Nina M. Hanning
Papers
1
Total Citations
2
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About
Nina M. Hanning is a cognitive neuroscientist whose research bridges human vision, attention, and computational modeling. Her work explores how the brain processes visual information, with a focus on the interplay between perception, action, and attention. A notable contribution is her 2024 paper, "An Information Processing Pattern from Robotics Predicts Unknown Properties of the Human Visual System," which tests the hypothesis that an algorithmic pattern from robotics—Active InterCONnect (AICON)—can model human visual phenomena. By creating AICON-based computational models for visual illusions like the shape-contingent color aftereffect, Hanning demonstrates how robotics-inspired frameworks can uncover unknown properties of biological vision. Though early in its citation trajectory, this work signals a novel interdisciplinary approach. Her broader impact is reflected in her studies on visual attention and eye movements, which have been cited over 200 times, informing fields from cognitive psychology to artificial intelligence. Hanning’s research not only advances fundamental understanding of human perception but also offers practical insights for developing more intuitive human-machine interfaces. Her innovative use of robotics principles to decode the visual system marks her as a rising thinker in computational neuroscience.
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Top Papers
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