Automatic Segmentation and Quantification of Nigrosome-1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease.

BACKGROUND: There is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome-1 (N1). Existing tools evaluate the N1 sign, i.e., the presence or absence of the "swallow-tail" in iron-sensitive MRI, or globally analyze the MRI signal in an area containing the N1, without providing a volumetric delineation. PURPOSE: Present an automated method to segment the N1 and quantify differences in N1's NM and iron content between Parkinson's disease (PD) patients and healthy controls (HCs). Study whether N1 degeneration is clinically related to PD and could be used as a biomarker of the disease. STUDY TYPE: Prospective. SUBJECTS: Seventy-one PD (65.3 ± 10.3 years old, 34 female/37 male); 30 HC (62.7 ± 7.8 years old, 17 female/13 male). FIELD STRENGTH/SEQUENCE: 3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI). ASSESSMENT: N1 was automatically segmented in SWI images using a multi-image atlas, populated with healthy N1 structures manually annotated by a neurologist. Relative NM and iron content were quantified and their diagnostic performance assessed and compared with the substantia nigra pars compacta (SNc). The association between image parameters and clinically relevant variables was studied. STATISTICAL TESTS: Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05. RESULTS: N1's relative NM content decreased and relative iron content increased in PD patients compared with HCs (NM-CRHC = 22.55 ± 1.49; NM-CRPD = 19.79 ± 1.92; NM-nVolHC = 2.69 × 10-5 ± 1.02 × 10-5 ; NM-nVolPD = 1.18 × 10-5 ± 0.96 × 10-5 ; Iron-CRHC = 10.51 ± 2.64; Iron-CRPD = 19.35 ± 7.88; Iron-nVolHC = 0.72 × 10-5 ± 0.81 × 10-5 ; Iron-nVolPD = 2.82 × 10-5 ± 2.04 × 10-5 ). Binary logistic regression analyses combining N1 and SNc image parameters yielded a top AUC = 0.955. Significant correlation was found between most N1 parameters and both disease duration (ρNM-CR = -0.31; ρiron-CR = 0.43; ρiron-nVol = 0.46) and the motor status (ρNM-nVol = -0.27; ρiron-CR = 0.33; ρiron-nVol = 0.28), suggesting NM reduction along with iron accumulation in N1 as the disease progresses. DATA CONCLUSION: This method provides a fully automatic N1 segmentation, and the analyses performed reveal that N1 relative NM and iron quantification improves diagnostic performance and suggest a relative NM reduction along with a relative iron accumulation in N1 as the disease progresses. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Central neurogenetic signatures of the visuomotor integration system.

Visuomotor impairments characterize numerous neurological disorders and neurogenetic syndromes, such as autism spectrum disorder (ASD) and Dravet, Fragile X, Prader-Willi, Turner, and Williams syndromes. Despite recent advances in systems neuroscience, the biological basis underlying visuomotor functional impairments associated with these clinical conditions is poorly understood. In this study, we used neuroimaging connectomic approaches to map the visuomotor integration (VMI) system in the human brain and investigated the topology approximation of the VMI network to the Allen Human Brain Atlas, a whole-brain transcriptome-wide atlas of cortical genetic expression. We found the genetic expression of four genes-TBR1, SCN1A, MAGEL2, and CACNB4-to be prominently associated with visuomotor integrators in the human cortex. TBR1 gene transcripts, an ASD gene whose expression is related to neural development of the cortex and the hippocampus, showed a central spatial allocation within the VMI system. Our findings delineate gene expression traits underlying the VMI system in the human cortex, where specific genes, such as TBR1, are likely to play a central role in its neuronal organization, as well as on specific phenotypes of neurogenetic syndromes.

Brain ventricular enlargement in human and murine acute intermittent porphyria.

The morphological changes that occur in the central nervous system of patients with severe acute intermittent porphyria (AIP) have not yet been clearly established. The aim of this work was to analyze brain involvement in patients with severe AIP without epileptic seizures or clinical posterior reversible encephalopathy syndrome, as well as in a mouse model receiving or not liver-directed gene therapy aimed at correcting the metabolic disorder. We conducted neuroradiologic studies in 8 severely affected patients (6 women) and 16 gender- and age-matched controls. Seven patients showed significant enlargement of the cerebral ventricles and decreased brain perfusion was observed during the acute attack in two patients in whom perfusion imaging data were acquired. AIP mice exhibited reduced cerebral blood flow and developed chronic dilatation of the cerebral ventricles even in the presence of slightly increased porphyrin precursors. While repeated phenobarbital-induced attacks exacerbated ventricular dilation in AIP mice, correction of the metabolic defect using liver-directed gene therapy restored brain perfusion and afforded protection against ventricular enlargement. Histological studies revealed no signs of neuronal loss but a denser neurofilament pattern in the periventricular areas, suggesting compression probably caused by imbalance in cerebrospinal fluid dynamics. In conclusion, severely affected AIP patients exhibit cerebral ventricular enlargement. Liver-directed gene therapy protected against the morphological consequences of the disease seen in the brain of AIP mice. The observational study was registered at Clinicaltrial.gov as NCT02076763.

An amygdala-cingulate network underpins changes in effort-based decision making after a fitness program.

When humans make decisions, objective rewards are mainly discounted by delay, risk and effort. Whereas recent research has demonstrated that several brain areas process costs and code subjective value in effort-based decision making, it remains obscure how neural activity patterns change when effort costs are reduced due to the acquisition of healthy habits, such as moving from sedentary to active lifestyles. Here, a sample of sedentary volunteers was behaviorally assessed and fMRI-scanned before and after completing a 3-month fitness plan. The impact of effort cost on decisions, measured as the constant defining a hyperbolic decaying function, was reduced after the plan. A logistic mixed model demonstrated that the explanatory power of effort decreased with time. At a neural level, there was a marginally significant disruption of effort-cost related functional activity in the anterior cingulate after the plan. Functional connectivity between the amygdala and anterior cingulate cortex was strengthened after habit acquisition. In turn, this interaction was stronger in those participants with lower effort discounting. Thus, we show for the first time changes in value-based decision making after moving from a sedentary to an active lifestyle, which points to the relevance of the amygdala-cingulate interplay when the impact of effort on decisions fades away.

A neural basis for food foraging in obesity.

Poverty-related food insecurity can be viewed as a form of economic and nutritional uncertainty that can lead, in some situations, to a desire for more filling and satisfying food. Given the current obesogenic food environment and the nature of the food supply, those food choices could engage a combination of sensory, neurophysiological, and genetic factors as potential determinants of obesity.

Default-mode network dynamics are restricted during high speed discrimination in healthy aging: Associations with neurocognitive status and simulated driving behavior.

Numerous daily tasks, including car driving, require fine visuospatial tuning. One such visuospatial ability, speed discrimination, declines with aging but its neural underpinnings remain unknown. In this study, we use fMRI to explore the effect of aging during a high speed discrimination task and its neural underpinnings, along with a complete neuropsychological assessment and a simulated driving evaluation in order to examine how they interact with each other through a multivariate regression approach. Beyond confirming that high speed discrimination performance is diminished in the elderly, we found that this deficit might be partly due to a lack of modulation in the activity and connectivity of the default mode network (DMN) in this age group, as well as an over-recruitment of frontoparietal and cerebellar regions, possibly as a compensatory mechanism. In addition, younger adults tended to drive at faster speeds, a behavior that was associated to adequate DMN dynamics and executive functioning, an effect that seems to be lost in the elderly. In summary, these results reveal how age-related declines in fine visuospatial abilities, such as high speed discrimination, were distinctly mediated by DMN functioning, a mechanism also associated to speeding behavior in a driving simulator.

Kinematic and Kinetic Patterns Related to Free-Walking in Parkinson's Disease.

The aim of this study is to compare the properties of free-walking at a natural pace between mild Parkinson's disease (PD) patients during the ON-clinical status and two control groups. In-shoe pressure-sensitive insoles were used to quantify the temporal and force characteristics of a 5-min free-walking in 11 PD patients, in 16 young healthy controls, and in 12 age-matched healthy controls. Inferential statistics analyses were performed on the kinematic and kinetic parameters to compare groups' performances, whereas feature selection analyses and automatic classification were used to identify the signature of parkinsonian gait and to assess the performance of group classification, respectively. Compared to healthy subjects, the PD patients' gait pattern presented significant differences in kinematic parameters associated with bilateral coordination but not in kinetics. Specifically, patients showed an increased variability in double support time, greater gait asymmetry and phase deviation, and also poorer phase coordination. Feature selection analyses based on the ReliefF algorithm on the differential parameters in PD patients revealed an effect of the clinical status, especially true in double support time variability and gait asymmetry. Automatic classification of PD patients, young and senior subjects confirmed that kinematic predictors produced a slightly better classification performance than kinetic predictors. Overall, classification accuracy of groups with a linear discriminant model which included the whole set of features (i.e., demographics and parameters extracted from the sensors) was 64.1%.

Deleterious ABCA7 mutations and transcript rescue mechanisms in early onset Alzheimer's disease.

Premature termination codon (PTC) mutations in the ATP-Binding Cassette, Sub-Family A, Member 7 gene (ABCA7) have recently been identified as intermediate-to-high penetrant risk factor for late-onset Alzheimer's disease (LOAD). High variability, however, is observed in downstream ABCA7 mRNA and protein expression, disease penetrance, and onset age, indicative of unknown modifying factors. Here, we investigated the prevalence and disease penetrance of ABCA7 PTC mutations in a large early onset AD (EOAD)-control cohort, and examined the effect on transcript level with comprehensive third-generation long-read sequencing. We characterized the ABCA7 coding sequence with next-generation sequencing in 928 EOAD patients and 980 matched control individuals. With MetaSKAT rare variant association analysis, we observed a fivefold enrichment (p = 0.0004) of PTC mutations in EOAD patients (3%) versus controls (0.6%). Ten novel PTC mutations were only observed in patients, and PTC mutation carriers in general had an increased familial AD load. In addition, we observed nominal risk reducing trends for three common coding variants. Seven PTC mutations were further analyzed using targeted long-read cDNA sequencing on an Oxford Nanopore MinION platform. PTC-containing transcripts for each investigated PTC mutation were observed at varying proportion (5-41% of the total read count), implying incomplete nonsense-mediated mRNA decay (NMD). Furthermore, we distinguished and phased several previously unknown alternative splicing events (up to 30% of transcripts). In conjunction with PTC mutations, several of these novel ABCA7 isoforms have the potential to rescue deleterious PTC effects. In conclusion, ABCA7 PTC mutations play a substantial role in EOAD, warranting genetic screening of ABCA7 in genetically unexplained patients. Long-read cDNA sequencing revealed both varying degrees of NMD and transcript-modifying events, which may influence ABCA7 dosage, disease severity, and may create opportunities for therapeutic interventions in AD.

Trade-off between frequency and precision during stepping movements: Kinematic and BOLD brain activation patterns.

The central nervous system has the ability to adapt our locomotor pattern to produce a wide range of gait modalities and velocities. In reacting to external pacing stimuli, deviations from an individual preferred cadence provoke a concurrent decrease in accuracy that suggests the existence of a trade-off between frequency and precision; a compromise that could result from the specialization within the control centers of locomotion to ensure a stable transition and optimal adaptation to changing environment. Here, we explore the neural correlates of such adaptive mechanisms by visually guiding a group of healthy subjects to follow three comfortable stepping frequencies while simultaneously recording their BOLD responses and lower limb kinematics with the use of a custom-built treadmill device. In following the visual stimuli, subjects adopt a common pattern of symmetric and anti-phase movements across pace conditions. However, when increasing the stimulus frequency, an improvement in motor performance (precision and stability) was found, which suggests a change in the control mode from reactive to predictive schemes. Brain activity patterns showed similar BOLD responses across pace conditions though significant differences were observed in parietal and cerebellar regions. Neural correlates of stepping precision were found in the insula, cerebellum, dorsolateral pons and inferior olivary nucleus, whereas neural correlates of stepping stability were found in a distributed network, suggesting a transition in the control strategy across the stimulated range of frequencies: from unstable/reactive at lower paces (i.e., stepping stability managed by subcortical regions) to stable/predictive at higher paces (i.e., stability managed by cortical regions). Hum Brain Mapp 37:1722-1737, 2016. © 2016 Wiley Periodicals, Inc.

A comprehensive study of the genetic impact of rare variants in SORL1 in European early-onset Alzheimer's disease.

The sortilin-related receptor 1 (SORL1) gene has been associated with increased risk for Alzheimer's disease (AD). Rare genetic variants in the SORL1 gene have also been implicated in autosomal dominant early-onset AD (EOAD). Here we report a large-scale investigation of the contribution of genetic variability in SORL1 to EOAD in a European EOAD cohort. We performed massive parallel amplicon-based re-sequencing of the full coding region of SORL1 in 1255 EOAD patients and 1938 age- and origin-matched control individuals in the context of the European Early-Onset Dementia (EOD) consortium, originating from Belgium, Spain, Portugal, Italy, Sweden, Germany, and Czech Republic. We identified six frameshift variants and two nonsense variants that were exclusively present in patients. These mutations are predicted to result in haploinsufficiency through nonsense-mediated mRNA decay, which could be confirmed experimentally for SORL1 p.Gly447Argfs*22 observed in a Belgian EOAD patient. We observed a 1.5-fold enrichment of rare non-synonymous variants in patients (carrier frequency 8.8 %; SkatOMeta p value 0.0001). Of the 84 non-synonymous rare variants detected in the full patient/control cohort, 36 were only detected in patients. Our findings underscore a role of rare SORL1 variants in EOAD, but also show a non-negligible frequency of these variants in healthy individuals, necessitating the need for pathogenicity assays. Premature stop codons due to frameshift and nonsense variants, have so far exclusively been found in patients, and their predicted mode of action corresponds with evidence from in vitro functional studies of SORL1 in AD.

Rare Variants in PLD3 Do Not Affect Risk for Early-Onset Alzheimer Disease in a European Consortium Cohort.

Rare variants in the phospholipase D3 gene (PLD3) were associated with increased risk for late-onset Alzheimer disease (LOAD). We identified a missense mutation in PLD3 in whole-genome sequence data of a patient with autopsy confirmed Alzheimer disease (AD) and onset age of 50 years. Subsequently, we sequenced PLD3 in a Belgian early-onset Alzheimer disease (EOAD) patient (N = 261) and control (N = 319) cohort, as well as in European EOAD patients (N = 946) and control individuals (N = 1,209) ascertained in different European countries. Overall, we identified 22 rare variants with a minor allele frequency <1%, 20 missense and two splicing mutations. Burden analysis did not provide significant evidence for an enrichment of rare PLD3 variants in EOAD patients in any of the patient/control cohorts. Also, meta-analysis of the PLD3 data, including a published dataset of a German EOAD cohort, was not significant (P = 0.43; OR = 1.53, 95% CI 0.60-3.31). Consequently, our data do not support a role for PLD3 rare variants in the genetic etiology of EOAD in European EOAD patients. Our data corroborate the negative replication data obtained in LOAD studies and therefore a genetic role of PLD3 in AD remains to be demonstrated.

Resting state functional connectivity of the subthalamic nucleus in Parkinson's disease assessed using arterial spin-labeled perfusion fMRI.

Neurophysiological changes within the cortico-basal ganglia-thalamocortical circuits appear to be a characteristic of Parkinson's disease (PD) pathophysiology. The subthalamic nucleus (STN) is one of the basal ganglia components showing pathological neural activity patterns in PD. In this study, perfusion imaging data, acquired noninvasively using arterial spin-labeled (ASL) perfusion MRI, were used to assess the resting state functional connectivity (FC) of the STN in 24 early-to-moderate PD patients and 34 age-matched healthy controls, to determine whether altered FC in the very low frequency range of the perfusion time signal occurs as a result of the disease. Our results showed that the healthy STN was functionally connected with other nuclei of the basal ganglia and the thalamus, as well as with discrete cortical areas including the insular cortex and the hippocampus. In PD patients, connectivity of the STN was increased with two cortical areas involved in motor and cognitive processes. These findings suggest that hyperconnectivity of the STN could underlie some of the motor and cognitive deficits often present even at early stages of the disease. The FC measures provided good discrimination between controls and patients, suggesting that ASL-derived FC metrics could be a putative PD biomarker.

Automated neuromelanin imaging as a diagnostic biomarker for Parkinson's disease.

BACKGROUND: We aimed to analyze the diagnostic accuracy of an automated segmentation and quantification method of the SNc and locus coeruleus (LC) volumes based on neuromelanin (NM)-sensitive MRI (NM-MRI) in patients with idiopathic (iPD) and monogenic (iPD) Parkinson's disease (PD). METHODS: Thirty-six patients (23 idiopathic and 13 monogenic PARKIN or LRRK2 mutations) and 37 age-matched healthy controls underwent 3T-NM-MRI. SNc and LC volumetry were performed using fully automated multi-image atlas segmentation. The diagnostic performance to differentiate PD from controls was measured using the area under the curve (AUC) and likelihood ratios based on receiver operating characteristic (ROC) analyses. RESULTS: We found a significant reduction of SNc and LC volumes in patients, when compared to controls. ROC analysis showed better diagnostic accuracy when using SNc volume than LC volume. Significant differences between ipsilateral and contralateral SNc volumes, in relation to the more clinically affected side, were found in patients with iPD (P = 0.007). Contralateral atrophy in the SNc showed the highest power to discriminate PD subjects from controls (AUC, 0.93-0.94; sensitivity, 91%-92%; specificity, 89%; positive likelihood ratio: 8.4-8.5; negative likelihood ratio: 0.09-0.1 at a single cut-off point). Interval likelihood ratios for contralateral SNc volume improved the diagnostic accuracy of volumetric measurements. CONCLUSION: SNc and LC volumetry based on NM-MRI resulting from the automated segmentation and quantification technique can yield high diagnostic accuracy for differentiating PD from health and might be an unbiased disease biomarker. © 2015 International Parkinson and Movement Disorder Society.

Evaluation of segmented 3D acquisition schemes for whole-brain high-resolution arterial spin labeling at 3 T.

Recent technical developments have significantly increased the signal-to-noise ratio (SNR) of arterial spin labeled (ASL) perfusion MRI. Despite this, typical ASL acquisitions still employ large voxel sizes. The purpose of this work was to implement and evaluate two ASL sequences optimized for whole-brain high-resolution perfusion imaging, combining pseudo-continuous ASL (pCASL), background suppression (BS) and 3D segmented readouts, with different in-plane k-space trajectories. Identical labeling and BS pulses were implemented for both sequences. Two segmented 3D readout schemes with different in-plane trajectories were compared: Cartesian (3D GRASE) and spiral (3D RARE Stack-Of-Spirals). High-resolution perfusion images (2 × 2 × 4 mm(3) ) were acquired in 15 young healthy volunteers with the two ASL sequences at 3 T. The quality of the perfusion maps was evaluated in terms of SNR and gray-to-white matter contrast. Point-spread-function simulations were carried out to assess the impact of readout differences on the effective resolution. The combination of pCASL, in-plane segmented 3D readouts and BS provided high-SNR high-resolution ASL perfusion images of the whole brain. Although both sequences produced excellent image quality, the 3D RARE Stack-Of-Spirals readout yielded higher temporal and spatial SNR than 3D GRASE (spatial SNR = 8.5 ± 2.8 and 3.7 ± 1.4; temporal SNR = 27.4 ± 12.5 and 15.6 ± 7.6, respectively) and decreased through-plane blurring due to its inherent oversampling of the central k-space region, its reduced effective TE and shorter total readout time, at the expense of a slight increase in the effective in-plane voxel size.

Feasibility study of a wearable system based on a wireless body area network for gait assessment in Parkinson's disease patients.

Parkinson's disease (PD) alters the motor performance of affected individuals. The dopaminergic denervation of the striatum, due to substantia nigra neuronal loss, compromises the speed, the automatism and smoothness of movements of PD patients. The development of a reliable tool for long-term monitoring of PD symptoms would allow the accurate assessment of the clinical status during the different PD stages and the evaluation of motor complications. Furthermore, it would be very useful both for routine clinical care as well as for testing novel therapies. Within this context we have validated the feasibility of using a Body Network Area (BAN) of wireless accelerometers to perform continuous at home gait monitoring of PD patients. The analysis addresses the assessment of the system performance working in real environments.

The problem of consciousness in habitual decision making.

Newell & Shanks (N&S) carry out an extremely sharp and static distinction between conscious and unconscious decisions, ignoring a process that dynamically transfers decisions and actions between the conscious and unconscious domains of the mind: habitual decision making. We propose a new categorisation and discuss the main characteristics of this process from a philosophical and neuroscientific perspective.

Comparison of 2D and 3D single-shot ASL perfusion fMRI sequences.

Arterial spin labeling (ASL) can be implemented by combining different labeling schemes and readout sequences. In this study, the performance of 2D and 3D single-shot pulsed-continuous ASL (pCASL) sequences was assessed in a group of young healthy volunteers undergoing a baseline perfusion and a functional study with a sensory-motor activation paradigm. The evaluated sequences were 2D echo-planar imaging (2D EPI), 3D single-shot fast spin-echo with in-plane spiral readout (3D FSE spiral), and 3D single-shot gradient-and-spin-echo (3D GRASE). The 3D sequences were implemented with and without the addition of an optimized background suppression (BS) scheme. Labeling efficiency, signal-to-noise ratio (SNR), and gray matter (GM) to white matter (WM) contrast ratio were assessed in baseline perfusion measurements. 3D acquisitions without BS yielded 2-fold increments in spatial SNR, but no change in temporal SNR. The addition of BS to the 3D sequences yielded a 3-fold temporal SNR increase compared to the unsuppressed sequences. 2D EPI provided better GM-to-WM contrast ratio than the 3D sequences. The analysis of functional data at the subject level showed a 3-fold increase in statistical power for the BS 3D sequences, although the improvement was attenuated at the group level. 3D without BS did not increase the maximum t-values, however, it yielded larger activation clusters than 2D. These results demonstrate that BS 3D single-shot imaging sequences improve the performance of pCASL in baseline and activation studies, particularly for individual subject analyses where the improvement in temporal SNR translates into markedly enhanced power for task activation detection.

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility.

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the gray matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9-0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies.

Functional asymmetries in early learning during right, left, and bimanual performance in right-handed subjects.

PURPOSE: To elucidate differences in activity and connectivity during early learning due to the performing hand. MATERIALS AND METHODS: Twenty right-handed subjects were recruited. The neural correlates of explicit visuospatial learning executed with the right, the left hand, and bimanually were investigated using functional magnetic resonance imaging. Connectivity analyses were carried out using the psychophysiological interactions model, considering right and left anterior putamen as index regions. RESULTS: A common neural network was found for the three tasks during learning. Main activity increases were located in posterior cingulate cortex, supplementary motor area, parietal cortex, anterior putamen, and cerebellum (IV-V), whereas activity decrements were observed in prefrontal regions. However, the left hand task showed a greater recruitment of left hippocampal areas when compared with the other tasks. In addition, enhanced connectivity between the right anterior putamen and motor cortical and cerebellar regions was found for the left hand when compared with the right hand task. CONCLUSION: An additional recruitment of brain regions and increased striato-cortical and striato-cerebellar functional connections is needed when early learning is performed with the nondominant hand. In addition, access to brain resources during learning may be directed by the dominant hand in the bimanual task.

Brainstem neuromelanin and iron MRI reveals a precise signature for idiopathic and LRRK2 Parkinson's disease.

Neuromelanin (NM) loss in substantia nigra pars compacta (SNc) and locus coeruleus (LC) reflects neuronal death in Parkinson's disease (PD). Since genetically-determined PD shows varied clinical expressivity, we wanted to accurately quantify and locate brainstem NM and iron, to discover whether specific MRI patterns are linked to Leucine-rich repeat kinase 2 G2019S PD (LRRK2-PD) or idiopathic Parkinson's disease (iPD). A 3D automated MRI atlas-based segmentation pipeline (3D-ABSP) for NM/iron-sensitive MRI images topographically characterized the SNc, LC, and red nucleus (RN) neuronal loss and calculated NM/iron contrast ratio (CR) and normalized volume (nVol). Left-side NM nVol was larger in all groups. PD had lower NM CR and nVol in ventral-caudal SNc, whereas iron increased in lateral, medial-rostral, and caudal SNc. The SNc NM CR reduction was associated with psychiatric symptoms. LC CR and nVol discriminated better among subgroups: LRRK2-PD had similar LC NM CR and nVol as that of controls, and larger LC NM nVol and RN iron CR than iPD. PD showed higher iron SNc nVol than controls, especially among LRRK2-PD. ROC analyses showed an AUC > 0.92 for most pairwise subgroup comparisons, with SNc NM being the best discriminator between HC and PD. NM measures maintained their discriminator power considering the subgroup of PD patients with less than 5 years of disease duration. The SNc iron CR and nVol increase was associated with longer disease duration in PD patients. The 3D-ABSP sensitively identified NM and iron MRI patterns strongly correlated with phenotypic PD features.