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Institute of Cognitive and Brain Sciences

University of California at Berkeley
3210 Tolman Hall MC 1650
Berkeley, CA 94720-1650

Administration support for the Institute is provided by the staff of the Helen Wills Neuroscience Institute. See the administration page for help and information.

Colloquia

All talks are in 5101 Tolman Hall, 11am-12:30pm.

January 29

Presenter: Mark Bickhard, LeHigh University

Title: Interactivism and Central Nervous System Dynamics

Abstract: There are at least two problems with standard computational/information processing models of brain functioning: 1) the framework is metaphysically incoherent, and 2) what we know about brain functioning is at best anomalous for, if not contradictory to, these models. I will outline a pragmatism based interactivist model of cognition as an alternative to computational models, and a model of central nervous system functioning derived from it. These models are jointly theoretically coherent and comport with such CNS phenomena as volume transmitters, functional astrocytes, non-zero baseline rates of firing, and so on. The central functional relationship in the brain is modulation, not semantic information processing.

February 12

Presenter: Tyler Burge, UCLA

Title: Do Apes and Very Young Children Attribute Mental States?

March 4

Presenter: Pieter Abbeel, UC Berkeley

Title: Making Robots Learn

Abstract: Programming robots remains notoriously difficult. Equipping robots with the ability to learn would by-pass the need for what often ends up being time-consuming task specific programming. In this talk I will describe the ideas behind two promising types of robot learning: Apprenticeship learning, in which robots learn from human demonstrations. Reinforcement learning, in which robots learn through their own trial and error. I will highlight capabilities enabled by these approaches, such as autonomous helicopter aerobatics, knot-tying, cloth manipulation, basic suturing, and locomotion. I will also discuss some of our latest work in deep reinforcement learning, which I believe has the potential to significantly advance robotics in the foreseeable future.

March 18

Presenter: Janet Werker, University of British Columbia

Title: Critical Periods in Speech Perception Development

Abstract: The foundations of language acquisition begin in perception long before infants produce or even understand, their first words. In this talk, I will review the preparation infants have at birth for processing language, and the rapid changes in auditory, visual, and multimodal speech perception that occur in the first months of life as infants begin to acquire the native language. I will then present evidence that, while under typical circumstances the timing of perceptual attunement seems to be constrained by maturation, there are identifiable variations in experiences that can accelerate, slow down, or modify this developmental trajectory. Finally, I will introduce new data that question whether our studies on the timing of plasticity, and indeed on the foundations of language, have considered all the relevant input systems.

April 1

Presenter: Poppy Crum, Dolby Audio Laboratories

April 15

Presenter: David Bamman, UC Berkeley

Title: Quantitative Interpretability

Abstract: The use of empirical methods in historically qualitative disciplines has grown radically over the past decade, giving rise to such hybrid communities of practice as computational social science, computational journalism and the digital humanities. One barrier these methods have seen, however, concerns issues of algorithmic trust: in models that contain high degrees of complexity (such as through the cardinality of the parameter space or the presence of non-linear interactions, among others), what exactly are quantitative methods learning, and to what degree can their results be trusted to supply evidence in support of a larger argument? In this talk, I will describe some of our recent, ongoing work leveraging user studies in decision making to operationalize the concept of model interpretability in order to encourage transparency even within highly complex models.

April 29

Presenter: Scott Kelso, Florida Atlantic University

May 6

Presenter: Emma Brunskill, Carnegie Mellon University