Metaanalytic connectivity modeling: delineating the functional connectivity of the human amygdala - PubMed (original) (raw)

Meta-Analysis

Metaanalytic connectivity modeling: delineating the functional connectivity of the human amygdala

Jennifer L Robinson et al. Hum Brain Mapp. 2010 Feb.

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.

(c) 2009 Wiley-Liss, Inc.

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Figures

Figure 1

Figure 1

Anatomical 3D‐renderings of the amygdala ROIs used for the meta‐analysis. The right amygdala is represented in red and the left amygdala is represented in blue. Figure created using Mango (

http://ric.uthscsa.edu/mango

).

Figure 2

Figure 2

Papers reporting activation within the left and right amygdala ROIs were drawn from the BrainMap Database for subsequent metaanalysis. The graphs below demonstrate the number of papers coded in each behavioral domain in the entire BrainMap database (a), as well as the behavioral domain breakdown of the papers included in the amygdala‐specific meta‐analysis (b). From the emotion domain, which contained the highest percentage of papers, a variety of affective states were represented (c).

Figure 3

Figure 3

Coactivation patterns obtained from meta‐analysis with the left (blue) and right (red) amygdala. Regions of the brain that coactivated with both left and right amygdala are indicated in purple. Maps thresholded at P < 0.001. Figure created using Mango (

http://ric.uthscsa.edu/mango

).

Figure 4

Figure 4

The 3D renderings of coactivation patterns for the left (top panel) and right (bottom panel) amygdala. AC = anterior cingulate; BA = Brodmann area; MFG = medial frontal gyrus; PC = posterior cingulate cortex; PHIPP = parahippocampal gyrus; SFG = superior frontal gyrus; THAL = thalamus.

Figure 5

Figure 5

Images were constructed using the CoCoMac‐Paxinos3D Viewer. Panel A shows all 151 slices of the atlas in stereotaxic space. Within each of the panels BF, the brain region is displayed in this space (left side of each panel) in addition to a magnified image of the connectivity results. Please see Table IV for a list of all abbreviations. B = Anterior amygdaloid area, C = Amygdalopiriform transition area, D = Basolateral amygdaloid nucleus, E = Basomedial amygdaloid nucleus, F = Central medial amygdaloid nucleus, medial division. Blue arrows indicate evidence for no anatomical connectivity, gray represents anatomical connectivity of unknown density, yellow is weak anatomical connectivity, and red indicates strong anatomical connections.

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