Indiana University Bloomington
NSF
An IGERT Training Program

The Dynamics of Brain-Body-Environment Systems in Behavior and Cognition

Spring 2014

Fall 2014

September 8: 4:00 in PY 101
Probing Human Brain Network Dynamics During Learning
Danielle S. Bassett
Dept. of Bioengineering
University of Pennsylvania

Human learning is a complex phenomenon requiring network-wide flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we investigate the properties of brain network dynamics that predict individual differences in learning. Functional interactions between brain regions co-evolve with one another during learning in distributed patterns that decrease in size with practice, indicating the emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. This consolidation of network dynamics is mirrored in higher-level summary statistics describing the modular organization of the brain, a property that plays a critical role in the selective adaptability present during evolution, development, and optimal network function. Our results indicate that more flexibility during early practice sessions, which we measure by the allegiance of nodes to modules, predicts more extensive learning in later practice sessions. Flexibility is greatest in a periphery of high-level processing regions whose connectivity changes frequently, and is least in a relatively stiff core of output regions whose connectivity changes little in time. The temporal core-periphery structure of human brain dynamics provides a fundamental new approach for understanding how separable functional modules are linked. This, in turn, enables the prediction of fundamental capacities, including the production of complex goal-directed behavior, in humans. (Background Paper)

December 1: 4:00 in PY 101
Critical Periods Re-examined: Evidence from Children treated for Dense Cataracts
Daphne Maurer
Dept. of Psychology, Neuroscience & Behaviour
McMaster University

We have been taking advantage of a natural experiment: children treated for dense cataracts that blocked all patterned vision to the retina until the cataracts were removed surgically and the eyes fit with compensatory contact lenses. I will describe the general principles that have emerged from comparing the effects of bilateral and unilateral cataracts and from studying the consequences of deprivation that began at different ages. Together, the results suggest different critical periods for damaging different aspects of vision and different principles for low level (e.g., acuity) and higher level vision (e.g., global motion; face processing). Nevertheless, some potential for rehabilitation remains even in adulthood. (Background Paper)


Spring 2014

March 31: Dennis Proffitt, Dept. of Psychology, University of Virginia, "Perception Viewed as a Phenotypic Expression"

April 7: Thomas Palmeri, Psychological Sciences, Vanderbilt University, "Neurocognitive modeling of perceptual decision making"

April 21:, Arthur Glenberg, Dept. of Psychology, Arizona State University, "Individual differences as a crucible for testing embodied theories of language comprehension"


Fall 2013

September 9: Morana Alac, Communication and Science Studies, University of California, San Diego, "Being social as rooted in practical situations of interaction"

October 21: William Warren, Dept. of Cognitive, Linguistic and Psychological Sciences, Brown University, "Self-organization in human crowds: From individual to collective behavior"

December 2: Nicholas Turk-Browne, Dept. of Psychology, Princeton University, "Statistical learning in the mind and brain"


Spring 2013

March 18: Amy Needham, Department of Psychological Sciences, Vanderbilt University, "Perceptual-Motor Learning in Infancy"

April 15: , Melanie Mitchell, Computer Science Department, Portland State University, "Using Analogy to Discover the Meaning of Images"


Fall 2012

September 24: Scott Makeig, Swartz Center for Computational Neuroscience, University of California, San Diego, "Mining Event-Related Brain Dynamics"

October 22: Antonio Rangel, Economics and Neuroscience, Caltech, "The Neuroeconomics of Simple Choice"


Spring 2012

February 6: Brian Scassellati, Department of Computer Science, Yale University, "Using Human-Robot Interactions to Study Human-Human Social Behavior"

March 19: John Spencer, Department of Psychology, University of Iowa, "The Integration Challenge in Cognitive Science and the Promise of Embodied Neural Dynamics"


Fall 2011

October 24: Jeffrey Krichmar, Dept. of Cognitive Sciences and Dept. of Computer Science, University of California at Irvine, "Neuromodulation as a Brain-Inspired Strategy for Controlling Autonomous Robots and a Means to Investigate Social Cognition during Human-Robot Interactions"

November 28: Anthony Chemero, Psychology, Franklin & Marshall College, "Interaction-Dominant Dynamics, Phenomenology, and Extended Cognition"


Spring 2011

January 24: Hod Lipson, Mechanical and Aerospace Engineering, Cornell University, "Self-reflective machines"

March 21: Lawrence Barsalou, Department of Psychology, Emory University, "Grounding Knowledge in the Brain's Modal Systems"

April 4: Susan Goldin-Meadow, Department of Psychology, University of Chicago, "How Our Hands Help Us Think"


Fall 2010

September 13: Michael Richardson, Center for Cognition, Action and Perception, Psychology Department, University of Cincinnati, "Affording structured coordination: An ecological approach to self-organized social action"

October 18: Ennio Mingolla, Department of Cognitive and Neural Systems, Department of Psychology, Boston University, "Neural models of visually-guided steering, obstacle avoidance, and route selection"


Spring 2010

February 22: Mary Hayhoe, Dept. of Psychology, The University of Texas at Austin, "Adaptive Control of Attention and Gaze in the Natural World".

February 24: Dana Ballard, Dept. of Computer Sciences, The University of Texas at Austin, "Modular Reinforcement Learning as a Model of Embodied Cognition".

April 5: Asif Ghazanfar, Dept. of Psychology, Princeton University, "Vocal Communication Through Coupled Oscillations: Substrates for the Evolution of Speech".