Aims and Scope
The undergraduate CNS option provides a foundation in math, physics, biology and computer science to prepare students for interdisciplinary graduate studies in neuroscience and career paths that involve computational applications inspired by properties of biological systems, such as artificial intelligence and computer vision. By graduation, students will have acquired knowledge in neurobiology, computation principles across different systems, methods used in modern neuroscience research, as well as the ability to critically evaluate and understand neuroscience literature, and be able to work in a team and communicate effectively.
To accomplish these goals, students are expected to complete a series of math and physics courses to establish solid quantitative skills. Then, they are expected to take two groups of courses, of which one has a biology focus, while the other has a CS focus. Through these courses, students are exposed to different sub-disciplines of neuroscience while also acquiring the quantitative skills needed in graduate research and industry jobs. Students will receive instruction in scientific communications through SEC 10 and SEC 11, SEC 12, SEC 13, or Bi/BE 24.
Undergraduate research is encouraged both during the academic year and through participation in summer research programs.
Students with a grade-point average lower than 1.9 will not be allowed to continue in the option except with special permission from the option representative.
CNS Option Requirements
- Take 4 courses from the extended math core:
a. Differential Equations (Ma 2 or equivalent listed below):
i. Intro Applied Mathematics for the Physical Sciences (ACM 95 ab)
ii. Numerical Methods for Integrals, PDEs, Spectral Theory (ACM 101 ab)
iii. Theory and Implementation of Linear Algebra, Approximation Theory, and Differential Equations (ACM 106 ab)
iv. Analysis (Ma 108 abc) or Topology (Ma 109 abc)
b. Probability and Statistics (Ma 3 or equivalent listed below):
i. Statistical Inference in the Biological Sciences (BE/Bi 103 b)
ii. Bayesian Statistics (Ec/ACM/CS 112)
iii. Introduction to Probability Models (ACM 116)
iv. Probability Theory and Computational Mathematics (CMS/ACM 117)
v. Bayesian Statistics and Data Analysis (Ge/Ay 117)
vi. Statistical Inference (IDS/ACM/CS 157)
c. Other math core:
i. Algebra (Ma 5 abc), Discrete Math (Ma 6 abc)
ii. Applied Linear Algebra (ACM 104)
iii. Linear Analysis with Applications (ACM 107 ab)
iv. Mathematics in Biology (Bi/CNS/NB 195)
d. Analytical science (choose two courses from one of the following sets):
i. Sophomore Physics: Ph 2 abc, Ph 12 abc.
ii. Advanced Physics: Ph 106 abc, Ph 125 abc.
iii. Optics: Aph 23, Aph 24, Ph 107.
iv. Organic Chemistry: Ch 41 abc.
v. Physical Chemistry: Ch 21 abc.
vi. Chemical Engineering: ChE 63 ab, ChE 62.
vii. Electrical engineering: EE 44, EE 119 ab, EE 114 ab
viii. Mechanical Engineering: ME 11 abc, ME 12 abc - Demonstration of competency in computer programming or computer science by taking CS 1, CS 2, and CS 3; or more advanced alternatives listed below:
i. Systems (CS 24)
ii. Decidability and Tractability (CS 21)
iii. Algorithms (CS 38)
iv. Data Analysis in Biology (BE 103 ab)
v. Introduction to Computational Biology and Bioinformatics (Bi/BE/CS 183)
vi. Another course approved by the option representative. - Bi/CNS 162 and 9 units of laboratory courses taken from the following list: CS/CNS 171, CS/CNS 174, EE 45, EE 90, EE 91 ab, ME 72 ab, ME 50ab, BE/EE/MedE 189 a, BE/CS 196a, Bi/BE 227, Bi/CNS/BE/NB 230, ME/CS/EE 134, or an equivalent course.
- SEC 10 and SEC 11, SEC 12, or SEC 13; or Bi/BE 24.
- Bi 8, Bi 9, NB/Bi/CNS 150, Bi/CNS/NB 164.
- Choose five CNS-(co)labeled 3-digit courses.
- 45 units of electives chosen from either advanced EAS courses or advanced science courses offered by BBE, CCE, GPS, or PMA divisions.
No course can count for more than one of the CNS requirements above, and all courses used to satisfy the option requirements must be taken on grades.
Senior Thesis (optional)
Either one of the two paths can be taken for graduation.
a. 45 units of electives; or
b. 27 units of electives, and three terms (27 units) taken of a senior thesis, completed in either junior or senior year in CNS X abc Senior thesis.
CNS Typical Course Schedule
Units per term | ||||
1st | 2nd | 3rd | ||
First Year | ||||
CS 1 |
Introduction to Computer
Programming |
9 | - | - |
CS 2 | Introduction to Programming Methods | - | 9 | - |
First-Year Humanities | 9 | 9 | 9 | |
First-Year Core | 27 | 27 | 27 | |
Total | 45 | 45 | 36 | |
Second Year | ||||
Ph 2 ac | Waves, Statistical Mechanics | 9 | - | 9 |
Ma 2 | Sophomore Mathematics | 9 | - | - |
Ma 3 | Sophomore Mathematics | - | 9 | - |
ACM 95 ab | Intro. Methods of Applied Math | - | 12 | 12 |
EE 111 | Signals and systems | 9 | - | - |
Bi 8, 9 | Molecular, Cell Biology | - | 9 | 9 |
NB 150 | Introduction to Neuroscience | - | - | 10 |
HSS Electives | 9 | 9 | 9 | |
Electives | 9 | 9 | - | |
Total | 45 | 48 | 49 | |
Third Year | ||||
BE 103a | Introduction to Data Analysis in Biological Sciences | 9 | - | - |
BE 103b | Statistical Inference in the Biological Sciences | - | 9 | - |
Bi 164 | Tools in Neurobiology | 9 | - | - |
CS 156 a | Learning Systems | 9 | - | - |
Bi 162 |
Cellular and Systems
Neuroscience Lab |
- | 12 | - |
BE/CS 191 a | Comparative Nervous Systems | - | 9 | - |
Engineering Lab | - | - | 9 | |
HSS Electives | 9 | 9 | 9 | |
Electives | 9 | 9 | 27 | |
Total | 45 | 48 | 45 | |
Fourth Year | ||||
CNS 187 | Neural Computation | 9 | - | - |
CNS 186 | Vision: From Computational Theory to Neuronal Mechanisms | - | 12 | - |
CS 159 | Advanced Topic in Machine Learning | - | - | 9 |
SEC 10, SEC 11-13 | Scientific Communication | 3 | - | 3 |
HSS Electives | 9 | 9 | 9 | |
Electives | 18 | 18 | 18 | |
Total | 39 | 39 | 39 |