Comparison of multi‐subject ICA methods for analysis of fMRI data

Erhardt, Erik B.; Rachakonda, Srinivas; Bedrick, Edward J.; Allen, Elena A.; Adalı, Tülay; Calhoun, Vince D.

doi:10.1002/hbm.21170

Cited by 672 publications

(681 citation statements)

References 38 publications

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“…In a first analysis step requiring minimal prior assumptions on data characteristics, we applied a multivariate group independent component analysis (ICA) (16)(17)(18)(19) to the data of 26 healthy subjects (13 pairs) in step A. This data-driven approach identified 16 maximally independent sources (components) that, together, account for the observed fMRI data of all subjects (Fig.…”

Section: Resultsmentioning

confidence: 99%

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

Bilek¹,

Ruf

Schäfer³

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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144

131

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Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender's and receiver's temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.fMRI | hyperscanning | joint attention H uman social interactions have likely shaped brain evolution and are critical for development, health, and society. Defining their neural underpinnings is a key goal of social neuroscience. Interacting dyads, the simplest and fundamental form of human interaction, have been examined with behavioral setups that used real movement interactions during communication in real time as a proxy (1-4), providing mathematical models representing human interaction, goal sharing, mutual engagement, and coordination. To identify the neural systems supporting these behaviors, neuroimaging would be the tool of choice, but studying dyadic interactions with this method is both experimentally and analytically challenging. Consequently, the neural processes underlying human social interactions remain incompletely understood.Experimentally, studying dyads with neuroimaging technology that allows only one participant per scanner provides challenges that have been addressed in the literature in one of two ways. First, the audiovisual experiences of human social contact have been simulated using stimuli such as photographs, recorded videos, or computerized avatars in the absence of human interaction (5-7), or, recently, immersive audiovisual linkups have been used with one of the two participants being scanned (8, 9). Secondly, pioneering neuroimaging experiments have coupled two scanner sites over the Internet, a setup called hyperscanning, enabling subjects to observe higher-level behavioral responses such as choices made to accept or reject an offer in real time while in the scanners (10, 11). In the current study, we aimed to combine the advantages of these experimental approaches by enabling two humans to see (and possibly hear) each other in a hyperscanning framework, enabling an immersive social interaction while both participant's brains are imaged. To do so, we implemented a setup with delay-free data transmission and precisely synchronized data acquisitio...

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Section: Resultsmentioning

confidence: 99%

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

Bilek¹,

Ruf

Schäfer³

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

144

131

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“…Fourth, the study sample was Caucasian and thus the generalizability of the findings across racial and ethnic groups should not be assumed. Fifth, the optimal ICA methodology for making group-level inferences from resting fMRI data is still an open question (Erhardt et al, 2011). Although our approach to ICA has been previously validated (Wang and Peterson, 2008), it is nonetheless possible that our methodology influenced our findings.…”

Section: Dmn-dlpfc Connectivitymentioning

confidence: 88%

Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression

Posner

Cha

Wang

et al. 2015

Neuropsychopharmacol

117

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Research into the pathophysiology of major depressive disorder (MDD) has focused largely on individuals already affected by MDD. Studies have thus been limited in their ability to disentangle effects that arise as a result of MDD from precursors of the disorder. By studying individuals at high familial risk for MDD, we aimed to identify potential biomarkers indexing risk for developing MDD, a critical step toward advancing prevention and early intervention. Using resting-state functional connectivity MRI (rs-fcMRI) and diffusion MRI (tractography), we examined connectivity within the default mode network (DMN) and between the DMN and the central executive network (CEN) in 111 individuals, aged 11-60 years, at high and low familial risk for depression. Study participants were part of a threegeneration longitudinal, cohort study of familial depression. Based on rs-fcMRI, individuals at high vs low familial risk for depression showed increased DMN connectivity, as well as decreased DMN-CEN-negative connectivity. These findings remained significant after excluding individuals with a current or lifetime history of depression. Diffusion MRI measures based on tractography supported the findings of decreased DMN-CEN-negative connectivity. Path analyses indicated that decreased DMN-CEN-negative connectivity mediated a relationship between familial risk and a neuropsychological measure of impulsivity. Our findings suggest that DMN and DMN-CEN connectivity differ in those at high vs low risk for depression and thus suggest potential biomarkers for identifying individuals at risk for developing MDD.

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“…The time courses of remaining 53 components for each subject and condition, which were computed from the group ICA time courses by a PCA‐based back‐reconstruction method [Erhardt et al, 2011], were used for the following FNC analyses [Allen et al, 2011; Doucet et al, 2011; Jafri et al, 2008]. …”

Section: Methodsmentioning

confidence: 99%

Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

Liu

Erkkinen

Healey

et al. 2015

Human Brain Mapping

182

102

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Creativity, a multifaceted construct, can be studied in various ways, for example, investigating phases of the creative process, quality of the creative product, or the impact of expertise. Previous neuroimaging studies have assessed these individually. Believing that each of these interacting features must be examined simultaneously to develop a comprehensive understanding of creative behavior, we examined poetry composition, assessing process, product, and expertise in a single experiment. Distinct activation patterns were associated with generation and revision, two major phases of the creative process. Medial prefrontal cortex (MPFC) was active during both phases, yet responses in dorsolateral prefrontal and parietal executive systems (DLPFC/IPS) were phase‐dependent, indicating that while motivation remains unchanged, cognitive control is attenuated during generation and re‐engaged during revision. Experts showed significantly stronger deactivation of DLPFC/IPS during generation, suggesting that they may more effectively suspend cognitive control. Importantly however, similar overall patterns were observed in both groups, indicating the same cognitive resources are available to experts and novices alike. Quality of poetry, assessed by an independent panel, was associated with divergent connectivity patterns in experts and novices, centered upon MPFC (for technical facility) and DLPFC/IPS (for innovation), suggesting a mechanism by which experts produce higher quality poetry. Crucially, each of these three key features can be understood in the context of a single neurocognitive model characterized by dynamic interactions between medial prefrontal areas regulating motivation, dorsolateral prefrontal, and parietal areas regulating cognitive control and the association of these regions with language, sensorimotor, limbic, and subcortical areas distributed throughout the brain. Hum Brain Mapp 36:3351–3372, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc..

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Comparison of multi‐subject ICA methods for analysis of fMRI data

Cited by 672 publications

References 38 publications

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression

Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

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