Dance Intervention Impact on Brain Plasticity: A Randomized 6-Month fMRI Study in Non-expert Older Adults

Background: Dance is a complex activity combining physical exercise with cognitive, social, and artistic stimulation.

Objectives: We aimed to assess the effects of dance intervention (DI) on intra and inter-network resting-state functional connectivity (rs-FC) and its association to cognitive changes in a group of non-demented elderly participants.

Methods: Participants were randomly assigned into two groups: DI and life as usual (LAU). Six-month-long DI consisted of supervised 60 min lessons three times per week. Resting-state fMRI data were processed using independent component analysis to evaluate the intra and inter-network connectivity of large-scale brain networks. Interaction between group (DI, LAU) and visit (baseline, follow-up) was assessed using ANOVA, and DI-induced changes in rs-FC were correlated with cognitive outcomes.

Results: Data were analyzed in 68 participants (DI; n = 36 and LAU; n = 32). A significant behavioral effect was found in the attention domain, with Z scores increasing in the DI group and decreasing in the LAU group (p = 0.017). The DI as compared to LAU led to a significant rs-FC increase of the default mode network (DMN) and specific inter-network pairings, including insulo-opercular and right frontoparietal/frontoparietal control networks (p = 0.019 and p = 0.023), visual and language/DMN networks (p = 0.012 and p = 0.015), and cerebellar and visual/language networks (p = 0.015 and p = 0.003). The crosstalk of the insulo-opercular and right frontoparietal networks were associated with attention/executive domain Z-scores (R = 0.401, p = 0.015, and R = 0.412, p = 0.012).

Conclusion: The DI led to intervention-specific complex brain plasticity changes that were of cognitive relevance.

Cognitive effects of dance-movement intervention in a mixed group of seniors are not dependent on hippocampal atrophy

Dance-movement intervention (DMI) offers multi-component stimulation of cognitive functions, and it may ameliorate cognitive deficits in the elderly. We investigated the effects of intensive DMI on the cognitive performances of healthy seniors (HS) and patients with mild cognitive impairment (MCI). In addition, we evaluated whether the baseline MRI hippocampus-to-cortex volume (HV:CTV) ratio (i.e., a marker of a typical AD-specific brain atrophy and of distribution of neurofibrillary tangles in the brain) has any impact on the DMI-induced cognitive changes. The research cohort consisted of 99 subjects who were randomly assigned (in a 1:1 ratio) to a DMI group or to a control (life-as-usual) group. The DMI group consisted of 49 subjects with an average age of 69.16 years (SD = 5.36), of which 34 were HS (69.4%) and 15 had MCI (30.6%). The control group consisted of 50 subjects aged 68.37 years (SD = 6.10), of which 31 were HC (62%) and 19 (38%) had MCI. The DMI group underwent a 6-month intervention, which consisted of 60 lessons supervised by a qualified instructor. Statistical analysis yielded a significant improvement of the figural fluency task as measured by the five-point test in the DMI group as compared to the control group [t (97) = 2.72; p = 0.008]. The baseline HV:CTV ratio was not associated with cognitive changes on that task or with changes in any cognitive domain's Z scores. We observed DMI-induced effect on the test evaluating executive functions across the spectrum of HS and MCI, which was not dependent on the magnitude of AD-related brain pathology.

Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease

To meet the need for Parkinson's disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson's disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson's disease patients and 54 healthy controls) were collected using b-values of 0-4000s/mm2. Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm2 (fractional anisotropy (FA), Axial-, Mean- and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson's disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson's disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.

Patterns of Grey Matter Atrophy at Different Stages of Parkinson's and Alzheimer's Diseases and Relation to Cognition

Using MRI, a characteristic pattern of grey matter (GM) atrophy has been described in the early stages of Alzheimer's disease (AD); GM patterns at different stages of Parkinson's disease (PD) have been inconclusive. Few studies have directly compared structural changes in groups with mild cognitive impairment (MCI) caused by different pathologies (AD, PD). We used several analytical methods to determine GM changes at different stages of both PD and AD. We also evaluated associations between GM changes and cognitive measurements. Altogether 144 subjects were evaluated: PD with normal cognition (PD-NC; n = 23), PD with MCI (PD-MCI; n = 24), amnestic MCI (aMCI; n = 27), AD (n = 12), and age-matched healthy controls (HC; n = 58). All subjects underwent structural MRI and cognitive examination. GM volumes were analysed using two different techniques: voxel-based morphometry (VBM) and source-based morphometry (SBM), which is a multivariate method. In addition, cortical thickness (CT) was evaluated to assess between-group differences in GM. The cognitive domain z-scores were correlated with GM changes in individual patient groups. GM atrophy in the anterior and posterior cingulate, as measured by VBM, in the temporo-fronto-parietal component, as measured by SBM, and in the posterior cortical regions as well as in the anterior cingulate and frontal region, as measured by CT, differentiated aMCI from HC. Major hippocampal and temporal lobe atrophy (VBM, SBM) and to some extent occipital atrophy (SBM) differentiated AD from aMCI and from HC. Correlations with cognitive deficits were present only in the AD group. PD-MCI showed greater GM atrophy than PD-NC in the orbitofrontal regions (VBM), which was related to memory z-scores, and in the left superior parietal lobule (CT); more widespread limbic and fronto-parieto-occipital neocortical atrophy (all methods) differentiated this group from HC. Only CT revealed subtle GM atrophy in the anterior cingulate, precuneus, and temporal neocortex in PD-NC as compared to HC. None of the methods differentiated PD-MCI from aMCI. Both MCI groups showed distinct limbic and fronto-temporo-parietal neocortical atrophy compared to HC with no specific between-group differences. AD subjects displayed a typical pattern of major temporal lobe atrophy which was associated with deficits in all cognitive domains. VBM and CT were more sensitive than SBM in identifying frontal and posterior cortical atrophy in PD-MCI as compared to PD-NC. Our data support the notion that the results of studies using different analytical methods cannot be compared directly. Only CT measures revealed some subtle differences between HC and PD-NC.