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BEGIN:VEVENT
UID:09700f78cc8cac6949671917ac196546
CATEGORIES:RuCCS Colloquia:Fall 2019
CREATED:20190919T110359
SUMMARY:"RAGNAROC: A Computational Model for Determining Winners and Losers in the Competition for Visual Attention", Chloe Callahan-Flintoft (U.S. Army Research Laboratory)
LOCATION:Busch Campus\, Psych 105
DESCRIPTION: \nGoogle Scholar Page (https://scholar.google.com/citations?user=44GBTPcAA
AAJ&hl=en&oi=ao)\n \n
\n \nAbstract: A major challenge for the human visual system is
deciding what to attend to. While a vast amount of visual information is av
ailable, the brain must decide what to prioritize for enhanced processing.
This decision is based on a combination of goal-defined, top-down control (
e.g. searching for a highway sign while driving), and stimulus driven, bott
om-up salience (e.g. a deer suddenly appearing in front of your car). Media
ting between these two competing requirements is a major challenge that the
brain meets by allowing stimuli to compete for attention, a competition th
at is ultimately resolved by enhancing some information while suppressing o
thers. In my talk I will begin by introduce the Reflexive Attention Gradien
t through Neural AttRactOr Competition (RAGNAROC), a model that uses hierar
chical neural circuits specifically adapted for rapid, parallel decision ma
king to deploy attention across the visual field. In doing so, the model, u
sing a single set of neural mechanisms, is able to account for seemingly co
nflicting findings in the literature, such as how attentional capture can o
ccur under certain circumstances while the suppression of distracting infor
mation occurs in others. Finally, I will conclude by demonstrating how the
model can be used as a cognitive framework by which to test predictions and
ultimately advise the development of visually augmented displays aimed at
improving the situational awareness of Soldiers in the field.\n \nRAGNAROC MODEL PAPER
a>\n
X-ALT-DESC;FMTTYPE=text/html:
Abstract: A maj or challenge for the human visual system is deciding what to attend to. Whi le a vast amount of visual information is available, the brain must decide what to prioritize for enhanced processing. This decision is based on a com bination of goal-defined, top-down control (e.g. searching for a highway si gn while driving), and stimulus driven, bottom-up salience (e.g. a deer sud denly appearing in front of your car). Mediating between these two competin g requirements is a major challenge that the brain meets by allowing stimul i to compete for attention, a competition that is ultimately resolved by en hancing some information while suppressing others. In my talk I will begin by introduce the Reflexive Attention Gradient through Neural AttRactOr Comp etition (RAGNAROC), a model that uses hierarchical neural circuits specific ally adapted for rapid, parallel decision making to deploy attention across the visual field. In doing so, the model, using a single set of neural mec hanisms, is able to account for seemingly conflicting findings in the liter ature, such as how attentional capture can occur under certain circumstance s while the suppression of distracting information occurs in others. Finall y, I will conclude by demonstrating how the model can be used as a cognitiv e framework by which to test predictions and ultimately advise the developm ent of visually augmented displays aimed at improving the situational aware ness of Soldiers in the field.
DTSTAMP:20240329T075809 DTSTART;TZID=America/New_York:20191112T130000 DTEND;TZID=America/New_York:20191112T143000 SEQUENCE:0 TRANSP:OPAQUE END:VEVENT END:VCALENDAR