The Major in Cognitive Science


Cognitive science is the empirical study of intelligent systems, including the human mind. An interdisciplinary science, it combines results from biology, computer science, linguistics, mathematics, neuroscience, philosophy and psychology to the study of language processing, perception, action, learning, concept formation, inference and other activities of the mind, with applications for information technology and the study of artificial intelligence.  Penn has a long and prominent tradition in cognitive science. Our program, for research as well as education, has placed a special focus on formal and computational methods, which bring about a certain level of rigor, concreteness, and precision.

Read me First: What really is COGS? 

Practically every aspect of human activities have to the mind/brain: art, literature, aesthetics, ethics, history, politics, business, education, social organizations, etc. all are product of the lump north of the neck, so why aren’t all of these part of the COGS program?

That’s a very good question. In answering it, we can highlight the nature of cognitive science as a field, and the principles by which our COGS curriculum is constructed.

Cognitive science reflects the natural progression of the scientific method, which has found tremendous success in the natural sciences–and its application to the mind.  Modern science is founded on the commitment that the world has a mechanistic basis that can be understood as such. Why do objects in the air fall back to the ground? The pre-scientific answer would be that the ground is the “natural” place for objects. There is nothing mechanical about this explanation, not to mention that it is wrong: just observe the dust particles bouncing around in the sunlight while suspended in the air, as noted by the ancient Greeks (who got a lot of things right).

The founders of modern science also wondered about the nature of the mind. Galileo, for instance, marveled at human language, which permits us to construct “from 25 or 30 sounds an infinite variety of expressions, which although not having any resemblance in themselves to that which passes through our minds, nevertheless do not fail to reveal all of the secrets of the mind, and to make intelligible to others who cannot penetrate into the mind all that we conceive and all of the diverse movements of our souls.” These observations are very much the core problem for modern linguistics and cognitive science of language. Descartes developed a theory of vision: Light rays reflected on objects are focused by the lenses on the retinas, and tools from trigonometry for the purpose of distance estimation based on the retinal images. While he got a lot of the details wrong, his general approach is very similar to the modern theory of perception, and is still of enduring interest to the historians and philosophers of science.

A mechanical view of science requires a precise formal “language” to formulate scientific hypotheses from which (non-trivial) consequences can be derived and tested, which may in turn lead to revisions of the hypotheses so we can make progress. This should be familiar to everyone who has taken high school science. In some cases, the formal language had to be invented in order to understand nature: for example, Newton and Leibniz invented calculus to formulate theories of mechanics. In other cases, the formal language had been around all along but the right scientist had to come along to put the pieces together. While Darwin famously proposed the theory of evolution by natural selection, it was not until the early half of the 20th century did mathematicians and biologists figure out a way–actually very simple mathematics–to lay a formal foundation of the theory of evolution. (The delay was also caused by the ignorance of the genetic basis of inheritance and transmission: Mendel did his work at roughly the same time as Darwin but it was forgotten and only rediscovered in the early 1900s.) Closer to home, the initiation and transmission of the action potentials of the neuron are described as mathematical equations like those in the theory of electrical conductance.

For the study of the mind to be a genuine science, we had to wait for the right formal language to come along. That turns out to be the modern theory of computation, which emerged as a branch of mathematics, logic, and philosophy. Computer Science as a field came into existence shortly afterwards, with Penn playing a leading role. It was no accident that linguistics and psychology underwent a revolution, the so-called Cognitive Revolution at roughly the same time, and Artificial Intelligence popped up in the intersection of these fields.

The computational theory of the mind is a research program in which the mechanical basis of the mind is understood and modeled as a computer program. Some objections notwithstanding, it has proven to be enormously successful, so much that we can define cognitive science as theories of the mind that can be in principle be implemented on a computer. The requirement of in-principle-implementation forces us to develop theories in a rigorous and, again, mechanistic, way: a computer tolerates no ambiguity. Indeed, the most successful theories in cognitive science have been implemented: language, vision, learning, memory, etc., and you use these implementations everyday on your smartphone. The topics and classes in our program reflect this general principle: If it can be implemented on a computer from which no trivial consequences follow, then it is Cognitive Science. With luck although without guarantee, other areas of the mind may someday reach the level of mechanistic explanations, and our program will expand.

It should also be noted that our program focuses on the descriptive aspect of the mind–how it works–and not the prescriptive aspect of mind–how it should work, so that people are healthier, happier, make better decisions, etc. These two aspects are obviously related but they are not the same and are in fact frequently out of sync. For instance, medicine may discover a drug that alleviates some symptoms of a mental disorder, which is obviously a good thing for the patient, without understanding the mechanistic basis of that mental disorder. Again, this is not unusual in the history of sciences, where practice is ahead of theory: someday theory may catch up.

Logistical Matters

For advising information about the SAS undergraduate major in Cognitive Science, general remarks about the study of Cognitive Science, and the principles that underpin our curriculum, please contact Program Director Dr. Charles Yang.

For general program information, please contact Program Manager Jessica Marcus: jmarcus@upenn.edu.

Cognitive Science Advising is currently held online. Spring 2022 advising hours are Wednesday 3:00-5:00pm or by appointment, at this link.

The BA in Cognitive Science in the College requires a total of 16 unique course units:

  • ONE credit for the core course COGS 1001,
  • SIX credits in the breadth requirement,
  • and NINE credits in a concentration area chosen by the student.

See Guidelines for Study Abroad in Cognitive Science.

Core Course: 1 credit

The interdisciplinary field of Cognitive Science is surveyed in the following course, which should normally be your first stop if you are interested in the major.

The core course is offered every year in the Fall term ONLY. In Fall 2022, the course will meet on Tuesdays and Thursdays, 1:45-3:15pm. 

  • Introduction to Cognitive Science (COGS 1001/CIS 1400/LING 1005/PHIL 1840/PSYC 1333)

Breadth Requirement: 6 credits

To ensure more substantive knowledge of the wide-ranging fields that contribute to Cognitive Science, all students must take one course from each of the following six areas. The breadth requirement classes do not count (again) toward the concentrations. Please note that the courses listed are those typically used for the breadth requirement.  Almost all PSYC and PHIL classes accepted in the concentrations listed below can be used to satisfy the breadth requirements as well. To determine whether a course meets the breadth requirement for the COGS major, please contact Dr. Charles Yang at: cogs-pd@sas.upenn.edu.

  • Psychology (PSYC 0001, PSYC 1310)
  • Computation (CIS 1100, CIS 1200, CIS 1210)
  • Language (LING 0001; LING0500 accepted for students who are not in the computation & cognition concentration)
  • Philosophy (PHIL 1170, PHIL 1710, PHIL 2260, PHIL 2640; any PHIL class listed below works as well)
  • Neuroscience (NRSC 2249/PSYC 1230, NRSC 1110/BIOL 1110/PSYC 1210)
  • Mathematics (STAT 1110, MATH 1040, MATH 1140/1150)

Advanced Placement credit will not be counted toward the major requirements.

Concentration: 9 credits

Beyond the more structured breadth requirements, the student chooses one of four concentrations. The three main concentrations are Cognitive Neuroscience, Computation and Cognition, Language and Mind.  They are broad enough that virtually all interests in cognitive science can be sufficiently served but a special Independent Concentration constructed to meet a set of interests can be pursued in consultation with the Program Director.

The Program Director advises students when they are first considering the major and while still fulfilling the breadth requirements; handles administrative duties such as major declaration and certification; and is the final authority in all matters relating to the major requirements. When looking for classes for your own concentration, keep in mind that many classes from other concentrations often work as well. Sometimes a class is cross-listed in multiple departments: it does not matter which one your class is registered under.  To determine whether a specific course works for yours, please contact the Program Director at: cogs-pd@sas.upenn.edu.

Cognitive Science has become even more interdisciplinary as the field matures. We recognize the importance of specialized skills, especially those honed in the biological, economic, computational and mathematical sciences, in cognitive research, education, and application. At the same time, we strive to ground our program in the empirical studies of cognition in Linguistics, Psychology, and Neuroscience; tools are important, but we also need to know what they are for. In light of these considerations, we broadly limit technical courses — generally in Biology, Chemistry, Computer and Information Science, Mathematics, Statistics, etc. — to no more than 4, in any combination, among the 9 concentration credits. A technical class is one which provides useful background for the student’s concentration, but contains no or virtually no content on the empirical study of cognitive science. For students in the Computation and Cognition concentration, a fifth credit in Artificial Intelligence, or other topics directly related to human cognition, may be allowed upon approval. Those four credits are usually drawn from the list of courses below; for suitability of courses not listed below, please contact the Program Director.

We would like our students to maximize their educational experience in the Cognitive Science Program by forming a deeper understanding of some select topics or themes. To this end, we suggest that the course selection, similar to other Majors, consists of a mix of lower-level introductory classes and higher-level advanced courses, including graduate level courses (subject to prerequisites and/or instructor’s permission). We especially advise against taking introductory classes that have significant overlapping materials, including similar courses that are offered in different departments. Please contact the Program Director should these concerns arise during your course planning and selection process.

Currently, only the Cognitive Neuroscience concentration has a specific required course: Introduction to Brain and Behavior (NRSC 1110); but in many instances the advisor will identify one or more courses essential to the track of interest to the student. For example, at least one course in Statistics, such as STAT 1110 or higher, is strongly recommended to students specializing in Cognitive Neuroscience.

The list below indicates courses that have historically been approved for Concentration requirements. We strive to keep this list comprehensive as well as up to date under our general principle (see Read me First above). The courses in Psychology suitable for Cognitive Science generally have an odd course number; they are courses in the area of Brain, Cognitive, and Decision science, following the research program and numbering convention in the Department of Psychology.

Please note: Nearly all COGS-eligible classes at Penn are listed below. To find out whether a course not listed here will be approved for the COGS major, please contact Dr. Charles Yang at: cogs-pd@sas.upenn.edu.

Courses that are offered in Fall 2022 are highlighted in the list below.

Concentration 1: Cognitive Neuroscience

• Introduction to Brain and Behavior (NRSC 1110/BIOL 1110/PSYC 1210) – required
• Language and Thought (PSYC 1310)
• Perception (PSYC 1340)
• Memory (PSYC 1530)
• Intro to Developmental Psychology (PSYC 1777)
• Philosophy of Biology (PHIL 1830)
• Molecular and Cellular Neurobiology (BIOL 2110/NRSC 2110)
• Evolution of Behavior (PSYC 2220/BIOL 2140)
• Physiology of Motivated Behaviors (NRSC 2227/PSYC 1212)
• Psychology of Language (PSYC 2310)
• Visual Neuroscience (PSYC 2240/NRSC 2217/VLST 2170)
• Introduction to Cognitive Neuroscience (NRSC 2249/PSYC 1230)
• Drugs, Brain and Mind (NRSC 2270/PSYC 2250)
• Neuroscience and Society (PSYC 2288)
• Human Memory (PSYC 2300)
• Cognitive Development (PSYC 2377)
• Language Acquisition (LING 2700)
• Judgment and Decisions (PSYC 2737)
• Behavioral Economics and Psychology (PSYC 2750/PPE 3003)
• Seminar in cognitive neuroscience (PSYC 3230): not all sections; check with the PD.
• Computational Neuroscience lab (PSYC 3281/NRSC 3334)
• Psycholinguistics (PSYC 3310)
• Neuroeconomics (PSYC 3790)
• Neural Systems of Behavior (BIOL 4110)
• Big Data, Memory, and the Human Brain (COGS 4290)
• Human Brain Imaging (NRSC 4421)
• Neurobiology of Autism (NRSC 4430)
• Neurobiology of Learning and Memory (NRSC 4442/PSYC 3301/BIOL 4142)
• Neurodegenerative Diseases (NRSC 4475)
• Biological Bases of Psychological Disorders (NRSC 4480)
• Computer Analysis and Modeling of Biological Signals and Systems (LING 5250)
• Theoretical Neuroscience (PHYS 5585)

Concentration 2: Computation and Cognition

• Programming Languages and Techniques I/II (CIS 1200, CIS 1210)
• Language and Thought (PSYC 1310)
• Perception (PSYC 1340)
• Mathematical Foundations of Computer Science (CIS 1600)
• Formal Logic I = Ideas in Logic and Computation (PHIL 1710/LGIC 1710)
• Philosophy of Science (PHIL 1800)
• Human Memory (PSYC 2300)
• Psychology of Language (PSYC 2310/LING 1750)
• What is Meaning? (PHIL 2260)
• Discrete Probability, Stochastic Processes and Statistical Inference (CIS 2610)
• Automata, Computability, and Complexity (CIS 2620)
• Epistemology (PHIL 2620)
• Language Acquisition (LING 2700)
• Judgment and Decisions (PSYC 2737)
• Physical Models of Biological Systems (PHYS 2280)
• Decision Processes (OIDD 2900)
• Strategic Reasoning (PPE 3001)
• Behavioral Economics and Psychology (PPE 3003/PSYC 2750)
• Introduction to Algorithms (CIS 3200)
• Seminar in cognitive neuroscience (PSYC 3230): not all sections; check with the PD
• Computational Neuroscience lab (NRSC 3334/PSYC 3281)
• Philosophy of Perception (PHIL 3620)
• Neuroeconomics (PSYC 3790)
• Artificial Intelligence (CIS 4210)
• Big Data, Memory, and the Human Brain (COGS 4290)
• Origins of Analytic Philosophy (PHIL 4600)
• Theory of Knowledge (PHIL 4620)
• Philosophy of Mind (PHIL 4640)
• Logic II (PHIL 4722)
• Formal Logic II = Logic I (PHIL 4723)
• Logic in Computer Science (CIS 4820)
• Philosophy of Psychology (PHIL 4840)
• Philosophy & Visual Perception (PHIL 4843)
• Machine Learning (CIS 5200)
• Theory of Machine Learning (CIS 6250)
• Topics in Logic (PHIL 6720/MATH 6770)
• Philosophy of Mathematics (PHIL 6770)

Concentration 3: Language and Mind

• Introduction to Formal Linguistics (LING 0500)
• Introduction to Sociolinguistics (LING 0600)
• Language and Brain (LING 0740)
• Language and Thought (PSYC 1310)
• Formal Logic I = Ideas in Logic and Computation (PHIL 1710/LGIC 1710)
• Introduction to Developmental Psychology (PSYC 1777)
• Sound Structure of Language (LING 2300)
• Psychology of Language (PSYC 2310/LING 1750)
• Introduction to Syntax (LING 2500)
• Introduction to the Philosophy of Mind (PHIL 2640)
• What is Meaning? (PHIL 2660)
• Language Acquisition (LING 2700)
• Wittgenstein: Mind and Language (PHIL 3200)
• Morphology I (LING 3410)
• Neurolinguistics (LING 3740)
• Semantics I (LING 3810/5810)
• Origins of Analytic Philosophy (PHIL 4600)
• Philosophy of Language (PHIL 4660)
• Dynamics of Language (LING 5150)
• Phonetics I, II (LING 5210, 5220)
• Computer Analysis and Modeling of Biological Signals and Systems (LING 5250)
• Computational Linguistics (CIS 5300)
• Phonology I, II (LING 5310, 5320)
• The Mental Lexicon (LING 5450)
• Syntax I, II (LING 5510, 5520)
• Developmental Psycholinguistics (LING 5700)
• Semantics II (LING 5820)
• Theory of Machine Learning (CIS 6250)


Additional information

• At most, 3 of the 6 credits required for the COGS minor may be counted to fulfill the requirements of another major or minor.

• The minimum grade for any course counted toward the COGS program is C-. Students must have a GPA of 2.0 in courses counted towards the major in order to be admitted to the COGS major.

• Students who wish to enroll in COGS 3999 (Independent Study) or COGS 3998 (Senior Thesis) must develop a research plan with their research advisor prior to enrolling in either course. Click here for more information.

• Students who wish to receive a degree with honors must have a minimum GPA of 3.5 for courses counted toward the major, and 3.0 cumulative for all courses. The student must also complete a senior-year research project on a topic in cognitive science approved by the Program Director and supervised by the concentration advisor. Credit can be received by enrolling in COGS 3998 (Senior Thesis); see the Program Director for details. Typically, a thesis of approximately 30-40 pages is expected.

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