Hugo C. Baggio

Progression of cortical thinning in early Parkinson's disease.

The aim of this study was to investigate the progression of cortical thinning and gray‐matter (GM) volume loss in early Parkinsons disease (PD). MRI and neuropsychological assessment were obtained at baseline and follow‐up (mean ± standard deviation = 35.50 ± 1.88 months) in a group of 16 early‐PD patients (H & Y stage ≤II and disease duration ≤5 years) and 15 healthy controls matched for age, gender, and years of education. FreeSurfer software was used for the analysis of cortical thickness as well as for cortical and subcortical volumetric analyses. Voxel‐based morphometry analysis was performed using SPM8. Compared to controls, PD patients showed greater regional cortical thinning in bilateral frontotemporal regions as well as greater over‐time total GM loss and amygdalar volume reduction. PD patients and controls presented similar over‐time changes in cognitive functioning. In early‐PD patients, global GM loss, amygdalar atrophy, and cortical thinning in frontotemporal regions are specifically associated with the PD‐degenerative process.

Rich club organization and cognitive performance in healthy older participants

The human brain is a complex network that has been noted to contain a group of densely interconnected hub regions. With a putative “rich club” of hubs hypothesized to play a central role in global integrative brain functioning, we assessed whether hub and rich club organizations are associated with cognitive performance in healthy participants and whether the rich club might be differentially involved in cognitive functions with a heavier dependence on global integration. A group of 30 relatively older participants (range = 39–79 years of age) underwent extensive neuropsychological testing, combined with diffusion-weighted magnetic resonance imaging to reconstruct individual structural brain networks. Rich club connectivity was found to be associated with general cognitive performance. More specifically, assessing the relationship between the rich club and performance in two specific cognitive domains, we found rich club connectivity to be differentially associated with attention/executive functions—known to rely on the integration of distributed brain areas—rather than with visuospatial/visuoperceptual functions, which have a more constrained neuroanatomical substrate. Our findings thus provide first empirical evidence of a relevant role played by the rich club in cognitive processes.

Resting-State Functional Brain Networks in Parkinson's Disease

The network approach is increasingly being applied to the investigation of normal brain function and its impairment. In the present review, we introduce the main methodological approaches employed for the analysis of resting‐state neuroimaging data in Parkinsons disease studies. We then summarize the results of recent studies that used a functional network perspective to evaluate the changes underlying different manifestations of Parkinsons disease, with an emphasis on its cognitive symptoms. Despite the variability reported by many studies, these methods show promise as tools for shedding light on the pathophysiological substrates of different aspects of Parkinsons disease, as well as for differential diagnosis, treatment monitoring and establishment of imaging biomarkers for more severe clinical outcomes.

Structural MRI correlates of the MMSE and pentagon copying test in Parkinson's disease

BACKGROUND Cognitive impairment in Parkinsons disease (PD) is common and recent studies have focused on addressing the most suitable screening tool for its assessment. MMSE is commonly used in clinical practice and longitudinal studies found a relationship between the MMSE pentagon copying item and progression to dementia, but its neuroanatomical correlates have been poorly investigated. The aim of this study is to investigate the MRI structural correlates of the global MMSE and the pentagon item scores in PD patients in the absence of dementia. METHODS We selected a sample of 92 PD patients and 36 controls. MMSE was used as a global measure of cognitive status, and the pentagon copying test as a measure of visuospatial performance. FreeSurfer software was used to assess intergroup differences in cortical thickness (CTh) and global atrophy measures, as well as their relationship with cognitive performance. RESULTS Compared to controls, patients showed significant differences in measures of global atrophy, which correlated with performance on MMSE and the pentagon item. Regional differences in CTh were seen between PD patients and controls bilaterally in the temporo-parietal-occipital region. Patients with impaired performance compared with those of normal performance also showed CTh reductions in these regions. CONCLUSION Our results suggest MMSE and the pentagon item reflect brain changes which at a regional level involve mainly posterior regions. Correlates of the pentagon item were seen in the same regions where PD patients exhibited significant thinning, and involved more areas and bigger cluster sizes than the correlates of MMSE global scores.

Nigral and striatal connectivity alterations in asymptomatic LRRK2 mutation carriers: A magnetic resonance imaging study

The study of functional connectivity by means of magnetic resonance imaging (MRI) in asymptomatic LRRK2 mutation carriers could contribute to the characterization of the prediagnostic phase of LRRK2‐associated Parkinsons disease (PD). The objective of this study was to characterize MRI functional patterns during the resting state in asymptomatic LRRK2 mutation carriers.

Discriminating cognitive status in Parkinson’s disease through functional connectomics and machine learning

There is growing interest in the potential of neuroimaging to help develop non-invasive biomarkers in neurodegenerative diseases. In this study, connection-wise patterns of functional connectivity were used to distinguish Parkinson’s disease patients according to cognitive status using machine learning. Two independent subject samples were assessed with resting-state fMRI. The first (training) sample comprised 38 healthy controls and 70 Parkinson’s disease patients (27 with mild cognitive impairment). The second (validation) sample included 25 patients (8 with mild cognitive impairment). The Brainnetome atlas was used to reconstruct the functional connectomes. Using a support vector machine trained on features selected through randomized logistic regression with leave-one-out cross-validation, a mean accuracy of 82.6% (p < 0.002) was achieved in separating patients with mild cognitive impairment from those without it in the training sample. The model trained on the whole training sample achieved an accuracy of 80.0% when used to classify the validation sample (p = 0.006). Correlation analyses showed that the connectivity level in the edges most consistently selected as features was associated with memory and executive function performance in the patient group. Our results demonstrate that connection-wise patterns of functional connectivity may be useful for discriminating Parkinson’s disease patients according to the presence of cognitive deficits.

Cortical thinning correlates of changes in visuospatial and visuoperceptual performance in Parkinson's disease: A 4-year follow-up

BACKGROUND Growing evidence highlights the relevance of posterior cortically-based cognitive deficits in Parkinsons disease (PD) as possible biomarkers of the evolution to dementia. Cross-sectional correlational studies have established a relationship between the degree of atrophy in posterior brain regions and visuospatial and visuoperceptual (VS/VP) impairment. The aim of this study is to address the progressive cortical thinning correlates of VS/VP performance in PD. METHODS Forty-four PD patients and 20 matched healthy subjects were included in this study and followed for 4 years. Tests used to assess VS/VP functions included were: Bentons Judgement of Line Orientation (JLOT), Facial Recognition (FRT), and Visual Form Discrimination (VFDT) Tests; Symbol Digit Modalities Test (SDMT); and the Pentagon Copying Test (PCT). Structural magnetic resonance imaging data and FreeSurfer were used to evaluate cortical thinning evolution. RESULTS PD patients with normal cognition (PD-NC) and PD patients with mild cognitive impairment (PD-MCI) differed significantly in the progression of cortical thinning in posterior regions. In PD-MCI patients, the change in VS/VP functions assessed by PCT, JLOT, FRT, and SMDT correlated with the symmetrized percent change of cortical thinning of occipital, parietal, and temporal regions. In PD-NC patients, we also observed a correlation between changes in FRT and thinning in parieto-occipital regions. CONCLUSION In this study, we establish the neuroanatomical substrate of progressive changes in VS/VP performance in PD patients with and without MCI. In agreement with cross-sectional data, VS/VP changes over time are related to cortical thinning in posterior regions.

Functional MRI in Parkinson's Disease Cognitive Impairment

Functional magnetic resonance imaging (fMRI) has been used to study the neural bases of cognitive deficits in Parkinsons disease for several years. Traditionally, task-based fMRI has been applied to study specific cognitive functions, providing information on disease-related alterations and regarding the physiological bases of normal cognition, the dopaminergic system, and the frontostriatal circuits. More recently, functional connectivity techniques using resting-state fMRI data have been developed. Unconstrained by specific cognitive tasks, these techniques allow assessing whole-brain patterns of connectivity believed to be useful proxies for the underlying functional architecture of the brain. These methods have shown that different types of Parkinsons disease-related cognitive deficits are associated with patterns of altered connectivity within and between resting-state intrinsic connectivity networks. Although methodological standardization and the vulnerability of fMRI techniques to artifacts mandate further technical refinement, early studies provide encouraging results regarding the potential of fMRI-derived parameters for the ultimate goal of individual-subject classification.

Statistical inference in brain graphs using threshold-free network-based statistics

The description of brain networks as graphs where nodes represent different brain regions and edges represent a measure of connectivity between a pair of nodes is an increasingly used approach in neuroimaging research. The development of powerful methods for edge‐wise group‐level statistical inference in brain graphs while controlling for multiple‐testing associated false‐positive rates, however, remains a difficult task. In this study, we use simulated data to assess the properties of threshold‐free network‐based statistics (TFNBS). The TFNBS combines threshold‐free cluster enhancement, a method commonly used in voxel‐wise statistical inference, and network‐based statistic (NBS), which is frequently used for statistical analysis of brain graphs. Unlike the NBS, TFNBS generates edge‐wise significance values and does not require the a priori definition of a hard cluster‐defining threshold. Other test parameters, nonetheless, need to be set. We show that it is possible to find parameters that make TFNBS sensitive to strong and topologically clustered effects, while appropriately controlling false‐positive rates. Our results show that the TFNBS is an adequate technique for the statistical assessment of brain graphs.

Differential Progression of Regional Hippocampal Atrophy in Aging and Parkinson’s Disease

Hippocampal subfields have different vulnerability to the degenerative processes related to aging, amnestic mild cognitive impairment (MCI) and Alzheimer’s disease (AD), but the temporal evolution in Parkinson’s disease (PD) is unknown. The purposes of the current work are to describe regional hippocampal changes over time in a sample of PD patients classified according to their baseline cognitive status and to relate these changes to verbal memory loss. T1-weighted images and verbal memory assessment were obtained at two separate time points (3.8 ± 0.4 years apart) from 28 PD with normal cognition (PD-NC), 16 PD with MCI (PD-MCI) and 21 healthy controls (HCs). FreeSurfer 6.0 automated pipeline was used to segment the hippocampus into 12 bilateral subregions. Memory functions were measured with Rey’s Auditory Verbal learning test (RAVLT). We found significant reductions in cornu ammonis 1 (CA1) over time in controls as well as in PD subgroups. Right whole-hippocampal volumes showed time effects in both PD groups but not in controls. PD-NC patients also displayed time effects in the left hippocampal tail and right parasubiculum. Regression analyses showed that specific hippocampal subfield volumes at time 1 predicted almost 60% of the variability in RAVLT delayed-recall score decline. Changes in several hippocampal subregions also showed predictive value for memory loss. In conclusion, CA1 changes in PD were similar to those that occur in normal aging, but PD patients also had more decline in both anterior and posterior hippocampal segments with a more pronounced atrophy of the right hemisphere. Hippocampal segments are better predictors of changes in memory performance than whole-hippocampal volumes.