The program consists of the following core activities:

  • Coursework in computational neuroscience, quantitative methodologies and experimental neuroscience
  • Exposure to experimental approaches through rotations or thesis research
  • Training in teaching, scientific presentations and responsible conduct of research
  • Successful defense of a Ph.D. Thesis

Additional satellite activities through the CNBC will also foster students’ professional and scientific development.

A typical student will take 2-3 courses per term in their first year and complete all coursework by the end of their third year in the program. Because of differences in background and educational goals, course requirements for each student in the program will be adapted to their individual needs.

CNBC Core Course Requirement

Students must complete the four-course requirement of the CNBC certificate program:

They must gain graduate level training through coursework in the following three areas: (i) cell and molecular neuroscience/neurophysiology, (ii) systems neuroscience, and (iii) cognitive neuroscience. Recommended courses fulfilling this requirement include

  • (i) 03-762 Advanced Cellular Neuroscience (CMU) or NROSCI 2100/2101 Cellular and Molecular Neurobiology (Pitt)
  • (ii) 03-763 Systems Neuroscience (CMU) or NROSCI 2102 Systems Neuroscience (Pitt), and
  • (iii) 85-765 Cognitive Neuroscience.

To complete the computational requirement, students must take:

  • 36-759 Statistical Models of the Brain (CMU) / Math 3375 Computational Neuroscience (Pitt)
  • Math 3370 Mathematical Neuroscience / CMU course number TBD.

Note that this is not exactly the same as the standard CNBC computational requirement.

Computational Neuroscience

Students are required to take at least one additional computational neuroscience course, including mathematical, statistical and computational approaches.

Recommended courses fulfilling this requirement include:

15-686 Neural Computation (CMU)
15-883 Computational Models of Neural Systems (CMU)
18-698/42-632 Neural Signals Processing (CMU)
85-719 Introduction to Parallel Distributed Processing (CMU)
86-631 Neural Data Analysis (CMU)
86-675 Computational Perception (CMU)

Quantitative Methods

Students must take at least two graduate level courses in one quantitative subject (e.g. math, computer science or statistics) to ensure depth of knowledge in this area. Courses listed above under the Computational Neuroscience requirement are not eligible to fulfill this requirement. Under the quantitative methods requirement, we have identified two examples of focus areas:

Dynamical Systems focus
MATH 2940 Applied Stochastic Methods (PITT)
MATH 2950 Applied Math Methods (PITT)

Statistics and Machine Learning focus
10-701 or 10-715 Machine Learning (CMU)
36-705 Intermediate Statistics (CMU)
36-707 Regression Analysis (CMU)

Other foci, including “brain imaging and signal processing” have been discussed and may be added as recommended course sets, subject to approval by the program co-directors. Note that to be eligible to take certain of these course, students might first need to complete course pre-requisites. These pre-requisites would not count towards the two course depth requirement.

Program Milestones

First year research requirement: By the end of the first calendar year in the program, all students are required to complete a computational project. This project will be evaluated by a committee consisting of at least three faculty, of whom at least two are PNC training faculty. The project requires the student to identify a biological problem, understand the data collection process, articulate the goals of building a model or performing a particular kind of analysis and implement this computational approach. In some cases this project may be a precursor to the student’s eventual thesis project. This project cannot substantially overlap with a project completed for a class, although it may be on the same topic as a class project, provided that it represents a substantial extension of that work.

Students should begin formally discussing this research project no later than the end of the spring term. Initial steps should include forming this committee and organizing a meeting to discuss/outline the project with your committee. The makeup of this committee should be approved by the program co-directors. At this first meeting the committee should approve the project proposal or indicate steps necessary to identify a new project. Then, before the start of the fall term, students must schedule a committee meeting where they present/defend their results. This meeting should occur before Oct 15. The initial part of this meeting involves a 30 minute presentation by the student, which is open to the public. This will be followed by a meeting with the committee and the student, during which the committee will ask detailed questions about the work. Based on this meeting, the committee will evaluate the student’s work and will decide whether a student passes, fails or needs to revise the project, subject to re-evaluation. Questions about the content of the presentation should be raised by the student with committee members well before the evaluation meeting.

Second year research requirement: In the second year, students are expected to work on research about 1/3 of their time during the academic year and full time during the summer. By the end of the second full year in the program all students are required to complete a deeper computational project. The student’s work on the project should demonstrate that the student has 1) the ability to analyze and interpret experimental data in a particular area 2) the ability to develop and implement a computational approach incorporating the relevant level of biological detail and 3) the ability to organize, interpret and present the results of the computational work. This project should be a body of work suitable for publication. It is expected that this work will be written up as a manuscript suitable for submission to a journal in the relevant field; a draft of this manuscript must be submitted to the committee at least a week in advance of the meeting. In most cases this project will be on an area related to the student’s eventual thesis project.

The evaluation of this milestone is similar to that of the first year milestone described above. Initial steps include forming this committee and organizing a meeting to discuss/outline the project with your committee. At this first meeting the committee should approve the project proposal or indicate steps necessary to identify a new project. Then, before the start of the fall term, students must schedule a committee meeting at which they will present/defend their results. The initial part of this meeting involves a 30 minute presentation by the student, which is open to the public. This seminar must be advertised to the PNC communities at least one week prior to the event. (To advertise, send the talk announcement including the date, time, place, title, abstract, and faculty committee to the PNC graduate program coordinator.) This will be followed by a meeting with the committee and the student, during which the committee will ask detailed questions about the work. Based on this meeting, and the submitted manuscript draft, the committee will evaluate the student’s work and will decide whether a student passes, fails or needs to revise the project, subject to re-evaluation.

Ph.D. Thesis proposal: Required coursework should be completed by the end of the third year. During the fourth year a Ph.D. candidate should present a thesis proposal to his or her thesis committee and the community. The proposal should include:

  • a clear statement of the proposed research problem
  • the significance of the proposed research
  • a review of relevant literature relating to the problem
  • a review of the candidate’s work leading up to the thesis
  • a tentative schedule for completing the work

Advising on scheduling the proposal, and guiding in the formation of the dissertation committee, is the thesis advisor’s responsibility. The thesis committee should be composed of at least four members, one being an external member and at least two being PNC training faculty. The external member is typically from outside the two participating Universities. All thesis committees are subject to approval by the PNC training faculty.

Ph.D. Thesis Defense: Normally, the dissertation is completed during the student’s fifth year. The student should set up a pre-defense meeting with their committee members six months prior to their defense. The final defense is a public presentation, in accordance with the College and University requirements for the Ph.D. It is the candidate’s responsibility to ensure that the College and University’s guidelines are followed for publicity of the defense and the availability of the thesis document at least two weeks prior to the defense. Note that the defense must be held at least 21 days before the date the degree is awarded.