Abstract
Functional neuroimaging has evolved into an indispensable tool for noninvasively investigating brain function. A recent development of such methodology is the creation of connectivity models for brain regions and related networks, efforts that have been inhibited by notable limitations. We present a new method for ascertaining functional connectivity of specific brain structures using metaanalytic connectivity modeling (MACM), along with validation of our method using a nonhuman primate database. Drawing from decades of neuroimaging research and spanning multiple behavioral domains, the method overcomes many weaknesses of conventional connectivity analyses and provides a simple, automated alternative to developing accurate and robust models of anatomically-defined human functional connectivity. Applying MACM to the amygdala, a small structure of the brain with a complex network of connections, we found high coherence with anatomical studies in nonhuman primates as well as human-based theoretical models of emotive-cognitive integration, providing evidence for this novel method's utility.
Original language | English (US) |
---|---|
Pages (from-to) | 173-184 |
Number of pages | 12 |
Journal | Human Brain Mapping |
Volume | 31 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2010 |
Keywords
- Brainmap
- CoCoMac
- Meta-analysis
- PET
- fMRI
ASJC Scopus subject areas
- Anatomy
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Neurology
- Clinical Neurology