When planning fails: Individual differences and error-related brain activity in problem solving.

The neuronal processes underlying correct and erroneous problem solving were studied in strong and weak problem-solvers using functional magnetic resonance imaging (fMRI). During planning, the right dorsolateral prefrontal cortex was activated, and showed a linear relationship with the participants' performance level. A similar pattern emerged in right inferior parietal regions for all trials, and in anterior cingulate cortex for erroneously solved trials only. In the performance phase, when the pre-planned moves had to be executed by means of an fMRI-compatible computer mouse, the right dorsolateral prefrontal cortex was again activated jointly with right parahippocampal cortex, and displayed a similar positive relationship with the participants' performance level. Incorrectly solved problems elicited stronger bilateral prefrontal and left inferior parietal activations than correctly solved trials. For both individual ability and trial-specific performance, our results thus demonstrate the crucial involvement of right prefrontal cortex in efficient visuospatial planning

Detection of Motor Changes in Huntington's Disease Using Dynamic Causal Modeling

Neurological Motor Disorder

Cross-sectional and longitudinal voxel-based grey matter asymmetries in Huntington's disease

Huntington's disease (HD) is a progressive neurodegenerative disorder that can be genetically confirmed with certainty decades before clinical onset. This allows the investigation of functional and structural changes in HD many years prior to disease onset, which may reveal important mechanistic insights into brain function, structure and organization in general. While regional atrophy is present at early stages of HD, it is still unclear if both hemispheres are equally affected by neurodegeneration and how the extent of asymmetry affects domain-specific functional decline. Here, we used whole-brain voxel-based analysis to investigate cross-sectional and longitudinal hemispheric asymmetries in grey matter (GM) volume in 56 manifest HD (mHD), 83 pre-manifest HD (preHD), and 80 healthy controls (HC). Furthermore, a regression analysis was used to assess the relationship between neuroanatomical asymmetries and decline in motor and cognitive measures across the disease spectrum. The cross-sectional analysis showed striatal leftward-biased GM atrophy in mHD, but not in preHD, relative to HC. Longitudinally, no net 36-month change in GM asymmetries was found in any of the groups. In the regression analysis, HD-related decline in quantitative-motor (Q-Motor) performance was linked to lower GM volume in the left superior parietal cortex. These findings suggest a stronger disease effect targeting the left hemisphere, especially in those with declining motor performance. This effect did not change over a period of three years and may indicate a compensatory role of the right hemisphere in line with recent functional imaging studies

Robust intra-individual estimation of structural connectivity by Principal Component Analysis

Fiber tractography based on diffusion-weighted MRI provides a non-invasive characterization of the structural connectivity of the human brain at the macroscopic level. Quantification of structural connectivity strength is challenging and mainly reduced to “streamline counting” methods. These are however highly dependent on the topology of the connectome and the particular specifications for seeding and filtering, which limits their intra-subject reproducibility across repeated measurements and, in consequence, also confines their validity. Here we propose a novel method for increasing the intra-subject reproducibility of quantitative estimates of structural connectivity strength. To this end, the connectome is described by a large matrix in positional-orientational space and reduced by Principal Component Analysis to obtain the main connectivity “modes”. It was found that the proposed method is quite robust to structural variability of the data

Hemodynamics of cerebral veins analyzed by 2d and 4d flow mri and ultrasound in healthy volunteers and patients with multiple sclerosis

Background Hemodynamic alterations of extracranial veins are considered an etiologic factor in multiple sclerosis (MS). However, ultrasound and MRI studies could not confirm a pathophysiological link. Because of technical challenges using standard diagnostics, information about the involvement of superficial intracranial veins in proximity to the affected brain in MS is scarce. Purpose To comprehensively investigate the hemodynamics of intracranial veins and of the venous outflow tract in MS patients and controls. Study Type Prospective. Population Twenty‐eight patients with relapsing‐remitting MS (EDSS1.9 ± 1.1; range 0–3) and 41 healthy controls. Field Strength/Sequence 3T/2D phase‐contrast and time‐resolved 4D flow MRI, extra‐ and transcranial sonography. Assessment Hemodynamics within the superficial and deep intracranial venous system and outflow tract including the internal, basal, and great cerebral vein, straight, superior sagittal, and transverse sinuses, internal jugular and vertebral veins. Sonography adhered to the chronic cerebrospinal venous insufficiency (CCSVI) criteria. Statistical Tests Multivariate repeated measure analysis of variance, Student's two‐sample t‐test, chi‐square, Fisher's exact test; separate analysis of the entire cohort and 32 age‐ and sex‐matched participants. Results Multi‐ and univariate main effects of the factor group (MS patient vs. control) and its interactions with the factor vessel position (lower flow within dorsal superior sagittal sinus in MS, 3 ± 1 ml/s vs. 3.8 ± 1 ml/s; P < 0.05) in the uncontrolled cohort were attributable to age‐related differences. Age‐ and sex‐matched pairs showed a different velocity gradient in a single segment within the deep cerebral veins (great cerebral vein, vena cerebri magna [VCM] 7.6 ± 1.7 cm/s; straight sinus [StS] 10.5 ± 2.2 cm/s vs. volunteers: VCM 9.2 ± 2.3 cm/s; StS 10.2 ± 2.3 cm/s; P = 0.01), reaching comparable velocities instantaneously downstream. Sonography was not statistically different between groups. Data Conclusion Consistent with previous studies focusing on extracranial hemodynamics, our comprehensive analysis of intracerebral venous blood flow did not reveal relevant differences between MS patients and controls

Large-scale brain network abnormalities in Huntington's disease revealed by structural covariance

Huntington's disease (HD) is a progressive neurodegenerative disorder that can be diagnosed with certainty decades before symptom onset. Studies using structural MRI have identified grey matter (GM) loss predominantly in the striatum, but also involving various cortical areas. So far, voxel-based morphometric studies have examined each brain region in isolation and are thus unable to assess the changes in the interrelation of brain regions. Here, we examined the structural covariance in GM volumes in pre-specified motor, working memory, cognitive flexibility, and social-affective networks in 99 patients with manifest HD (mHD), 106 presymptomatic gene mutation carriers (pre-HD), and 108 healthy controls (HC). After correction for global differences in brain volume, we found that increased GM volume in one region was associated with increased GM volume in another. When statistically comparing the groups, no differences between HC and pre-HD were observed, but increased positive correlations were evident for mHD, relative to pre-HD and HC. These findings could be explained by a HD-related neuronal loss heterogeneously affecting the examined network at the pre-HD stage, which starts to dominate structural covariance globally at the manifest stage. Follow-up analyses identified structural connections between frontoparietal motor regions to be linearly modified by disease burden score (DBS). Moderator effects of disease load burden became significant at a DBS level typically associated with the onset of unequivocal HD motor signs. Together with existing findings from functional connectivity analyses, our data indicates a critical role of these frontoparietal regions for the onset of HD motor signs

Cross-sectional and longitudinal voxel-based grey matter asymmetries in Huntington's disease

Neurological Motor Disorder