Effective connectivity analysis of response inhibition functional network
IntroductionInhibition mechanisms are essential in daily life, helping individuals adapt to environmental demands. However, the causal interactions between large-scale functional networks involved in response inhibition remain poorly understood.MethodsIn this study, we examined the effective connect...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2025.1525038/full |
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| author | Monica Di Giuliano Andy Schumann Feliberto de la Cruz Pedro Henrique Rodrigues Da Silva Karl-Jürgen Bär |
| author_facet | Monica Di Giuliano Andy Schumann Feliberto de la Cruz Pedro Henrique Rodrigues Da Silva Karl-Jürgen Bär |
| author_sort | Monica Di Giuliano |
| collection | DOAJ |
| description | IntroductionInhibition mechanisms are essential in daily life, helping individuals adapt to environmental demands. However, the causal interactions between large-scale functional networks involved in response inhibition remain poorly understood.MethodsIn this study, we examined the effective connectivity (EC) underlying inhibitory processes in the brain using dynamic causal modeling (DCM) and independent component analysis (ICA). We conducted a Go-NoGo fMRI task with 19 healthy participants to investigate these networks.ResultsOur results identified four functional networks activated during correct motor response inhibition: the salience network (SN), the right and left executive control networks (ECNs), and the ventral default mode network (vDMN). We observed a significant causal inhibitory influence from the vDMN to the left ECN (lECN). Under conditions of unsuccessful response inhibition, the SN, bilateral ECNs, and somatomotor network (SMN) were found to be prominently activated. Furthermore, we identified a significant correlation between the inhibitory influence from the SMN to the SN and the commission error rate. Finally, correlation analyses between self-reported impulsivity levels and causal network interactions revealed that highly impulsive individuals require greater interhemispheric integration between the right and left ECNs for effective inhibition, as well as a causal excitatory modulation from the right executive control network (rECN) to the vDMN.DiscussionIn summary, our study reveals complex hierarchical dynamics among functional networks during response inhibition. These findings offer valuable insight into the neural mechanisms supporting inhibition and provide avenues for future research on the neural underpinnings of this critical cognitive function across the lifespan. |
| format | Article |
| id | doaj-art-18a9466a74e445e9bbdb6b4e9f0a4a36 |
| institution | OA Journals |
| issn | 1662-453X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Neuroscience |
| spelling | doaj-art-18a9466a74e445e9bbdb6b4e9f0a4a362025-08-20T02:26:09ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2025-04-011910.3389/fnins.2025.15250381525038Effective connectivity analysis of response inhibition functional networkMonica Di Giuliano0Andy Schumann1Feliberto de la Cruz2Pedro Henrique Rodrigues Da Silva3Karl-Jürgen Bär4Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, GermanyLab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, GermanyLab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, GermanyInstitute of Psychiatry of the Hospital das Clínicas of the Faculty of Medicine of the University of São Paulo, Ribeirão Preto, BrazilLab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, GermanyIntroductionInhibition mechanisms are essential in daily life, helping individuals adapt to environmental demands. However, the causal interactions between large-scale functional networks involved in response inhibition remain poorly understood.MethodsIn this study, we examined the effective connectivity (EC) underlying inhibitory processes in the brain using dynamic causal modeling (DCM) and independent component analysis (ICA). We conducted a Go-NoGo fMRI task with 19 healthy participants to investigate these networks.ResultsOur results identified four functional networks activated during correct motor response inhibition: the salience network (SN), the right and left executive control networks (ECNs), and the ventral default mode network (vDMN). We observed a significant causal inhibitory influence from the vDMN to the left ECN (lECN). Under conditions of unsuccessful response inhibition, the SN, bilateral ECNs, and somatomotor network (SMN) were found to be prominently activated. Furthermore, we identified a significant correlation between the inhibitory influence from the SMN to the SN and the commission error rate. Finally, correlation analyses between self-reported impulsivity levels and causal network interactions revealed that highly impulsive individuals require greater interhemispheric integration between the right and left ECNs for effective inhibition, as well as a causal excitatory modulation from the right executive control network (rECN) to the vDMN.DiscussionIn summary, our study reveals complex hierarchical dynamics among functional networks during response inhibition. These findings offer valuable insight into the neural mechanisms supporting inhibition and provide avenues for future research on the neural underpinnings of this critical cognitive function across the lifespan.https://www.frontiersin.org/articles/10.3389/fnins.2025.1525038/fullresponse inhibitiondynamic causal modelingspatial independent component analysisGo-NoGo taskimpulsivityfunctional networks |
| spellingShingle | Monica Di Giuliano Andy Schumann Feliberto de la Cruz Pedro Henrique Rodrigues Da Silva Karl-Jürgen Bär Effective connectivity analysis of response inhibition functional network Frontiers in Neuroscience response inhibition dynamic causal modeling spatial independent component analysis Go-NoGo task impulsivity functional networks |
| title | Effective connectivity analysis of response inhibition functional network |
| title_full | Effective connectivity analysis of response inhibition functional network |
| title_fullStr | Effective connectivity analysis of response inhibition functional network |
| title_full_unstemmed | Effective connectivity analysis of response inhibition functional network |
| title_short | Effective connectivity analysis of response inhibition functional network |
| title_sort | effective connectivity analysis of response inhibition functional network |
| topic | response inhibition dynamic causal modeling spatial independent component analysis Go-NoGo task impulsivity functional networks |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2025.1525038/full |
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