David E Osher
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
David E Osher has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
Gretchen Reynolds
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
1 shared publicationJohn D E Gabrieli
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
1 shared publication- Kami Koldewyn
Department of Psychology, School of Psychology and Sport Science, Bangor University, Bangor, UK
1 shared publication Rebecca R Saxe
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
1 shared publication- Zeynep M. Saygin
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
1 shared publication
Latest Publications
- Open Access
- 25 December 2011
- Published by Springer Nature in Nature Neuroscience
- Vol. 15 (2) , 321-327
Anatomical connectivity patterns predict face selectivity in the fusiform gyrus
The authors show that structural connectivity, as measured by diffusion-weighted imaging, can predict functional activation to faces in the fusiform gyrus. The structure–function correspondence developed in one group of subjects outperformed two other predictive models and was able to predict activation in a second group of subjects. A fundamental assumption in neuroscience is that brain structure determines function. Accordingly, functionally distinct regions of cortex should be structurally distinct in their connections to other areas. We tested this hypothesis in relation to face selectivity in the fusiform gyrus. By using only structural connectivity, as measured through diffusion-weighted imaging, we were able to predict functional activation to faces in the fusiform gyrus. These predictions outperformed two control models and a standard group-average benchmark. The structure–function relationship discovered from the initial participants was highly robust in predicting activation in a second group of participants, despite differences in acquisition parameters and stimuli. This approach can thus reliably estimate activation in participants who cannot perform functional imaging tasks and is an alternative to group-activation maps. Additionally, we identified cortical regions whose connectivity was highly influential in predicting face selectivity within the fusiform, suggesting a possible mechanistic architecture underlying face processing in humans.
- 25 December 2011
- Published by Springer Nature in Nature Neuroscience
- Vol. 15 (2) , 321-327
Open AccessAnatomical connectivity patterns predict face selectivity in the fusiform gyrus
The authors show that structural connectivity, as measured by diffusion-weighted imaging, can predict functional activation to faces in the fusiform gyrus. The structure–function correspondence developed in one group of subjects outperformed two other predictive models and was able to predict activation in a second group of subjects. A fundamental assumption in neuroscience is that brain structure determines function. Accordingly, functionally distinct regions of cortex should be structurally distinct in their connections to other areas. We tested this hypothesis in relation to face selectivity in the fusiform gyrus. By using only structural connectivity, as measured through diffusion-weighted imaging, we were able to predict functional activation to faces in the fusiform gyrus. These predictions outperformed two control models and a standard group-average benchmark. The structure–function relationship discovered from the initial participants was highly robust in predicting activation in a second group of participants, despite differences in acquisition parameters and stimuli. This approach can thus reliably estimate activation in participants who cannot perform functional imaging tasks and is an alternative to group-activation maps. Additionally, we identified cortical regions whose connectivity was highly influential in predicting face selectivity within the fusiform, suggesting a possible mechanistic architecture underlying face processing in humans.