Parkinson's disease and local atrophy in subcortical nuclei: insight from shape analysis

Grit Is Associated with Structure of Nucleus Accumbens and Gains in Cognitive Training

There is a long-standing interest in the determinants of successful learning in children. “Grit” is an individual trait, reflecting the ability to pursue long-term goals despite temporary setbacks. Although grit is known to be predictive of future success in real-world learning situations, an understanding of the underlying neural basis and mechanisms is still lacking. Here we show that grit in a sample of 6-year-old children (n = 55) predicts the working memory improvement during 8 weeks of training on working memory tasks (p = .009). In a separate neuroimaging analysis performed on a partially overlapping sample (n = 27), we show that interindividual differences in grit were associated with differences in the volume of nucleus accumbens (peak voxel p = .021, x = 12, y = 11, z = −11). This was also confirmed in a leave-one-out analysis of gray matter density in the nucleus accumbens (p = .018). The results can be related to previous animal research showing the role of the nucleus accumbens to search out rewards regardless of delays or obstacles. The results provide a putative neural basis for grit and could contribute a cross-disciplinary connection of animal neuroscience to child psychology.

Low-Dimensional Statistics of Anatomical Variability via Compact Representation of Image Deformations

Using image-based descriptors to investigate clinical hypotheses and therapeutic implications is challenging due to the notorious "curse of dimensionality" coupled with a small sample size. In this paper, we present a low-dimensional analysis of anatomical shape variability in the space of diffeomorphisms and demonstrate its benefits for clinical studies. To combat the high dimensionality of the deformation descriptors, we develop a probabilistic model of principal geodesic analysis in a bandlimited low-dimensional space that still captures the underlying variability of image data. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than models based on the high-dimensional state-of-the-art approaches such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA).

Magnetic resonance imaging as a potential biomarker for Parkinson's disease

Although a magnetic resonance imaging (MRI) biomarker for Parkinson's disease (PD) remains an unfulfilled objective, there have been numerous developments in MRI methodology and some of these have shown promise for PD. With funding from the National Institutes of Health and the Michael J Fox Foundation there will be further validation of structural, diffusion-based, and iron-focused MRI methods as possible biomarkers for PD. In this review, these methods and other strategies such as neurochemical and metabolic MRI have been covered. One of the challenges in establishing a biomarker is in the selection of individuals as PD is a heterogeneous disease with varying clinical features, different etiologies, and a range of pathologic changes. Additionally, longitudinal studies are needed of individuals with clinically diagnosed PD and cohorts of individuals who are at great risk for developing PD to validate methods. Ultimately an MRI biomarker will be useful in the diagnosis of PD, predicting the course of PD, providing a means to track its course, and provide an approach to select and monitor treatments.

The volumetric and shape changes of the putamen and thalamus in first episode, untreated major depressive disorder

Previous MRI studies confirmed abnormalities in the limbic-cortical-striatal-pallidal-thalamic (LCSPT) network or limbic-cortico-striatal-thalamic-cortical (LCSTC) circuits in patients with major depressive disorder (MDD), but few studies have investigated the subcortical structural abnormalities. Therefore, we sought to determine whether focal subcortical grey matter (GM) changes might be present in MDD at an early stage. We recruited 30 first episode, untreated patients with major depressive disorder (MDD) and 26 healthy control subjects. Voxel-based morphometry was used to evaluate cortical grey matter changes, and automated volumetric and shape analyses were used to assess volume and shape changes of the subcortical GM structures, respectively. In addition, probabilistic tractography methods were used to demonstrate the relationship between the subcortical and the cortical GM. Compared to healthy controls, MDD patients had significant volume reductions in the bilateral putamen and left thalamus (FWE-corrected, p < 0.05). Meanwhile, the vertex-based shape analysis showed regionally contracted areas on the dorsolateral and ventromedial aspects of the bilateral putamen, and on the dorsal and ventral aspects of left thalamus in MDD patients (FWE-corrected, p < 0.05). Additionally, a negative correlation was found between local atrophy in the dorsal aspects of the left thalamus and clinical variables representing severity. Furthermore, probabilistic tractography demonstrated that the area of shape deformation of the bilateral putamen and left thalamus have connections with the frontal and temporal lobes, which were found to be related to major depression. Our results suggested that structural abnormalities in the putamen and thalamus might be present in the early stages of MDD, which support the role of subcortical structure in the pathophysiology of MDD. Meanwhile, the present study showed that these subcortical structural abnormalities might be the potential trait markers of MDD.

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Structural abnormalities in putamen and thalamus might be the potential trait marker of MDD at the early stage.

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The abnormality of LCSTC circuits, or LCSPT circuit, may contribute to the pathophysiology of MDD.

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The shape analysis is more sensitive to subtle structural changes than volumetric and VBM analysis.

The association between perceived social support and amygdala structure

The subjective perception of social support plays a crucial role in human well-being. However, its structural neural substrates remain unknown. We hypothesized that the amygdala, specifically its laterobasal and superficial subregions, which have been suggested to serve social functions, could be associated with the level of perceived social support. To test this hypothesis, we assessed perceived social support using the Multidimensional Scale of Perceived Social Support. In addition, we measured the volume and shape of the amygdala using structural magnetic resonance imaging in 49 healthy participants. Global amygdala volume in the left hemisphere was positively associated with the perceived social support score after adjusting for total cerebral volume, sex, age, intelligence, and five-factor personality domains. The local shape of the laterobasal and superficial subregions of the left amygdala showed the same association with perceived social support. These data suggest that the social subregions of the left amygdala are associated with the implementation of perceived social support.

Resting-state functional connectivity of the striatum in early-stage Parkinson's disease: Cognitive decline and motor symptomatology

Parkinson's disease is a neurodegenerative disorder characterized by changes to dopaminergic function in the striatum and a range of cognitive and motor deficits. Neuroimaging studies have repeatedly shown differences in activation and functional connectivity patterns of the striatum between symptomatic individuals with Parkinson's disease and healthy controls. However, the presence and severity of cognitive and motor symptoms seem to differ dramatically among individuals with Parkinson's disease at the early-stages. To investigate the neural basis of such heterogeneity, we examined the resting state functional connectivity patterns of caudate and putamen subdivisions in relation to cognitive and motor impairments among 62 early-stage individuals with Parkinson's disease (21 females, 23 drug naive, ages 39-77 years, average UPDRS motor scores off medication = 18.56, average H&Y stage = 1.66). We also explored how changes in striatal connectivity relate to changes in symptomatology over a year. There are two main findings. First, higher motor deficit rating was associated with weaker coupling between anterior putamen and midbrain including substantia nigra. Intriguingly, steeper declines in functional connectivity between these regions were associated with greater declines in motor function over the course of 1 year. Second, decline in cognitive function, particularly in the memory and visuospatial domains, was associated with stronger coupling between the dorsal caudate and the rostral anterior cingulate cortex. These findings remained significant after controlling for age, medication, gender, and education. In sum, our findings suggest that cognitive decline and motor deficit are each associated with a differentiable pattern of functional connectivity of striatal subregions. Hum Brain Mapp 37:648-662, 2016. © 2015 Wiley Periodicals, Inc.

Gray and White Matter Contributions to Cognitive Frontostriatal Deficits in Non-Demented Parkinson's Disease

Objective

This prospective investigation examined: 1) processing speed and working memory relative to other cognitive domains in non-demented medically managed idiopathic Parkinson’s disease, and 2) the predictive role of cortical/subcortical gray thickness/volume and white matter fractional anisotropy on processing speed and working memory.

Methods

Participants completed a neuropsychological protocol, Unified Parkinson’s Disease Rating Scale, brain MRI, and fasting blood draw to rule out vascular contributors. Within group a priori anatomical contributors included bilateral frontal thickness, caudate nuclei volume, and prefrontal white matter fractional anisotropy.

Results

Idiopathic Parkinson’s disease (n = 40; Hoehn & Yahr stages 1–3) and non-Parkinson’s disease ‘control’ peers (n = 40) matched on demographics, general cognition, comorbidity, and imaging/blood vascular metrics. Cognitively, individuals with Parkinson’s disease were significantly more impaired than controls on tests of processing speed, secondary deficits on working memory, with subtle impairments in memory, abstract reasoning, and visuoperceptual/spatial abilities. Anatomically, Parkinson’s disease individuals were not statistically different in cortical gray thickness or subcortical gray volumes with the exception of the putamen. Tract Based Spatial Statistics showed reduced prefrontal fractional anisotropy for Parkinson’s disease relative to controls. Within Parkinson’s disease, prefrontal fractional anisotropy and caudate nucleus volume partially explained processing speed. For controls, only prefrontal white matter was a significant contributor to processing speed. There were no significant anatomical predictors of working memory for either group.

Conclusions

Caudate nuclei volume and prefrontal fractional anisotropy, not frontal gray matter thickness, showed unique and combined significance for processing speed in Parkinson’s disease. Findings underscore the relevance for examining gray-white matter interactions and also highlight clinical processing speed metrics as potential indicators of early cognitive impairment in PD.

Multimodal MRI assessment of nigro-striatal pathway in multiple system atrophy and Parkinson disease

BACKGROUND

Parkinson's disease (PD) and multiple system atrophy (MSA) are two neurodegenerative alpha-synucleinopathies characterized by severe impairment of the nigro-striatal pathway. Based on T1-, T2*-, and diffusion-weighted magnetic resonance imaging (MRI), macro-structural and micro-structural abnormalities in these diseases can be detected.

OBJECTIVE

This study was undertaken to compare the nigro-striatal changes that occur in patients with PD with those in patients with both variants of MSA (the parkinsonian variant, MSA-P, and the cerebellar variant, MSA-C), and to explore correlations between different MRI parameters and clinical data.

METHODS

We simultaneously measured volume, T2* relaxation rates, and mean diffusivity in nigro-striatal structures (substantia nigra, caudate nucleus, and putamen) of 26 patients with PD and 29 patients with MSA (16 with MSA-P and 13 with MSA-C).

RESULTS

Significant changes in the putamina in patients with MSA were observed compared with patients with PD. Patients with MSA-P had higher mean diffusivity values in their putamina than did patients with PD or MSA-C. The putamina of both subgroups of MSA had higher T2* relaxation rates values than PD. Remarkably, discriminant analysis showed that using two measurements of microstructural damage (T2* relaxation rates and mean diffusivity in the putamen) allowed 96% accuracy to distinguish patients with PD from those with MSA-P. Correlation analyses between MRI findings and clinical variables revealed that patients with PD showed significant correlations only at the nigra. In patients with MSA, clinical variables correlated with MRI findings in both the nigra and striatum.

CONCLUSIONS

Multimodal MRI reveals different pattern of nigro-striatal involvement in patients with PD and patients with MSA.

Fall risk is associated with amplified functional connectivity of the central executive network in patients with Parkinson's disease

Falls are debilitating problems that markedly impact the health-related quality of life of many patients with Parkinson's disease (PD). Numerous studies point to the role of executive function and attention in falls; however, the brain mechanisms underlying these relationships are less clear. Here, we aim to evaluate the brain mechanisms underlying the role of executive function in falls. Patients with PD who were fallers (n = 27) or non-fallers (n = 53) and 27 healthy older adults were examined in a cross-sectional study. Gray matter volumes of the caudate head and posterior putamen were evaluated, as these striatal regions play a role in the executive and the sensorimotor cortico-striatal networks, respectively. The functional connectivity of the central executive network and of the sensorimotor network was measured using intrinsic brain connectivity during resting state functional magnetic resonance imaging. Compared to non-fallers and healthy controls, fallers had lower gray matter volume in the caudate head, but not in the posterior putamen, and increased connectivity between posterior partial regions of the central executive network, with no difference within the sensorimotor network. Mediation analysis demonstrated that the relationships between caudate head gray matter volume and fall history and risk were mediated by increased connectivity within the central executive network, apparently via attentional changes. The above findings provide additional converging evidence for the involvement of executive-related brain changes in falls in PD and support the important role of attention and executive function in fall risk.

Morphologic changes in the mesolimbic pathway in Parkinson's disease motor subtypes

BACKGROUND

Parkinson's disease (PD) is a common neurodegenerative disorder associated with gray matter atrophy. Cortical atrophy patterns may further help distinguish between PD motor subtypes. Comparable differences in subcortical volumes have not been found.

METHODS

Twenty-one cognitively intact and treated PD patients, including 12 tremor dominant (TD) subtype, Nine postural instability gait dominant (PIGD) subtype, and 20 matched healthy control subjects underwent 3.0 T high-resolution structural MRI scanning. Subcortical volumetric analysis was performed using FreeSurfer and shape analysis was performed with FIRST to assess for differences between PD patients and controls and between PD subtypes.

RESULTS

No significant differences in subcortical volumes were found between motor PD subtypes, but comparing grouped PD patients with controls revealed a significant increase in hippocampal volume in PD patients (p = 0.03). A significant shape difference was detected in the right nucleus accumbens (NAcc) between PD and controls and between motor subtypes. Shape differences were driven by positive deviations in the TD subtype. Correlation analysis revealed a trend between hippocampal volume and decreasing MDS-UPDRS (p = 0.06).

CONCLUSION

While no significant differences in subcortical volumes between PD motor subtypes were found, increased hippocampal volumes were observed in PD patients compared to controls. Right NAcc shape differences in PD patients were driven by changes in the TD subtype. These unexpected findings may be related to the effects of chronic dopaminergic replacement on the mesolimbic pathway. Further studies are needed to replicate and determine the clinical significance of such morphologic changes.