Cognitive neuroscience is the study of higher cognitive functions in humans and its underlying neural bases. By definition, it is an integrative area of study drawing principally from cognitive science, psychology, neuroscience, and linguistics. There are two broad directions which can be taken in this concentration—one is behavioral/experimental and the other is computational/modeling. In either case, the goal is to understand the nature of cognition from a neural perspective.
A total of 16 courses are required for the concentration. Each student is required to pass 9 courses designed to introduce students to the foundations, systems level, and integrative aspects which uniquely define cognitive neuroscience; two laboratory courses; four elective courses; and either a senior seminar course (CG 195) or an independent research course. The laboratory and elective courses should fit within a particular theme or category such as general cognition, vision, language, or computational/modeling. The design of the concentration and selection of courses should be made in consultation with the faculty advisor.
BN 1, Introduction to Neuroscience
MA 9, Introductory Calculus (or the equivalent)
BI 20, The Foundation of Living Systems
CG/PY 9, Quantitative Methods in Psychology, AM 165, Statistical Inference, PY 206, Experimental Design, or BC 213 Principles of Biostatistics and Data Analysis
Note: Students who wish to pursue a computational/modeling track are encouraged to take AM 165.
Systems Level and Integrative Courses:
PY 47, Brain Damage and the Mind
BN 106, Cognitive Neuroscience
CG 128, Computational Cognitive Science or AM 40 Mathematic Methods in the Brain Sciences
Students must choose two laboratory courses. Please note that due to enrollment limits in some lab courses, priority may be given to concentrators in that department. Students should therefore be prepared to choose from the other laboratory options.
BN 160, Experimental Neurobiology
BN 165, Structure of the Nervous System
BN 167, Neuropharmacology and Synaptic Transmission
BN 168, Computational Neuroscience
PY 103, Techniques in Physiological Psychology
PY 119, Human Sensory Processing
PY 120, Animal Learning and Behavior Laboratory
PY 184, Functional Magnetic Resonance Imaging: Theory and Practice
CG 102, Neural Modeling Laboratory
CG 124, Research Methods in Physiologic and Acoustic Phonetics
CG 145, Research in Psycholinguistics
CG/PY 153, Laboratory in Cognitive Processes
CG 198; BN 195, 196; or PY 199, Independent Study (may be used for only one laboratory in either the biological or cognitive category)
Four additional courses around a particular theme. Normally only one elective course that is below the 100 level may count towards the elective courses required. An appropriate (but additional) laboratory course may be used in lieu of one of the four elective courses.
CG 32, Biology and Evolution of Language
CG 48, Human Thinking and Problem Solving
CG/PY 63, Children's Thinking: The Nature of Cognitive Development
CG 105, Music and Mind (MU 123)
CG 123, Production, Perception and Analysis of Speech
CG 138, Ecological Approach to Perception and Action
CG 142, Syntactic Theory and Syntactic Processing
CG 143, Child Language Acquisition
CG 147, Language Learning Disorders
CG 148, Language and the Brain
CG 150, Subcortical Bases of Language and Thought
CG 154, The Evolution of Perceptual Systems
CG 156, Human Memory and Learning
CG 174, Topics in Language Acquisition
CG 186, Topics in Cognitive Science
CG 187, Concepts and Categories
BN 168, Computational Neuroscience
PY 75, Principles of Behavioral Neuroscience
PY 94, Developmental Psychopathology
PY 102, Psychophysiology of Sleep and Dreams
PY 178, Psychological Acoustics
PY 181, Seminar in Cognitive Neuroscience
PY 182, Cognitive Neuroscience of Emotion
Students are advised to take AM 33 (Methods of Applied Analysis I) and AM 34 (Methods of Applied Analysis II) as their two supporting science courses. Note that MA 10 is a prerequisite for these courses.
BN 168, Computational Neuroscience
AM 10, Introduction to Modeling
AM 136, Topics in Chaotic Dynamics
CG 136/CS 146, Introduction to Computational Linguistics
CS 141, Introduction to Artificial Intelligence
CS 148, Building Intelligent Robots
Students who would like to pursue a degree with honors are normally expected to have a B+ average within the concentration and are required to satisfactorily complete a written thesis and an oral defense.
Page last updated in April, 2006.