We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Charles F. Cadieu is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 2012 — 2013 |
Cadieu, Charles F |
F32Activity Code Description:
To provide postdoctoral research training to individuals to broaden their scientific background and extend their potential for research in specified health-related areas. |
Understanding the Neural Basis of Visual Face Processing @ Massachusetts Institute of Technology
DESCRIPTION (provided by applicant): From even a brief glance of a scene the human visual system achieves a rich interpretation that includes the objects that are present and where they are, the surfaces that compose the space and how they move, and the identity of the individuals that are present and even their cognitive intentions. The visual face processing system provides a unique opportunity to discover the computations and neural basis of this astonishing perceptual ability. It has recently been discovered that the face processing subsystem of macaque visual cortex consists of six discrete cortical patches that are preferentially driven by face stimuli, form a strongly connected subnetwork, and subserve a transformation into neurons selective for identity and robust to visual changes. However, the precise nature of the transformation that occurs within the face patch system and the encoding of face features within each patch is far from understood. In order to understand precisely these processes we seek to develop novel computational models of this transformation and rigorously test these models experimentally. The overall aim of this proposal is to produce testable computational hypotheses of visual face processing and to quantitatively test these hypotheses, along with already existing hypotheses, as models of neural responses in the face patches. The results of this study will provide insight into the principals that govern the transformation of visual information in cortex and will serve as a substrate for the further investigation of normal and abnormal face perception in humans. PUBLIC HEALTH RELEVANCE: Specific cortical mechanisms are involved in visual face perception. We seek to develop computational models and test these models against neural recordings of these specific cortical mechanisms involved in visual face perception. Understanding how faces are processed in cortex may help us understand general information processing in the brain and may lead to treatments and understanding of persons with deficits in visual face perception.
|
1 |