PhDs in Neuroscience and Computational Neuroscience
The Graduate Program for Neuroscience (GPN) is a University-wide PhD degree-granting training program in neuroscience that unites the graduate training faculty and students present on our two campuses, the Charles River Campus (CRC) and the Medical Campus (MED). Faculty administration of the program is delivered by the Program Director in association with the GPN Steering Committee, Graduate Education Committee, and the Computational Neuroscience Curriculum Committee. The research of GPN training faculty covers virtually all areas of neuroscience, from molecular and cellular to systems and computational.
In addition to the PhD in Neuroscience, there is a specialized PhD in Computational Neuroscience for students interested in a more rigorous curriculum in the area. Students pursuing the PhD in Computational Neuroscience get a strong primary training in neuroscience that is shared with their fellow students pursuing the PhD in Neuroscience through the “Core” Curriculum.
An essential feature of the GPN training mission for all students (PhD in Neuroscience and PhD in Computational Neuroscience) is a set of core courses that are aimed at developing a community of thinkers, who move through their training together, building relationships that cross interdepartmental and inter-campus barriers, and foster cross-disciplinary collaborations.
As members of the unified program, the Neuroscience faculty serve as thesis research mentors and/or knowledge facilitators and work together to help students close any gaps between their knowledge base of individual disciplines as well as their understanding of computational and experimental models. Every effort is expended to provide an individually tailored mentorship and educational program for each student that builds upon their unique strengths and interests, while also recognizing areas that need enrichment through faculty guidance and curriculum choice.
There are four aspects of modern neuroscience that our program addresses:
- First, it is becoming increasingly clear that important breakthroughs in the field require ideas, approaches, and techniques originating from many disciplines. The GPN curriculum provides both (i) a broad cross-disciplinary core education including molecular, cellular, and systems; cognitive and behavioral; computational; and clinical neuroscience; and (ii) the flexibility to take neuroscience-related coursework in any of the departments and programs of the University to build depth of specialization along different perspectives in a particular area of neuroscience.
- Second, a critical aspect of GPN is the formation of a unified group of graduate students from across BU, including the Colleges of Arts & Sciences, Engineering, Health & Rehabilitation Sciences: Sargent College, and BU’s medical school. For the first year of training in GPN, these students take the “core” curriculum courses together, have the opportunity to be involved in common projects, and participate as a community in all Boston University neuroscience activities.
- Third, critical to the interdisciplinary focus of the training, is the participation of traditional science departments, which provide a large number of the elective courses and specialized training opportunities to complement the GPN curriculum. Several departments at the Medical Campus (Anatomy & Neurobiology and Pharmacology & Experimental Therapeutics) also offer a joint degree in neuroscience that is coordinated with GPN to further enhance the interdisciplinary nature of the student community.
- Fourth, a strong emphasis is placed on building relationships among students and faculty across multiple disciplines to complement the traditional mentorship by the thesis advisor and to provide entry into the neuroscience research/student community of multiple BU schools with alternative scientific perspectives.
The Diverse Student Body
Because students who enter GPN come from diverse backgrounds—including psychology, engineering, biology, chemistry, physics, and mathematics—upon their mutual acceptance into the program, they will be given the opportunity to fill any gaps in their training that might interfere with their ability to do their best in the upcoming core curriculum of their first and second years. This could mean enrolling in a particular summer course(s); taking a summer hands-on laboratory methods section (Tools of the Trade) organized by GPN faculty to introduce basic techniques in molecular or behavioral research; or even structured readings/discussions over the summer with a faculty member that are designed to stimulate a deeper understanding of a core discipline such as biology, biochemistry, or mathematics that might not have been fully emphasized in undergraduate coursework.
It is our belief that with a coherent educational program that embraces multiple complementary attitudes and approaches to scientific inquiry—breath vs. depth, multidisciplinary vs. traditional discipline, basic vs. clinical science, and experimental approaches vs. theoretical (computational)—there is the greatest opportunity to create a young generation of researchers with sufficient expertise and flexibility to be able to come together and address some of the “big problems” in neuroscience.
Most students take 28 credits of required academic study, although there is no limit on the amount of coursework that an individual can take upon approval from the GPN Graduate Education Committee. Likewise, students can petition to take fewer elective credits based on their prior graduate level experience. Additional required credits come from laboratory rotations and clinical rounds as described below. To fulfill the 64-credit requirement for the PhD, students also get credit for participating in the graduate student seminar series, attending GPN-sponsored activities such as the distinguished lecture series, the Neuroscience Retreat, and from directed study with their thesis research mentor or faculty facilitator.
In the first year students take 14 credits of integrated “core” coursework (courses taken together as an entering class from both PhD pathways, Neuroscience and Computational Neuroscience) that is delivered by leading GPN training faculty from across the University and covers the diverse field of neuroscience (from molecular to cellular, and systems to human cognition) using research findings and new technologies applied to model systems and to human subjects; an introductory course in computational modeling that is tuned to the specific background of individual students (2 credits); and Frontiers in Neuroscience (4 credits) where they share lunch every week with a BU faculty member and give oral presentations to them that cover their lab’s research mission. Here they also develop important writing skills through faculty and peer mentoring, learn to critically evaluate the literature in their field of interest as well as in areas outside of their earlier academic and research training, and acquire the basic skills to write a compelling Specific Aims section of an individual training grant application.
During the first year students also receive required credit (2–4 credits) for participating in laboratory rotations that help them develop important skills in lab bench research as well as identify a laboratory for future thesis research.
During their second year, students choose elective curriculum (10 credits) that enhances their research interests, develop an appreciation for the human condition by participating in a unique opportunity to observe clinical cases in neurology, neurosurgery, and psychiatry (1–2 credits), and dependent upon background, take an elective in probability and statistics that is relevant to their research. Together throughout their time in GPN they also take the mandated workshop requirement in Responsible Conduct in Research (RCR) that is offered across the University with BU faculty participation and have access to multiple GMS and faculty organized workshops in grant writing and professional development. GMS is especially proud of its accomplishments in being able to deliver an exceptional professional development curriculum, having received the BEST award from NIH in 2015.
For those students wanting to specialize in computational neuroscience, there is additional required study that leads to the PhD in Computational Neuroscience. Computational neuroscience students take their first-year “core” classes with all GPN students and a minimum of two (rather than three) laboratory rotations, with at least one that gives them the experience of experimental research. Additional rotations can be arranged if a student wants to do more and this is encouraged by GPN leadership.
All students have the option of taking additional academic coursework rather than using directed study credits with the thesis mentor to make up the 64-credit requirement for the degree, especially as needed based upon their research interests or to supplement a lack of certain background during undergraduate study.
The goal for the majority of students will be to complete core requirements and to choose the laboratory for their thesis research by the end of the first year. Course requirements for elective study will most likely be completed by the end of the second year. All efforts will be made to tailor the training program to the individual goals of the student, taking into account their previous training experiences either at the undergraduate or master’s level. GPN committees will continually evaluate, expand, and redesign core coursework and choices of advanced electives in order to offer students the best curriculum available across the University.
An essential feature of the program is a set of “core” courses: these are taken by all students in GPN during their first year and are aimed at developing a community of thinkers who move through the training program together, building relationships that cross departmental and campus barriers, and foster cross-disciplinary collaborations.
Students complete 12 credits of “core” neuroscience coursework that provides a strong foundation in this diverse field of graduate study. The Fall Semester course Systems Neuroscience I (4 credits) is team-taught by directors from each of the two BU campuses, CRC and MED, and is aimed at establishing a graduate-level understanding of the field of Neuroscience. The curriculum engages students to develop basic skills in critical thinking as well as basic principles of brain function, neuroanatomy, and the cellular and molecular neurobiology that will be essential for them as they move into the Spring Semester integrated curriculum (8 credits) that critically evaluates the use of novel technologies, model vertebrate/invertebrate systems, computational models, and studies with human subjects, in the goal of providing the most up-to-date thinking that can elaborate on the function and dysfunction of the human brain.
Additional core Neuroscience requirements (2 credits) include a 7-week intensive introductory course in data analysis and mathematical models for students who do not have a strong background in computation. This introductory course combines lectures and hands-on computer time to treat real laboratory data like case studies and motivates students to use the mathematical approach as a means to better understand their own research via statistical data analysis and modeling.
- An Introduction to Mathematical Models and Data Analysis in Neuroscience (GRS MA 665) (2 cr)
Students pursuing the PhD in Computational Neuroscience (or who have taken an undergraduate course in the area) can substitute a more advanced elective for this requirement. Likewise, students who have taken the required course and would like more exposure to the area can continue on in the class to take the next module that is offered sequentially (4 credits instead of 2 credits).
Additional Required Curriculum
In addition to the core curriculum, students take the following seminar coursework during their first year and enroll in laboratory rotations:
- Frontiers in Neuroscience (NE 500/501) (4 cr)
All students attend a unique weekly journal club and professional development class, run by the GPN Director, over lunch on Fridays (Fall and Spring of Year 1). In the Fall Semester, students are assigned key papers from a BU faculty member’s laboratory and supporting manuscripts in the field. The particular faculty member, whose research is being reviewed, co-hosts the class with the GPN Director. During the two-hour session, student presenters review and critique experimental findings and approaches, building their skills in critical thinking and developing the basic tools for successful oral presentations. They also get to share their scientific ideas and interests with the leaders of neuroscience at Boston University, an activity that enriches our neuroscience community. Research from monthly GPN distinguished lecturers from across the world are integrated into the training experience to provide a balanced exposure for students to all areas of neuroscience and to give them first-hand interactions with exceptional individuals who are defining the field of the future. In the Spring Semester, students learn to write a compelling Specific Aims and Approach section for an individual training grant application and develop the peer group skills to help each other grow professionally in both oral and writing exercises.
Providing an enriching set of laboratory research experiences directed by GPN faculty for students during their first year is a central feature of the neuroscience training program at Boston University. The multitude of highly talented mentors who have funded research projects provides students with a large number of potential laboratories from which to choose the thesis research mentor who will complement their current interests, and through laboratory rotations, expand their horizons into different areas of investigation that they may grow toward in the future. The majority of students pursuing the PhD in Neuroscience take a minimum of three rotations, with at least one rotation in an area outside of their initial research interests; students pursuing the PhD in Computational Neuroscience take a minimum of two rotations, with at least one in an experimental laboratory. Students can also request additional rotations should they not find a mentor, or if they would like more exposure to other methodologies used in neuroscience.
Hands-On Laboratory Boot Camp/Neuroscience Retreat
Before starting in the training program, the Graduate Education Committee (GEC) reviews the research experiences of each student to determine whether they have had basic training in molecular, behavioral, and/or cognitive research. Based upon their history of undergraduate or post-baccalaureate experiences, they will be advised to take a series of group method sessions called Tools of the Trade, run by faculty in the summer, that provides students with the essential hands-on experience necessary to make their laboratory rotations in the fall meaningful for their graduate-level training. In Tools of the Trade, students learn some of the basic techniques necessary for conducting laboratory research in the field of neuroscience, independent of their current research interests. Students who have already had experience in both molecular and cognitive research can petition to the GEC to waive the requirement and students who are unable to attend during the summer can take the sessions as part of their Laboratory Research Experience class during the Fall Semester, before beginning laboratory rotations.
For instance, group activities may be organized around detection of an important neuronal RNA via real-time PCR, the identification of a single nucleotide polymorphism in a DNA sample from a patient with a neurodegenerative disease, identification of protein in brain slices using immunohistochemistry and fluorescence microscopy, electrophysiological measurements or calcium imaging of living neurons, interaction of transcription factors with DNA regulatory elements that control expression of neural-specific genes, neuroimaging of the brain to detect the activation of particular brain structures, and running of a behavioral task with animals to address questions of learning and memory. Projects vary with the expertise and interests of the participating GPN faculty. Students will receive 1 directed study credit by registering for Tools of the Trade.
The entering class in GPN is also invited to the annual GPN Neuroscience Retreat. Every effort is made to schedule the retreat right after the Tools of the Trade so that students are well integrated in our community before arriving in the fall for formal admittance.
The rest of the credits toward the PhD in Neuroscience come from required clinical rounds (1 credit) and elective study (10-credit minimum). Please see specific details for the PhD in Computational Neuroscience as there is additional required coursework for the PhD.
Taking advantage of the translational research and history of clinical training at the Medical Campus and rehabilitative health sciences at the CRC, students can take coursework and participate in additional clinical rounds that provide exposure to topics relevant to human disease (such as autism, Alzheimer’s, drug abuse, epilepsy, Parkinson’s, schizophrenia, and hearing and speech disorders). They also take a required course in probability and statistics that is appropriate to their area of thesis research.
Additional program credits come from directed study during thesis research to make up the 64-credit PhD requirement. Students also take required workshops in neuroscience ethics and responsible conduct of research, attend all seminars and program events of the GPN, and attend workshops in professional development. In addition, all students are encouraged to participate in at least one teaching or outreach activity. GPN holds several teaching fellowships for those students who want to participate in the deliverance of GPN-specific curriculum, as well as curriculum in undergraduate neuroscience.
As members of GPN, students will acquire their more advanced training from coursework offered in departments around the University in order to fulfill the credit requirements for the PhD degree. The following is a list of potential electives organized by topic area as a guide to help students choose their curriculum.
Relevant to Molecular, Cellular & Systems (see also Computational)
- CAS BI 520 Sensory Neurobiology (4)
- CAS BI 545 Neurobiology of Motivated Behavior (4)
- CAS BI 575 Techniques in Cellular and Molecular Neuroscience (4)
- CAS BI 599 Neurobiology of Synapses (4)
- CAS PS 530 Neural Models of Memory Function (4)
- GMS AN 702 *Neurobiology of Learning and Memory (2)
- GMS AN 709 *Neural Development and Plasticity (2)
- GMS AN 804 *Methods in Neuroscience (4)
- GMS AN 807 *Neurobiology of the Visual System (2)
- GMS BN 798 *Functional Neuroanatomy in Neuropsychology (4)
- GMS PM 860 *Electrophysiology and Pharmacology of the Synapse (2)
- GMS PM 892 *Molecular and Neural Bases of Learning Behaviors (2)
- GRS BI 644 Neuroethology (4)
- GRS BI 645 Cellular and Molecular Neurophysiology (4)
- GRS BI 655 Developmental Neurobiology (4)
- GRS BI 681 Molecular Biology of the Neuron (4)
- SAR HS 550 Neural Systems (4)
- SAR HS 755 Readings in Neuroscience (4)
Relevant to Biomedical & Translational
- CAS BI 554 Neuroendocrinology (4)
- GMS AN 808 *Neuroanatomical Basis of Neurological Disorders (2)
- GMS AN 707 *Neurobiology of Aging (2)
- GMS AN 713 *Autism: Clinical and Neuroscience Perspectives (2)
- GMS AN 804 *Methods in Neuroscience (4)
- GMS AN 808 *Neuroanatomical Basis of Neurological Disorders (2)
- GMS PM 820 *Neuropsychopharmacology (2)
- GMS PM 840 *Neuroendocrine Pharmacology (2)
- GMS PM 850 *Biochemical Neuropharmacology (2)
- GMS IM 690 *Imaging of Neurologic Disease (2)
- GMS BN 782 *Forensic Neuropsychology (4)
- GMS BN 793 *Adult Communication Disorders (4)
- GMS BN 891 & 892 *Case Studies in Neuropsychology (three different clinical rounds, sections A1, B1, and C1) (2 credits each section)
- GMS BN 893 *Child Clinical Neuropsychology (4)
- GMS BN 796 *Neuropsychological Assessment I (4)
- GMS BN 797 *Neuropsychological Assessment II (4)
- GMS BN 821 *Neuroimaging Seminar (2)
Behavioral & Cognitive Neuroscience
- CAS PS 520 Research Methods in Perception and Cognition (4)
- CAS PS 525 Cognitive Science (4)
- CAS PS 528 Human Brain Mapping (4)
- CAS PS 544 Developmental Neuropsychology (4)
- CAS PS 721 General Experimental (4)
- CAS PS 734 Psychopharmacology (4)
- CAS PS 737 Memory Systems of the Brain (4)
- CAS PS 738 Techniques in Systems & Behavioral Neuroscience (4)
- CAS PS 821 Learning (4)
- CAS PS 822 Visual Perception (4)
- CAS PS 824 Cognitive Psychology (4)
- CAS PS 828 Seminar in Psycholinguistics (4)
- CAS PS 831 Seminar in Neuropsychology (4)
- CAS PS 833 Advanced Physiological Psychology (4)
- CAS PS 835 Attention (4)
- ENG BE 715 Functional Neuroimaging (4)
- GMS BN 795 *Neuropsychology of Perception and Memory (4)
- GMS AN 716 *Developmental Cognitive Neuroscience (4)
- GRS PS 829 Principles in Neuropsychology (4)
Theoretical & Computational Neuroscience
- CAS CN 500 Computational Methods in Cognitive and Neural Systems (4)
- CAS CN 510 Principles and Methods of Cognitive and Neural Modeling I (4)
- CAS CN 520 Principles and Methods of Cognitive and Neural Modeling II (4)
- CAS CN 530 Neural and Computational Models of Vision (4)
- CAS CN 540 Neural and Computational Models of Adaptive Movement and Planning Control (4)
- CAS CN 550 Neural and Computational Models of Recognition, Memory, and Attention (4)
- CAS CN 560 (co-listed as BE 509) Neural and Computational Models of Speech and Hearing (4)
- CAS CN 570 Neural and Computational Models of Conditioning, Reinforcement, Motivation, and Rhythm (4)
- CAS CN 580 Introduction to Computational Neuroscience (4)
- GRS CN 700 Computational and Mathematical Methods in Neural Modeling (4)
- GRS CN 710 Advanced Topics in Neural Modeling: Comparative Analysis of Learning Systems (4)
- GRS CN 720 Neural and Computational Models of Planning and Temporal Structure in Behavior (4)
- GRS CN 730 Models of Visual Perception (4)
- GRS CN 740 Topics in Sensory Motor Control (4)
- GRS CN 760 Topics in Speech Perception and Recognition (4)
- GRS CN 780 Topics in Computational Neuroscience (4)
- GRS CS 640 Artificial Intelligence (4)
- ENG BE 509 (co-listed as CN 560) Quantitative Physiology of the Auditory System (4)
- ENG BE 570 Introduction to Computational Vision (4)
- ENG BE 701 Auditory Signal Processing: Peripheral (4)
- ENG BE 702 Auditory Signal Processing: Central (4)
- ENG BE 707 Quantitative Studies of Excitable Membranes (4)
- ENG BE 710 Neural Plasticity and Perceptual Learning (4)
Coursework in related disciplines:
- CAS MA 565 Math Models in the Life Sciences (4)
- CAS MA 573 Qualitative Theory of Ordinary Differential Equations (4)
- CAS MA 581 Probability (4)
- CAS MA 582 Mathematical Statistics (4)
- CAS MA 583 Introduction to Stochastic Processes (4)
- CAS MA 584 Multivariate Statistical Analysis (4)
- CAS MA 585 Time Series and Forecasting (4)
- CAS MA 684 Applied Multiple Regression and Multivariable Method (4)
- ENG BE 515 Introduction to Medical Imaging (4)
- ENG BE 540 Bioelectrical Signals: Analysis and Interpretation (4)
- ENG BE 550 Bioelectromechanics (4)
- ENG BE 560 Biomolecular Architecture (4)
- ENG BE 740 Parameter Estimation and Systems Identification (4)
- ENG BE 747 Advanced Signals and Systems Analysis for Biomedical Engineering (4)
- CAS BI 552/553 Molecular Biology (4,4)
- GMS BI 782 *Molecular Biology (4)
- CAS BI 555 Techniques in Cell Biology (4)
- GRS BI 735 Advanced Cell Biology (4)
- CAS BI 721 Biochemistry (4)
- CAS MB 722 Advanced Biochemistry (4)
- GMS BL 755/756 *Biochemistry (4,4)
- GRS BI 621/622 Biochemistry (4,4)
- GMS BI 789 *Physical Biochemistry (2)
- CAS BI 556 Membrane Biochemistry and Cell Signaling (4)
- CAS BI 551 Biology of Stem Cells (4)
- ENG BE 561 DNA and Protein Sequence Analysis (4)
- ENG BE 700 Advanced Topics in Biomedical Engineering (4)
- GMS BI 776 *Gene Targeting in Transgenic Mice (2)
- GMS BI 786 *Biochemical Mechanisms of Aging (2)
- GMS BI 797 *Molecular Mechanisms of Growth and Development (2)
- GMS PM 800 *Systems Pharmacology (4)
- GMS PM 832 *Pharmacogenomics (2)
- GMS PM 843 *Pharmacologic Intervention in Inflammatory Responses (2)
- GMS PM 880 *Gene Regulation and Pharmacology (2)
- GMS PM 881 *Drug Discovery and Development (2)
- GMS MI 713 *Comprehensive Immunology (4)
- GMS MM 701 *Genetics and Epidemiology of Human Disease (2)
- GMS MM 703 *Cancer Biology and Genetics (2)
- GMS MM 710 *Molecules to Molecular Therapeutics: The Translation of Molecular Observations to Clinical Implementation (4)
- MET AD 893 Technology Commercialization: From Lab to Market (4)