Morphometric mapping of the macrostructural abnormalities of midsagittal corpus callosum in Wilson's disease.

Background and Purpose: The corpus callosum (CC) consists of topographically arranged white matter (WM) fibers. Previous studies have indicated the CC to be discretely involved in WD. In this study, we strived to characterize the macrostructural properties of the CC using midsagittal cross-sectional area and thickness profile measurements. Materials and Methods: This study was performed using archived magnetic resonance imaging (MRI) scans of 14 patients with WD and 14 age- and gender-matched healthy controls. Using an automated software pipeline for morphometric profiling, the midsagittal CC was segmented into five sub-regions (CC1-5) according to the Hofer-Frahm scheme. The mean thickness and area of different CC segments and their clinical and cognitive correlates were identified. Results: The mean area was significantly different only in CC2 segment (94.2 ± 25.5 vs. 118.6 ± 19.7 mm2, corrected P < 0.05). The mean thickness was significantly different in CC1 (5.06 ± 1.15 vs. 6.93 ± 0.89 mm, corrected P < 0.05), CC2 (3.73 ± 0.96 vs. 4.87 ± 1.01 mm, corrected P < 0.05), and CC3 segments (3.42 ± 0.84 vs. 3.94 ± 0.72 mm, corrected P < 0.05). The age at onset of neurological symptoms and MMSE score was significantly correlated with the morphometric changes of CC1 and CC2 segments. Conclusion: Morphological changes of the CC are discrete in WD. Morphometric loss of CC was associated with an earlier onset of neurological symptoms and cognitive dysfunction in WD.

Abnormal Subcortical Volumes and Cortical Thickness in Parkinson's Disease with Impulse Control Disorders.

BACKGROUND: The occurrence of impulse control disorders (ICDs) in Parkinson's disease (PD) is frequently attributed to dopamine replacement therapy. However, not all patients who receive medication develop ICDs. Recent imaging studies have suggested specific neuroanatomical abnormalities in patients with PD and ICD. OBJECTIVES: This study aims to identify changes in volumes of subcortical structures and cortical thickness specific to patients with PD and ICDs. METHODOLOGY: A total of 11 patients with PD and ICD (PDICD(+)), 15 patients with PD without ICD (PDICD(-)), and 15 healthy controls were analyzed in this study. ICDs were diagnosed and quantified using the Questionnaire for Impulsive-Compulsive Disorders in PD-Rating Scale (QUIP-RS). Structural imaging was performed on a 3T scanner; volumes of subcortical structures and cortical thickness were obtained using first in FSL and FreeSurfer. RESULTS: Significant volume loss of the nucleus accumbens was observed in the PDICD(+) group. Several areas of significant cortical thinning were observed in the PDICD(+) group in comparison PDICD(-) group. Thinning of the left middle temporal gyrus, transverse temporal gyrus, and bilateral temporal poles was observed in the PDICD(+) group. No correlations were observed between QUIP-RS scores and areas of cortical thinning. CONCLUSIONS: The PDICD(+) group has specific neuroanatomical variations in the nucleus accumbens and temporal lobes, which may contribute to the development of ICD and perhaps predispose a patient to ICDs on exposure to dopamine replacement therapy.

Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy.

PURPOSE: Quasi-stable electrical distribution in EEG called microstates could carry useful information on the dynamics of large scale brain networks. Using machine learning techniques we explored if abnormalities in microstates can identify patients with Temporal Lobe Epilepsy (TLE) in the absence of an interictal discharge (IED). METHOD: 4 Classes of microstates were computed from 2 min artefact free EEG epochs in 42 subjects (21 TLE and 21 controls). The percentage of time coverage, frequency of occurrence and duration for each of these microstates were computed and redundancy reduced using feature selection methods. Subsequently, Fishers Linear Discriminant Analysis (FLDA) and logistic regression were used for classification. RESULT: FLDA distinguished TLE with 76.1% accuracy (85.0% sensitivity, 66.6% specificity) considering frequency of occurrence and percentage of time coverage of microstate C as features. CONCLUSION: Microstate alterations are present in patients with TLE. This feature might be useful in the diagnosis of epilepsy even in the absence of an IED.

Shaky and unsteady: Dynamic posturography in essential tremor.

BACKGROUND: The spectrum of symptoms exhibited by patients with essential tremor (ET) extends far beyond the classical tremor. This study aims to explore and establish the presence of subtle balance abnormalities in ET using dynamic posturography (DP). METHODS: DP was performed on 18 patients with ET and 26 controls. Diagnosis of ET was based on the Consensus Statement of the Movement Disorder Society on Tremor. Dynamic stability which included the overall balance index, anterior-posterior index and mediolateral index, and limits of stability were measured. RESULTS: Patients with ET had significantly impaired balance indices. Impairment of dynamic stability revealed poor static balance control in all directions. Lower limits of stability scores indicated a smaller range of motion prior to which patients have to shift foot balance. No correlations were observed between age at evaluation, age at onset, duration of illness and the balance indices. CONCLUSIONS: Dynamic posturography reveals significant balance impairment in patients with ET which is unrelated to the age at onset, age at evaluation or duration of illness. This finding concurs with pre-existing reports and adds to the growing body evidence of cerebellar involvement in ET.

A Single Session of rTMS Enhances Small-Worldness in Writer's Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph.

Background and Purpose: Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method: Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result: A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI (p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion: Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo. Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not "noise".