University Relations

Victoria Interrante, PhD
Computer Science & Engineering

Associate Director
Jeanette Gundel, PhD
Professor, Linguistics

Research Assistant Professor
Trenton Jerde, PhD
Cognitive Science

FALL 2015 Colloquia

Thursdays, 4:00 - 5:30 pm, Elliott N119

October 8

Maria Chait, Auditory Cognitive Neuroscience Lab, University College London

"How the brain discovers patterns in sound sequences"

Sensitivity to patterns is fundamental to sensory processing, perhaps particularly so in the auditory system, since most auditory signals only have meaning as successions over time. Indeed, accumulating evidence suggests that the brain is tuned to the statistics of sensory stimulation. However, the process through which these statistical regularities are discovered in the first instance has eluded investigation. In my presentation I will review recent brain imaging and psychophysics findings in my lab that suggest that the auditory brain is a well-tuned 'pattern seeker', continuously scanning the unfolding auditory input for regularities, even when listeners' attention is focused elsewhere. Our data demonstrate that listeners are remarkably sensitive to the emergence of complex patterns within rapidly evolving sound sequences, performing on par with an ideal observer model. Brain responses reveal online processes of evidence accumulation - dynamic changes in tonic activity precisely correlate with the expected precision or predictability of ongoing auditory input. Source analysis demonstrates an interaction between primary auditory cortex, hippocampus, and inferior frontal gyrus in the process of 'discovering' the regularity within the ongoing sound sequence.

Suggested background reading:





Mondays, 12:00 pm, Elliott Hall S204, Lunch will be provided.

October 5 - Replication - Part 1

More Is Different - P.W. Anderson

"The reductionist hypothesis may still be a topic for controversy among philosophers, but among the great majority of active scientists I think it is accepted without question. The workings of our minds and bodies, and of all the animate or inaminate matter of which we have any detailed knowledge, are assumed to be controlled by the same set of fundamental laws, which except under certain extreme conditions we feel we know pretty well.

"It seems inevitable to go on uncritically to what appears at first sight to be an obvious corollary of reductionism: that if everything obeys the same fundamental laws, then the only scientists who are studying anything really fundamental are those who are working on those laws. In practice, that amounts to some astrophysicists, some elementary particle physicists, some logicians and other mathematicians, and few others ..." More ...




Christopoulos and Schrater in PLOS Computational Biology

The September 22, 2015 issue of PLOS Computational Biology features a paper by CCS members Paul Schrater and Vasileios Christopoulos entitled, "Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making".

From their Conclusion:
"In sum, decisions require integrating both good values and action costs, which are often time and state dependent such that simple approaches pre-selection of goals or fixed weighted mixture of policies cannot account for the complexities of natural behavior. By focusing on a fundamental probabilistic computation, we provide a principled way to dynamically integrate these values that can merge work on decision making with motor control."

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation

Their paper may be downloaded in Portable Document Format (pdf, 2.3 mb) at .
(This is an open access article distributed under the terms of the Creative Commons Attribution License.)




Updated October 3, 2015->