Resting-state networks and dissociation in psychogenic non-epileptic seizures

S.J.M. van der Kruijs, S.R. Jagannathan, N.M.G. Bodde, R.M.H. Besseling, R.H.C. Lazeron, K.E.J. Vonck, P.A J.M. Boon, P.J.M. Cluitmans, P.A.M. Hofman, W.H. Backes, A.P. Aldenkamp, J.F.A. Jansen

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Abstract

Objective: Psychogenic non-epileptic seizures (PNES) are epilepsy-like episodes which have an emotional rather than organic origin. Although PNES have often been related to the process of dissociation, the psychopathology is still poorly understood. To elucidate underlying mechanisms, the current study applied independent component analysis (ICA) on resting-state fMRI to investigate alterations within four relevant networks, associated with executive, fronto-parietal, sensorimotor, and default mode activation, and within a visual network to examine specificity of between-group differences. Methods: Twenty-one patients with PNES without psychiatric or neurologic comorbidities and twenty-seven healthy controls underwent resting-state functional MR imaging at 3.0T (Philips Achieva). Additional neuropsychological testing included Raven's Matrices test and dissociation questionnaires. ICA with dual regression was used to identify resting-state networks in all participants, and spatial maps of the networks of interest were compared between patients and healthy controls. Results: Patients displayed higher dissociation scores, lower cognitive performance and increased contribution of the orbitofrontal, insular and subcallosal cortex in the fronto-parietal network; the cingulate and insular cortex in the executive control network; the cingulate gyrus, superior parietal lobe, pre- and postcentral gyri and supplemental motor cortex in the sensorimotor network; and the precuneus and (para-) cingulate gyri in the default-mode network. The connectivity strengths within these regions of interest significantly correlated with dissociation scores. No between-group differences were found within the visual network, which was examined to determine specificity of between-group differences. Conclusions: PNES patients displayed abnormalities in several resting-state networks that provide neuronal correlates for an underlying dissociation mechanism.

Original languageEnglish
Pages (from-to)126-133
Number of pages8
JournalJournal of Psychiatric Research
Volume54
Issue number1
DOIs
Publication statusPublished - 2014

Fingerprint

Gyrus Cinguli
Seizures
Parietal Lobe
Cerebral Cortex
Crows
Somatosensory Cortex
Executive Function
Motor Cortex
Psychopathology
Nervous System
Psychiatry
Comorbidity
Epilepsy
Magnetic Resonance Imaging
Dissociation
Cortex
Group Differences

Keywords

  • Dissociation
  • Independent component analysis
  • Magnetic resonance imaging
  • Psychogenic non-epileptic seizures
  • Resting-state networks

Cite this

van der Kruijs, S.J.M. ; Jagannathan, S.R. ; Bodde, N.M.G. ; Besseling, R.M.H. ; Lazeron, R.H.C. ; Vonck, K.E.J. ; Boon, P.A J.M. ; Cluitmans, P.J.M. ; Hofman, P.A.M. ; Backes, W.H. ; Aldenkamp, A.P. ; Jansen, J.F.A. / Resting-state networks and dissociation in psychogenic non-epileptic seizures. In: Journal of Psychiatric Research. 2014 ; Vol. 54, No. 1. pp. 126-133.
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title = "Resting-state networks and dissociation in psychogenic non-epileptic seizures",
abstract = "Objective: Psychogenic non-epileptic seizures (PNES) are epilepsy-like episodes which have an emotional rather than organic origin. Although PNES have often been related to the process of dissociation, the psychopathology is still poorly understood. To elucidate underlying mechanisms, the current study applied independent component analysis (ICA) on resting-state fMRI to investigate alterations within four relevant networks, associated with executive, fronto-parietal, sensorimotor, and default mode activation, and within a visual network to examine specificity of between-group differences. Methods: Twenty-one patients with PNES without psychiatric or neurologic comorbidities and twenty-seven healthy controls underwent resting-state functional MR imaging at 3.0T (Philips Achieva). Additional neuropsychological testing included Raven's Matrices test and dissociation questionnaires. ICA with dual regression was used to identify resting-state networks in all participants, and spatial maps of the networks of interest were compared between patients and healthy controls. Results: Patients displayed higher dissociation scores, lower cognitive performance and increased contribution of the orbitofrontal, insular and subcallosal cortex in the fronto-parietal network; the cingulate and insular cortex in the executive control network; the cingulate gyrus, superior parietal lobe, pre- and postcentral gyri and supplemental motor cortex in the sensorimotor network; and the precuneus and (para-) cingulate gyri in the default-mode network. The connectivity strengths within these regions of interest significantly correlated with dissociation scores. No between-group differences were found within the visual network, which was examined to determine specificity of between-group differences. Conclusions: PNES patients displayed abnormalities in several resting-state networks that provide neuronal correlates for an underlying dissociation mechanism.",
keywords = "Dissociation, Independent component analysis, Magnetic resonance imaging, Psychogenic non-epileptic seizures, Resting-state networks",
author = "{van der Kruijs}, S.J.M. and S.R. Jagannathan and N.M.G. Bodde and R.M.H. Besseling and R.H.C. Lazeron and K.E.J. Vonck and Boon, {P.A J.M.} and P.J.M. Cluitmans and P.A.M. Hofman and W.H. Backes and A.P. Aldenkamp and J.F.A. Jansen",
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Resting-state networks and dissociation in psychogenic non-epileptic seizures. / van der Kruijs, S.J.M.; Jagannathan, S.R.; Bodde, N.M.G.; Besseling, R.M.H.; Lazeron, R.H.C.; Vonck, K.E.J.; Boon, P.A J.M.; Cluitmans, P.J.M.; Hofman, P.A.M.; Backes, W.H.; Aldenkamp, A.P.; Jansen, J.F.A.

In: Journal of Psychiatric Research, Vol. 54, No. 1, 2014, p. 126-133.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Resting-state networks and dissociation in psychogenic non-epileptic seizures

AU - van der Kruijs, S.J.M.

AU - Jagannathan, S.R.

AU - Bodde, N.M.G.

AU - Besseling, R.M.H.

AU - Lazeron, R.H.C.

AU - Vonck, K.E.J.

AU - Boon, P.A J.M.

AU - Cluitmans, P.J.M.

AU - Hofman, P.A.M.

AU - Backes, W.H.

AU - Aldenkamp, A.P.

AU - Jansen, J.F.A.

PY - 2014

Y1 - 2014

N2 - Objective: Psychogenic non-epileptic seizures (PNES) are epilepsy-like episodes which have an emotional rather than organic origin. Although PNES have often been related to the process of dissociation, the psychopathology is still poorly understood. To elucidate underlying mechanisms, the current study applied independent component analysis (ICA) on resting-state fMRI to investigate alterations within four relevant networks, associated with executive, fronto-parietal, sensorimotor, and default mode activation, and within a visual network to examine specificity of between-group differences. Methods: Twenty-one patients with PNES without psychiatric or neurologic comorbidities and twenty-seven healthy controls underwent resting-state functional MR imaging at 3.0T (Philips Achieva). Additional neuropsychological testing included Raven's Matrices test and dissociation questionnaires. ICA with dual regression was used to identify resting-state networks in all participants, and spatial maps of the networks of interest were compared between patients and healthy controls. Results: Patients displayed higher dissociation scores, lower cognitive performance and increased contribution of the orbitofrontal, insular and subcallosal cortex in the fronto-parietal network; the cingulate and insular cortex in the executive control network; the cingulate gyrus, superior parietal lobe, pre- and postcentral gyri and supplemental motor cortex in the sensorimotor network; and the precuneus and (para-) cingulate gyri in the default-mode network. The connectivity strengths within these regions of interest significantly correlated with dissociation scores. No between-group differences were found within the visual network, which was examined to determine specificity of between-group differences. Conclusions: PNES patients displayed abnormalities in several resting-state networks that provide neuronal correlates for an underlying dissociation mechanism.

AB - Objective: Psychogenic non-epileptic seizures (PNES) are epilepsy-like episodes which have an emotional rather than organic origin. Although PNES have often been related to the process of dissociation, the psychopathology is still poorly understood. To elucidate underlying mechanisms, the current study applied independent component analysis (ICA) on resting-state fMRI to investigate alterations within four relevant networks, associated with executive, fronto-parietal, sensorimotor, and default mode activation, and within a visual network to examine specificity of between-group differences. Methods: Twenty-one patients with PNES without psychiatric or neurologic comorbidities and twenty-seven healthy controls underwent resting-state functional MR imaging at 3.0T (Philips Achieva). Additional neuropsychological testing included Raven's Matrices test and dissociation questionnaires. ICA with dual regression was used to identify resting-state networks in all participants, and spatial maps of the networks of interest were compared between patients and healthy controls. Results: Patients displayed higher dissociation scores, lower cognitive performance and increased contribution of the orbitofrontal, insular and subcallosal cortex in the fronto-parietal network; the cingulate and insular cortex in the executive control network; the cingulate gyrus, superior parietal lobe, pre- and postcentral gyri and supplemental motor cortex in the sensorimotor network; and the precuneus and (para-) cingulate gyri in the default-mode network. The connectivity strengths within these regions of interest significantly correlated with dissociation scores. No between-group differences were found within the visual network, which was examined to determine specificity of between-group differences. Conclusions: PNES patients displayed abnormalities in several resting-state networks that provide neuronal correlates for an underlying dissociation mechanism.

KW - Dissociation

KW - Independent component analysis

KW - Magnetic resonance imaging

KW - Psychogenic non-epileptic seizures

KW - Resting-state networks

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U2 - 10.1016/j.jpsychires.2014.03.010

DO - 10.1016/j.jpsychires.2014.03.010

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