Cognitive Modeling
(Sequential Dependencies in Human Cognition)

CSCI 7782 / CSCI 4830 / PSYC 7215
Spring 2008

Tu, Th 14:00-15:15
ECOT 831


Professor Matt Jones (
Department of Psychology
Muenzinger E229
Phone TBA
Office Hours:  W 13:30-15:30 or by appointment

Professor Michael Mozer (
Department of Computer Science
Engineering Center Office Tower 7-41
(303) 492-4103
Office Hours:  Tu 12:30-13:30, W 13:00-14:00, or by appointment

Course Overview

Cognitive modeling involves the design of computer simulation and mathematical models of human cognition and perception.  The goals of cognitive modeling include:
The range of  modeling tools in cogntiive science are vast, and include production systems (sequential rule fiiring), neural networks, Bayesian probabilistic models, and pure mathematical theories.  All of these tools share the following virtues:
Models can be built at many levels of the reductionist hierarchy.  Single cell models characterize the details of neural function:  ion flow, membrane depolarization, neurotransmitter release, action potentials, neuromodulatory interactions.  Network models focus on neurophysiology and neuroanatomy of cortical regions, cell firing patterns, inhibitory interactions, and neural mechanisms of learning.. Functional models characterize the operation and interaction of components of the cognitive architecture and emphasize the transformation of representations.  Finally, models at the computational level focus on the input-output behavior of the system and provide a mathematical characterization of cognition and learning.  In this seminar, we'll emphasize the functional and computational level models.  Randy O'Reilly and Yuko Munakata in psychology teach an outstanding course that focuses on the single-cell and network levels.

We will read state-of-the-art research in the field of cognitive modeling, critique the work, and discuss its contributions to the field. Students will have the opportunity to develop their own models as well.  The course participants are likely to be a diverse group of students and faculty, some with primarily an engineering/CS focus and others primarily interested in cognitive science and cognitive neuroscience.

In 2008, we plan to focus on sequential dependencies in human cognition, i.e., how one experience influences subsequent perceptions, decisions, and judgements.  As a trivial example, if I ask the following question: "On a 1 to 10 scale, how bad is it to steal from a homeless person?", your response will depend on the preceding question I've asked.  Stealing will be given a lower rating if the previous question is, "How bad is it to shoot at someone who annoys you?" than if the previous question is, "How bad is it to not leave a 10% tip?

The instructors believe that sequential dependencies offer deep insight into mechanisms and principles of learning in the brain. Sequential dependencies occur across domains of cognition -- perception, attention, categorization, decision making, language, choice -- and at multiple time scales.  We will examine both experimental papers and models that have been built to explain sequential dependencies.  And throughout the course, we will seek common underlying mechanisms and normative principles to explain sequential dependencies.


The course is open to any students who have some background in cognitive science or artificial intelligence.  Some background in proababilty and statistics will be helpful, but iis not essential as long as you are willing to learn.

Course Requirements


In the style of graduate seminars, your primary responsibility for the course will be to read the series of papers before class and be prepared to come into class to discuss the paper (asking clarification questions, working through the math in the paper, relating the paper to other readings, critiquing the paper, presenting original ideas related to the paper).

Written Commentaries

For some of the readings, we'll ask you to write a one-page commentary on the paper, The commentary consists of approximately one page of comments, questions, or critiques of the assigned reading(s) for that class. This page will be due the day of class, and can include one or more of the following:
These commentaries are intended to promote careful thought about a paper before the session in which it is discussed. The point is not to give you more busy work, but rather to encourage you to jot down notes and questions as you read the papers. They will not be accepted after the class in which the paper is discussed.


You are required to present  a share of the papers during the course of the semester.  The presentation is meant to be a summary of the paper and its main ideas.  Ideally, two class members will collaborate to do each presentation, allowing you to work through the papers together.  We expect grad students to do twice the presentations that undergrads do.  We guess that grad students will do 2 or 3 presentations and undergrads will do 1.  

Presentations may be of the main article for the class (which everyone is required to read), or a supplementary article that we recommend.  By assigning students to present the supplementary articles, we can cover a lot more material without asking everyone to read every paper.

Semester Grades

Grades will be based roughly on the following:  oral presentations 20%, class discussions 20%, written commentary on papers 60%.

Class-By-Class Plan and Course Readings

All papers for the course can be found here or click on the individual readings.

Date Activity Reading Supplementary Reading(s) presenter
1/15 Course introduction
1/17 Vision and eye movements Fecteau & Munoz (2003) Exploring the consequences of the previous trial
1/22 Sharma et al. (2003) V1 neurons signal acquisition of an internal representation of stimulus location Maloney, L. T., Dal Martello, M. F., Sahm, C., & Spillmann, L. (2005). Past trials influence perception of ambiguous motion quartets through pattern completion Jones
1/24 Visual attention Kristjansson (2006) Rapid learning in attention shifts:  A review Kristjansson et al. (2006). Neural basis for priming of pop-out during visual search revealed with fMRI. Mozer
1/29 Mozer, Shettel, & Vecera (2006).  Control of visual attention: A rational account
Mozer & Baldwin (2008).  Experience-guided search: A theory of attentional control Mozer
1/31 Distinct mechanisms underlying sequential effects
Cho, Nystrom, Brown, Jones, Braver, Holmes, & Cohen (2002). Mechanisms underlying dependencies of performance on stimulus history in a two alternative forced choice task

2/5 Jentzsch & Sommer (2002) Functional localization and mechanisms of sequential effects in serial reaction time
Notebaert & Soetens (2003) . The influence of irrelevant stimulus changes on stimulus and response repetition effects. Jones
2/7 Motor control and response intiation Mozer, Kinoshita, & Davis (2004) Control of response initiation: Mechanisms of adaptation to recent experience
Song & Nakayama (2007). Automatic adjustment of visuomotor readiness Mozer;
Jones (Song & Nakayama)
2/12 Dixon & Glover (2004). Action and memory.
2/14 Sequence perception Gilovich, T., Vallone, R., & Tversky, A. (1985). The hot hand in basketball: On the misperception of random sequences

Gilden & Wilson (1995) Streaks in skilled performance

Bar-Eli, Avugos, & Raab (2006).  Twenty years of “hot hand” research: Review and critique

Matt Wilder, Dan Knights
Holger Dick (Gilden)
2/19 Steyvers & Brown (2006). Optimal change detection Johnson J, Tellis GJ (2005).  Blowing bubbles: Heuristics and biases in the run-up of stock prices Adam Bates (Johnson & Tellis); Mozer (Steyvers & Brown)
2/21 Perceptual judgement and estimation DeCarlo & Cross (1990) Sequential effects in magnitude estimation: Models and theory
Jesteadt, Luce, & Green (1977) Sequential effects in judgments of loudness Jones
2/26 Treisman & Williams (1984) A theory of criterion setting with an application to sequential dependencies
Lockhead & King (1983) A memory model for sequential effects in scaling tasks Mozer  & Adam Bates
2/28 Petrov & Anderson (2005) The dynamics of scaling
COMMENTARY IS NOT REQUIRED, BUT TRY TO HAVE A LOOK AT THE PAPER (We decided that two heavy papers in one week was too much.)

Petrov, Dosher, & Lu (2005). The dynamics of perceptual learning: An incremental reweighting model

Petrov, Dosher, & Lu (2006). Perceptual learning without feedback in non-stationary contexts: Data and model
3/4 Stewart, Brown, & Chater (2005). Absolute identification by relative judgement Brown, Marley, & Lacouture (2007) Is absolute identification always relative?
Stewart, N. (2007). Absolute identification is relative: A reply to Brown, Marley, and Lacouture
Laura Rassbach (Stewart, Brown & Chater, 2005)
3/6 Probability learning Myers, JL (1976). Probability learning. In W. K. Estes (Ed.), Handbook of learning and cognitive processes: Vol. 3. Approaches to human learning and motivation (pp. 171-205). Hillsdale, NJ: Erlbaum. Sutton & Barto (1998) Reinforcement learning, Section 2.6
Estes (1957) Theory of learning with constant, variable, or contingent probabilities of reinforcement
Anderson (1960) Effects of first-order conditional probability in a two-choice learning situation
Matt Wilder, Dan Knights
3/11 SUMMARY DAY Mozer & Jones
3/13 Gallistel et al.(2001)  The rat approximates an ideal detector of changes in rates of reward Tae Kwon
3/18 Sugrue, Corrado, & Newsome (2004). Matching behavior and the representation of value in the parietal cortex. Science, 304, 1782-1787. Adam Bates
3/20 Spacing of Practice
Landauer, T K (1986) How Much Do People Remember? Some Estimates of the Quantity of Learned Information in Long-term Memory, Cognitive Science 10, 477-493.
Landauer, T. K. (1975) Memory Without Organization: Properties of a Model with Random Storage and Undirected Retrieval, Cognitive Psychology, 7, 495-531.
Tom Landauer
4/1 Probability learning Behrens et al. (2007)  Learning the value of information in an uncertain world Supplementary material for article Laura Rassbach
4/3 Foraging Cuthill, Kacelnik, Krebs, Haccou, & Iwasa (1990) Starlings exploiting patches: The effect of recent experience on foraging decisions Real, L. A. (1991). Animal choice behavior and the evolution of cognitive architecture

Dukas & Real (1993) Effects of nectar variance on learning by bumble bees
Tres Spicher (Cuthill et al., 1990); Holger Dick (Real, 1991); Ron Le Bel (Dukas & Real, 1993)
4/8 Causality Chapman (1991) Trial order affects cue interaction in coningency judgment Lopez, Shanks, Almaraz, & Fernandez (1998) Effects of trial order on contingency judgments: a comparison of associative and probabilistic contrast accounts Kelsey Anderson (Lopez et al.)
4/10 Matute, Vegas, & Marez (2002) Flexible use of recent information in causal and predictive judgments
Mark Lewis-Pranzen
4/15 (Mozer away) Category Learning Jones & Sieck (2003). Learning myopia: An adaptive recency effect in category learning Stewart, Brown, & Chater (2002) Sequence effects in categorization of simple perceptual stimul Jones
4/17 (Mozer away) Jones, Love, & Maddox (2006) Recency effects as a window to generalization Jones, Maddox, & Love (2006) Stimulus generalization in category learning Jones (main reading); Hadjar Homaei (supplementary paper)
4/22 Sakamoto, Jones, & Love (2008) Putting the psychology back into psychological models: Mechanistic vs. rational approaches Nosofsky, Kruschke, & McKinley (1992) Combining exemplar-based category representations and connectionist learning rules Jones;
Hadjar Homaei (Nosofsky et al.)
4/24  Memory  Anderson, J. R.  & Schooler, L. (1991) Reflections of the environment in memory, Psychological Science, 2, 396-408. Anderson, Tweney, Rivardo, & Duncan (1997) Need probability affects retention: A direct demonstration Tres Spicher (Anderson & Schooler, 1991); Braden Wright (Anderson et al., 1997)
4/29 Brown, Steyvers, & Hemmer (2007). Modeling experimentally induced strategy shifts

Kruschke, J. (2006). Locally Bayesian learning.

Brown S, Steyvers M. (2005).  The dynamics of experimentally induced criterion shifts

Ron Le Bel (Brown et al., 2007); Hadjar Homaei (Kruschke, 2006)
5/1 Long-term dependencies Gilden (2001) Cognitive emissions of 1/f noise Sanborn & Griffiths. (2008). MCMC with people.
Kello, Beltz, Holden, & van Orden (2007) The emergent coordination of cognitive function
Mark Lewis-Pranzen (Gilden, 2001); Adam Bates (Sanborn & Griffiths)

Other Papers


Mozer, Kinoshita, & Shettel (2007). Sequential dependencies offer insight into cognitive control 

Stimulus and Response sequences -- alternation, priming of repetition, response priming

Jentzsch & Leuthold (2006?).  Response conflict determines sequential effects in short response-stimulus-interval serial response time tasks.  JEP:HPP
repetition suppression paper?

Soetens, Deboek, & Hueting (1984). Automatic Aftereffects in Two-Choice Reaction Time: A Mathematical Representation of Some Concepts

Dobbins, I.G., Schnyer, D.M., Verfaellie, M. & Schacter, D.L. (2004). Cortical activity reductions during repetition priming can result from rapid response learning. Nature, 428, 316-319.

Pashler & Baylis (1991). Procedural learning 2: Intertrial repetition effrects in speeded-choice tasks.  This paper suggests that the locus of sequential effects is primarily in the S-R mapping.

Task Difficulty

            Marios G. Philiastides, Roger Ratcliff, and Paul Sajda1. Neural representation of task difficulty and decision making during perceptual categorization:  A timing diagram.


Neo & Chua (2006). Capturing focused attention -- probably not worth doing a class on, but Vecera suggested reintrepreting these results in terms of sequential effects
Geng, J. J. and Behrmann, M. (2006). Spatial probability as an attentional bias in visual search, Perception and Psychophysics, 67, 7, 1252-1568.


Busemeyer & Myung (1988) A new method for investigating prototype learning


Anderson, J. (1997). A production system theory of serial memory.  Psychological Review, 104, 728-748.


Huettel, S. A.,  & Lockwood, G. R. (1999). Range effects of an irrelevant dimension on classification. Perception & Psychophysics, 61, 1624-45.
Lockhead (2004) Absolute judgements are relative: A reinterpretation of some psychophysical ideas
Brown, Marley, & Lacouture (2007) Is absolute identification always relative?
Stewart, N. (2007). Absolute identification is relative: A reply to Brown, Marley, and Lacouture. Psychological Review, 114, 533-538.
Mozer, Jones, & Shettel (2007). Context effects in category learning: An investigation of four probabilistic models
Jesteadt, Luce, & Green (1977) Sequential effects in judgments of loudness
Ward & Lockhead (1970) Sequential effects and memory in category judgments
Lockhead & King (1983) A memory model for sequential effects in scaling tasks
Parducci paper?

Change Detection

Steyvers slides 

Causal Learning

Allan (1993) Human contingency judgments: Rule based or associative?

Probability & Reinforcement Learning

Flood, MM (1954). Environmental non-stationarity in a sequential decision-making experiment. (Hardcopy)


Bouton (1993) Context, time, and memory retrieval in the interference paradigms of Pavlovian learning
Miller & Escobar (2001) Contrasting acquisition-focused and performance-focused models of acquired behavior


Bock 2002

Game theory

Vlaev & Chater (2006) Game relativity: How context influences strategic decision making
Jones & Zhang (2004) Rationality and bounded information in repeated games, with application to the iterated Prisoner’s Dilemma
Colman (1998). Rationality assumptions of game theory and the backward induction paradox. In: Rational models of cognition, ed. M. Oaksford & N. Chater. Oxford University Press. (BF311.R34 1998)

Long-term effects

Gilden & Wilson (1995) On the nature of streaks in signal detection
Gilden, Thornton, & Mallon (1995) 1/f noise in human cognition
Gilden (1997) Fluctuations in the time required for elementary decisions
Thornton & Gilden (2005) Provenance of correlations in psychological data
Wagenmakers, Farrell, & Ratcliff (2005) Human cognition and a pile of sand: A discussion on serial correlations and self-organized criticality
Farrell, Wagenmakers, & Ratcliff (2006) 1/f noise in human cognition: Is it ubiquitous and what does it mean?
van Orden, Holden, & Turvey (2005) Human cognition and 1/f scaling
van Orden, Holden, & Turvey (2003) Self-organization of cognitive performance
Gilden & Hancock (2007) Response variability in attention deficit disorders
Wagenmakers, Farrell, & Ratcliff (2004) Estimation and interpretation of 1/f^\alpha noise in human cognition

Decision Making

Vlaev, I., Chater, N., & Stewart, N. (2007b). Relativistic financial decisions: Context effects on retirement saving and investment risk preferences. Judgment and Decision Making, 2, 292-311.
Vlaev, I., Chater, N., & Stewart, N. (2007a). Financial prospect relativity: Context effects in financial decision-making under risk. Journal of Behavioral Decision Making, 20, 273-304

Legal Disclaimers

If you qualify for accommodations because of a disability, please submit a letter from Disability Services in a timely manner so that your needs may be addressed.  Disability Services determines accommodations based on documented disabilities.  Contact: 303-492-8671, Willard 322, and http://www.Colorado.EDU/disabilityservices.

Campus policy regarding religious observances requires that faculty make every effort to reasonably and fairly deal with all students who, because of religious obligations, have conflicts with scheduled exams, assignments or required attendance.  Please see me if you have concerns with our syllabus.  See full details of campus policy at

Students and faculty each have responsibility for maintaining an appropriate learning environment. Students who fail to adhere to such behavioral standards may be subject to discipline. Faculty have the professional responsibility to treat all students with understanding, dignity and respect, to guide classroom discussion and to set reasonable limits on the manner in which they and their students express opinions.  Professional courtesy and sensitivity are especially important with respect to individuals and topics dealing with differences of race, culture, religion, politics, sexual orientation, gender variance, and nationalities.  Class rosters are provided to the instructor with the student's legal name. I will gladly honor your request to address you by an alternate name or gender pronoun. Please advise me of this preference early in the semester so that I may make appropriate changes to my records.  See polices at and at

All students of the University of Colorado at Boulder are responsible for knowing and adhering to the academic integrity policy of this institution.  Violations of this policy may include: cheating, plagiarism, aid of academic dishonesty, fabrication, lying, bribery, and threatening behavior.  All incidents of academic misconduct shall be reported to the Honor Code Council (; 303-725-2273). Students who are found to be in violation of the academic integrity policy will be subject to both academic sanctions from the faculty member and non-academic sanctions (including but not limited to university probation, suspension, or expulsion). Other information on the Honor Code can be found at  and at

The University of Colorado at Boulder policy on Discrimination and Harassment (, the University of Colorado policy on Sexual Harassment and the University of Colorado policy on Amorous Relationships applies to all students, staff and faculty.  Any student, staff or faculty member who believes s/he has been the subject of discrimination or harassment based upon race, color, national origin, sex, age, disability, religion, sexual orientation, or veteran status should contact the Office of Discrimination and Harassment (ODH) at 303-492-2127 or the Office of Judicial Affairs at 303-492-5550.  Information about the ODH and the campus resources available to assist individuals regarding discrimination or harassment can be obtained at