Changes in Brain Lateralization in Patients with Mild Cognitive Impairment and Alzheimer's Disease: A Resting-State Functional Magnetic Resonance Study from Alzheimer's Disease Neuroimaging Initiative

Association of handgrip strength asymmetry and weakness with cognitive function: a nationally representative cohort study

OBJECTIVE

To describe the association of handgrip strength asymmetry and weakness with cognitive function among Chinese middle-aged and older adults.

STUDY DESIGN

We used data from four waves (2011, 2013, 2015, and 2018) of the China Health and Retirement Longitudinal Study. Handgrip strength was measured at baseline. Handgrip strength asymmetry was defined on the basis of the ratio of handgrip strength of the non-dominant hand to that of the dominant hand (i.e. non-dominant/dominant): a ratio of <0.9 defined as dominant handgrip strength asymmetry and >1.1 as non-dominant handgrip strength asymmetry. Weakness was defined as a handgrip strength of <28 kg for males or <18 kg for females.

MAIN OUTCOME MEASURES

Cognitive function with its two core dimensions (episodic memory and mental status) at each wave was assessed and standardized.

RESULTS

9333 participants (48.3 % female, age 58.2 ± 9.0 years) were included. Non-dominant but not dominant handgrip strength asymmetry was significantly associated with poorer cognitive function at baseline (β = -0.121, -0.092, and -0.132 for mental status, episodic memory, and global cognition, respectively). In longitudinal analyses over 2 years, dominant handgrip strength asymmetry significantly slowed cognitive decline (β = -0.078 and -0.069 for mental status and global cognition, respectively), and non-dominant handgrip strength asymmetry accelerated cognitive decline (β = 0.053 and 0.043 for episodic memory and global cognition, respectively). Weakness was associated with poorer cognitive function at baseline and cognitive decline over 2, 4, and 7 years (all P < 0.05).

CONCLUSIONS

In middle-aged and older adults, non-dominant handgrip strength asymmetry and weakness were associated with poorer cognitive function and predicted accelerated cognitive decline. Dominant handgrip strength asymmetry may be beneficial for maintaining cognitive function.

The spatial distribution of coupling between tau and neurodegeneration in amyloid-β positive mild cognitive impairment

Synergies between amyloid-β (Aβ), tau, and neurodegeneration persist along the Alzheimer's disease (AD) continuum. This study aimed to evaluate the extent of spatial coupling between tau and neurodegeneration (atrophy) and its relation to Aβ positivity in mild cognitive impairment (MCI). Data from 409 participants were included (95 cognitively normal controls, 158 Aβ positive (Aβ+) MCI, and 156 Aβ negative (Aβ-) MCI). Florbetapir PET, Flortaucipir PET, and structural MRI were used as biomarkers for Aβ, tau and atrophy, respectively. Individual correlation matrices for tau load and atrophy were used to layer a multilayer network, with separate layers for tau and atrophy. A measure of coupling between corresponding regions of interest (ROIs) in the tau and atrophy layers was computed, as a function of Aβ positivity. Fewer than 25% of the ROIs across the brain showed heightened coupling between tau and atrophy in Aβ+ , relative to Aβ- MCI. Coupling strengths in the right rostral middle frontal and right paracentral gyri, in particular, mediated the association between Aβ burden and cognition in this sample.

Associations of Handgrip Strength Weakness and Asymmetry with Lower Cognitive Function: Results from the National Health and Nutrition Examination Survey (2011-2014)

Background

The joint associations of handgrip strength (HGS) weakness and asymmetry with cognitive decline remain understudied in older adults.

Objective

To investigate the associations between HGS weakness, asymmetry, and lower cognitive function in a nationally representative sample of older Americans.

Methods

This cross-sectional study utilized data from the National Health and Nutrition Examination Survey 2011-2014. Weakness was defined as HGS <26 kg for men and <16 kg for women. Asymmetry was determined by calculating the ratio of dominant to non-dominant HGS. Participants with an HGS ratio <0.90 or >1.10 were classified as having any HGS asymmetry. Those with an HGS ratio >1.10 exhibited dominant HGS asymmetry, while those with an HGS ratio <0.90 displayed nondominant HGS asymmetry, respectively. Lower cognitive functioning was defined as global cognitive composite scores more than 1 standard deviation below the mean. Covariate-adjusted logistic regression models were used to analyze the associations between HGS asymmetry/weakness and lower cognitive functioning.

Results

Compared to individuals with non-weak and symmetric HGS, those with any HGS asymmetry alone and weakness alone had 1.017 (95% confidence interval [CI]: 0.707-1.463) and 1.391 (95% CI: 0.542-3.571) greater odds for cognitive decline, while co-occurrence of both HGS asymmetry and weakness was associated with 3.724 (95% CI: 1.711-8.107) greater odds for lower cognitive function after controlling for confounders.

Cnclusions

Individuals exhibiting both diminished and asymmetrical HGS demonstrated an elevated susceptibility to cognitive impairment, thereby implying that the inclusion of HGS asymmetry assessment in conjunction with weakness evaluation may enhance the accuracy of prognosticating cognitive decline.

Basal forebrain activity predicts functional degeneration in the entorhinal cortex in Alzheimer's disease

Recent models of Alzheimer's disease suggest the nucleus basalis of Meynert (NbM) as an early origin of structural degeneration followed by the entorhinal cortex (EC). However, the functional properties of NbM and EC regarding amyloid-β and hyperphosphorylated tau remain unclear. We analysed resting-state functional fMRI data with CSF assays from the Alzheimer's Disease Neuroimaging Initiative (n = 71) at baseline and 2 years later. At baseline, local activity, as quantified by fractional amplitude of low-frequency fluctuations, differentiated between normal and abnormal CSF groups in the NbM but not EC. Further, NbM activity linearly decreased as a function of CSF ratio, resembling the disease status. Finally, NbM activity predicted the annual percentage signal change in EC, but not the reverse, independent from CSF ratio. Our findings give novel insights into the pathogenesis of Alzheimer's disease by showing that local activity in NbM is affected by proteinopathology and predicts functional degeneration within the EC.

Preoperative low handgrip strength (HGS) with HGS asymmetry is associated with adverse outcomes among older adults with gastric cancer

INTRODUCTION

This study aimed to explore the associations of low hand grip strength (HGS), HGS asymmetry, their combinations, and frailty on hospital readmissions, total complications, and prolonged length of stay (PLOS) among older adults with gastric cancer.

MATERIALS AND METHODS

This study included 342 patients with gastric cancer aged ≥60 years who were scheduled to undergo radical surgery. The Tilburg Frailty Indicator (TFI) was used to collect information on frailty. HGS was measured twice for each hand using an electronic handgrip dynamometer. The highest HGS readings on each hand were used for calculating the HGS asymmetry ratio: non-dominant HGS (kg)/dominant HGS (kg). The Fine and Gray proportional subdistribution hazard model and the logistic regression model were used for the analyses, with covariates adjusted.

RESULTS

Low HGS (subdistribution hazard ratios [SHR] = 2.10, 95% confidence interval [CI] = 1.05-3.93, P = 0.036) and low HGS with HGS asymmetry (SHR = 3.95, 95% CI = 1.50-10.36, P = 0.005) were significantly associated with hospital readmissions. Frailty was associated with total complications (odds ratio [OR] = 2.87, 95% CI = 1.61-5.13, P < 0.001) and PLOS (OR = 1.98, 95% CI = 1.19-3.29, P < 0.001). Low HGS, HGS asymmetry, and their combinations were not significantly associated with total complications and PLOS.

DISCUSSION

Preoperative low HGS and low HGS with HGS asymmetry were associated with hospital readmissions, while frailty was associated with total complications and PLOS among older adults with gastric cancer. In the future, more rigorously designed studies are needed to verify our results further to improve preoperative clinical assessment and frailty evaluation among older adults with gastric cancer.

Evaluation of volumetric asymmetry of the dorsolateral prefrontal cortex and medial temporal lobe in Alzheimer's disease using the atlas-based method

Brain areas affected during neurodegenerative disease progression are considered anatomically connected to the first affected areas. The dorsolateral prefrontal cortex (DLPFC) has connections with the medial temporal lobe (MTL), which includes regions that become atrophic in Alzheimer's disease. In this study, we aimed to investigate the degree of volumetric asymmetry of DLPFC and MTL structures. This is a cross-sectional volumetric study involving 25 Alzheimer's disease patients and 25 healthy adults who underwent MRI with a 3D turbo spin echo sequence at 1.5 Tesla. The atlas-based method incorporated MRIStudio software to automatically measure the volume of brain structures. We compared the asymmetry index and volumetric changes across study groups and correlated them with Mini-Mental State Examination scores. We observed significant volumetric rightward lateralization in the DLPFC and superior frontal gyrus in Alzheimer's disease patients compared to the healthy controls. There was a significant volume loss in the MTL structures of Alzheimer's disease patients. Atrophy of MTL structures was positively correlated with right DLPFC volume changes in Alzheimer's disease patients. Volumetric asymmetry of the DLPFC may be a characteristic for determining disease progression in Alzheimer's disease patients. Future studies are recommended to evaluate whether these volumetric asymmetrical changes are specific to Alzheimer's disease and whether asymmetry measurements can serve as diagnostic markers.

TMS-EEG perturbation biomarkers for Alzheimer's disease patients classification

The combination of TMS and EEG has the potential to capture relevant features of Alzheimer's disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45-80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients' classification as well as longitudinal disease tracking.

Basal forebrain activity predicts functional degeneration in the entorhinal cortex and decreases with Alzheimer's Disease progression

BACKGROUND AND OBJECTIVES

Recent models of Alzheimer's Disease (AD) suggest the nucleus basalis of Meynert (NbM) as the origin of structural degeneration followed by the entorhinal cortex (EC). However, the functional properties of NbM and EC regarding amyloid-β and hyperphosphorylated tau remain unclear.

METHODS

We analyzed resting-state (rs)fMRI data with CSF assays from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n=71) at baseline and two years later.

RESULTS

At baseline, local activity, as quantified by fractional amplitude of low-frequency fluctuations (fALFF), differentiated between normal and abnormal CSF groups in the NbM but not EC. Further, NbM activity linearly decreased as a function of CSF ratio, resembling the disease status. Finally, NbM activity predicted the annual percentage signal change in EC, but not the reverse, independent from CSF ratio.

DISCUSSION

Our findings give novel insights into the pathogenesis of AD by showing that local activity in NbM is affected by proteinopathology and predicts functional degeneration within the EC.

Atrophy asymmetry in hippocampal subfields in patients with Alzheimer's disease and mild cognitive impairment

Volumetric analysis of hippocampal subfields and their asymmetry assessment recently has been useful biomarkers in neuroscience. In this study, hippocampal subfields atrophy and pattern of their asymmetry in the patient with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were evaluated. MRI images of 20 AD patients, 20 MCI patients, and 20 healthy control (HC) were selected. The volumes of hippocampal subfields were extracted automatically using Freesurfer toolkit. The subfields asymmetry index (AI) and laterality ([Formula: see text]) were also evaluated. Analysis of covariance was used to compare the subfields volume between three patient groups (age and gender as covariates). We used ANOVA (P < 0.05) test for multiple comparisons with Bonferroni's post hoc correction method. Hippocampal subfields volume in AD patients were significantly lower than HC and MCI groups (P < 0.02); however, no significant difference was observed between MCI and HC groups. The asymmetry index (AI) in some subfields was significantly different between AD and MCI, as well as between AD and HC, while there was not any significant difference between MCI groups with HC. In all three patient groups, rightward laterality ([Formula: see text]) was seen in several subfields except subiculum, presubiculum, and parasubiculum, while in AD patient, rightward lateralization slightly decrease. Hippocampal subfields asymmetry can be used as a quantitative biomarker in neurocognitive disorders. In this study, it was observed that the asymmetry index of some subfields in AD is significantly different from MCI. In AD, patient rightward laterality was less MCI an HC group.

Diffusion kurtosis imaging and diffusion tensor imaging parameters applied to white matter and gray matter of patients with anti-N-methyl-D-aspartate receptor encephalitis

Objectives

To compare parameters of diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) to evaluate which can better describe the microstructural changes of anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis patients and to characterize the non-Gaussian diffusion patterns of the whole brain and their correlation with neuropsychological impairments in these patients.

Materials and methods

DTI and DKI parameters were measured in 57 patients with anti-NMDAR encephalitis and 42 healthy controls. Voxel-based analysis was used to evaluate group differences between white matter and gray matter separately. The modified Rankin Scale (mRS) was used to evaluate the severity of the neurofunctional recovery of patients, the Montreal Cognitive Assessment (MoCA) was used to assess global cognitive performance, and the Hamilton Depression Scale (HAMD) and fatigue severity scale (FSS) were used to evaluate depressive and fatigue states.

Results

Patients with anti-NMDAR encephalitis showed significantly decreased radial kurtosis (RK) in the right extranucleus in white matter (P < 0.001) and notably decreased kurtosis fractional anisotropy (KFA) in the right precuneus, the right superior parietal gyrus (SPG), the left precuneus, left middle occipital gyrus, and left superior occipital gyrus in gray matter (P < 0.001). Gray matter regions with decreased KFA overlapped with those with decreased RK in the left middle temporal gyrus, superior temporal gyrus (STG), supramarginal gyrus (SMG), postcentral gyrus (POCG), inferior parietal but supramarginal gyrus, angular gyrus (IPL) and angular gyrus (ANG) (P < 0.001). The KFA and RK in the left ANG, IPL and POCG correlated positively with MoCA scores. KFA and RK in the left ANG, IPL, POCG and SMG correlated negatively with mRS scores. KFA in the left precuneus and right SPG as well as RK in the left STG correlated negatively with mRS scores. No significant correlation between KFA and RK in the abnormal brain regions and HAMD and FSS scores was found.

Conclusion

The microstructural changes in gray matter were much more extensive than those in white matter in patients with anti-NMDAR encephalitis. The brain damage reflected by DKI parameters, which have higher sensitivity than parameters of DTI, correlated with cognitive impairment and the severity of the neurofunctional recovery.

Functional Connectivity Dynamics Altered of the Resting Brain in Subjective Cognitive Decline

Background

Subjective cognitive decline (SCD) appears in the preclinical stage of the Alzheimer's disease continuum. In this stage, dynamic features are more sensitive than static features to reflect early subtle changes in functional brain connectivity. Therefore, we studied local and extended dynamic connectivity of the resting brain of people with SCD to determine their intrinsic brain changes.

Methods

We enrolled cognitively normal older adults from the communities and divided them into SCD and normal control (NC) groups. We used mean dynamic amplitude of low-frequency fluctuation (mdALFF) to evaluate region of interest (ROI)-wise local dynamic connectivity of resting-state functional MRI. The dynamic functional connectivity (dFC) between ROIs was tested by whole-brain-based statistics.

Results

When comparing SCD (N = 40) with NC (N = 45), mdALFF_mean decreased at right inferior parietal lobule (IPL) of the frontoparietal network (FPN). Still, it increased at the right middle temporal gyrus (MTG) of the ventral attention network (VAN) and right calcarine of the visual network (VIS). Also, the mdALFF_var (variance) increased at the left superior temporal gyrus of AUD, right MTG of VAN, right globus pallidum of the cingulo-opercular network (CON), and right lingual gyrus of VIS. Furthermore, mdALFF_mean at right IPL of FPN are correlated negatively with subjective complaints and positively with objective cognitive performance. In the dFC seeded from the ROIs with local mdALFF group differences, SCD showed a generally lower dFC_mean and higher dFC_var (variance) to other regions of the brain. These weakened and unstable functional connectivity appeared among FPN, CON, the default mode network, and the salience network, the large-scale networks of the triple network model for organizing neural resource allocations.

Conclusion

The local dynamic connectivity of SCD decreased in brain regions of cognitive executive control. Meanwhile, compensatory visual efforts and bottom-up attention rose. Mixed decrease and compensatory increase of dynamics of intrinsic brain activity suggest the transitional nature of SCD. The FPN local dynamics balance subjective and objective cognition and maintain cognitive preservation in preclinical dementia. Aberrant triple network model features the dFC alternations of SCD. Finally, the right lateralization phenomenon emerged early in the dementia continuum and affected local dynamic connectivity.

Cognitive stimulation has potential for brain activation in individuals with Rett syndrome

BACKGROUND

Knowledge regarding neuropsychological training in Rett syndrome (RS) is scarce. The aim of this study was to assess the outcome and the duration of the effect of cognitive stimulation on topographic electroencephalography (EEG) data in RS.

METHODS

Twenty female children diagnosed with RS were included in the analysis. Girls with RS conducted a cognitive task using an eye-tracker designed to evaluate access and choice skills. EEG data were acquired during the experimental procedure including two 10-min baseline stages before and after the task. Topographical changes of several EEG spectral markers including absolute and relative powers, Brain Symmetry Index and entropy were assessed.

RESULTS

Topographic significance probability maps suggested statistical decreases on delta activity and increases on beta rhythm associated with the cognitive task. Entropy increased during and after the task, likely related to more complex brain activity. A significant positive interaction was obtained between Brain Symmetry Index and age showing that the improvement of interhemispheric symmetry was higher in younger girls (5-10 years).

CONCLUSIONS

According to our findings, significant alterations of brain rhythms were observed during and after cognitive stimulation, suggesting that cognitive stimulation may have effects on brain activity beyond the stimulation period. Finally, our promising results also showed an increase brain symmetry that was especially relevant for the younger group. This could suggest an interaction of the eye-tracking cognitive task; however, further studies in this field are needed to assess the relation between brain asymmetries and age.

Structural brain network correlations with amyloid burden in elderly individuals at risk of Alzheimer's disease

Alzheimer's disease (AD) has a long preclinical phase during which beta-amyloid accumulates in the brain without cognitive impairment. However, the pattern of brain network alterations in this early stage of the disease remains to be clarified. In this study we examined the relationships between regional brain network indices and beta-amyloid deposits. Twenty-four elderly subjects with the APOE4 allele underwent both a 1.5-Tesla magnetic resonance imaging (MRI) scan and a positron emission tomography (PET) scan using [¹⁸F]Florbetapir. We computed network metrics such as the degree, betweenness centrality, and clustering coefficient, and examined the relationships between the beta-amyloid accumulation and these regional brain network connectivity metrics. We found a significant positive correlation between the global standardized uptake value ratio (SUVR) of [¹⁸F]Florbetapir and the betweenness centrality in the left parietal region. However, there were no significant correlations between the SUVR score and other network indices or the regional gray matter volume. Our data suggest a relationship between the beta-amyloid accumulation and the regional brain network connectivity in subjects at risk of AD. The brain connectome may provide an adjunct biomarker for the early detection of AD.

Electrophysiological Biomarkers of Epileptogenicity in Alzheimer's Disease

Cortical network hyperexcitability is an inextricable feature of Alzheimer’s disease (AD) that also might accelerate its progression. Seizures are reported in 10–22% of patients with AD, and subclinical epileptiform abnormalities have been identified in 21–42% of patients with AD without seizures. Accurate identification of hyperexcitability and appropriate intervention to slow the compromise of cognitive functions of AD might open up a new approach to treatment. Based on the results of several studies, epileptiform discharges, especially those with specific features (including high frequency, robust morphology, right temporal location, and occurrence during awake or rapid eye movement states), frequent small sharp spikes (SSSs), temporal intermittent rhythmic delta activities (TIRDAs), and paroxysmal slow wave events (PSWEs) recorded in long-term scalp electroencephalogram (EEG) provide sufficient sensitivity and specificity in detecting cortical network hyperexcitability and epileptogenicity of AD. In addition, magnetoencephalogram (MEG), foramen ovale (FO) electrodes, and computational approaches help to find subclinical seizures that are invisible on scalp EEGs. We performed a comprehensive analysis of the aforementioned electrophysiological biomarkers of AD-related seizures.

Assessing a Sensory-Motor-Cognition Triad in Amnestic Mild Cognitive Impairment With Dichotic Listening While Walking: A Dual-Task Paradigm

A contemporary topic in aging research relates to the significance of cognitive changes proper to mild cognitive impairment (MCI) to higher risk of falls and gait deteriorations. The present study addresses this question in the amnestic type of MCI (aMCI) by examining a triad of interrelated comorbidities occurring in the MCI condition: attentional impairments, hearing loss and gait disturbances. To this end, we applied a dichotic listening (DL) test during over-ground walking. DL assesses spontaneous and lateralized auditory attention in three conditions (i.e., free report or Non-forced (NF), Forced-Right (FR) ear and Forced-Left (FL) ear). Earlier reports suggest that this dual-task paradigm evoke asymmetric gait effects on healthy controls, which are moderated by degree of hearing loss. Therefore, the aim of the present study was to evaluate the effects of DL on bilateral (data from both limbs) and lateralized (each limb separately) gait outcomes in a group of forty-three aMCI participants (mean = 71.19) and fifty-two healthy older controls (mean = 70.90) by using hearing loss as a covariate in all analyses. Results showed the aMCI group presented overall compromised gait parameters, especially higher gait variability in all DL conditions during lateralized attentional control. These findings were observed bilaterally, and no lateralized effects on gait were observed. Only after controlling for hearing acuity, gait asymmetries on step length variability emerged almost exclusively in healthy controls. It was concluded that hearing loss in the aMCI group together with higher attentional impairments preclude aMCI individuals to properly execute DL and therefore, they do not display gait asymmetries. The present data demonstrate that varied demands on attentional control dependent on hearing acuity affects gait negatively in healthy older adults and aMCI individuals in very different ways. The appearance of asymmetric effects seems to be a perturbation related to normal aging, while the lack of asymmetries but exaggerated gait variability characterizes aMCI. The present findings show the intricate interplay of sensory, cognitive, and motor deteriorations in different group of older adults, which stresses the need of addressing co-occurring comorbidities behind gait perturbations in individuals prone to develop a dementia state.

Functional Connectivity Lateralisation Shift of Resting State Networks is Linked to Visuospatial Memory and White Matter Microstructure in Relapsing-Remitting Multiple Sclerosis

Laterality patterns of resting state networks (RSN) change in various neuropsychiatric conditions. Multiple sclerosis (MS) causes neuro-cognitive symptoms involving dysfunctional large-scale brain networks. Yet, whether healthy laterality patterns of RSNs are maintained in MS and whether altered laterality patterns explain disease symptoms has not been explicitly investigated. We analysed functional MRI and diffusion tensor imaging data from 24 relapsing–remitting MS patients and 25 healthy participants. We performed group-level independent component analysis and used dual regression to estimate individual versions of well-established RSNs. Voxelwise laterality indices were calculated for each RSN. Group differences were assessed via a general linear model-based approach. The relationship between functional laterality and white matter microstructural asymmetry was assessed using Tract-Based Spatial Statistics. Spearman’s correlation was calculated between laterality indices and Brief International Cognitive Assessment for Multiple Sclerosis scores. Functional laterality of the dorsal attention network showed a significant leftward shift in the MS group in the posterior intraparietal sulcus (p < 0.033). Default-mode network laterality showed a significant leftward shift in the MS group in the angular gyrus (p < 0.005). Diminished dorsal attention network laterality was associated with increased fractional anisotropy asymmetry in the superior longitudinal fasciculus (p < 0.02). In the default-mode network, leftward laterality of the angular gyrus was associated with higher BVMT-R scores (R = − 0.52, p < 0.023). Our results confirm previous descriptions of RSN dysfunction in relapsing–remitting MS and show that altered functional connectivity lateralisation patterns of RSNs might contibute to cognitive performance and structural remodellation even in patients with mild clinical symptoms.

White Matter Integrity Underlies the Physical-Cognitive Correlations in Subjective Cognitive Decline

Objective: Although previous studies postulated that physical and cognitive decline codeveloped in preclinical dementia, the interconnected relationship among subjective cognitive complaints (SCCs), objective cognitive performance, and physical activity remained hazy. We investigated the mediating roles of physical activity between subjective and objective cognition. Diffusion tensor imaging (DTI) was utilized to test our hypothesis that brain white matter microstructural changes underlie the physical-cognitive decline in subjective cognitive decline (SCD).

Methods: We enrolled cognitively normal older adults aged > 50 years in the Community Medicine Research Center of Keelung Chang Gung Memorial Hospital during 2017–2020. Regression models analyzed mediation effects of physical activity between subjective and objective cognition. The self-reported AD8 questionnaire assessed SCCs. The SCD group, defined by AD8 score ≥ 2, further underwent diffusion MRI scans. Those who agreed to record actigraphy also wore the SOMNOwatch™ for 72 h. Spearman's correlation coefficients evaluated the associations of diffusion indices with physical activity and cognitive performance.

Results: In 95 cognitively normal older adults, the AD8 score and the Montreal Cognitive Assessment (MoCA) score were mediated partially by the metabolic equivalent of the International Physical Activity Questionnaire-Short Form (IPAQ-SF MET) and fully by the sarcopenia score SARC-F. That is, the relation between SCCs and poorer cognitive performance was mediated by physical inactivity. The DTI analysis of 31 SCD participants found that the MoCA score correlated with mean diffusivity at bilateral inferior cerebellar peduncles and the pyramids segment of right corticospinal tract [p < 0.05, false discovery rate (FDR) corrected]. The IPAQ-SF MET was associated with fractional anisotropy (FA) at the right posterior corona radiata (PCR) (p < 0.05, FDR corrected). In 15 SCD participants who completed actigraphy recording, the patterns of physical activity in terms of intradaily variability and interdaily stability highly correlated with FA of bilateral PCR and left superior corona radiata (p < 0.05, FDR corrected).

Conclusions: This study addressed the role of physical activity in preclinical dementia. Physical inactivity mediated the relation between higher SCCs and poorer cognitive performance. The degeneration of specific white matter tracts underlay the co-development process of physical-cognitive decline in SCD.

Reduced Microstructural Lateralization in Males with Chronic Schizophrenia: A Diffusional Kurtosis Imaging Study

Decreased brain lateralization is considered a trait marker of schizophrenia. Whereas reductions in both functional and macrostructural gray matter laterality in schizophrenia are well established, the investigation of gray matter microstructural lateralization has so far been limited to a small number of ex vivo studies, which limits the understanding of neurobiological substrates involved and development of adequate treatments. The aim of the current study was to assess in vivo gray matter microstructure lateralization patterns in schizophrenia by employing the diffusion kurtosis imaging (DKI)-derived mean kurtosis (MK) metric. MK was calculated for 18 right-handed males with chronic schizophrenia and 19 age-matched healthy control participants in 46 bilateral gray matter regions of interest (ROI). Microstructural laterality indexes (μLIs) were calculated for each subject and ROI, and group comparisons were conducted across regions. The relationship between μLI values and performance on the Wisconsin Card Sorting Test (WCST) was also evaluated. We found that compared with healthy controls, males with chronic schizophrenia had significantly decreased μLI across cortical and subcortical gray matter regions, which was correlated with poorer performance on the WCST. Our results suggest the ability of DKI-derived MK to capture gray matter microstructural lateralization pathology in vivo.

A profile of brain reserve in adults at genetic risk of Alzheimer's disease

INTRODUCTION

The apolipoprotein E (APOE) ε4 allele is the greatest genetic risk factor for Alzheimer's disease (AD). Our aim was to identify the structural brain measures that mitigate the negative effect of APOE ε4 on cognition, which would have implications for AD diagnosis and treatment trial selection.

METHODS

A total of 742 older adults (mean age: 70.1 ± 8.7 years) were stratified by APOE status and classified as cognitively normal (CDR 0) or with very mild dementia (CDR 0.5). Regional brain volume and cognitive performance were measured.

RESULTS

There were significant interactions between APOE and CDR on the left precuneus and on bilateral superior frontal volumes. These regions were preserved in CDR-0 ε3/ε4 and ε4/ε4 carriers but were reduced in CDR-0.5 ε3/ε4 and ε4/ε4 carriers, compared to their respective ε3/ε3 counterparts. Educational attainment predicted greater brain reserve.

DISCUSSION

This pattern of preserved brain structure in cognitively normal ε4 carriers with comprised medial temporal volume is consistent with the theory of brain reserve.

Signatures of white-matter microstructure degradation during aging and its association with cognitive status

Previous studies have shown an association between cognitive decline and white matter integrity in aging. This led to the formulation of a "disconnection hypothesis" in the aging-brain, which states that the disruption in cortical network communication may explain the cognitive decline during aging. Although some longitudinal studies have already investigated the changes occurring in white matter microstructure, most focused on specific white matter tracts. Our study aims to characterize the longitudinal whole-brain signatures of white matter microstructural change during aging. Furthermore, we assessed the relationship between distinct longitudinal alterations in white matter integrity and cognition. White matter microstructural properties were estimated from diffusion magnetic resonance imaging, and cognitive status characterized from extensive neurocognitive testing. The same individuals were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24) between first and last assessment. Our results show that age is associated with a decline in cognitive performance and a degradation in white matter integrity. Additionally, significant associations were found between diffusion measures and different cognitive dimensions (memory, executive function and general cognition). Overall, these results suggest that age-related cognitive decline is related to white matter alterations, and thus give support to the "disconnected hypothesis" of the aging brain.

Brain Asymmetry Detection and Machine Learning Classification for Diagnosis of Early Dementia

Early identification of degenerative processes in the human brain is considered essential for providing proper care and treatment. This may involve detecting structural and functional cerebral changes such as changes in the degree of asymmetry between the left and right hemispheres. Changes can be detected by computational algorithms and used for the early diagnosis of dementia and its stages (amnestic early mild cognitive impairment (EMCI), Alzheimer’s Disease (AD)), and can help to monitor the progress of the disease. In this vein, the paper proposes a data processing pipeline that can be implemented on commodity hardware. It uses features of brain asymmetries, extracted from MRI of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, for the analysis of structural changes, and machine learning classification of the pathology. The experiments provide promising results, distinguishing between subjects with normal cognition (NC) and patients with early or progressive dementia. Supervised machine learning algorithms and convolutional neural networks tested are reaching an accuracy of 92.5% and 75.0% for NC vs. EMCI, and 93.0% and 90.5% for NC vs. AD, respectively. The proposed pipeline offers a promising low-cost alternative for the classification of dementia and can be potentially useful to other brain degenerative disorders that are accompanied by changes in the brain asymmetries.

Handgrip Weakness and Asymmetry Independently Predict the Development of New Activity Limitations: Results from Analyses of Longitudinal Data from the US Health and Retirement Study

OBJECTIVES

Examining strength asymmetries in assessments of muscle function may improve screenings for limitations in independent living tasks such as instrumental activities of daily living (IADL). We sought to determine the associations between handgrip strength (HGS) asymmetry and future IADL limitations in aging Americans.

DESIGN

Longitudinal panel.

SETTING AND PARTICIPANTS

Secondary analyses of data from participants aged at least 50 years from the 2006-2016 waves of the Health and Retirement Study. The analytic sample included 18,235 Americans who identified hand dominance and had measures of HGS for both hands in a single wave.

METHODS

Hand dominance was self-reported, and a handgrip dynamometer measured HGS on each hand. The highest HGS values on each hand were used to calculate the HGS asymmetry ratio: (nondominant HGS/dominant HGS). Individuals with HGS asymmetry ratio <0.80 or >1.20 had HGS asymmetry. Persons with HGS asymmetry ratio <0.80 had dominant HGS asymmetry, whereas participants with HGS asymmetry ratio >1.20 had nondominant HGS asymmetry. Persons with HGS asymmetry ratio <1.0 also had their ratio inversed to make all HGS asymmetry ratios ≥1.0. IADL were self-reported. Covariate-adjusted generalized estimating equations were used for the analyses.

RESULTS

Participants with HGS asymmetry had 1.12 [95% confidence interval (CI): 1.03-1.20] greater odds for future IADL limitations. Each HGS asymmetry dominance group also had greater odds for future IADL limitations: 1.09 (CI: 1.01-1.18) for individuals with dominant HGS asymmetry and 1.29 (CI: 1.09-1.52) for persons with nondominant HGS asymmetry. Every 0.10 increase in inverted HGS asymmetry ratio was associated with 1.30 (CI: 1.07-1.57) greater odds for future IADL limitations.

CONCLUSIONS AND IMPLICATIONS

Assessing HGS asymmetry, as another potential biomarker of impaired muscle function, may provide novel insights for predicting IADL limitations. Future research should continue examining how strength asymmetries, and other aspects of muscle function beyond maximal strength, factor into the disabling cascade.

Divergence in the metabolome between natural aging and Alzheimer's disease

Alzheimer's disease (AD) is a progressive and debilitating neurodegenerative disorder and one of the leading causes of death in the United States. Although amyloid plaques and fibrillary tangles are hallmarks of AD, research suggests that pathology associated with AD often begins 20 or more years before symptoms appear. Therefore, it is essential to identify early-stage biomarkers in those at risk for AD and age-related cognitive decline (ARCD) in order to develop preventative treatments. Here, we used an untargeted metabolomics analysis to define system-level alterations following cognitive decline in aged and APP/PS1 (AD) mice. At 6, 12, and 24 months of age, both control (Ctrl) and AD mice were tested in a 3-shock contextual fear conditioning (CFC) paradigm to assess memory decline. AD mice exhibited memory deficits across age and these memory deficits were also seen in naturally aged mice. Prefrontal cortex (PFC), hippocampus (HPC), and spleen were then collected and analyzed for metabolomic alterations. A number of significant pathways were altered between Ctrl and AD mice and naturally aged mice. By identifying systems-level alterations following ARCD and AD, these data could provide insights into disease mechanisms and advance the development of biomarker panels.

A Brain Network Constructed on an L1-Norm Regression Model Is More Sensitive in Detecting Small World Network Changes in Early AD

Most previous imaging studies have used traditional Pearson correlation analysis to construct brain networks. This approach fails to adequately and completely account for the interaction between adjacent brain regions. In this study, we used the L1-norm linear regression model to test the small-world attributes of the brain networks of three groups of patients, namely, those with mild cognitive impairment (MCI), Alzheimer's disease (AD), and healthy controls (HCs); we attempted to identify the method that may detect minor differences in MCI and AD patients. Twenty-four AD patients, 33 MCI patients, and 27 HC elderly subjects were subjected to functional MRI (fMRI). We applied traditional Pearson correlation and the L1-norm to construct the brain networks and then tested the small-world attributes by calculating the following parameters: clustering coefficient (Cp), path length (Lp), global efficiency (Eg), and local efficiency (Eloc). As expected, L1 could detect slight changes, mainly in MCI patients expressing higher Cp and Eloc; however, no statistical differences were found between MCI patients and HCs in terms of Cp, Lp, Eg, and Eloc, using Pearson correlation. Compared with HCs, AD patients expressed a lower Cp, Eloc, and Lp and an increased Eg using both connectivity metrics. The statistical differences between the groups indicated the brain networks constructed by the L1-norm were more sensitive to detect slight small-world network changes in early stages of AD.

Asymmetric Differences in the Gray Matter Volume and Functional Connections of the Amygdala Are Associated With Clinical Manifestations of Alzheimer's Disease

Objective

Asymmetry is a subtle but pervasive aspect of the human brain, which may be altered in several neuropsychiatric conditions. Magnetic resonance imaging (MRI) studies have reported that cerebral structural asymmetries are altered in Alzheimer’s disease (AD), but most of these studies were conducted at the region-of-interest level. At the functional level, there are few reports of resting-state functional asymmetries based on functional MRI. In this study, we investigated lateral differences in structural volumes and strengths of functional connectivity between individuals with AD and healthy controls (HCs) at the voxel level.

Methods

Forty-eight patients with AD and 32 matched HCs were assessed. An analysis of voxel-based morphometry (VBM) of gray matter volume was performed at the whole-brain level to explore anatomical cerebral asymmetries in AD. We then performed a seed-to-whole-brain functional connectivity (FC) analysis to reveal FC asymmetries in AD. An asymmetry index (AI) was used to measure these changes, and the relationship between the structural and functional AIs and the clinical symptoms of AD was explored.

Results

A VBM analysis revealed a rightward and a leftward lateralization in the amygdala and the thalamus, respectively, in patients with AD. FC between the amygdala and the precuneus showed a rightward lateralization in AD, which was the opposite of the lateralization in the HCs. The asymmetric changes in structure and function were associated with disease severity and functional impairment in AD.

Conclusion

Our study highlights the value of considering asymmetries in the amygdala and the thalamus in clinical evaluations and their relevance to clinical measures.

New Approaches to Studying Silent Mesial Temporal Lobe Seizures in Alzheimer's Disease

Silent seizures were discovered in mouse models of Alzheimer's disease over 10 years ago, yet it remains unclear whether these seizures are a salient feature of Alzheimer's disease in humans. Seizures that arise early in the course of Alzheimer's disease most likely originate from the mesial temporal lobe, one of the first structures affected by Alzheimer's disease pathology and one of the most epileptogenic regions of the brain. Several factors greatly limit our ability to identify mesial temporal lobe seizures in patients with Alzheimer's disease, however. First, mesial temporal lobe seizures can be difficult to recognize clinically, as their accompanying symptoms are often subtle or even non-existent. Second, electrical activity arising from the mesial temporal lobe is largely invisible on the scalp electroencephalogram (EEG), the mainstay of diagnosis for epilepsy in this population. In this review, we will describe two new approaches being used to study silent mesial temporal lobe seizures in Alzheimer's disease. We will first describe the methodology and application of foramen ovale electrodes, which captured the first recordings of silent mesial temporal lobe seizures in humans with Alzheimer's disease. We will then describe machine learning approaches being developed to non-invasively identify silent mesial temporal lobe seizures on scalp EEG. Both of these tools have the potential to elucidate the role of silent seizures in humans with Alzheimer's disease, which could have important implications for early diagnosis, prognostication, and development of targeted therapies for this population.

EEG Window Length Evaluation for the Detection of Alzheimer's Disease over Different Brain Regions

Alzheimer's Disease (AD) is a neurogenerative disorder and the most common type of dementia with a rapidly increasing world prevalence. In this paper, the ability of several statistical and spectral features to detect AD from electroencephalographic (EEG) recordings is evaluated. For this purpose, clinical EEG recordings from 14 patients with AD (8 with mild AD and 6 with moderate AD) and 10 healthy, age-matched individuals are analyzed. The EEG signals are initially segmented in nonoverlapping epochs of different lengths ranging from 5 s to 12 s. Then, a group of statistical and spectral features calculated for each EEG rhythm (δ, θ, α, β, and γ) are extracted, forming the feature vector that trained and tested a Random Forests classifier. Six classification problems are addressed, including the discrimination from whole-brain dynamics and separately from specific brain regions in order to highlight any alterations of the cortical regions. The results indicated a high accuracy ranging from 88.79% to 96.78% for whole-brain classification. Also, the classification accuracy was higher at the posterior and central regions than at the frontal area and the right side of temporal lobe for all classification problems.

Altered functional connectivity in patients with subcortical ischemic vascular disease: A resting-state fMRI study

Patients with subcortical ischemic vascular disease (SIVD) may hold a high risk of cognitive impairment (CI) by affecting the functional connectivity (FC) of resting-state networks (RSNs). Current studies have mainly focused on the patients with CI but have ignored the prodromal stage when people suffered subcortical vascular damage, but without CI. Independent component analysis (ICA) of rs-fMRI could detect altered FC in RSNs at the early stage of the disease. 81 SIVD patients with CI (SVCI = 29) and without CI (pre-SVCI = 25), and 27 normal controls (NCs) were scanned with rs-fMRI, analyzed by ICA and assessed by neuropsychological examinations. We found significantly altered FC within the RSNs of sensorimotor network (SMN), posterior default mode networks (pDMN), right frontoparietal network (rFPN) and language network (LN) (P < 0.05, AlphaSim corrected). The pre-SVCI group showed significantly increased FC in brain regions of the multiple RSNs when compared with the other two groups. The mean values extracted from the right inferior frontal gyrus (IFG.R) and the left posterior cingulate gyrus (PCG.L) were significantly correlated with clock drawing test (CDT). The right precentral/postcentral gyrus (PreCG.R/PoCG.R) and the right supramarginal gyrus (SMG.R) were positively correlated with Stroop-1 Test. We concluded the FC in RSNs had already been changed at the early stage of the disease as the maladaptive response or compensatory reallocation of the cognitive resources. The ICA of rs-fMRI can be applied as a potential approach to identify the underlying mechanisms of SIVD.

Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Normal Controls With Subnetwork Selection and Graph Kernel Principal Component Analysis Based on Minimum Spanning Tree Brain Functional Network

Effective and accurate diagnosis of Alzheimer's disease (AD), as well as its early stage (mild cognitive impairment, MCI), has attracted more and more attention recently. Researchers have constructed threshold brain function networks and extracted various features for the classification of brain diseases. However, in the construction of the brain function network, the selection of threshold is very important, and the unreasonable setting will seriously affect the final classification results. To address this issue, in this paper, we propose a minimum spanning tree (MST) classification framework to identify Alzheimer's disease (AD), MCI, and normal controls (NCs). The proposed method mainly uses the MST method, graph-based Substructure Pattern mining (gSpan), and graph kernel Principal Component Analysis (graph kernel PCA). Specifically, MST is used to construct the brain functional connectivity network; gSpan, to extract features; and subnetwork selection and graph kernel PCA, to select features. Finally, the support vector machine is used to perform classification. We evaluate our method on MST brain functional networks of 21 AD, 25 MCI, and 22 NC subjects. The experimental results show that our proposed method achieves classification accuracy of 98.3, 91.3, and 77.3%, for MCI vs. NC, AD vs. NC, and AD vs. MCI, respectively. The results show our proposed method can achieve significantly improved classification performance compared to other state-of-the-art methods.

Advances in Resting State Neuroimaging of Mild Cognitive Impairment

The rapidly increasing number of patients with Alzheimer's disease (AD) worldwide has become a major public concern. Mild cognitive impairment (MCI), characterized with accelerated memory decline than normal aging, is a stage between cognitively unimpaired and dementia. Identification of MCI in the Alzheimer's continuum from normal aging, is important for early diagnosis and improved intervention of AD. The imaging technique has been extensively used for diagnose and understanding the mechanisms of MCI. Firstly, we review the recent progresses in the research framework of MCI depending on the clinical and/or biomarker findings. Secondly, we cover studies that use of rs-fMRI (resting state functional magnetic resonance imaging) for the brain activities and functional connectivity between normal aging and MCI. Other methodologies and multi-modal studies for investigating the mechanism and early diagnosis of MCI are also discussed. Finally, we discuss how genetic and environmental factors such as education could interact with in MCI. Overall, MCI is a heterogeneous state and employing resting state neuroimaging with other AD biomarker approaches will be able to target in the more precise population and AD-related pathology process.