The overall objective of the present proposal is to develop, evaluate, distribute, and apply tools for the BrainMap Project, which provides the human brain mapping (HBM) community with data sets, computational tools, and informatics resources for quantitative meta-analyses and meta-analysis-based data interpretation. The development of coordinate-based, voxel-wise meta-analysis (CVM) has been a breakthrough for HBM, enabling statistically rigorous meta-analysis and systems-level modeling of published results. The HBM literature suitable for CVM meta-analysis was estimated in 2007 to be ~6,000 papers, with ~1000 new conforming papers being published each year. In this renewal, we propose numerous enhancements to widely used coordinate-based meta-analysis tools (Aim 1). Meta-analytic connectivity mapping (MACM) is a new application of CVM, which derives inter-regional connectivity maps from inter-study co-occurrence patterns. In this renewal, we propose to extend the functionality of our MACM tools, construct connectivity atlases through data mining, and validate these atlases by comparison to non-meta-analytic approaches (Aim 2). In BrainMap, behavioral meta-data are coded using a taxonomy developed and progressively refined by the BrainMap team. Recent application of independent component analysis (ICA) to BrainMap extracted intrinsic neural systems that were well, but not perfectly, discriminated by the BrainMap coding scheme. This observation suggests robust computational approaches both for providing a behavioral ontology for intrinsically connected networks and also for programmatic refinement of the BrainMap coding scheme (Aim 3). Finally, it has recently been demonstrated that CVM can be applied to voxel-based morphometry (VBM) structural neuroimaging studies.
In Aim 4, we anticipate the rapid growth of VBM research by creating a BrainMap-like database of the standards- compliant VBM literature. These proposed enhancements and extensions of the BrainMap Project will allow this rich set of neuroinformatics tools to continue to meet the research and educational needs for knowledge discovery and data mining in the neuroimaging community. 1

Public Health Relevance

An extraordinary amount of neuroimaging data has been acquired and analyzed over the last two decades in both healthy subjects and patients diagnosed with various neurologic or psychiatric diseases and disorders. The BrainMap Project aims to improve public health by developing methods that will enable more informed cognitive, perceptual, and motor models of brain function and dysfunction. The proposed research will allow 2

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH074457-06
Application #
8115191
Study Section
Neurotechnology Study Section (NT)
Program Officer
Freund, Michelle
Project Start
2005-09-01
Project End
2015-03-31
Budget Start
2011-06-01
Budget End
2012-03-31
Support Year
6
Fiscal Year
2011
Total Cost
$658,731
Indirect Cost
Name
University of Texas Health Science Center San Antonio
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
800772162
City
San Antonio
State
TX
Country
United States
Zip Code
78229
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Tahmasian, Masoud; Eickhoff, Simon B; Giehl, Kathrin et al. (2017) Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis. Cortex 92:119-138
Hwang, Kai; Bertolero, Maxwell A; Liu, William B et al. (2017) The Human Thalamus Is an Integrative Hub for Functional Brain Networks. J Neurosci 37:5594-5607
Bellucci, Gabriele; Chernyak, Sergey V; Goodyear, Kimberly et al. (2017) Neural signatures of trust in reciprocity: A coordinate-based meta-analysis. Hum Brain Mapp 38:1233-1248
Genon, Sarah; Reid, Andrew; Li, Hai et al. (2017) The heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization. Neuroimage :
Reid, Andrew T; Hoffstaedter, Felix; Gong, Gaolang et al. (2017) A seed-based cross-modal comparison of brain connectivity measures. Brain Struct Funct 222:1131-1151
Varikuti, Deepthi P; Hoffstaedter, Felix; Genon, Sarah et al. (2017) Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps. Brain Struct Funct 222:1447-1468
Pool, Eva-Maria; Leimbach, Martha; Binder, Ellen et al. (2017) Network dynamics engaged in the modulation of motor behavior in stroke patients. Hum Brain Mapp :
Nichols, Thomas E; Das, Samir; Eickhoff, Simon B et al. (2017) Best practices in data analysis and sharing in neuroimaging using MRI. Nat Neurosci 20:299-303
Ishaque, Mariam; Manning, Janessa H; Woolsey, Mary D et al. (2017) Functional integrity in children with anoxic brain injury from drowning. Hum Brain Mapp 38:4813-4831

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