Philosophical framework for analyzing cognitive sciences. Recent developments in metaphysics and epistemology. Nature of scientific theories, methodologies of cognitive sciences, relations among cognitive sciences, relation of cognitive science to epistemology, and various philosophical problems.

Relations between brain activity and cognitive function in mammals. Working memory, attention, decision processing, executive function, categorization, planning, sequence processing. Behavioral/physiological perspectives. Disruption of cognitive function following brain damage. Extracellular recording of single neuron activity in nonhuman primates. Functional neuroimaging/magnetoencephalography in humans. prereq: instr consent

Advanced topics in cognition, brain, and behavior. Lecture, discussion, and student-led presentations of research papers on core topics of attention, memory, emotion, categorization, thinking, and language, and intersections between these areas. prereq: Psy grad student or instr consent

Lectures/discussions in cognitive sciences by local/visiting faculty.

Perceptual, motor, cognitive, and language development, and biological bases of each. Conceptual framework of research issues. prereq: Doctoral student, instr consent

This course is an introduction to the theories, data, and methods of Educational Psychology most relevant to understanding student thinking and learning. The first third of the course reviews those aspects of cognitive development that are foundational for education. The second third considers how cognitive psychology informs questions of learning, memory, knowledge, and transfer. With this background in place, the final third of the course will focus on the classroom: on instruction, motivation, individual differences, and group differences. The course concludes by considering the neural correlates of classroom learning.

Cognitive science research. Papers investigating how adults/children understand fundamental mathematical concepts. Papers drawn from psychology, neuroscience, education literatures. prereq: 5114 or equiv

Cognitive processes that take place during reading comprehension/implications of these processes for instruction/assessment.

This course is a graduate introduction to cognitive psychology. It is "advanced" in the sense that it focuses on higher-level cognition, and also in its emphasis on theories and models in addition to empirical results. Graduate students interested in cognitive psychology are invited to register for the course, regardless of disciplinary background.

Human memory encoding/retrieval. How we adaptively use memory. Brain systems that support memory. Episodic/semantic memory. Working/short-term memory. Procedural memory. Repetition priming. Prospective remembering. Autobiographical memory. prereq: 3011 or 3051 or honors or grad student

Human cognitive abilities (perception, memory, attention) from different perspectives (e.g., cognitive psychological approach, cognitive neuroscience approach). prereq: [Honors or grad] or [[jr or sr], [3011 or 3031 or 3051 or 3061]] or instr consent

Cognitive, computational, and neuroscience perspectives on visual perception. Topics include color vision, pattern vision, image formation in the eye, object recognition, reading, and impaired vision. prereq: 3031 or 3051 or instr consent

Theories/experimental evidence in past/present conceptions of psychology of language. prereq: Grad or [[jr or sr], [3011 or 3031 or 3051 or 3061]] or instr consent

Consequences of different types of brain damage on human perception/cognition. Neural mechanisms of normal perceptual/cognitive functions. Vision/attention disorders, split brain, language deficits, memory disorders, central planning deficits. Emphasizes function/phenomenology. Minimal amount of brain anatomy. prereq: Grad or [[jr or sr], [3011 or 3031 or 3051 or 3061]] or instr consent

Introduction to affective neuroscience. How brain promotes emotional/motivated behavior in animals/humans. Biological theories of emotion in historical/current theoretical contexts. Fundamental brain motivational systems, including fear, pleasure, attachment, stress, and regulation of motivated behavior. Implications for emotional development, vulnerability to psychiatric disorders. prereq: 3061 or 5061 or instr consent

Contemporary topics in learning and behavior theory. prereq: 5012 or instr consent

Recent research in visual psychophysics, visual neuroscience, and computer vision. prereq: 5031 or 5036 or equiv or instr consent

Recent advances in analysis of neural bases of cognitive functions. prereq: 5015 or instr consent

Social psychological theory/research on social inference and reasoning processes. Psychology of prejudice/stereotyping. prereq: Psych PhD candidate

Theory, design, programming, and evaluation of interactive application interfaces. Human capabilities and limitations, interface design and engineering, prototyping and interface construction, interface evaluation, and topics such as data visualization and World Wide Web. Course is built around a group project. prereq: 4041 or instr consent

In this course, you will learn and apply the principles of embodied computing to human-centered challenges. Through a semester-long team project, you will learn and demonstrate mastery of human-centered embodied computing through two phases: (1) investigating human needs and current embodied practices and (2) rapidly prototyping and iterating embodied computing solutions. One of the ways you will demonstrate this mastery is through the collaborative creation of a written document and project capstone video describing your process and prototype. prereq: CSci 4041, upper division or graduate student, or instructor permission; CSci 5115 or equivalent recommended.

Fundamental paradigms of algorithm and data structure design. Divide-and-conquer, dynamic programming, greedy method, graph algorithms, amortization, priority queues and variants, search structures, disjoint-set structures. Theoretical underpinnings. Examples from various problem domains. prereq: 4041 or instr consent

Introduction to AI. Problem solving, search, inference techniques. Logic/theorem proving. Knowledge representation, rules, frames, semantic networks. Planning/scheduling. Lisp programming language. prereq: [2041 or instr consent], grad student

Problems of pattern recognition, feature selection, measurement techniques. Statistical decision theory, nonstatistical techniques. Automatic feature selection/data clustering. Syntactic pattern recognition. Mathematical pattern recognition/artificial intelligence. Prereq: [2031 or 2033], STAT 3021, and knowledge of partial derivatives

Models of learning. Supervised algorithms such as perceptrons, logistic regression, and large margin methods (SVMs, boosting). Hypothesis evaluation. Learning theory. Online algorithms such as winnow and weighted majority. Unsupervised algorithms, dimensionality reduction, spectral methods. Graphical models. prereq: Grad student or instr consent

Issues in perspective transformations, edge detection, image filtering, image segmentation, and feature tracking. Complex problems in shape recovery, stereo, active vision, autonomous navigation, shadows, and physics-based vision. Applications. prereq: CSci 5511, 5521, or instructor consent.

Fundamental theory/practice in data visualization. Programming applications. Perceptual issues in effective data representation, multivariate visualization, information visualization, vector field/volume visualization. prereq: [1913, 4041] or equiv or instr consent

Introduction to software, technology/applications in virtual/augmented reality, 3D user interaction. Overview of current research. Hands-on projects. prereq: 4611 or 5607 or 5115 or equiv or instr consent

Current research issues in human-computer interaction, user interface toolkits and frameworks, and related areas. Research techniques, model-based development, gesture-based interfaces, constraint-based programming, event processing models, innovative systems, HCI in multimedia systems. prereq: 5115 or instr consent

Theories of intelligent agents. Agent architectures; knowledge representation, communication, cooperation, and negotiation among multiple agents; planning and learning; issues in designing agents with a physical body; dealing with sensors and actuators; world modeling. prereq: 5511 or instr consent

Scientific study of human language. Methods, questions, findings, and perspectives of modern linguistics. Components of the language system (phonetics/phonology, syntax, semantics/pragmatics); language acquisition; language and social variables; language and cognition; language change; language processing; language and public policy; language and cognition.

Concepts/issues in current syntactic theory. Prereq: LING 5001 and graduate student or honors student, or instructor consent

Modern syntactic theory. Syntactic phenomena in various languages. Syntactic argumentation, development of constraints on grammar formalisms. prereq: 5201 or instructor consent. LING 5201 is directed towards honors students and graduate students.

Analysis of sentence meaning. Semantic properties. Relations such as analyticity, entailment, quantification, and genericity. Philosophical background, formal techniques of semantic analysis, how sentence meaning depends on word meaning, syntax, and context. The role of semantics in grammatical theory. prereq: [4201 or 5201] or instr consent

Analysis of linguistic phenomena in relation to beliefs and intentions of language users; speech act theory, conversational implicature, presupposition, information structure, relevance theory, discourse coherence. prereq: [4201 or 5201] or instr consent

In this course, we will explore some semi-advanced to advanced topics in the field of natural language semantics. Broadly construed, natural language semanticists study how human beings process complexity in meaning in language, with the building blocks being how small units of meaning compose together to form larger and larger units, all of which are produced and understood in milliseconds. Building on the fundamental foundations of semantic theory learnt in Semantics, Advanced Semantics is geared towards providing expansive knowledge on several vital topics that current vibrant research in the field is concerned with. The array of topics include quantifier scope, definiteness and indefiniteness, plurals and mass/count nouns, attitude predicates and attitude ascription, event semantics, tense and aspect, modality and conditionals, questions, focus and alternative semantics, and imperatives. As we make our way through the critical last few decades of formal semantics through these vast and diverse topics, we will balance empirical coverage and formalism with development of intuition and methodology. Prerequisites: LING 5205 - Semantics I

Methods/issues in computer understanding of natural language. Programming languages, their linguistic applications. Lab projects. prereq: [4201 or 5201] or programming experience or instr consent

Syntax and semantics of natural language, with particular emphasis on the interface between the two. prereq: 5202, 5205 or instr consent

Current issues in syntactic theory. Topics vary. prereq: 5202, 5205 or instr consent

Topics vary. See Class Schedule. prereq: instr consent

Language-related issues in cognitive science from a linguistic perspective. Serves as elective for cognitive science minor, but only for linguistics nonmajors. prereq: instr consent

Lectures by team of faculty, problem sets in important physiological concepts, discussion of original research papers. prereq: NSc grad student or instr consent

Principles of organization of neural systems forming the basis for sensation/movement. Sensory-motor/neural-endocrine integration. Relationships between structure and function in nervous system. Team taught. Lecture, laboratory. prereq: NSc grad student or instr consent

Advanced seminar. prereq: 5561 or instr consent

The purpose of this course is to provide the student with a familiarity with the mathematical and statistical techniques to practice contemporary systems neuroscience. Topics are chosen with a focus on current areas of active research, as well as problems that have driven the field over the past twenty years. The class will combine lectures with discussions of important systems neuroscience papers, and will move at a fast pace. It is intended for graduate students and ambitious undergraduates. One major difference between this course and other math and statistics courses is the focus on systems neuroscience. Our examples will come from the Systems Neuroscience field. Our research priorities will come from Systems Neuroscience and our Friday paper discussions will draw exclusively from scholarly papers in Systems Neuroscience.

Mind-body problem. Philosophical relevance of cybernetics, artificial intelligence, computer simulation. Mental phenomena present the philosopher with a number of deep but inescapable puzzles and challenges. We tend to suppose that we know what it is to have a mind, to have beliefs, desires, etc., and we think that we know how to explain our own behavior and that of others -- and all of this without any formal training in the relevant science. All of this is surely amazing; indeed it verges on the outrageous. We admit to not knowing the makeup of the simplest structures, to not knowing how to explain the behavior of the simplest organisms -- we, OF COURSE, leave such issues to scientific investigation. Yet, at the same time, we think we know how to explain the behavior of this most complex of systems; we know how to do it, and we know what we are talking about when we explain behavior by citing the relevant beliefs, desires, etc. And, to repeat, we know all of this with no formal training. Strange indeed. Not only is this initial confidence puzzling, but attempts to articulate the mental story and to integrate it into the larger scientific picture have all proven problematical. We start our investigation with a very brief glance at a mid-century proposal that initiated a very different way of thinking about mind: the proposal by Turing -- one of the great minds of the 20th Century--that machines of a certain kind could exhibit intelligence. A story told in part in the recent movie, The Imitation Game. We then turn to some more traditional approaches to mind: Cartesianism, Behaviorism and Materialism. prereq: one course in philosophy or instr consent

Survey, against background of traditional issues, of contemporary developments in theory of knowledge.

Topics vary by offering. prereq: 4231 or instr consent

Topics vary by offering.

Topics vary by offering. prereq: instr consent

Contemporary issues concerning representation and explanation of scientific facts.