All colloquia take place on Friday from 12:00 to 2:00 pm (unless otherwise noted) in Room D428 and D430 on the fourth floor of the Muenzinger Psychology Building.
If you have questions, please call the ICS Office at 303-492-5063.
August 28, 2017
First Day of Classes
September 8, 2017
Opening Session - Tamara Sumner
Director, Institute of Cognitive Science
September 15, 2017 - Distinguished Speaker Talk
*Moved to Muen E214*
Seth Merrin Professor of Philosophy, Co-director - Center for Cognitive Studies, Tufts University
Title: What Can You Say Without Syntax? A Hierarchy of Grammatical Complexity
Abstract: What would a language be like which lacked syntactic structure, and which mapped directly between phonology and meaning? To explore this question, we propose a hierarchy of grammatical complexity for natural languages. Unlike the familiar Chomsky hierarchy, which deals only with uninterpreted formal languages, this hierarchy concerns the machinery available to map between sound and meaning. It ranges from languages that allow only one-word utterances to fully complex languages such as English, and includes a number of possibilities that lack recursion.
Corresponding to each of these types of grammar, we propose a set of possible interface rules that correlate linguistic structure with meaning. In particular, the interface rules allow for pragmatic elaborations of meaning beyond that provided by the individual words. As the linguistic structure becomes more complex, it offers more affordances for complex principles of interpretation. In many cases, interface rules can do the sort of work normally attributed to syntax. For instance, a rule such as “Agent First” correlates a thematic role in semantics with a linear position in linguistic expression. It can implement constraints on word order even with a grammar that lacks grammatical categories and that simply concatenates words. Crucially, it turns out that the interface rules useful for less complex languages scale up to fully complex languages as well.
This hierarchy proves useful in differentiating various linguistic and quasi-linguistic phenomena for which linguists have previously had only the binary distinction “grammar” versus “no grammar.” Examples include the early stages of language acquisition by children and adults, homesigns, emerging sign languages such as Al-Sayyid Bedouin Sign Language and Central Taurus Sign Language, and the “perceptual strategies” found in language comprehension by normal speakers. Many peripheral constructions of English and other fully developed languages utilize only the power of lower steps in the hierarchy. Finally, some “full” languages such as Riau Indonesion and Pirahã appear only to use principles from lower domains of the hierarchy.
We conclude that the human language faculty is a palimpsest that includes many of these layers. The upper layers are more difficult to acquire and process, and possibly require the lower layers for scaffolding. It is plausible that some of of these layers represent stages in the evolution of the modern human language capacity.
September 29, 2017
Assistant Professor, Department of Computer Science, Courant Institute of Mathematical Sciences, Center for Data Science, New York University
October 6, 2017
Assistant Professor, Department of Human Development and Family Studies, Colorado State University
Title: Modifiers of Structural and Functional Brain Aging - From Physical Activity to Occupational Exposures
Abstract: As the world’s population is aging, there is a pressing need to understand how lifestyle exposures shape the adult brain, slowing down or accelerating age-related decline. I will present our reserach on the associations of physical activity, aerobic fitness, and occupational exposures with structural and functional MRI indices of brain health, as well as results from the exercise and dance intervention study in older adults.
October 13, 2017
Professor, Institute of Cognitive Science, University of Colorado Boulder
Title: Amplifying Human Capabilities on Visual Categorization Tasks
We are developing methods to improve human learning and performance on challenging visual categorization tasks, e.g., bird species identification, diagnostic dermatology. Our approach involves inferring _psychological embeddings_ -- internal representations that individuals use to reason about a domain. Using predictive cognitive models that operate on an embedding, we perform surrogate-based optimization to determine efficient and effective mean of training domain novices as well as amplifying an individual's capabilities at any stage of training. Our cognitive models leverage psychological theories of: similarity judgement and generalization, contextual and sequential effects in choice, attention shifts among embedding dimensions. Rather than searching over all possible training policies, we focus our search on policy spaces motivated by the training literature, including manipulation of exemplar difficulty and the sequencing of category labels. We show that our models predict human behavior not only in the aggregate but at the level of individual learners and individual exemplars, and preliminary experiments show the benefits of surrogate-based optimization on learning and performance.
This work was performed in collaboration with Brett Roads at the University of Colorado.
October 20, 2017
Title: A Dynamical Systems Model of the Nervous System
Many key issues in neuroscience are limited by our understanding of how different parts of the nervous system interact during different states of activity, and how these interactions give rise to emergent physiological and behavioral states. Several buzzwords such as "probability machine", "oscillatory coupling", and "quantum computing" are often associated with popular models of these interactions, but there is still considerable debate about what these processes imply about brain and behavior. In this talk, I will describe a model of the nervous system that attempts to shed light on these emergent interactions and their underlying mechanisms. This model describes similarities in the anatomical and functional organization of six general classes of nervous system activity: transduction, FATS encoding, integration, cognition, executive function, and modulation; and how dynamical interactions between these different components can give rise to observable phenomena such as local field potentials, EEG/MEG, neural oscillations, and hemodynamic responses. I will discuss how these emergent phenomena may inform our understanding of the probabilistic, oscillatory, and quantum models of the brain, and will demonstrate and discuss the possible experimental and clinical applications of this and other systems models…all in less than an hour!
November 3, 2017
Professor, Philosophy, University of Colorado Boulder
Title: Cognition without Persons?
What is cognitive science out to explain? What are its ultimate explananda? In this talk, I contrast two possibilities, arguing against the first and exploring the implications of the second. The first view, which predominates in philosophy of mind, takes the ultimate explananda of cognitive science to be personal-level capacities or properties, where the personal-level is a layer of reality populated by the states and entities we encounter in first-person reflection or delivered by common sense; here we find conscious persons with beliefs, desires, hopes, and fears. According to this view, we know – by commonsense, introspection, or pure conceptual analysis – truths about persons, and the goal of cognitive science is to explain the mechanistic grounding for these truths, the nitty-gritty processes that implement or enable personal-level abilities and experiences. On the second view, cognitive science’s goal is to explain data, in particular, data thought to be produced by thought or cognition. According to this approach, intuitions generated by reflection or given by common sense often inspire experimental designs and even entire research programs. Ultimately, however, the modeling of the data thereby collected need not vindicate the claims about persons and their abilities made by fans of the personal level – not even the claims that inspired the relevant experimental designs in the first place! I’ll work through a pair of examples trying to show how to capture what’s correct in our intuitions about the personal level, while doing without it. I conclude that, if, by definition, persons exist only at the personal level, cognitive science can do without persons as well.
November 10, 2017
Professor, Computer Science, University of Colorado Boulder
November 23-24, 2017
Thanksgiving - CU Closed
December 1, 2017
Assistant Professor, LEEDS School of Business, University of Colorado Boulder
December 8, 2017
Assistant Professor, Department of Psychology, University of Denver