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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Behrmann, Marlene Nestor, Adrian Plaut, David C. |
| Description | Author Affiliation: Nestor A ( Department of Psychology at Scarborough, University of Toronto, Toronto, ON, M1C 1A4, Canada); Plaut DC ( Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213-3890); Behrmann M ( Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213-3890); |
| Abstract | The reconstruction of images from neural data can provide a unique window into the content of human perceptual representations. Although recent efforts have established the viability of this enterprise using functional magnetic resonance imaging (MRI) patterns, these efforts have relied on a variety of prespecified image features. Here, we take on the twofold task of deriving features directly from empirical data and of using these features for facial image reconstruction. First, we use a method akin to reverse correlation to derive visual features from functional MRI patterns elicited by a large set of homogeneous face exemplars. Then, we combine these features to reconstruct novel face images from the corresponding neural patterns. This approach allows us to estimate collections of features associated with different cortical areas as well as to successfully match image reconstructions to corresponding face exemplars. Furthermore, we establish the robustness and the utility of this approach by reconstructing images from patterns of behavioral data. From a theoretical perspective, the current results provide key insights into the nature of high-level visual representations, and from a practical perspective, these findings make possible a broad range of image-reconstruction applications via a straightforward methodological approach. |
| ISSN | 00278424 |
| e-ISSN | 10916490 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Issue Number | 2 |
| Volume Number | 113 |
| Language | English |
| Publisher | National Academy of Sciences |
| Publisher Date | 2016-01-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Algorithms Brain Physiology Facial Recognition Image Processing, Computer-Assisted Brain Mapping Magnetic Resonance Imaging Pattern Recognition, Automated Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Multidisciplinary |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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