How Feedback Shapes Sensory Representations During Cognition

Cognitive abilities such as memory, attention, and control, allow people to flexibly process sensory information to guide adaptive behavior. To accomplish this, cognition recruits a distributed network of brain areas including frontal, parietal, and even sensory cortices. The idea that neural circuits in sensory cortex can become active during cognitive tasks is not new; even in the absence of sensory inputs, such as during retrieval from long-term memory, high level brain areas can trigger responses in sensory cortex via feedback. However, whether and how such sensory activation is used to guide behavior is not established. Nor is it understood whether and how feedback flexibly drives sensory responses in accord with task demands. Thus, investigating the impact of feedback on shaping visual representations is imperative for forming better models of how healthy brain systems can flexibly process information. This requires a sophisticated research program grounded in measurements of brain and behavior, coupled to innovative computational modeling. My dissertation work thus far has used fMRI and computational methods to elucidate the role feedback plays in shaping cortical representations during visual working memory and long-term memory. This work has involved the development of innovative fMRI experiments and neural network models. The findings thus far have contributed significantly to understanding how feedback shapes the precision of memory responses in visual cortex, and the link between memory responses and behavior. In the proposed research and training program, I will continue to study how feedback mechanisms shape cortical representations during visual memory. The extensive training in visual, cognitive, and computational neuroscience will provide me with the expertise and perspective needed to study the neurobiological basis of memory and cognition. In the proposed post-doctoral training phase I will build upon my computational background and gain training in electrophysiological data analysis and modeling. This extension will help me to bridge fMRI and electrophysiological measurements through a common theoretical framework, enabling me to test innovative hypotheses of how feedback signals transform neural representations during perception and memory, with the added benefit of linking findings across human and non-human research. This research program has significant potential to (1) elucidate the role cortical mechanisms play in supporting healthy cognition, (2) identify targets for the diagnosis of, and treatment for, neurodegenerative and psychiatric diseases that impair cognition, and (3) link electrophysiology and neuroimaging research. I am well situated to take advantage of this research program, and am confident that through such training I will gain the experimental and theoretical expertise necessary to successfully perform independent research on pressing questions that lie at the heart of systems and cognitive neuroscience. Project Number: 1F99NS143867-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of Neurological Disorders and Stroke (NINDS) | Principal Investigator: Robert Woodry | Institution: NEW YORK UNIVERSITY, NEW YORK, NY | Award Amount: $44,714 | Activity Code: F99 | Study Section: Special Emphasis Panel[ZRG1 CN-X (54)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11210929