These findings are consistent with dysfunction of antinociceptive systems in MOH, which is influenced by anxiety. Dysfunction of the reward system may be a neurobiological basis for dependence in a subgroup of MOH patients.

Diffusion tensor imaging (DTI) is rarely applied in spinal cord injury (SCI). The aim of this study was to correlate diffusion properties after SCI with electrophysiological and neurological measures. Nineteen traumatic cervical SCI subjects and 28 age-matched healthy subjects participated in this study. DTI data of the spinal cord were acquired with a Philips Achieva 3 T MR scanner using an outer volume suppressed, reduced field of view (FOV) acquisition with oblique slice excitation and a single-shot EPI readout. Neurological and electrophysiological measures, American Spinal Injury Association (ASIA) impairment scale scores, and motor (MEP) and somatosensory evoked potentials (SSEP) were assessed in SCI subjects. Fractional anisotropy (FA) values were decreased in the SCI subjects compared to the healthy subjects. In upper cervical segments, the decrease in FA was significant for the evaluation of the entire cross-sectional area of the spinal cord, and for corticospinal and sensory tracts. A decreasing trend was also found at the thoracic level for the corticospinal tracts. The decrease of DTI values correlated with the clinical completeness of SCI, and with SSEP amplitudes. The reduced DTI values seen in the SCI subjects are likely due to demyelination and axonal degeneration of spinal tracts, which are related to clinical and electrophysiological measures. A reduction in DTI values in regions remote from the injury site suggests their involvement with wallerian axonal degeneration. DTI can be used for the quantitative evaluation of the extent of spinal cord damage, and eventually to monitor the effects of future regeneration-inducing treatments. This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. Abstract

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Our case supports the existence of a late onset adult form of LCC.

DT imaging revealed asymmetric anatomic changes in spinal cord NAWM, which corresponded to asymmetric electrophysiological deficits for both arms and legs, and reflected a specific structure-function relationship in the human spinal cord.

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There is much controversy about the link between motor symptom progression and the plethora of reported brain atrophy patterns in idiopathic Parkinson’s disease (PD). The main goal of this study is to provide empirical evidence for unique and common contributions of clinical phenotype characteristics on the dynamic changes of brain structure over time. We analyzed the behavioral and magnetic resonance imaging (MRI) data of PD patients (n = 22) and healthy individuals (n = 21) acquired two years apart through the computational anatomy framework of longitudinal voxel-based morphometry (VBM). This analysis revealed a symmetrical bi-hemispheric pattern of accelerated grey matter decrease in PD extending through the insula, parahippocampal gyrus, medial temporal lobes and the precuneus. We observed a hemisphere-specific correlation between the established scores for motor symptoms severity and the rate of atrophy within motor regions, which was further differentiated by the clinical phenotype characteristics of PD patients. Baseline cerebellum anatomy differences between the tremor-dominant and akineto-rigid PD remained stable over time and can be regarded as trait rather than state-associated features. We interpret the observed pattern of progressive brain anatomy changes as mainly linked to insular areas that determine together with basal ganglia the motor and non-motor phenotype in PD. Our findings provide empirical evidence for the sensitivity of computational anatomy to dynamic changes in PD, offering additional opportunities to establish reliable models of disease progression.