Distinct network topology in Alzheimer's disease and behavioral variant frontotemporal dementia.

BACKGROUND: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) cause distinct atrophy and functional disruptions within two major intrinsic brain networks, namely the default network and the salience network, respectively. It remains unclear if inter-network relationships and whole-brain network topology are also altered and underpin cognitive and social-emotional functional deficits. METHODS: In total, 111 participants (50 AD, 14 bvFTD, and 47 age- and gender-matched healthy controls) underwent resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessments. Functional connectivity was derived among 144 brain regions of interest. Graph theoretical analysis was applied to characterize network integration, segregation, and module distinctiveness (degree centrality, nodal efficiency, within-module degree, and participation coefficient) in AD, bvFTD, and healthy participants. Group differences in graph theoretical measures and empirically derived network community structures, as well as the associations between these indices and cognitive performance and neuropsychiatric symptoms, were subject to general linear models, with age, gender, education, motion, and scanner type controlled. RESULTS: Our results suggested that AD had lower integration in the default and control networks, while bvFTD exhibited disrupted integration in the salience network. Interestingly, AD and bvFTD had the highest and lowest degree of integration in the thalamus, respectively. Such divergence in topological aberration was recapitulated in network segregation and module distinctiveness loss, with AD showing poorer modular structure between the default and control networks, and bvFTD having more fragmented modules in the salience network and subcortical regions. Importantly, aberrations in network topology were related to worse attention deficits and greater severity in neuropsychiatric symptoms across syndromes. CONCLUSIONS: Our findings underscore the reciprocal relationships between the default, control, and salience networks that may account for the cognitive decline and neuropsychiatric symptoms in dementia.

Whole Brain White Matter Microstructure and Upper Limb Function: Longitudinal Changes in Fractional Anisotropy and Axial Diffusivity in Post-Stroke Patients.

BACKGROUND: Diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) measuring fractional anisotropy (FA) and axial diffusivity (AD) may be a useful biomarker for monitoring changes in white matter after stroke, but its associations with upper-limb motor recovery have not been well studied. We aim to describe changes in the whole-brain FA and AD in five post-stroke patients in relation to kinematic measures of elbow flexion to better understand the relationship between FA and AD changes and clinico-kinematic measures of upper limb motor recovery. METHODS: We performed DTI MRI at two timepoints during the acute phase of stroke, measuring FA and AD across 48 different white matter tract regions in the brains of five hemiparetic patients with infarcts in the cortex, pons, basal ganglia, thalamus, and corona radiata. We tracked the progress of these patients using clinical Fugl-Meyer Assessments and kinematic measures of elbow flexion at the acute phase within 14 (mean: 9.4 ± 2.49) days of stroke symptom onset and at a follow-up appointment 2 weeks later (mean: 16 ± 1.54) days. RESULTS: Changes in FA and AD in 48 brain regions occurring during stroke rehabilitation are described in relation to motor recovery. In this case series, one patient with a hemipontine infarct showed an increase in FA of the ipsilateral and contralateral corticospinal tract, whereas other patients with lesions involving the corona radiata and middle cerebral artery showed widespread decreases in perilesional FA. On the whole, FA and AD seemed to behave inversely to each other. CONCLUSIONS: This case series describes longitudinal changes in perilesional and remote FA and AD in relation to kinematic parameters of elbow flexion at the subacute post-stroke period. Although studies with larger sample sizes are needed, our findings indicate that longitudinally measured changes in DTI-based measurements of white matter microstructural integrity may aid in the prognostication of patients affected by motor stroke.

Regional White Matter Hyperintensity Influences Grey Matter Atrophy in Mild Cognitive Impairment.

The association between cerebrovascular disease pathology (measured by white matter hyperintensities, WMH) and brain atrophy in early Alzheimer's disease (AD) remain to be elucidated. Thus, we investigated how WMH influence neurodegeneration and cognition in prodromal and clinical AD. We examined 51 healthy controls, 35 subjects with mild cognitive impairment (MCI), and 30 AD patients. We tested how total and regional WMH is related to specific grey matter volume (GMV) reductions in MCI and AD compared to controls. Stepwise regression analysis was further performed to investigate the association of GMV and regional WMH volume with global cognition. We found that total WMH volume was highest in AD but showed the strongest association with lower GMV in MCI. Frontal and parietal WMH had the most extensive influence on GMV loss in MCI. Additionally, parietal lobe WMH volume (but not hippocampal atrophy) was significantly associated with global cognition in MCI while smaller hippocampal volume (but not WMH volume) was associated with lower global cognition in AD. Thus, although WMH volume was highest in AD subjects, it had a more pervasive influence on brain structure and cognitive impairment in MCI. Our study thus highlights the importance of early detection of cerebrovascular disease, as its intervention at the MCI stage might potentially slow down neurodegeneration.

Carrying the past to the future: Distinct brain networks underlie individual differences in human spatial working memory capacity.

Spatial working memory (SWM) relies on the interplay of anatomically separated and interconnected large-scale brain networks. EEG studies often observe load-associated sustained negative activity during SWM retention. Yet, whether and how such sustained negative activity in retention relates to network-specific functional activation/deactivation and relates to individual differences in SWM capacity remain to be elucidated. To cover these gaps, we recorded concurrent EEG-fMRI data in 70 healthy young adults during the Sternberg delayed-match-to-sample SWM task with three memory load levels. To a subset of participants (N = 28) that performed the task properly and had artefact-free fMRI and EEG data, we employed a novel temporo-spatial principal component analysis to derive load-dependent negative slow wave (NSW) from retention-related event-related potentials. The associations between NSW responses with SWM capacity were divergent in the higher (N = 14) and lower (N = 14) SWM capacity groups. Specifically, larger load-related increase in NSW amplitude was associated with greater SWM capacity for the higher capacity group but lower SWM capacity for the lower capacity group. Furthermore, for the higher capacity group, larger NSW amplitude was related to greater activation in bilateral parietal areas of the fronto-parietal network (FPN) and greater deactivation in medial frontal gyrus and posterior mid-cingulate cortex of the default mode network (DMN) during retention. In contrast, the lower capacity group did not show similar pattern. Instead, greater NSW was linked to higher deactivation in right posterior middle temporal gyrus. Our findings shed light on the possible differential EEG-informed neural network mechanism during memory maintenance underlying individual differences in SWM capacity.