Fall 2014
Topics In Cognitive Science
CSCI 7772 | EDUC 7775 | LING 7775 | PHIL 7775 | PSYC 7775 | SLHS 7775

Fri 12:00-14:00
Muenzinger D430


Professor Michael Mozer
Department of Computer Science
Engineering Center Office Tower 741
Office Hours

Course Objectives

The intent of this course is to expose students to the breadth and depth of current research issues in the field of Cognitive Science. Students will attend presentations of innovative theories and methodologies of Cognitive Science that they will be expected to critically evaluate. Students will participate in the ICS Colloquium Series and also the ICS Distinguished Speakers series that hosts internationally recognized Cognitive Scientists who share and discuss their current research. Following colloquia, students will have the opportunity to engage in analysis and discussion of the work that was presented to further their understanding of the material.


This course is a requirement for students interested in obtaining either the joint Cognitive Science Ph.D. or a graduate certificate in Cognitive Science.  Others may enroll in the course as space is available.

There are no prerequisite courses. This course is primarily offered for one unit of credit, and students in one of the Cognitive Science academic programs must enroll in this course for two semesters.  Students who have strong need to obtain two units of credit for this course in one semester may potentially do so with the instructor's permission. For each unit of credit, students must attend at least six talks and write commentaries on these talks.

Course requirements

Talk attendance

The primary requirement for the course is to attend and comment on a minimum of 6 (or 12) colloquia in Cognitive Science, including the ICS Distinguished Speaker series. The primary opportunity to attend Cognitive Science colloquia is via the ICS speaker series, the schedule for which can be found at  However, not every talk in the ICS series is approved for this course, and many other talks on campus are approved.  The official list of approved talks for this semester appears on this page.

When I am alerted to talks on campus with significant cognitive science content, but which are not part of the ICS speaker series, I will announce them to the class. If you hear of one that I haven't announced, please forward the time, location, abstract, and title to me, and if I determine it to have significant cognitive science content, I will announce the talk to the class as an option.  If for any reason we have a shortage of talks this semester, I can supplement the ICS schedule by bringing in advanced graduate students and faculty during the ICS colloquium slot.

In some semesters that this course is taught, ICS asks students in this course to sign an attendance sheet.  I do not operate like this.  Instead, the commentary you write (see below) will be the mark of your attendance.  

Background readings

For the ICS colloquia, students are responsible for reading appropriate background materials (e.g., journal articles, book chapters) provided by the speaker to serve as grounding for the colloquium.  These materials will be distributed to students 1-2 weeks prior to the colloquium.


For each talk attended, students are to write a commentary of no more than one page.  For the commentary, I want to get your reactions to the talk.  The commentary can include:
  • a summary of what you think the main or most interesting ideas are behind the work, However, there is no need to provide a complete abstract of the talk. I want to know the student's perspective on what the work had to offer.
  • questions about the material for further discussion, either clarification questions or points of disagreement with the authors (``I don't see how such and such will work as the speaker claims...'').
  • comments on how the talk relates to other talks the student has attended or other papers the student has read.
  • a critique of the work. What are the flaws in the ideas presented? What are the limitations? Did the speaker place their work in the appropriate theoretical context? Did the speaker overstate their results? 
  • If the talk gave you inspiration for new research ideas, describe these ideas.  The ideas might be extensions of the work, new directions to move in, or applications of the work to other subfields of cognitive science.
Think of the commentary as your opportunity to share your thoughts and insights with both me and the entire class. I have created a google group,, and your commentaries should be sent to the group for reaction by the professor and other students. To simplify our lives, I'd like the commentaries to be mailed to the group, with a email subject line "[STUDENT LAST NAME] COMMENTARY [SPEAKER]". You are invited to comment on commentaries and to add your reactions to the commentaries, so that we get a group electronic discussion going.

You may find that the number of emails associated with the group is too large. If you wish, you may change your group settings so that you receive weekly summaries of the group discussions or that you log into the group to read the discussions.

You will recieve an invitation from me to join the google group.  You may join either using your University of Colorado login as your google login (including the, or you may join with a gmail address. You may have to request an invitation to join with your gmail address.

Commentaries are due within two weeks of the talk date. I've taught this course in the past without including a deadline, and some students delayed submitting commentaries until the semester's end and the discussion group became temporally disjointed. It will benefit our discussions if we're all thinking about the same talks at the same time. I would tighten the deadline even further, but some participants mentioned that they needed a bit of time to digest a talk and read some of the opinions of their classmates before having the confidence to broadcast their views.

All commentaries are due by December 14, 2014.


To receive an "A" grade in the course, the student must submit 6 (or 12) commentaries that reflect an informed opinion on the research discussed, and student must participate in some electronic discussion of others' commentaries and of the talks in general.  Students will fail the course if they do not submit at least 5 commentaries.

Sanctioned colloquia                NOTE: MORE WILL BE ADDED AS SEMESTER GOES ON

Date and Location Speaker Topic Reading
9/11 15:30-16:30
Eng Center ECCR 265
Gerhard Fischer, Comp Sci. Dept, University of Colorado Rich landscapes of learning: Exploring core competentcies for MOOCs and residential, research-based universities

Learning is the central activity of the 21st century. It needs to be reconceptualized, nurtured, and supported to meet numerous intellectual and economic challenges by taking advantage of transformative theoretical frameworks and innovative technologies. Massive, Open, Online Courses (MOOCs) are receiving world-wide attention as a means to revolutionize education. The excitement and hype around MOOCs is grounded in promises being disruptive, being free, and providing a totally new kind of learning experience. The attention for MOOCs has moved beyond academic circles. Neither panacea nor snake oil, MOOCs evoke serious questions that deserve informed debate grounded in the learning sciences complementing the current existing discussions from economics and technology.  The presentation will analyze MOOCs as one component of a rich landscape for learning. In doing so, MOOCs can serve as a forcing function to identify and reflect on the core competencies of residential, research-based universities (such as CU Boulder) in nurturing and supporting aspects of learning that cannot be easily addressed by MOOCs.
Muenzinger D430
Todd Gureckis, Psychology Dept., NYU Understanding the decision to learn

Any complete theory of human learning must explain not only what is gleaned from the information we experience, but also the capacity for our choices and actions to expose that information.  Interestingly, many experimental studies of learning and memory emphasize "passive" learning by limiting participants’ control over the information they experience at each point in time. In this talk, I will discuss recent work in my lab exploring how people gather information in "self-directed" learning environments - those where the learner is in control of what to learn about and when to learn it.  The primary aim of this research is to characterize the information sampling strategy that participants use to reduce their uncertainty, and to examine how self-directed learning influences acquisition of new knowledge.  The evidence presented in the talk suggests three key take-home points:  1.) people can learn faster when they can select and sequence learning episodes themselves, but this depends, in a dynamic way, on the structure of the to-be-learned concepts and the space of hypotheses that the learner considers 2.) people select information gathering strategies in an adaptive fashion which trades off their expected performance and implied cognitive effort and 3.) self-directed learning helps to enhance memory by helping learners coordinate stimulus presentation with their current preparatory or attentional state.  Implications of this work for education, instructional design, as well as the cognitive science of learning will be entertained.

9/18 15:30-16:30 ECCS 265 Aaron Clauset, Computer Science, U. of Colorado research area: computational social science, network theory, complex systems
Muenzinger D430
Samar Husain
Linguistics Dept., University of Potsdam
Strong expectations cancel locality effects: Evidence from Hindi

Expectation-driven facilitation (Hale, 2001; Levy, 2008) and locality-driven retrieval difficulty (Gibson, 1998, 2000; Lewis & Vasishth, 2005) are widely recognized to be two critical factors in incremental sentence processing; there is accumulating evidence that both can influence processing difficulty. However, it is unclear whether and how expectations and memory interact. We first confirm a key prediction of the expectation account: a Hindi self-paced reading study shows that when an expectation for an upcoming part of speech is dashed, building a rarer structure consumes more processing time than building a less rare structure. This is a strong validation of the expectation-based account. In a second study, we show that when expectation is strong, i.e., when a particular verb is predicted, strong facilitation effects are seen when the appearance of the verb is delayed; however, when expectation is weak, i.e., when only the part of speech “verb” is predicted but a particular verb is not predicted, the facilitation disappears and a tendency towards a locality effect is seen. The interaction seen between expectation strength and distance shows that strong expectations cancel locality effects, and that weak expectations allow locality effects to emerge.
Muenzinger E214
Stephen Palmer, UC Berkeley, Psychology Dept. Visual perception and aesthetics
10/6 16:00-17:00 Muenzinger E214 Matt Jones, Psychology Department, U. of Colorado Learning and Representation

Representation -- the manner in which information or knowledge is encoded in the mind -- is at the heart of cognitive science. Moreover, flexibility of representation is arguably fundamental to the power of human intelligence, in that representing a problem or task environment in a way that somehow captures its inherent structure can be critical to successful learning, generalization, and discovery. This talk will summarize my work on two questions: (1) how can we as researchers identify the representation a person is using in a given task, and (2) how do people adapt or construct representations to suit their needs? For the first question, I will focus on my work using sequential effects in repeated tasks to reveal representations and learning mechanisms, the basic principle being that sequential effects are a signature of how knowledge is updated. For the second question, I will describe a theoretical framework integrating theories of representation with reinforcement learning, and my lab's efforts to develop models that build new concepts by discovering structure in the world. Finally, I will summarize some of my more meta-theoretical work on the explanatory contributions of computational models of cognition, and explain how some of the problems I have identified in currently influential models of decision-making might be solved by incorporating my work on learning and sequential effects.
Muenzinger D430
Jordan Boyd-Graber,
Comp. Sci. Dept., University of Colorado
Thinking on your Feet: Reinforcement Learning for Incremental Language Tasks

In this talk, I'll discuss two real-world language applications that require "thinking on your feet": synchronous machine translation (or "machine simultaneous interpretation") and question answering (when questions are revealed one piece at a time).  In both cases, effective algorithms for these tasks must interrupt the input stream and decide when to provide output.

Synchronous machine translation is when a sentence is being produced one word at a time in a foreign language and we want to produce a translation in English simultaneously (i.e., with as little delay between a foreign language word and its English translation). This is particularly difficult in verb-final languages like German or Japanese, where an English translation can barely begin until the verb is seen. Effective translation thus requires predictions of unseen elements of the sentence (e.g., the main verb in German and Japanese, or relative clauses in Japanese, or post-positions in Japanese). We use reinforcement learning to decide when to trust our verb predictions. It must learn to balance incorrect translation versus timely translations, and must use those predictions to translate the sentence.

For question answering, we use a specially designed dataset that challenges humans: a trivia game called quiz bowl. These questions are written so that they can be interrupted by someone who knows more about the answer; that is, harder clues are at the start of the question and easier clues are at the end of the question. We create a recursive neural network to predict answers from incomplete questions and use reinforcement learning to decide when to guess.  We are able to answer questions earlier in the questions than most college trivia contestants.
10/10 18:00-19:30 Duane Physics G125 William Bechtel, Philosophy, UCSD Networks and Dynamics: 21st Century Neuroscience

This talk is part of the conference entitled, "Neurons, Mechanisms, and the Mind: The History and Philosophy of Cognitive Neuroscience".  Two other talks at the conference are also authorized for the Topics course -- Carrie Figdor (U. of Iowa), "On the proper domain of psychological predicates" (Saturday Oct 11, 17:00-18:30, Duane G131) and Tor Wager (CU Boulder), "Role of verbal reports in studies on emotion and pain" (Sunday Oct 12, 16:00-17:30, Duane G125)
Muenzinger D430
Tom Yeh, Computer Science, University of Colorado 3D Tactile Picture Books for Children with Visual Impairments

Abstract: Tactile pictures and graphics are critical to the development of emergent literacy skills for children with visual impairments. However the practices of designing and producing tactile graphics have previously been limited to a small community due to the cost of manufacturing processes and bounded expertise in tactile graphic design and 3D modeling. In this talk, I will present findings from seven workshops, conducted to identify and evaluate the barriers stakeholders encounter when designing 3D printable tactile picture books, along with a series of design guidelines to reduce or eliminate these barriers. Moreover, I will describe a set of 3D-printable models designed as building blocks for creating movable tactile pictures that can be touched, moved, and understood by children with visual impairments. Examples of these models are canvases, connectors, hinges, spinners, sliders, lifts, walls, and cutouts.

3D printed tactile picture books for children with visual impairments: a design probe

Technology to support emergent literacy skills in young children with visual impairments
10/23 15:30-16:30 ECCR 265

Warning: date may shift later in the semester to accommodate outside speakers
Michael Mozer, Comp. Sci., University of Colorado Bayesian Optimization: From A/B Testing To A-Z Testing

A/B testing is a traditional method of conducting a randomized controlled experiment to compare the effect of two treatments, A and B, on human subjects. For example, two alternative banner ads may be served to evaulate which is more effective in driving click throughs. A/B testing is used not only for marketing and web design but is the dominant paradigm in the experimental behavioral sciences used to understand human learning, reasoning, and decision making. Although the method can be extended to compare a handful of treatments, it does not solve the problem one often faces:  searching over a large, possibly combinatorial or continuous space of alternatives to identify the treatment that achieves the best outcome.  We describe a solution to this problem using Gaussian process surrogate-based optimization, a Bayesian method that relies on generative probabilistic models of human choice and judgment. Instead of assigning many human subjects to each of a few of treatments, the technique evaluates a few subjects on each of many treatments. The technique leverages structure in the space of treatments to infer the function that relates treatment to outcomes.  We show the efficiency and accuracy of the technique on a range of problems, including: identifying preferred color combinations, maximizing charitable donations, and improving student learning of facts and concepts.
10/24 12:00-13:00 Muenzinger D430 Shaun Kane, Computer Science, University of Colorado
research area: Accessible user interfaces, mobile human-computer interaction
10/30 15:30-16:30 ECCR 265 Karon MacLean, University of British Columbia Applied  Perspectives on Haptic Interaction with Regard to Attention, Affect and Pushing Robots Around

Buzzing cell phones and jolty game controllers: This is where the vast majority of users today still are when they think "haptics" (interaction through the sense of touch), despite accelerating technical innovation in recent years. What will ultimately change this?  Within the haptics research community and related industries, developments include pre-commercial advances in tactile and force feedback actuation and sensor development (much of it driven by the popularity and shortcomings of mobile and touchscreen interfaces). These are further spurred by advances in wearable and context-aware computing, robotics, embedded sensing and flexible graphic displays.  Human computer interaction designers meanwhile seek haptic solutions to problems ranging from everyday to esoteric or highly specialized.

MacLean’s group has tried to bring effective haptic interaction into people's lives by closely examining how touch (in either direction) can help address real human needs with the benefit of both low- and high-tech innovation. MacLean will give a sense of these efforts with several stories that highlight some of their driving research questions, including:

-- Attention: Touch may be great way to offload the visual sense, but it can just as easily make matters worse. Through integration with contextual information, can we craft a display system with broad potential utility that is attentionally sustainable?
-- Affect: What kind of affective information is available in gestural touch? If you could sense it (easily, at low cost) what are some things you could do with it?
-- Pushing Robots Around: What's the right place for informal, functional touch in the close-proximity robot-human workplace?

BIO: Karon MacLean is Professor of Computer Science at the University of British Columbia, Canada, with a B.Sc. in Biology and Mech. Eng. (Stanford) and a M.Sc. and Ph.D. (Mech. Eng., MIT)  and time spent as professional robotics engineer (Center for Engineering Design, University of Utah) and interaction researcher (Interval Research, Palo Alto). At UBC since 2000, her research specializes in haptic interaction: cognitive, sensory and affective design for people interacting with the computation we touch, emote and move with, whether robots, touchscreens or mobile activity sensors. She has innovated in human computer interaction curriculum design and teaching practices.
10/31 12:00-13:00 Muenzinger D430 R. McKell Carter, Psychology and Neuroscience, University of Colorado The temporal parietal junction constructs a social context for decision making

Our preferences change dramatically with social context. While the presence of a grandmother may discourage the purchase of alcohol, the presence of an old friend may strongly increase the likelihood of drinking. In previous work, we have identified a region of the brain, the temporal parietal junction (TPJ), that is uniquely predictive of behavior in a social setting but not in a non-social setting. While this provides evidence that the TPJ is uniquely involved in social function, a number of alternative hypotheses describing TPJ function have been offered. In an effort to reconcile these alternative explanations, we propose the Nexus model of TPJ function. The Nexus model of TPJ function proposes that novel functions (like the ability to consider others intentions) arise when divergent processes like memory, attention, semantic, and social representations come into close proximity as is the case in the TPJ. This model makes specific function and localization predictions. I will describe ongoing work testing some of these predictions in both basic and translational settings, as well as some future work made possible by the extraordinary community at CU Boulder. We conclude that the TPJ constructs a social context that is utilized by frontal regions to produce the dramatic effects on decision making we see when interacting with others.

11/20 16:30-17:30 
Imig Music Chamber Hall (C199)
Ian Quinn, Yale Toward a computational archeology of pre-18th century music cognition

Standard accounts of the music-theoretic revolution of the 18th century speak of a transition from modal to tonal organization in the music itself. One effect of this transition is a reduction in the number of modes from twelve (in the systems of Glarean and Zarlino) to two: major and minor. Computerized analytical work on datasets of late medieval office chants, early Lutheran chorales, 17th-century English madrigals, and other repertories suggests that the local organization of music in different modes, particularly between cadences, does not differ as much as the standard accounts (based on contemporaneous treatises rather than on musical data) would have us believe. The history of solmization, which, as in modern la-based minor, does not typically hypostatize scale degree prior to the introduction of the rule of the octave, reinforces this view.

BIO: Ian Quinn is Professor and Director of Undergraduate Studies in the Department of Music at Yale, where he also teaches in the Cognitive Science Program. He has won the Emerging Scholar Award and the Outstanding Publication Award from the Society of Music Theory. He was Editor of the Journal of Music Theory from 2004 to 2011. Current projects focus on Steve Reich, 17th-century tonality, and computational methods for corpus analysis.
12/4 15:30-16:30 ECCR 265 Leysia Palen, Computer Science, University of Colorado Frontiers in Crisis Informatics
Crisis informatics addresses socio-technical concerns in large-scale emergency response. Additionally it expands consideration to include not only official responders (who tend to be the focus in policy and technology-focused matters), but also members of the public. It therefore views emergency response as a much broader socio-technical system where information is disseminated within and between official and public channels and entities. Crisis informatics wrestles with methodological concerns as it strives to develop new theory and support informed development of ICT and policy. Palen will describe the range of work her team has engaged in at CU-Boulder since 2006, and highlight the different branches of crisis informatics research through discussion of the multidisciplinary research they have conducted here.
12/4 17:00-18:00 SLHS 230 Ron Gillam, Utah State Information Processing, Cognitive Load, and Language Disorders: From Theory to Clinical Practice

This presentation will summarize a neural efficiency model of language disorders that is based on concepts from evolutionary psychology, cognitive load theory and Cowan’s embedded processes theory of working memory.  Dr. Gillam will explain how language disorders could result from interactions between deficits in biologically endowed language knowledge and working memory processes. He will present data from four preliminary studies that support the potential of functional Near Infrared Spectroscopy (fNIRS) as tool for informing our understanding of cognitive load and its relationship to attention, memory and language comprehension. Finally, he will discuss the therapeutic implications of the neural efficiency model and future research directions.
12/5 9:00-10:00 SLHS 230 Sandra Gillam, Utah State Fuzzy Connections Between Language Learning Principles and Intervention Strategies: Evidence from Narrative Intervention Studies

Alan Kamhi has suggested that we can improve clinical practices for children with language and learning disorders by employing intervention strategies that are based on learning principles from studies of language development.  However, general learning principles do not always translate readily into effective language intervention practices.  Even theoretically sound, well-intentioned,  and carefully implemented interventions can result in equivocal  outcomes.  This presentation will summarize what we have learned about narrative language intervention procedures in light of new theories of working memory and language development.
12/5 10:30-11:30 CINC "fishbowl" (conference room near building entrance) Karl Moritz Hermann, Oxford
Distributed Representations for Compositional Semantics

The mathematical representation of semantics is a key issue for Natural Language Processing (NLP). A lot of research has been devoted to finding ways of representing the semantics of individual words in vector spaces. However, natural language usually comes in structures beyond the word level, with meaning arising not only from the individual words but also the structure they are contained in at the phrasal or sentential level. In this talk we explore methods for learning distributed semantic representations and models for composing these into representations for larger linguistic units by exploiting neural models.

This talk focuses on extending the distributional hypothesis to multilingual data and joint-space embeddings by leveraging parallel data. The models of this class do not rely on word alignments or any syntactic information and are successfully applied to a number of diverse languages and tasks. Subsequently, I will present a novel technique for semantic frame identification, again by using distributed semantic representations. Here, we learn a model that projects the set of word representations for the syntactic context around a predicate to a low dimensional representation. With a standard argument identification method inspired by prior work, this approach achieves state-of-the-art results on FrameNet-style frame-semantic analysis.
12/9, 16:00-17:00, Muenzinger E214 Richie Davidson, Psychology & Psychiatry, University of Wisconsin Madison Order and Disorder in the Emotional Brain

Emotions are at the core of human personality, they define each person’s uniqueness and they shape resilience and vulnerability to adversity. Perhaps the single most salient characteristic of emotion is the variability across individuals in how each responds to emotional cues and challenges. This variability is termed “affective style.” Different parameters of affective style can be objectively measured and are instantiated in different underlying neural circuits. Activation patterns assessed with neuroimaging are related to different parameters of affective style and are consistent over time within individuals. Specific patterns of brain activity are related to vulnerability to particular types of disorders. Moreover, patterns of central brain function are related to peripheral biological systems that play a role in physical health and illness. Despite their consistency over time within individuals, these patterns of neural activity are not immutable to change but rather can be transformed through systematic mental training such as meditation. The literature on neuroplasticity provides a framework for understanding these changes. This latter body of evidence supports the view that happiness, well-being and emotional balance are best regarded as the product of trainable skills.
12/12 12:00-13:00 Muenzinger D430 Susan Brown,
University of Colorado
From Visual Prototypes of Action to Metaphors: The Imagact Visual Ontology and Its Extension to Figurative Meanings

Action verbs are some of the most polysemous words, with one form often covering a wide range of physical actions, as well as extending to various figurative meanings. The range of variations within and across languages can cause trouble for second language learners and natural language processing tasks. IMAGACT is a corpus-based ontology of action concepts that makes use of the universal language of images to identify the different physical action types expressed by verbs in English, Italian, Chinese and Spanish.  IMAGACT makes explicit the variation of meaning of action verbs within one language and allows comparisons of verb variations within and across languages. Because the action concepts are represented with videos, extension into new languages is easily done using competence-based judgments by native-language informants.
In the first half of this talk, I will describe the resource's rationale and infrastructure and demonstrate the types of linguistic information a user can derive from it. In the second half, I will describe the extension of this resource to figurative meanings. We first established three main categories of secondary meaning variation--metaphor, metonymy and idiom--and criteria for creating types within these categories for each verb. The criteria rely heavily on the images that compose the IMAGACT ontology of action and on widely accepted processes of meaning extension in linguistics. Although figurative language is known for its amorphous, subjective nature, we have endeavored to create a standard, justifiable process for determining figurative language types for individual verbs. We specifically highlight the benefits that IMAGACT’s representation of the primary meanings through videos brings to the understanding and annotation of secondary meanings.

Additional information for students (click to read)