A competing renewal of R01 award MH074457 (currently in year 9) is requested. The R01 seeking renewal sustains the BrainMap Project (www.brainmap.org). The overall goal of the BrainMap Project is to provide the human brain mapping community with data sets, computational tools, and related resources that enable quantitative meta-analyses and co-activation mapping and functional decoding of neuroimaging data. The BrainMap Project manages two coordinate-based databases: 1) a functional activation repository of >11,000 published experiments (~45,000 subjects); and, 2) a voxel-based morphometry (VBM) repository of >2,700 published experiments (~63,000 subjects). The BrainMap Project provides a suite of tools (Sleuth, GingerALE, and Scribe) to access, curate, and analyze these datasets. To date, the tools and data have been used in >350 peer-reviewed meta-analytic publications, of which >170 were published by the community in the past two years (2012-2013). Four tool-development aims and four data sharing objectives are proposed.
Aim 1 proposes to improve anatomical specificity, null-distribution modeling, and normalization of contrast analyses computed using Activation Likelihood Estimation (ALE).
Aim 2 proposes to develop tools for modeling large-scale co-activation patterns (i.e., across thousands of experiment) in the BrainMap database to extract & map functionally connected brain networks. Our tool development strategy adopts both bottom up (regional) and top down (global) approaches.
Aim 3 proposes to develop tools that utilize BrainMap's location-linked behavioral metadata for functional interpretation of brain regions and networks.
Aim 4 proposes to model neural networks affected by psychiatric and neurological disorders, both within and between disorders. Sharing Objectives 1 & 2 provide user-oriented support for data entry and access for in-progress meta- analyses as well as sharing of useful products of this projects and their publications. Sharing Objectives 3 & 4 provide tools that facilitate the incorporation of Brain-Map derived tools and data into other image-analysis software environments.
This project provides mathematical tools and data sets for large-scale mining of anatomical and functional imaging investigations of the human brain reported in the peer-reviewed scientific literature. These tools and data are shared through a widely used web portal (www.BrainMap.org) and by distribution to developers of highly used software systems. To date, more than 350 peer-reviewed, full-length publications have used these tools and data, including 79 in 2013 alone.
| Palomero-Gallagher, Nicola; Hoffstaedter, Felix; Mohlberg, Hartmut et al. (2018) Human Pregenual Anterior Cingulate Cortex: Structural, Functional, and Connectional Heterogeneity. Cereb Cortex : |
| Cauda, Franco; Nani, Andrea; Manuello, Jordi et al. (2018) Brain structural alterations are distributed following functional, anatomic and genetic connectivity. Brain 141:3211-3232 |
| Michely, J; Volz, L J; Hoffstaedter, F et al. (2018) Network connectivity of motor control in the ageing brain. Neuroimage Clin 18:443-455 |
| Cauda, Franco; Nani, Andrea; Costa, Tommaso et al. (2018) The morphometric co-atrophy networking of schizophrenia, autistic and obsessive spectrum disorders. Hum Brain Mapp 39:1898-1928 |
| Camilleri, J A; Müller, V I; Fox, P et al. (2018) Definition and characterization of an extended multiple-demand network. Neuroimage 165:138-147 |
| Acar, Freya; Seurinck, Ruth; Eickhoff, Simon B et al. (2018) Assessing robustness against potential publication bias in Activation Likelihood Estimation (ALE) meta-analyses for fMRI. PLoS One 13:e0208177 |
| Trevisi, Gianluca; Eickhoff, Simon B; Chowdhury, Fahmida et al. (2018) Probabilistic electrical stimulation mapping of human medial frontal cortex. Cortex 109:336-346 |
| Pool, Eva-Maria; Leimbach, Martha; Binder, Ellen et al. (2018) Network dynamics engaged in the modulation of motor behavior in stroke patients. Hum Brain Mapp 39:1078-1092 |
| Bzdok, Danilo; Altman, Naomi; Krzywinski, Martin (2018) Statistics versus machine learning. Nat Methods 15:233-234 |
| Wang, Hao-Ting; Poerio, Giulia; Murphy, Charlotte et al. (2018) Dimensions of Experience: Exploring the Heterogeneity of the Wandering Mind. Psychol Sci 29:56-71 |
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