Fall or Spring). |
| PSYC-224 | Perception This course covers perception in all of the sensory modalities (vision, hearing, taste, smell, touch). We will trace what happens to the physical stimulus as our sensory systems analyze it to produce complicated perceptions of the world around us. We will explore the fact that many complex perceptual phenomena draw upon explanations at the physiological, psychological, and cognitive levels. Topics on sensory perception in non-human animals may also be covered. This is a required course for psychology majors in the visual perception track. (Prerequisites: PSYC-101 or PSYC-101H or completion of one (1) 200 level PSYC course.) Lecture 3 (Fall, Spring). |
| PSYC-410 | Psychophysiology This course is intended for students in the biopsychology track. This course provides a comprehensive introduction to psycho-physiology. Students will learn about various psychophysiological measures and their use in the study of areas such as attention, emotion, and language. Topics may include mind-body interaction, somatic and autonomic nervous system function, central and peripheral physiological measures (e.g., EEG, EMG, cardiac reactivity, skin conductance responses), psychophysiological research methods, and applied psychophysiology. Students will be expected to be able to write at an upper level using APA format. Part of the biopsychology track for the psychology degree program. (Prerequisites: (PSYC-222 or 0514-548 or 0514-553) and (PSYC-251 or (0514-315, 0514-350 and 0514-400) or equivalent courses.) Lecture 3 (Biannual). |
| PSYC-411 | Psychopharmacology This course is intended for students in the biopsychology track. A comprehensive introduction to psychoactive drugs. Topics include pharmacokinetics, pharmacodynamics, synaptic transmission, drugs of abuse and drugs used in the treatment of mental disorders, and the behavioral and cognitive effects of these drugs. Students will be expected to be able to write at an upper level using APA format. (Prerequisites: PSYC-222 and PSYC-250 and STAT-145 or equivalent courses.) Lecture 3 (Biannual). |
Program Electives
| BIOL-205 | Animal Behavior This course is a comparative study of animal behavior from an evolutionary perspective. Lectures will examine the organization of behaviors including survival behaviors, social dynamics, and human behavior. Labs will demonstrate methods of gathering and interpreting behavioral data in the laboratory and in the field. (Prerequisites: (BIOL-101 and BIOL-102 and BIOL-103 and BIOL-104) or (BIOL-121 and BIOL-122) or (BIOL-123 and BIOL-124 and BIOL-125 and BIOL-126) or equivalent courses.) Lab 3, Lecture 3 (Fall). |
| BIOL-206 | Molecular Biology This course will address the fundamental concepts of Molecular Biology. Class discussions, assignments, and projects will explore the structure and function of biologically important molecules (DNA, RNA and proteins) in a variety of cellular and molecular processes. Students in this course will explore the molecular interactions that facilitate the storage, maintenance and repair of DNA and processes that drive the flow of genetic information and evolution. Students in this course will gain an understanding of various molecular mechanisms, structure/function relationships, and processes as they relate to molecular biology. The foundational molecular concepts in this course will be built upon in a variety of upper-level biology courses. (Prerequisite:(BIOL-101,BIOL-102,BIOL-103&BIOL-104) or (BIOL-121&BIOL-122) or (BIOL-123,BIOL-124,BIOL-125&BIOL-126)or equivalent courses with a grade of C- or higher.
Co-requisite:(CHMG-141&CHMG-145)or(CHEM-151&CHEM-155) or CHMG-131 or equivalent courses.) Lecture 3 (Fall, Spring). |
| BIOL-303 | Cell Physiology This course is a study of functional eukaryotic cellular physiology with an emphasis on the role of global gene expression in cellular function and disease. Nuclear and cytoplasmic regulation of macromolecular synthesis, regulation of cellular metabolism, control of cell growth, and the changes in cell physiology in disease are covered. This course also covers the technology used for studying changes in gene expression associated with cell differentiation and disease. The associated laboratory covers microarray techniques. This includes design and implementation of an experiment to acquire gene expression data, analyzing the acquired data using simple computer programs, such as MAGIC, and writing a research paper explaining findings. (Prerequisites: BIOL-201 or BIOL-302 or BIOG-240 or equivalent course.) Lab 3, Lecture 2 (Fall). |
| BIOL-309 | Comparative Vertebrate Anatomy This course is a comparative study of the evolution of organ systems among vertebrate animals with an emphasis on structural changes in homologous characters among representative vertebrate lineages. The course will explore the concepts of allometry, biomechanics, biophysics, ontogeny, phylogeny using examples from vertebrate integument, skeletal, muscular, respiratory, circulatory, digestive, urogenital, endocrine, nervous, and sensory systems. (Prerequisites: BIOL-265 or equivalent course.) Lab 3, Lecture 1 (Spring). |
| BIOL-313 | Comparative Animal Physiology This course is a comparative study of fundamental physiological mechanisms. It covers a broad range of organisms studied from the standpoint of evolution of functional systems, the mechanisms and morphological variations that exist to deal with functional problems posed by the environment, and the special mechanisms used to cope with extreme environments. (Prerequisites: BIOL-240 or BIOL-265 or BIOL-202 or BIOL-206 or BIOG-240 or equivalent course.) Lab 3, Lecture 3 (Spring). |
| BIOL-314 | Tissue Culture This course will present the techniques and applications of culturing eukaryotic cells, tissues, and organs in vitro. Emphasis will be placed on mammalian systems. Lectures will cover the historical background of tissue culture, how to authenticate cell lines, basic cell culture techniques; as well as stem cells, tissue engineering, and the role of cell culture in regenerative medicine. In the laboratory, students will be introduced to growth curves, cloning techniques, primary cell culture, and making a cell line; as well as detecting mycoplasma and other cell culture contaminants. (Prerequisites: BIOL-201 or equivalent course.) Lab 3, Lecture 3 (Fall). |
| BIOL-315 | Tissue Culture Laboratory This course will address the fundamental skills and concepts required to culture and maintain mammalian cells in culture. Laboratory discussions, assignments and projects will allow students to develop basic eukaryotic tissue culture techniques and explore tissue culture techniques in modern research and medical applications. (Prerequisites: BIOL-202 or (BIOL-206 and BIOL-216) or equivalent courses and students in BIOTECH-BS, BIOL-BS or NEURO-BS programs.
Co-requisites: BIOL 302 or equivalent course.) Lab 3 (Spring). |
| BIOL-330 | Bioinformatics Bioinformatics introduces students to the analysis of biological sequences: DNA, mRNA, and protein. Emphasis is placed on classical bioinformatics analyses such as gene prediction, sequence alignment, and phylogenetics. The methods are applicable to both human and model organism studies in medical, biotechnological, and classical biology research. (Prerequisites: BIOL-201 or equivalent course.) Lab 3, Lecture 2 (Fall). |
| BIOL-428 | Eukaryotic Gene Regulation and Disease This course presents an overview of gene expression in eukaryotic systems, with an emphasis on how disease can result when gene regulation is disrupted. Points of control that are examined include: chromatin structure, transcription initiation, transcript processing, stability and modification, RNA transport, translation initiation, post-translational events, and protein stability. The mechanisms involved in regulating these control points are discussed by exploring specific well studied cases. The significance of these processes is highlighted by a discussion of several diseases that have been shown to be due to defects in gene regulation. (Prerequisites: BIOL-201 or BIOL-302 or BIOG-240 or equivalent course.) Lecture 3 (Spring). |
| BIOL-470 | Statistical Analysis for Bioinformatics This course is an introduction to the probabilistic models and statistical techniques used in computational molecular biology. Examples include Markov models, such as the Jukes-Cantor and Kimura evolutionary models and hidden Markov models, and multivariate models use for discrimination and classification. (Prerequisites: (MATH-161 or MATH-173 or MATH-182) and (STAT-145 or MATH-251) or equivalent courses.) Lecture 3 (Spring). |
| CHMB-402 | Biochemistry I This course introduces the structure and function of biological macromolecules and their metabolic pathways. The relationship between the three-dimensional structure of proteins and their function in enzymatic catalysis will be examined. Membrane structure and the physical laws that apply to metabolic processes will also be discussed. (Prerequisite: CHMO-231 or CHMO-331 or equivalent course.) Lecture 3 (Fall, Spring, Summer). |
| CLRS-600 | Fundamentals of Color Science This asynchronous online course provides a technical introduction to color science and the CIE system of colorimetry. Topics covered include color perception, color measurement, color spaces, and applications. The course is intended for students with a technical background who are interested in adding an elective course in color science to their graduate program and for practitioners in the color field interested in a more thorough understanding of the science behind colorimetry. Cannot be taken for program credit by Color Science MS and PhD students. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Summer). |
| CSCI-331 | Introduction to Artificial Intelligence An introduction to the theories and algorithms used to create artificial intelligence (AI) systems. Topics include search algorithms, logic, planning, machine learning, and applications from areas such as computer vision, robotics, and natural language processing. Programming assignments are an integral part of the course. (Prerequisites: (CSCI-243 or SWEN-262) and (MATH-251 or STAT-205) or equivalent courses. Students cannot take and receive credit for this course if they have taken CSCI-630.) Lecture 3 (Fall, Spring, Summer). |
| EEEE-547 | Artificial Intelligence Explorations The course will start with the history of artificial intelligence and its development over the years. There have been many attempts to define and generate artificial intelligence. As a result of these attempts, many artificial intelligence techniques have been developed and applied to solve real life problems. This course will explore variety of artificial intelligence techniques, and their applications and limitations. Some of the AI techniques to be covered in this course are intelligent agents, problem-solving, knowledge and reasoning, uncertainty, decision making, learning (Neural networks and Bayesian networks), reinforcement learning, swarm intelligence, Genetic algorithms, particle swarm optimization, applications in robotics, controls, and communications. Students are expected to have any of the following programming skills listed above. Students will write an IEEE conference paper. (Students in EEEE-BS/MS must take 600 or 700 level course not 500 level course.) Lecture 3 (Fall). |
| ENGL-482 | Speech Processing I |
| ENGL-582 | Natural Language Processing II |
| LING-584 | Undergraduate Speech Processing This course introduces students to speech and spoken language processing with a focus on real-world applications including automatic speech recognition, speech synthesis, and spoken dialog systems, as well as tasks such as emotion detection and speaker identification. Students will learn the fundamentals of signal processing for speech and explore the theoretical foundations of how human speech can be processed by computers. Students will then collect data and use existing toolkits to build their own speech recognition or speech synthesis system. This course provides theoretical foundation as well as hands-on laboratory practice. Lecture 3 (Fall). |
| IMGS-221 | Vision & Psychophysics This course presents an overview of the organization and function of the human visual system and some of the psychophysical techniques used to study visual perception. (This course is restricted to IMGS-BS, DIGCIME-BS, IMGS-MN and SCIMGS-IM students.) Lecture 3 (Fall, Spring). |
| IMGS-351 | Fundamentals of Color Science This course will introduce students to the field of Color Science. Students will learn about the physical sources of color, the visual mechanisms that provide our experience of color, and the descriptive systems that have been developed for relating the physical and visual properties. Through hands-on projects, students will learn practical methods for measuring, modeling, and controlling color in digital imaging systems. (Prerequisites: SOFA-103 or equivalent course.) Lecture 3, Recitation 2 (Fall). |
| IMGS-361 | Image Processing This course provides an introduction to the concepts and methods of image processing. The student will be exposed to sampling and quantization methods; descriptors and enhancement techniques based upon the image histogram; geometrical manipulations; interpolation and resampling; feature generation with direct application to image registration/stitching and redundancy reduction; pixel and object-level classification; frequency-domain applications, including automated image registration, data embedding, and image reconstruction; and image data redundancy and compression concepts. Emphasis is placed on efficient algorithmic implementations and applications, in an object-oriented development environment. (Prerequisite: MATH-173 or MATH-182 and IMGS-180 or equivalent courses.) Lecture 3 (Fall). |
| MEDS-250 | Human Anatomy and Physiology I This course is an integrated approach to the structure and function of the nervous, endocrine, integumentary, muscular and skeletal systems. Laboratory exercises include histological examination, actual and simulated anatomical dissections, and physiology experiments with human subjects. (Pre-requisite: (BIOL-123 and BIOL-124 and BIOL-125 and BIOL-126) or (BIOL-123 and BIOL-124) or (BIOL-101 and BIOL-102) or (BIOL-121 and BIOL-122) or MEDG-102 or equivalent course or NUTR-BS or NUTRSC-BS students.) Lab 3, Lecture 3 (Fall). |
| MEDS-425 | Introduction to Neuroscience This course will focus on the human nervous system, and its regulation of behavior and complex function. Background information on neuroanatomy, cellular physiology, neurotransmission, and signaling mechanisms will pave the way for an in-depth analysis of specialization at the systems level. Our goal will be to understand the anatomic, physiologic and molecular mechanisms underlying normal human behaviors and pathogenic states. (Prerequisites: MEDS-250 or equivalent courses.) Lecture 3 (Fall). |
| MEDS-525 | Advanced Clinical Neuroanatomy This is an integrated course encompassing lectures, laboratory exercises and clinical case discussions. Laboratory exercises will focus on detailed examination of the human brain as well as the internal circuitry of myelin-stained sections through the spinal cord, brainstem, and forebrain. The exercises will reinforce concepts stressed in lectures and clinical case discussions. (Prerequisites: MEDS-425 or equivalent courses.) Lec/Lab 4 (Spring). |
| PHIL-404 | Philosophy of Mind |
| PSYC-412 | Biological Basis of Mental Disorders This course is intended for students in the biopsychology track. This course covers the biological underpinnings of psychiatric mental disorders such as anxiety disorders, mood disorders, psychotic disorders, and developmental disorders. Topics will include neuroanatomy, neurophysiology, genetics and biologically based treatments of mental disorders. Students will learn about biologically based research methods used to study mental disorders and to think critically about research findings in the field. Students will be expected to be able to write at an upper level using APA format. (Prerequisites: PSYC-222 and PSYC-250 and STAT-145 or equivalent courses.) Lecture 3 (Biannual). |
| PSYC-430 | Memory and Attention This course is intended for students in the cognitive track. This course reviews current research in the areas of memory and attention. This course will consider such memory topics as: classic theories of memory, Baddeley’s model of working memory, in-formation processing, implicit and explicit memory, principles of forgetting, developmental changes in memory, skill memory, autobiographical memory, eyewitness memory, and the neural bases of memory. Attention topics covered in this course will include: Selective and divided attention, search and vigilance, signal detection theory, and neural correlates of attention. (Prerequisites: PSYC-223 and (PSYC-251 or 0514-315, 0514-350 and 0514-400) or equivalent courses.) Lecture 3 (Biannual). |
| PSYC-431 | Language and Thought This course is intended for students in the cognitive track. This course examines the structure of human language and its relationship to thought, and surveys contemporary theory and research on the comprehension and production of spoken and written language. In addition, we will discuss categorization, representation of knowledge, expertise, consciousness, intelligence, and artificial intelligence. Topics on language and thought in non-human animals may also be covered. Part of the cognitive track for the psychology degree program. (Prerequisites: PSYC-223 and (PSYC-251 or 0514-315, 0514-350 and 0514-400) or equivalent courses.) Lecture 3 (Biannual). |
| PSYC-450 | Visual System & Psychophysics This course is intended for students in the visual perception track. The course focuses on visual perception and the methods used for studying sensation and perception. Structures in the human and other visual systems will be examined along with neurophysiology relevant to vision in particular and perception in general. Classical psychophysics, forced choice methods, staircases and other specialized techniques will be examined. Students will collect and analyze psychophysical data to demonstrate their understanding of the methods and their application in vision science. Part of the visual perception track for the psychology degree program. (Prerequisites: PSYC-224 and (PSYC-250 or 0514-315, 0514-350 and 0514-400) and STAT-145 or equivalent courses.) Lecture 3 (Biannual). |
| PSYC-451 | Color, Form & Object Perception This course is intended for students in the visual perception track. The course focuses on the perception of the surface properties of objects, including color, form and other attributes. The course will examine how information is encoded by the visual system, with an emphasis on recognizing objects in scenes and surfaces. Receptive field properties, parallel processing in vision, the binding problem and other issues in vision science will be presented and discussed. The course requires students to read primary sources and to gain some experience with the design of experiments. Empirical research in vision will be conducted including data collection and analysis. Students are recommended to take PSYC-350 Visual System and Psychophysics before this course, but it is not required. (Prerequisites: PSYC-224 and (PSYC-250 or 0514-315, 0514-350 and 0514-400) and STAT-145 or equivalent courses.) Lecture 3 (Biannual). |
| PSYC-452 | Depth, Motion & Space Perception This course is intended for students in the visual perception track. The course focuses on the perception of the three-dimensional space, including the perception of depth and motion. This course will examine how sensory data are used to produce an accurate representation of the world. This course will include some discussion of multimodal perception given the interactions that occur between audition, touch, and vision to produce a 3D representation. Topics will include receptive field properties in relevant areas of cortex, parallel processing in vision, the uncertainty of extracting accurate 3D properties from 2D input and related material. The course requires students to read primary sources and to gain some experience with the design of experiments. Empirical research in vision will be conducted including data collection and analysis. Students are recommended to take PSYC-350-Visual System and Psychophysics before this course, but it is not required. (Prerequisites: PSYC-224 and (PSYC-250 or 0514-315, 0514-350 and 0514-400) and STAT-145 or equivalent courses.) Lecture 3 (Biannual). |
| PSYC-462 | Cognitive and Perceptual Development This course takes an in-depth look at the processes of perception and cognition as they develop over the lifespan. Drawing on basic research and theory, we will use a developmental perspective to study changes in perception and cognition. The specific course content will vary depending on the expertise of the instructor, but might include topics like sensory awareness, perceptual learning, object representation, causality, language, theory of mind, memory, or problem solving. This course is part of the Developmental Track for psychology majors. (Prerequisites: PSYC-232/226 and PSYC-251 and STAT-145 or equivalent course.) Lecture 3 (Fall). |
Admissions and Financial Aid
First-Year Admission
First-year applicants are expected to demonstrate a strong academic background that includes:
- 4 years of English
- 3 years of social studies and/or history
- 3 years of mathematics is required and must include algebra, geometry, and algebra 2/trigonometry. Pre-calculus is recommended.
- 2-3 years of science is required and must include biology and chemistry.
Transfer Admission
Transfer applicants should meet these minimum degree-specific requirements:
- A minimum of college algebra is required. Pre-calculus or calculus is preferred.
- Chemistry and biology are required.
Financial Aid and Scholarships
100% of all incoming first-year and transfer students receive aid.
RIT’s personalized and comprehensive financial aid program includes scholarships, grants, loans, and campus employment programs. When all these are put to work, your actual cost may be much lower than the published estimated cost of attendance.
Learn more about financial aid and scholarships
Research
Undergraduate Research Opportunities
Many students join research labs and engage in research starting as early as their first year. Participation in undergraduate research leads to the development of real-world lab techniques, enhanced problem-solving skills, and broader career opportunities. Our students have opportunities to travel to national conferences for presentations and also become contributing authors on peer-reviewed manuscripts. Explore the variety of neuroscience undergraduate research projects happening across the university.
Contact
Program Contact
- Elena Fedorovskaya
- Research Faculty
- Integrated Sciences Academy
- College of Science
- 585‑475‑6952
- eafppr@rit.edu