Local white matter abnormalities in Parkinson's disease with mild cognitive impairment: Assessed with neurite orientation dispersion and density imaging

Investigation into white matter microstructure differences in visual training by using an automated fiber tract subclassification segmentation quantification method

Visual training has emerged as a useful framework for investigating training-related brain plasticity, a highly complex task involving the interaction of visual orientation, attention, reasoning, and cognitive functions. However, the effects of long-term visual training on microstructural changes within white matter (WM) is poorly understood. Therefore, a set of visual training programs was designed, and automated fiber tract subclassification segmentation quantification based on diffusion magnetic resonance imaging was performed to obtain the anatomical changes in the brains of visual trainees. First, 40 healthy matched participants were randomly assigned to the training group or the control group. The training group underwent 10 consecutive weeks of visual training. Then, the fiber tracts of the subjects were automatically identified and further classified into fiber clusters to determine the differences between the two groups on a detailed scale. Next, each fiber cluster was divided into segments that can analyze specific areas of a fiber cluster. Lastly, the diffusion metrics of the two groups were comparatively analyzed to delineate the effects of visual training on WM microstructure. Our results showed that there were significant differences in the fiber clusters of the cingulate bundle, thalamus frontal, uncinate fasciculus, and corpus callosum between the training group compared and the control group. In addition, the training group exhibited lower mean fractional anisotropy, higher mean diffusivity and radial diffusivity than the control group. Therefore, the long-term cognitive activities, such as visual training, may systematically influence the WM properties of cognition, attention, memory, and processing speed.

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.