# Neural basis of flexible decisions in naturalistic environments > **NIH NIH K99** · UNIVERSITY OF CHICAGO · 2023 · $114,774 ## Abstract PROJECT SUMMARY The brain does not simply passively process visual information about the objects in the world. It is charged with placing this information about objects in the context of their environment relative to us in a way that helps us interact with them. To forage for food in the wild, an animal recognizes distant fruits, weighs the effort to get to each fruit against its perceived ripeness, makes and executes a route plan, and learns from the experience. This is possible because our vision enables two remarkable abilities – filtering out irrelevant information like inedible branches and leaves to focus on the fruit and creating flexible plans to reach the goal that can be altered on the fly. To study the neural basis of these abilities, I will use new conceptual and technological advances to study object vision in the context of cognition and naturalistic interactions like navigation and foraging to formulate a unified theory of how vision enables flexible behavior. Several computations in brain areas, like the prefrontal cortex, entorhinal cortex, etc., have been thought to mediate flexible behavior in various cognitive contexts like attention, working memory, and navigation. In this proposal, I will test the central hypothesis that signals in the dorsolateral prefrontal cortex (dlPFC) related to those different forms of flexibility reflect computations that guide how object properties are read out of visual area V4. To encourage the combination of several sources of visual information and interaction with objects in the task, I have designed a virtual reality foraging platform to test the following hypotheses about how object vision enables flexible behavior. In aim 1, I will test whether and how computations in dlPFC (previously identified in the context of attention) mediate the foraging of objects that have a narrow range of learned desirable properties by affecting the readout of relevant and irrelevant properties from V4. In aim 2, I will study how object familiarity is encoded in a viewpoint-invariant fashion and how interactions between V4 and dlPFC guide foraging behavior. In aim 3, I will explore how visual processing enables learned associations between objects and sequential actions by comparing the changes in neural activity in V4 and dlPFC that lead to the execution of sequential choices. The results of these studies will have broad scientific implications for models of visual perception that explain behavior and clinical implications for how object interaction, association, and action execution can be impaired in stroke and Alzheimer’s disease patients while visual processing is spared. Skills gained in the mentored portion – developing a visual foraging VR task and measuring and manipulating attention-like signals in dlPFC – along with my experience in generating visual scenes to analyze neural coding, will set the stage for future studies of the cognitive processes that shape visually guided experiences and actions i... ## Key facts - **NIH application ID:** 10723707 - **Project number:** 1K99EY035362-01 - **Recipient organization:** UNIVERSITY OF CHICAGO - **Principal Investigator:** Ramanujan Srinath - **Activity code:** K99 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $114,774 - **Award type:** 1 - **Project period:** 2023-09-30 → 2025-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10723707 ## Citation > US National Institutes of Health, RePORTER application 10723707, Neural basis of flexible decisions in naturalistic environments (1K99EY035362-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10723707. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*