Course 6-9: Computation and Cognition
As human brains increasingly interact with technology that mimics their own capabilities, the need for students to understand both the science and engineering of intelligence continues to grow as well. Addressing these challenges will require a deeper understanding of how the brain produces intelligent behavior and how we may be able to replicate intelligence in machines.
The Departments of Electrical Engineering and Computer Science (EECS) and Brain and Cognitive Sciences (BCS) at MIT offer a joint curriculum leading to a Bachelor of Science in Computation and Cognition that focuses on computational and engineering approaches to brain science, cognition, and machine intelligence. Students in the program are full members of both EECS and BCS.
The Course 6-9 curriculum provides flexibility to accommodate students with a wide diversity of interests in this area. This includes topics from neuroengineering ( reverse engineering circuits in the brain and developing brain interfaces) to biologically-inspired approaches to artificial intelligence.
Students will learn the fundamentals required for understanding neural circuits and designing and building interfaces between neurons and artificial neural hardware. Suggested subjects are 6.002, 6.003 and 6.009.
Human and Machine Intelligence
Students will learn to tackle the challenges of designing and building artificial intelligent systems that attain or exceed human-level performance in complex tasks. Suggested subjects are 6.034, 6.006 and 6.009.
The 6-9 major will jointly reside in EECS and BCS. Enrolled students will have a primary academic advisor in BCS with a secondary advisor in EECS. Advisors are assigned to students by the BCS Academic Office.
The MIT subject listing and schedule can be found here.
The Course 6-9 Roadmap can be found here.
General Institute Requirements (GIRs)
|Summary of Subject Requirements||Subjects|
|Humanities, Arts, and Social Sciences (HASS) Requirement [two subjects can be satisfied by 9.46 and 9.85 in the Departmental Program]; at least two of these subjects must be designated as communication-intensive (CI-H) to fulfill the Communication Requirement.||8|
|Restricted Electives in Science and Technology (REST) Requirement [can be satisfied by 9.01 and 6.042[J], 18.03, or 18.06 in the Departmental Program]||2|
|Laboratory Requirement (12 units) [can be satisfied by a laboratory in the Departmental Program]||1|
|Total GIR Subjects Required for SB Degree||17|
|Physical Education Requirement|
|Swimming requirement, plus four physical education courses for eight points.|
|6.0001||Introduction to Computer Science Programming in Python||6|
|9.01||Introduction to Neuroscience||12|
|Mathematics for Computer Science|
|Introduction to Inference|
|Introduction to Probability|
|Statistics for Brain and Cognitive Science 1|
|6.036||Introduction to Machine Learning 1||12|
|6.003||Signals and Systems||12|
|or 6.034||Artificial Intelligence|
|Circuits and Electronics|
|Introduction to Algorithms|
|Fundamentals of Programming|
|Cellular and Molecular Neurobiology|
|The Human Brain|
|Cellular Neurophysiology and Computing|
|Introduction to Neural Computation 1|
|Computational Psycholinguistics 1|
|Neural Circuits for Cognition|
|Emergent Computations Within Distributed Neural Circuits|
|Computational Cognitive Science|
|Infant and Early Childhood Cognition (CI-M) 1|
|Seminar in Undergraduate Advanced Research (12 units, CI-M)|
|Oral Communication (CI-M)|
|Research and Communication in Neuroscience and Cognitive Science (CI-M)|
|Projects in the Science of Intelligence (CI-M)|
|Units in Major That Also Satisfy the GIRs||(36-60)|
|Total Units Beyond the GIRs Required for SB Degree||180|
The units for any subject that counts as one of the 17 GIR subjects cannot also be counted as units required beyond the GIRs.
BCS/EECS Joint Electives1
|6.027[J]||Biomolecular Feedback Systems||12|
|6.141[J]||Robotics: Science and Systems||12|
|6.803||The Human Intelligence Enterprise||12|
|6.806||Advanced Natural Language Processing 2||12|
|6.819||Advances in Computer Vision 2||12|
|9.21[J]||Cellular Neurophysiology and Computing 2||12|
|9.40||Introduction to Neural Computation||12|
|9.49||Neural Circuits for Cognition||12|
|9.66[J]||Computational Cognitive Science||12|
|9.09[J]||Cellular and Molecular Neurobiology||12|
|9.13||The Human Brain||12|
|9.24||Disorders and Diseases of the Nervous System 2||12|
|9.26[J]||Principles and Applications of Genetic Engineering for Biotechnology and Neuroscience 2||12|
|9.42||The Brain and Its Interface with the Body 2||12|
|9.46||Neuroscience of Morality 2||12|
|9.53||Emergent Computations Within Distributed Neural Circuits||12|
|9.85||Infant and Early Childhood Cognition 2||12|
|6.101||Introductory Analog Electronics Laboratory (CI-M)||12|
|6.111||Introductory Digital Systems Laboratory||12|
|6.115||Microcomputer Project Laboratory (CI-M)||12|
|6.129[J]||Biological Circuit Engineering Laboratory (CI-M)||12|
|6.141[J]||Robotics: Science and Systems (CI-M)||12|
|6.161||Modern Optics Project Laboratory (CI-M)||12|
|6.182||Psychoacoustics Project Laboratory (CI-M)||12|
|9.17||Systems Neuroscience Laboratory (CI-M)||12|
|9.59[J]||Laboratory in Psycholinguistics (CI-M)||12|
|9.60||Machine-Motivated Human Vision (CI-M) 2||12|
MIT's Undergraduate Research Opportunities Program (UROP) cultivates and supports research partnerships between MIT undergraduates and faculty. Participating in a UROP through the department of Brain and Cognitive Sciences and Electrical Engineering and Computer Science gives students an incredible opportunity to be a part of the exciting research taking place here at MIT.
Browse current UROP opportunities posted on MIT’s UROP website.
For more information or questions please contact firstname.lastname@example.org
The Computation and Cognition major provides students with outstanding preparation for research and development in the science and engineering of intelligent systems. The problem of intelligence — how the brain produces intelligent behavior and how it can be replicated in machines — is one of the greatest engineering and scientific challenges of our time. The fields of neuroscience and computer science are complementary and interacting. Transformative advances in machine intelligence will require an understanding of the mechanisms of the human mind and brain in engineering terms.
Graduates of the program will be well-positioned for careers in two rapidly emerging fields: 1) the science and engineering of computational approaches to cognition and intelligence, and 2) computational approaches to understanding the architecture, circuits and physiology of the brain. Our expectation is that graduates of the new joint program will be extremely attractive to companies working in the area of machine intelligence (Google, IBM, DeepMind, Facebook, GE, etc.), and will be highly competitive in graduate programs in the brain and cognitive sciences.
Sample Job Titles: