Computational Neuroscience Sequence

Recommended Common Core Electives

Choose four from at least three categories

  • Mathematics: MATH 032, or an approved equivalent course
  • General Physics: PHYS 030L KS, PHYS 031L KS, PHYS 033L KS, PHYS 034L KS, or an approved equivalent course
  • Computer/Data Science or Programming Course: for example, CS 4 SC, CS 5 HM, MATH 42 SC, NEUR 099, or an approved equivalent coruse
  • Statistics: BIOL 175 KS or PSYC 103 SC, PSYC 091 PZ, PSYC 109 CM, or an approved equivalent course

Sequence Courses

Four with a two-semester senior thesis, five with a one-semester thesis

Students should work with their academic advisers and/or Prof Borowski to select a set of cohesive courses relevant to their interests and career / professional goals.

  • Computational Neuroscience (NEUR 133L KS)
  • Data Structures (CSCI 062 CM)
  • Artificial Intelligence (CSCI 151 PO)
  • Neural Networks (CSCI 152 PO)
  • Machine Learning (CSCI 158 PZ)
  • Computational Partial Differential Equations (PHYS 105 KS)
  • Programming for Science and Engineering (PHYS 108 KS)
  • Introduction to MATLAB (PSYC 096 PZ)
  • Linear Algebra (MATH 060 PZ, SC)
  • Differential Equations (MATH 111 CM, SC) with modeling (MATH 102 PZ, SC)
  • Computational Psychiatry (NEUR 184 SC)
  • Neuroimaging with fMRI (NEUR 118 PO)
  • Mathematical Methods and Models in Neuroscience (NEUR 189A PO)
  • Genomics and Bioinformatics (BIOL 156L KS)
  • Advanced Data Analytics (BIOL 112 KS)
  • Computational Biology (BIOL 188 HM)
  • Genomics and Bioinformatics Laboratory (BIOL 173 PO)
  • Biophysics (PHYS 178L KS)