Metaanalytic Connectivity Modeling: Delineating the Functional Connectivity of the Human Amygdala

Neuroscience Institute, Scott and White Memorial Hospital, Temple, Texas 76508, USA.
Human Brain Mapping (Impact Factor: 6.92). 11/2009; 31(2):173-84. DOI: 10.1002/hbm.20854
Source: PubMed

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.

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Available from: Angela R Laird, Sep 02, 2015
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    • "Although previous studies have indirectly analyzed in neurological samples the functionality of BA37 using functional MRI (fMRI) and diffusion tensor imaging (DTI) [52] [53] [54] their results have limited generalizability due to the methodologies (e.g., task-specific fMRI which is not generalizable and DTI which is influenced by deeply myelinated regions and fails where fibers cross) being employed [47]. Thus, strong empirical evidence is lacking as to how BA37 is functionally connected to the rest of the brain, despite the importance of this multimodal brain area in visual and cognitive processes. "
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    ABSTRACT: Background. Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas. Objectives. The purpose of this paper was to analyze the connectivity of Brodmann area (BA) 37 (posterior, inferior, and temporal/fusiform gyrus) in relation to (1) language and (2) visual processing. Methods. Two meta-analyses were initially conducted (first level analysis). The first one was intended to assess the language network in which BA37 is involved. The second one was intended to assess the visual perception network. A third meta-analysis (second level analysis) was then performed to assess contrasts and convergence between the two cognitive domains (language and visual perception). The DataBase of Brainmap was used. Results. Our results support the role of BA37 in language but by means of a distinct network from the network that supports its second most important function: visual perception. Conclusion. It was concluded that left BA37 is a common node of two distinct networks—visual recognition (perception) and semantic language functions.
    Behavioural neurology 01/2015; Volume 2015 (2015):14 pages. DOI:10.1155/2015/565871 · 1.64 Impact Factor
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    • "amygdala volumes. The amygdala has extensive reciprocal connections with the anteriobasal subdivision of the insula (Augustine, 1996; Nieuwenhuys, 2012), and shows functional connectivity with the insula (Robinson et al., 2010), including during resting state (Roy et al., 2009; Cauda et al., 2011) and emotional processing (Stein et al., 2007). The amygdala enlargement observed in our study is unlikely to be driven by comorbid depression. "
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    Brain 11/2014; 138(1). DOI:10.1093/brain/awu305 · 10.23 Impact Factor
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    • "Research in humans (Roy et al., 2009; Robinson et al., 2010) is fundamentally in agreement with studies in macaque monkeys showing widespread connections of the amygdala with cortical and subcortical regions encompassing the anterior cingulate cortex (ACC) and the inferior and medial prefrontal cortex, the hippocampus and the parahippocampal gyrus, the temporal lobe and the insula (Amaral and Price, 1984; Barbas and De Olmos, 1990; Stefanacci et al., 1996; Ghashghaei and Barbas, 2002). Using probabilistic diffusion tensor parcellation, Bach et al. (2011) have shown that the superficial portion, approximately corresponding to the centromedial and the superficial nuclei, and the deep portion, corresponding to the basal nucleus, are preferentially connected with OFC and the temporal pole, respectively. "
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    ABSTRACT: In the last few decades there has been increasing interest in the role of the amygdala in psychiatric disorders and, in particular, in its contribution to the socio-emotional impairments in autism spectrum disorders (ASDs). Given that the amygdala is a component structure of the "social brain," several theoretical explanations compatible with amygdala dysfunction have been proposed to account for socio-emotional impairments in ASDs, including abnormal eye contact, gaze monitoring, face processing, mental state understanding, and empathy. Nevertheless, many theoretical accounts, based on the Amygdala Theory of Autism, fail to elucidate the complex pattern of impairments observed in this population, which extends beyond the social domain. As posited by the Relevance Detector theory (Sander et al., 2003), the human amygdala is a critical component of a brain circuit involved in the appraisal of self-relevant events that include, but are not restricted to, social stimuli. Here, we propose that the behavioral and social-emotional features of ASDs may be better understood in terms of a disruption in a "Relevance Detector Network" affecting the processing of stimuli that are relevant for the organism's self-regulating functions. In the present review, we will first summarize the main literature supporting the involvement of the amygdala in socio-emotional disturbances in ASDs. Next, we will present a revised version of the Amygdala Relevance Detector hypothesis and we will show that this theoretical framework can provide a better understanding of the heterogeneity of the impairments and symptomatology of ASDs. Finally, we will discuss some predictions of our model, and suggest new directions in the investigation of the role of the amygdala within the more generally disrupted cortical connectivity framework as a model of neural organization of the autistic brain.
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