Carnegie Mellon University

Psychology Events

100th Year Celebration of CMU Psychology


 “Developing Inhibitory Control”

Yuko Munakata, Ph.D.
Professor, University of Colorado, Boulder

Monday, October 15, 2018, 12pm, 336B Baker Hall

The development of inhibitory control over thoughts, actions, and emotions is essential in life. Decades of research have illuminated the cognitive and neural processes that support both the remarkable limitations that children show in inhibitory control, and their subsequent improvements. However, targeted intervention efforts based on such findings have shown limited success. I will present an alternative framework that integrates advances in understanding the temporal dynamics of developing control and the core components of mature inhibitory control. This framework provides a novel perspective on why children struggle with inhibitory control and how to effectively intervene.

“Stigma and Health: A Social Identity Threat Perspective”

Jeffrey Hunger, Ph.D.
Postdoctoral Scholar, Health Psychology, University of California, Los Angeles

Thursday, October 18, 2018, 12:00-1:30p, 340A Baker Hall

Dr. Hunger’s talk will focus on the health implications of stigma. In much of this work he will discuss stigma through the lens of social identity threat, which emphasizes anticipated stigma as a key psychological mechanism linking threat and health. He will showcase the utility of a social identity threat perspective across a series of correlational and experimental studies of weight stigma. He will conclude with a discussion of ongoing research as well as a new framework designed to more comprehensively capture the role that stigma plays in the health of marginalized populations.

“Deep Predictive Learning in Neocortex and Pulvinar”

Randy O’Reilly, Ph.D.
Professor, University of Colorado, Boulder

October 22, 2018, 12pm, 336B Baker Hall

Early developmental learning in babies appears largely passive, and yet forms the deep foundation of all that follows. Standard biologically-supported forms of self-organizing learning, e.g., Hebbian learning, which capture this largely passive and yet “magical” self-organizing aspect, are not computationally powerful enough to achieve many aspects of core cognitive function, including invariant object recognition. Instead, we propose a biologically-based form of error-driven predictive learning, which learns every 100 msec (10 Hz, i.e., the alpha frequency) from the difference between a prediction about what will be seen next, and what is actually seen. The deep layers of the neocortex drive predictions on the pulvinar nucleus of the thalamus, which is broadly interconnected with higher-order visual areas throughout the posterior neocortex, and serves as a kind of neural “projection screen” or “blackboard” (Mumford, 1991). A peculiar, strong, largely one-to-one projection from intrinsic bursting layer 5 neurons (5IB) in V1 and other lower-level areas provides the “ground truth” signal (bursting every 100msec). Where this signal differs from the preceding prediction, which is driven by much more numerous, weaker, and plastic layer 6 corticothalamic (CT) projections, there is a temporal difference error signal that drives learning throughout neocortex, via local synaptic mechanisms attuned to such temporal differences. This model is consistent with a wide range of detailed biological data, and we show that it can self-organize invariant, categorial object representations in its simulated inferotemporal (IT) cortex, based strictly on “passive” viewing of movies of objects moving through space, along with saccadic eye movements. Current work is focused on applying this framework to forward and inverse models in motor learning, and to learning a “predictive model of the self” that could support metacognitive awareness and enable full volitional control to emerge.