Cognitive domain-independent aberrant frontoparietal network strength in individuals with excessive smartphone use

•We investigated neural activity in individuals with excessive smartphone use (ESU).•Joint ICA was used to analyze fMRI-data from three separate experimental tasks.•A domain-independent frontoparietal network significantly differed between ESU and controls.•Significant associations were found betwee...

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Veröffentlicht in:Psychiatry research. Neuroimaging 2023-03, Vol.329, p.111593-111593, Article 111593
Hauptverfasser: Henemann, Gudrun M., Schmitgen, Mike M., Wolf, Nadine D., Hirjak, Dusan, Kubera, Katharina M., Sambataro, Fabio, Bach, Patrick, Koenig, Julian, Wolf, Robert Christian
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container_title Psychiatry research. Neuroimaging
container_volume 329
creator Henemann, Gudrun M.
Schmitgen, Mike M.
Wolf, Nadine D.
Hirjak, Dusan
Kubera, Katharina M.
Sambataro, Fabio
Bach, Patrick
Koenig, Julian
Wolf, Robert Christian
description •We investigated neural activity in individuals with excessive smartphone use (ESU).•Joint ICA was used to analyze fMRI-data from three separate experimental tasks.•A domain-independent frontoparietal network significantly differed between ESU and controls.•Significant associations were found between neural network strength and specific ESU dimensions. Excessive smartphone use (ESU) may fulfill criteria for addictive behavior. In contrast to other related behavioral addictions, particularly Internet Gaming Disorder, little is known about the neural correlates underlying ESU. In this study, we used functional magnetic resonance imaging (fMRI) to acquire task data from three distinct behavioral paradigms, i.e. cue-reactivity, inhibition, and working memory, in individuals with psychometrically defined ESU (n = 19) compared to controls (n-ESU; n = 20). The Smartphone Addiction Inventory (SPAI) was used to quantify ESU-severity according to a novel five-factor model (SPAI-I). A multivariate data fusion approach, i.e. joint Independent Component Analysis (jICA) was employed to analyze fMRI-data derived from three separate experimental conditions, but analyzed jointly to detect converging and domain-independent neural signatures that differ between persons with vs. those without ESU. Across the three functional tasks, jICA identified a predominantly frontoparietal system that showed lower network strength in individuals with ESU compared to n-ESU (p < 0.05 FDR-corrected). Furthermore, significant associations between frontoparietal network strength and SPAI-I's dimensions “time spent” and “craving” were found. The data suggest a frontoparietal cognitive control network as cognitive domain-independent neural signature of excessive and potentially addictive smartphone use.
doi_str_mv 10.1016/j.pscychresns.2023.111593
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Excessive smartphone use (ESU) may fulfill criteria for addictive behavior. In contrast to other related behavioral addictions, particularly Internet Gaming Disorder, little is known about the neural correlates underlying ESU. In this study, we used functional magnetic resonance imaging (fMRI) to acquire task data from three distinct behavioral paradigms, i.e. cue-reactivity, inhibition, and working memory, in individuals with psychometrically defined ESU (n = 19) compared to controls (n-ESU; n = 20). The Smartphone Addiction Inventory (SPAI) was used to quantify ESU-severity according to a novel five-factor model (SPAI-I). A multivariate data fusion approach, i.e. joint Independent Component Analysis (jICA) was employed to analyze fMRI-data derived from three separate experimental conditions, but analyzed jointly to detect converging and domain-independent neural signatures that differ between persons with vs. those without ESU. Across the three functional tasks, jICA identified a predominantly frontoparietal system that showed lower network strength in individuals with ESU compared to n-ESU (p &lt; 0.05 FDR-corrected). Furthermore, significant associations between frontoparietal network strength and SPAI-I's dimensions “time spent” and “craving” were found. 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Neuroimaging</title><addtitle>Psychiatry Res Neuroimaging</addtitle><description>•We investigated neural activity in individuals with excessive smartphone use (ESU).•Joint ICA was used to analyze fMRI-data from three separate experimental tasks.•A domain-independent frontoparietal network significantly differed between ESU and controls.•Significant associations were found between neural network strength and specific ESU dimensions. Excessive smartphone use (ESU) may fulfill criteria for addictive behavior. In contrast to other related behavioral addictions, particularly Internet Gaming Disorder, little is known about the neural correlates underlying ESU. In this study, we used functional magnetic resonance imaging (fMRI) to acquire task data from three distinct behavioral paradigms, i.e. cue-reactivity, inhibition, and working memory, in individuals with psychometrically defined ESU (n = 19) compared to controls (n-ESU; n = 20). 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source MEDLINE; Access via ScienceDirect (Elsevier)
subjects Addiction
Behavior, Addictive - diagnostic imaging
Cognition
Functional magnetic resonance imaging
Humans
Independent component analysis
Magnetic Resonance Imaging - methods
Prefrontal cortex
Smartphone
title Cognitive domain-independent aberrant frontoparietal network strength in individuals with excessive smartphone use
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