Project Grant 2522311
- This $234,610 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports collaborative research at Colgate University to study how the brain uses visual and linguistic information to achieve specific goals. The research aims to advance theories of human cognition and develop more adaptive, human-aligned artificial intelligence (AI) systems. Key project activities include training deep neural networks to predict...
- This $483,129 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences program (CFDA 47.075) supports research to advance understanding of human visual perception and scene processing. The project seeks to test whether state-of-the-art AI vision-language models can generate plausible visual scenes that mimic how the human brain perceives objects in peripheral vision during everyday activities. The research aims to provide insights into the...
- This $577,409 Project Grant from the National Science Foundation's Social, Behavioral, and Economic Sciences program will fund research at American University to study infant visual object recognition and its implications for computational models of human vision. Over a three-year period from September 2022 to August 2025, researchers will use electroencephalography to analyze how 12-15 month old infants represent and process visual objects. Results will be compared to predictions from...
- This federal Project Grant award of $301,800.00 from the National Science Foundation's Social, Behavioral, and Economic Sciences program (CFDA 47.075) supports a research project led by Yale University to study the neural mechanisms of object cognition using multilevel computational modeling. The overarching hypothesis is that the brain implements object cognition by building and manipulating generative models of physical scenes, their dynamics, and sensory inputs. The project aims to develop...
- This $1,090,678 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop computational algorithms that align deep neural networks (DNNs) with human visual processing. The project aims to rectify the growing "misalignment" between the behavior of large-scale DNNs and human cognition as AI systems become more capable. Researchers at Brown University will combine human...
- This federal Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $443,888 to the Research Foundation of the City University of New York (RFCUNY) to test theories of perceptual valuation using advanced machine learning and artificial intelligence (AI) techniques. The project aims to: 1) determine if deep neural network machine learning models can serve as proxies for people's internal models of visual objects, 2)...
- The National Science Foundation (NSF) awarded a $600,000 Project Grant to Carnegie Mellon University under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The 3-year project, running from June 1, 2025 to May 31, 2028, aims to investigate the computational mechanisms underlying a recently discovered neural process in the brain - the ability of neurons in the early visual cortex to rapidly form local recurrent circuits. The project seeks to...
- This Project Grant award of $310,000.00 was provided by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Southern California (USC) from October 1, 2025 to September 30, 2028. The goal of this project is to develop mathematical and computational frameworks to investigate how networks of neurons and non-neuronal cells self-organize to perform complex learning and decision-making. The research aims to replicate the...
- This federal Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences program (CFDA 47.075) provides $750,000 to Brown University to develop and test a novel computational model of cognitive control in the human brain. The project aims to gain a deeper understanding of the neural computations underlying humans' flexible, goal-directed behavior, which has implications for understanding disorders of cognitive control and informing the design of...
- This National Science Foundation (NSF) Project Grant, awarded under the STEM Education program (CFDA 47.076), provides $449,768 to the Concord Consortium, a non-profit research and development organization, to develop a digital learning tool that allows middle school students to visually and dynamically explore neural pathways in language-based AI systems. The project aims to enhance students' understanding of neural network interpretability and human-machine collaboration in AI development. Key...
This Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $378,352 to Barnard College to conduct research on how the brain uses visual and linguistic information to achieve specific goals. The project aims to understand the cognitive processes underlying goal-directed perception, using a combination of methods from visual AI, language AI, neuroscience, and cognitive science. Key activities include training deep neural networks to predict language embeddings of human scene descriptions, reverse-engineering the networks to identify task-relevant visual features, and validating the findings using behavioral experiments and electroencephalography (EEG). This interdisciplinary approach seeks to reveal how visual, conceptual, and neural systems interact to support adaptive, human-aligned artificial intelligence systems. The award period runs from September 1, 2025, to August 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $378.4k | 8/27/25 |