Cortical thickness alterations linked to somatoform and psychological dissociation in functional neurological disorders

Abstract

Background: Links between dissociation and functional neurological disorder (FND)/conversion disorder are well-established, yet the pathophysiology of dissociation remains poorly understood. This MRI study investigated structural alterations associated with somatoform and psychological dissociation in FND. We hypothesized that multimodal, paralimbic cingulo-insular regions would relate to the severity of somatoform dissociation in patients with FND. Methods: FreeSurfer cortical thickness and subcortical volumetric analyses were performed in 26 patients with motor FND and 27 matched healthy controls. Patients with high dissociation as measured by the Somatoform Dissociation Questionnaire-20 (SDQ) or Dissociative Experiences Scale (DES) were compared to controls in stratified analyses. Within-group analyses were also performed with SDQ and DES scores in patients with FND. All cortical thickness analyses were whole-brain corrected at the cluster-wise level. somatoform dissociation (SDQ > 35) showed reduced left caudal anterior cingulate cortex (ACC) cortical thickness compared to controls. In within-group analyses, SDQ scores inversely correlated with left caudal ACC cortical thickness in patients with FND. Depersonalization/derealization scores positively correlated with right lateral occipital cortical thickness. Both within-group findings remained statistically significant controlling for trait anxiety/depression, borderline personality disorder and posttraumatic stress disorder, adverse life events, and motor FND subtypes in post-hoc analyses. Conclusion: Using complementary between-group and within-group analyses, an inverse association between somatoform dissociation and left caudal ACC cortical thickness was observed in patients with FND. A positive relationship was also appreciated between depersonalization/derealization severity and cortical thickness in visual association areas. These findings advance our neuropathobiological understanding of dissociation in FND. Hum Brain Mapp 39:428-439, 2018.V C 2017 Wiley Periodicals, Inc.

<p>Widely Impaired White Matter Integrity and Altered Structural Brain Networks in Psychogenic Non-Epileptic Seizures</p>

“…Compared with DTI studies, there have been a greater number of morphological statistical neuroimaging studies of PNES. [29][30][31][32][33] In general, PNES shows frontal and temporal lobar abnormalities in gray matter volume or cortical thickness, although there are some inconsistencies. These areas are also related to normal aging during young adulthood to middle age, 34 which may explain the faster brain aging in patients with PNES.…”

White matter and neurite morphology differ in psychogenic nonepileptic seizures

“…Scales were selected based on prior literature on FNSDs demonstrating sensitivity to greater symptom severity compared to healthy controls, as well as relationships between limbic and motor brain regions structure and/or function. 3,[8][9][10][11]21,27 Independent samples t-tests were used to compare TBI and TBI + PNES groups for depressive (Beck Depression Inventory-II, BDI-II), 28 anxious (Beck Anxiety Inventory, BAI), 29 posttraumatic stress (PTSD Checklist-Specific version, PCL-S), 30 psychoticism (Symptom Checklist-90, SCL-90 PSY), somatization (SCL-90 SOM) 31 symptoms, and symptom severity (Global Assessment of Functioning). 32 Corrected degrees of freedom were used for any comparison that violated assumptions for homogeneity of variance between groups.…”

“…Specifically, based on prior literature, we hypothesized there would be group differences within the uncinate fasciculus (UF; prefrontal cortex-hippocampus-amygdala), fornix/stria terminalis (FST; hippocampus-amygdala-hypothalamus), cingulum (cingulate cortex-dorsal/ventral prefrontal cortex), and corticospinal tract (pre/post central gyrus-spinal cord). 6,[8][9][10][11][21][22][23] In order to further reduce the likelihood of type-I error, volume extent thresholds (mm 3 ) were calculated using AFNI's 3dClustSim based on an algorithm that uses randomization/ permutation simulation to produce 10 000 iterations of noise only generated t-tests and to determine the global cluster-level threshold values for each of the five separate diffusion measures. Only clusters identified by 3dLMEs exceeding 443 mm 3 for FA, 460 mm 3 for MD, 437 mm 3 for ODI, 548 mm 3 for ICVF, and 612 mm 3 for V-ISO were considered statistically significant (uncorrected P < 0.01, cluster threshold a = 0.05).…”

“…Based on prior literature, we hypothesized that increased depressive, anxious, posttraumatic and psychoticism symptoms of PNES would correspond to group differences within the uncinate fasciculus, fornix/stria terminalis, cingulum, whereas increased somatization symptoms would correspond to group differences within the corticospinal tract. 6,[8][9][10][11][21][22][23][24]…”

A new simple brain segmentation method for extracerebral intracranial tumors

“…3D-Slicer is available on multiple operating systems (Windows-64 bit, Linux, and MacOSX) and is used by surgeons for performing interactive segmentation, visualizing 3D medical images, and guiding therapy [3,4]. FreeSurfer requires Linux or MacOSX, either natively or a Windows-based virtual machine and is used mainly for the analysis and visualization of structural and functional neuroimaging data from patients with functional neurological disorders (FNDs) of the brain without structural damage, such as anxiety/depression, obsessive-compulsive disorder (OCD), epilepsy, posttraumatic brain syndrome (PTS) and so on [5]. For the hardware platform, we used a laptop with a 2.…”