Gray matter atrophy patterns of mild cognitive impairment subtypes

Distinct Patterns of Brain Atrophy in Amnestic Mild Cognitive Impairment and Motoric Cognitive Risk Syndromes

INTRODUCTION

Motoric cognitive risk (MCR) and amnestic mild cognitive impairment (aMCI) syndromes are each reliable predictors of incident Alzheimer's disease (AD), but MCR may be a stronger predictor of vascular dementia than AD. This study contrasted cortical and hippocampal atrophy patterns in MCR and aMCI.

METHODS

Cross-sectional data from 733 older adults without dementia or disability (M age = 73.6; 45% women) in the multicountry MCR consortium were examined. MCR was defined as presence of slow gait and cognitive concerns. Amnestic MCI was defined as poor episodic memory performance and cognitive concerns. Cortical thickness and hippocampal volumes were quantified from structural MRIs. Multivariate and univariate general linear models were used to examine associations between cortical thickness and hippocampal volume in MCR and aMCI, adjusting for age, sex, education, total intracranial volume, white matter lesions, and study site.

RESULTS

The prevalence of MCR and aMCI was 7.64% and 12.96%, respectively. MCR was associated with widespread cortical atrophy, including prefrontal, insular, cingulate, motor, parietal, and temporal atrophy. aMCI was associated with hippocampal atrophy.

CONCLUSION

Distinct patterns of atrophy were associated with MCR and aMCI. A distributed pattern of cortical atrophy - that is more consistent with VaD or mixed dementia- was observed in MCR. A more restricted pattern of atrophy - that is more consistent with AD - was observed in aMCI. The biological underpinnings of MCR and aMCI likely differ and may require tailored interventions.

INTRODUCTION

Motoric cognitive risk (MCR) and amnestic mild cognitive impairment (aMCI) syndromes are each reliable predictors of incident Alzheimer's disease (AD), but MCR may be a stronger predictor of vascular dementia than AD. This study contrasted cortical and hippocampal atrophy patterns in MCR and aMCI.

METHODS

Cross-sectional data from 733 older adults without dementia or disability (M age = 73.6; 45% women) in the multicountry MCR consortium were examined. MCR was defined as presence of slow gait and cognitive concerns. Amnestic MCI was defined as poor episodic memory performance and cognitive concerns. Cortical thickness and hippocampal volumes were quantified from structural MRIs. Multivariate and univariate general linear models were used to examine associations between cortical thickness and hippocampal volume in MCR and aMCI, adjusting for age, sex, education, total intracranial volume, white matter lesions, and study site.

RESULTS

The prevalence of MCR and aMCI was 7.64% and 12.96%, respectively. MCR was associated with widespread cortical atrophy, including prefrontal, insular, cingulate, motor, parietal, and temporal atrophy. aMCI was associated with hippocampal atrophy.

CONCLUSION

Distinct patterns of atrophy were associated with MCR and aMCI. A distributed pattern of cortical atrophy - that is more consistent with VaD or mixed dementia- was observed in MCR. A more restricted pattern of atrophy - that is more consistent with AD - was observed in aMCI. The biological underpinnings of MCR and aMCI likely differ and may require tailored interventions.

Machine Learning Model for Mild Cognitive Impairment Stage Based on Gait and MRI Images

In patients with mild cognitive impairment (MCI), a lower level of cognitive function is associated with a higher likelihood of progression to dementia. In addition, gait disturbances and structural changes on brain MRI scans reflect cognitive levels. Therefore, we aimed to classify MCI based on cognitive level using gait parameters and brain MRI data. Eighty patients diagnosed with MCI from three dementia centres in Gangwon-do, Korea, were recruited for this study. We defined MCI as a Clinical Dementia Rating global score of ≥0.5, with a memory domain score of ≥0.5. Patients were classified as early-stage or late-stage MCI based on their mini-mental status examination (MMSE) z-scores. We trained a machine learning model using gait and MRI data parameters. The convolutional neural network (CNN) resulted in the best classifier performance in separating late-stage MCI from early-stage MCI; its performance was maximised when feature patterns that included multimodal features (GAIT + white matter dataset) were used. The single support time was the strongest predictor. Machine learning that incorporated gait and white matter parameters achieved the highest accuracy in distinguishing between late-stage MCI and early-stage MCI.

Relationship between cognitive reserve, brain volume, and neuropsychological performance in amnestic and nonamnestic MCI

Cognitive Reserve (CR) is a theoretical construct that influences the onset and course of cognitive and structural changes that occur with aging and mild cognitive impairment (MCI). There is a paucity of research that examines the relationship of CR and brain volumes in amnestic (aMCI) and nonamnestic (naMCI) separately. This study is a retrospective chart review of MCI patients who underwent neuropsychological evaluation and brain MRI with NeuroReader™ (NR). NR is an FDA-cleared software that standardizes MRI volumes to a control sample. Classifications of aMCI and naMCI were based on Petersen criteria. CR was measured as education, occupation, and word reading. Data analysis included bivariate correlations between CR, neuropsychological test scores, and NR-brain volumes by MCI subtype. The Benjamini-Hochberg method corrected for multiple comparisons. The sample included 91 participants with aMCI and 41 with naMCI. Within naMCI, positive correlations were observed between CR and whole brain volume, total gray matter, bifrontal, left parietal, left occipital, and bilateral cerebellum. Within aMCI, no significant correlations were observed between CR and brain volumes. Positive correlations with CR were observed in language, attention, and visual learning in both aMCI and naMCI groups. The current study adds to the minimal literature on CR and naMCI. Results revealed that CR is associated with volumetrics in naMCI only, though cognitive findings were similar in both MCI groups. Possible explanations include heterogeneous disease pathologies, disease stage, or a differential influence of CR on volumetrics in MCI. Additional longitudinal and biomarker studies will better elucidate this relationship.

Application of Nanopore Sequencing for High Throughput Genotyping in Horses

Nanopore sequencing is a third-generation biopolymer sequencing technique that relies on monitoring the changes in an electrical current that occur as nucleic acids are passed through a protein nanopore. Increasing quality of reads generated by nanopore sequencing systems encourages their application in genome-wide polymorphism detection and genotyping. In this study, we employed nanopore sequencing to identify genome-wide polymorphisms in the horse genome. To reduce the size and complexity of genome fragments for sequencing in a simple and cost-efficient manner, we amplified random DNA fragments using a modified DOP-PCR and sequenced the resulting products using the MinION system. After initial filtering, this generated 28,426 polymorphisms, which were validated at a 3% error rate. Upon further filtering for polymorphism and reproducibility, we identified 9495 SNPs that reflected the horse population structure. To conclude, the use of nanopore sequencing, in conjunction with a genome enrichment step, is a promising tool that can be practical in a variety of applications, including genotyping, population genomics, association studies, linkage mapping, and potentially genomic selection.

Comparing three neuropsychological subgrouping approaches in subjective and mild cognitive impairment from a naturalistic multicenter study

Subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) are two clinical groups with an increased risk to develop dementia, but they are highly heterogeneous. This study compared three different approaches to subgroup SCI and MCI patients and investigated their capacity to disentangle cognitive and biomarker heterogeneity. We included 792 patients from the MemClin-cohort (142 SCI and 650 MCI). Biomarkers included cerebrospinal fluid measures of beta-amyloid-42 and phosphorylated tau, as well as visual ratings of medial temporal lobe atrophy and white matter hyperintensities on magnetic resonance imaging. We found that a more inclusive approach identified individuals with a positive beta-amyloid-42 biomarker; a less inclusive approach captured individuals with higher medial temporal lobe atrophy; and a data-driven approach captured individuals with high white matter hyperintensities burden. The three approaches also captured some neuropsychological differences. We conclude that choice of approach may differ depending on the purpose. This study helps to advance our current understanding of the clinical and biological heterogeneity within SCI and MCI, particularly in the unselected memory clinic setting.

Clinical Features, Brain-Structure Changes, and Cognitive Impairment in Basal Ganglia Infarcts: A Pilot Study

Introduction

Stroke has been considered to raise the risk of dementia in several studies, but the relationship between brain structural changes and poststroke cognitive impairment (PSCI) is unclear.

Methods

In this study, 23 PSCI patients with basal ganglia infarcts after 2 weeks and 29 age-matched controls underwent magnetic resonance imaging measuring cortical thickness and volume changes, as well as neuropsychological tests. CI was derived from a performance score <1.5 standard deviations for normally distributed scores. We compared Z scores in different cognitive domains and cortical thickness and volumes in two groups. Multiple linear regressions were used to investigate the relationship between cortical thickness and volumes and neuropsychological tests.

Results

A majority of PSCI patients were in their 50s (55.19±8.52 years). PSCI patients exhibited significantly decreased Z scores in multiple domains, such as memory, language, visuomotor speed, and attention/executive function. The volumes of the middle posterior corpus callosum, middle anterior corpus callosum, and hippocampus in PSCI patients were markedly lower than controls. The thickness of the right inferior temporal cortex and insula were significantly smaller than controls. It found that the reduced right hippocampus was related to executive dysfunction. Hippocampus dysfunction may be involved in language impairment (p<0.05) in PSCI patients with basal ganglia infarcts.

Conclusion

These findings demonstrated that brain structure changed after ischemic stroke, and different gray-matter structural changes could lead to specific cognitive decline in PSCI patients with basal ganglia infarcts. Atrophy of the right hippocampus potentially serves as an imaging marker of early executive function of PSCI.

Shared and specific dynamics of brain activity and connectivity in amnestic and nonamnestic mild cognitive impairment

AIMS

The present study aimed to compare temporal variability in the spontaneous fluctuations of activity and connectivity between amnestic MCI (aMCI) and nonamnestic MCI (naMCI), which enhances the understanding of their different pathophysiologies and provides targets for individualized intervention.

METHODS

Sixty-five naMCI and 48 aMCI subjects and 75 healthy controls were recruited. A sliding window analysis was used to evaluate the dynamic amplitude of low-frequency fluctuations (dALFF), dynamic regional homogeneity (dReHo), and dynamic functional connectivity (dFC). The caudal/rostral hippocampus was selected as the seeds for calculating dFC.

RESULTS

Both aMCI and naMCI exhibited abnormal dALFF, dReHo, and hippocampal dFC compared with healthy controls. Compared with individuals with naMCI, those with aMCI exhibited (1) higher dALFF variability in the right putamen, left Rolandic operculum, and right middle cingulum, (2) lower dReHo variability in the right superior parietal lobule, and (3) lower dFC variability between the hippocampus and other regions (left superior occipital gyrus, middle frontal gyrus, inferior cerebellum, precuneus, and right superior frontal gyrus). Additionally, variability in dALFF, dReHo, and hippocampal dFC exhibited different associations with cognitive scores in aMCI and naMCI patients, respectively. Finally, dReHo variability in the right superior parietal lobule and dFC variability between the right caudal hippocampus and left inferior cerebellum exhibited partially mediated effects on the different memory scores between people with aMCI and naMCI.

CONCLUSION

The aMCI and naMCI patients exhibited shared and specific patterns of dynamic brain activity and connectivity. The dReHo of the superior parietal lobule and dFC of the hippocampus-cerebellum contributed to the memory heterogeneity of MCI subtypes. Analyzing the temporal variability in the spontaneous fluctuations of brain activity and connectivity provided a new perspective for exploring the different pathophysiological mechanisms in MCI subtypes.

Triploid genetic algorithm for convolutional neural network-based diagnosis of mild cognitive impairment

The diagnosis of mild cognitive impairment (MCI), which is deemed a formative phase of dementia, may greatly assist clinicians in delaying its headway toward dementia. This article proposes a deep learning approach based on a triploid genetic algorithm, a proposed variant of genetic algorithms, for classifying MCI converts and non-converts using structural magnetic resonance imaging data. It also explores the effect of the choice of activation functions and that of the selection of hyper-parameters on the performance of the model. The proposed work is a step toward automated convolutional neural networks. The performance of the proposed method is measured in terms of accuracy and empirical studies exhibit the preeminence of our proposed method over the existing ones. The proposed model results in a maximum accuracy of 0.97961. Thus, it may contribute to the effective diagnosis of MCI and may prove important in clinical settings.

Associations Between Sub-Threshold Amyloid-β Deposition, Cortical Volume, and Cognitive Function Modulated by APOE ɛ4 Carrier Status in Cognitively Normal Older Adults

Background:

There has been renewed interest in the deteriorating effects of sub-threshold amyloid-β (Aβ) accumulation in Alzheimer’s disease (AD). Despite evidence suggesting a synergistic interaction between the APOE ɛ4 allele and Aβ deposition in neurodegeneration, few studies have investigated the modulatory role of this allele in sub-threshold Aβ deposition during the preclinical phase.

Objective:

We aimed to explore the differential effect of the APOE ɛ4 carrier status on the association between sub-threshold Aβ deposition, cortical volume, and cognitive performance in cognitively normal older adults (CN).

Methods:

A total of 112 CN with sub-threshold Aβ deposition was included in the study. Participants underwent structural magnetic resonance imaging, [¹⁸F] flutemetamol PET-CT, and a neuropsychological battery. Potential interactions between APOE ɛ4 carrier status, Aβ accumulation, and cognitive function for cortical volume were assessed with whole-brain voxel-wise analysis.

Results:

We found that greater cortical volume was observed with higher regional Aβ deposition in the APOE ɛ4 carriers, which could be attributed to an interaction between the APOE ɛ4 carrier status and regional Aβ deposition in the posterior cingulate cortex/precuneus. Finally, the APOE ɛ4 carrier status-neuropsychological test score interaction demonstrated a significant effect on the gray matter volume of the left middle occipital gyrus.

Conclusion:

There might be a compensatory response to initiating Aβ in APOE ɛ4 carriers during the earliest AD stage. Despite its exploratory nature, this study offers some insight into recent interests concerning probabilistic AD modeling, focusing on the modulating role of the APOE ɛ4 carrier status during the preclinical period.

Episodic Memory, Hippocampal Volume, and Function for Classification of Mild Cognitive Impairment Patients Regarding Amyloid Pathology

Background:

Previous studies of hippocampal function and volume related to episodic memory deficits in patients with amnestic mild cognitive impairment (aMCI) have produced mixed results including increased or decreased activity and volume. However, most of them have not included biomarkers, such as amyloid-β (Aβ) deposition which is the hallmark for early identification of the Alzheimer’s disease continuum.

Objective:

We investigated the role of Aβ deposition, functional hippocampal activity and structural volume in aMCI patients and healthy elderly controls (HC) using a new functional MRI (fMRI) ecological episodic memory task.

Methods:

Forty-six older adults were included, among them Aβ PET PIB positive (PIB+) aMCI (N = 17), Aβ PET PIB negative (PIB–) aMCI (N = 15), and HC (N = 14). Hippocampal volume and function were analyzed using Freesurfer v6.0 and FSL for news headlines episodic memory fMRI task, and logistic regression for group classification in conjunction with episodic memory task and traditional neuropsychological tests.

Results:

The aMCI PIB+ and PIB–patients showed significantly worse performance in relation to HC in most traditional neuropsychological tests and within group difference only on story recall and the ecological episodic memory fMRI task delayed recall. The classification model reached a significant accuracy (78%) and the classification pattern characterizing the PIB+ included decreased left hippocampal function and volume, increased right hippocampal function and volume, and worse episodic memory performance differing from PIB–which showed increased left hippocampus volume.

Conclusion:

The main findings showed differential neural correlates, hippocampal volume and function during episodic memory in aMCI patients with the presence of Aβ deposition.

Brain Functional Alterations in Prepubertal Boys With Autism Spectrum Disorders

Objectives

Abnormal brain function in ASD patients changes dynamically across developmental stages. However, no one has studied the brain function of prepubertal children with ASD. Prepuberty is an important stage for children’s socialization. This study aimed to investigate alterations in local spontaneous brain activity in prepubertal boys with ASD.

Materials and Methods

Measures of the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) acquired from resting-state functional magnetic resonance imaging (RS-fMRI) database, including 34 boys with ASD and 49 typically developing (TD) boys aged 7 to 10 years, were used to detect regional brain activity. Pearson correlation analyses were conducted on the relationship between abnormal ALFF and ReHo values and Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADI-R) scores.

Results

In the ASD group, we found decreased ALFF in the left inferior parietal lobule (IPL) and decreased ReHo in the left lingual gyrus (LG), left superior temporal gyrus (STG), left middle occipital gyrus (MOG), and right cuneus (p < 0.05, FDR correction). There were negative correlations between ReHo values in the left LG and left STG and the ADOS social affect score and a negative correlation between ReHo values in the left STG and the calibrated severity total ADOS score.

Conclusion

Brain regions with functional abnormalities, including the left IPL, left LG, left STG, left MOG, and right cuneus may be crucial in the neuropathology of prepubertal boys with ASD. Furthermore, ReHo abnormalities in the left LG and left STG were correlated with sociality. These results will supplement the study of neural mechanisms in ASD at different developmental stages, and be helpful in exploring the neural mechanisms of prepubertal boys with ASD.

Hippocampal Volumes in Amnestic and Non-Amnestic Mild Cognitive Impairment Types Using Two Common Methods of MCI Classification

OBJECTIVES

Mild cognitive impairment (MCI) types may have distinct neuropathological substrates with hippocampal atrophy particularly common in amnestic MCI (aMCI). However, depending on the MCI classification criteria applied to the sample (e.g., number of abnormal test scores considered or thresholds for impairment), volumetric findings between MCI types may change. Additionally, despite increased clinical use, no prior research has examined volumetric differences in MCI types using the automated volumetric software, Neuroreader™.

METHODS

The present study separately applied the Petersen/Winblad and Jak/Bondi MCI criteria to a clinical sample of older adults (N = 82) who underwent neuropsychological testing and brain MRI. Volumetric data were analyzed using Neuroreader™ and hippocampal volumes were compared between aMCI and non-amnestic MCI (naMCI).

RESULTS

T-tests revealed that regardless of MCI classification criteria, hippocampal volume z-scores were significantly lower in aMCI compared to naMCI (p's < .05), and hippocampal volume z-scores significantly differed from 0 (Neuroreader™ normative mean) in the aMCI group only (p's < .05). Additionally, significant, positive correlations were found between measures of delayed recall and hippocampal z-scores in aMCI using either MCI classification criteria (p's < .05).

CONCLUSIONS

We provide evidence of correlated neuroanatomical changes associated with memory performance for two commonly used neuropsychological MCI classification criteria. Future research should investigate the clinical utility of hippocampal volumes analyzed via Neuroreader™ in MCI.

Impaired Recognition of Facial and Vocal Emotions in Mild Cognitive Impairment

OBJECTIVE

The ability to recognize others' emotions is a central aspect of socioemotional functioning. Emotion recognition impairments are well documented in Alzheimer's disease and other dementias, but it is less understood whether they are also present in mild cognitive impairment (MCI). Results on facial emotion recognition are mixed, and crucially, it remains unclear whether the potential impairments are specific to faces or extend across sensory modalities.

METHOD

In the current study, 32 MCI patients and 33 cognitively intact controls completed a comprehensive neuropsychological assessment and two forced-choice emotion recognition tasks, including visual and auditory stimuli. The emotion recognition tasks required participants to categorize emotions in facial expressions and in nonverbal vocalizations (e.g., laughter, crying) expressing neutrality, anger, disgust, fear, happiness, pleasure, surprise, or sadness.

RESULTS

MCI patients performed worse than controls for both facial expressions and vocalizations. The effect was large, similar across tasks and individual emotions, and it was not explained by sensory losses or affective symptomatology. Emotion recognition impairments were more pronounced among patients with lower global cognitive performance, but they did not correlate with the ability to perform activities of daily living.

CONCLUSIONS

These findings indicate that MCI is associated with emotion recognition difficulties and that such difficulties extend beyond vision, plausibly reflecting a failure at supramodal levels of emotional processing. This highlights the importance of considering emotion recognition abilities as part of standard neuropsychological testing in MCI, and as a target of interventions aimed at improving social cognition in these patients.

Information Flow Pattern in Early Mild Cognitive Impairment Patients

Purpose: To investigate the brain information flow pattern in patients with early mild cognitive impairment (EMCI) and explore its potential ability of differentiation and prediction for EMCI.

Methods: In this study, 49 patients with EMCI and 40 age- and sex-matched healthy controls (HCs) with available resting-state functional MRI images and neurological measures [including the neuropsychological evaluation and cerebrospinal fluid (CSF) biomarkers] were included from the Alzheimer's Disease Neuroimaging Initiative. Functional MRI measures including preferred information flow direction between brain regions and preferred information flow index of each brain region parcellated by the Atlas of Intrinsic Connectivity of Homotopic Areas (AICHA) were calculated by using non-parametric multiplicative regression-Granger causality analysis (NPMR-GCA). Edge- and node-wise Student's t-test was conducted for between-group comparison. Support vector classification was performed to differentiate EMCI from HC. The least absolute shrinkage and selection operator (lasso) regression were used to evaluate the predictive ability of information flow measures for the neurological state.

Results: Compared to HC, disturbed preferred information flow directions between brain regions involving default mode network (DMN), executive control network (ECN), somatomotor network (SMN), and visual network (VN) were observed in patients with EMCI. An altered preferred information flow index in several brain regions (including the thalamus, posterior cingulate, and precentral gyrus) was also observed. Classification accuracy of 80% for differentiating patients with EMCI from HC was achieved by using the preferred information flow directions. The preferred information flow directions have a good ability to predict memory and executive function, level of amyloid β, tau protein, and phosphorylated tau protein with the high Pearson's correlation coefficients (r > 0.7) between predictive and actual neurological measures.

Conclusion: Patients with EMCI were presented with a disturbed brain information flow pattern, which could help clinicians to identify patients with EMCI and assess their neurological state.

Changes in brain activity related to episodic memory retrieval in adults with single domain amnestic mild cognitive impairment

The present fMRI study aimed to characterize the performance and the brain activity changes related to episodic memory retrieval in adults with single domain aMCI (sdaMCI), relative to cognitively unimpaired adults. Participants performed an old/new recognition memory task with words while BOLD signal was acquired. The sdaMCI group showed lower hits (correct recognition of old words), lower ability to discriminate old and new words, higher errors and longer reaction times for hits. This group also displayed brain hypoactivation in left precuneus and the left midcingulate cortex during the successful recognition of old words. These changes in brain activity suggest the presence of neural dysregulations in brain regions involved during successful episodic memory retrieval. Moreover, hypoactivation in these brain areas discriminated both groups with moderate sensitivity and specificity values, suggesting that it might constitute a potential neurocognitive biomarker of sdaMCI.

Cognitive impairment and depression: Meta-analysis of structural magnetic resonance imaging studies

Longitudinal comorbidity of depression and cognitive impairment has been reported by number of epidemiological studies but the underlying mechanisms explaining the link between affective problems and cognitive decline are not very well understood. Imaging studies have typically investigated patients with major depressive disorder (MDD) and mild cognitive impairment (MCI) separately and thus have not identified a structural brain signature common to these conditions that may illuminate potentially targetable shared biological mechanisms. We performed a meta-analysis of. 48 voxel-based morphometry (VBM) studies of individuals with MDD, MCI, and age-matched controls and demonstrated that MDD and MCI patients had shared volumetric reductions in a number of regions including the insula, superior temporal gyrus (STG), inferior frontal gyrus, amygdala, hippocampus, and thalamus. We suggest that the shared volumetric reductions in the insula and STG might reflect communication deficits and infrequent participation in mentally or socially stimulating activities, which have been described as risk factors for both MCI and MDD. We also suggest that the disease-specific structural changes might reflect the disease-specific symptoms such as poor integration of emotional information, feelings of helplessness and worthlessness, and anhedonia in MDD. These findings could contribute to better understanding of the origins of MDD-MCI comorbidity and facilitate development of early interventions.

Engagement in cognitively stimulating activities in individuals with Mild Cognitive Impairment: relationships with neuropsychological domains and hippocampal volume

Late-life participation in cognitively stimulating activities is thought to contribute to an individual's cognitive reserve and thus protect against cognitive decline, yet its association with clinical markers of neurodegeneration is not well established. To investigate, we developed a 13-item self-report "cognitively stimulating activities" questionnaire (CSA-Q), which was completed by a community sample of 269 older adults (>50 years) at risk of dementia. Participants met criteria for Mild Cognitive Impairment (MCI) and were classified as amnestic (aMCI; n = 93) or non-amnestic (naMCI; n = 176). Weighted CSA-Q dimensions were calculated for activity intensity, mental engagement and social engagement via a panel of 23 inter-raters. The CSA-Q mean and its dimensions were examined in relation to: (a) demographics (age, sex), (b) cognitive reserve proxies (years of education, premorbid IQ), (c) neuropsychological markers across cognitive domains of executive function, processing speed, learning, and memory storage, and (d) neuroimaging markers (left and right hippocampal volume). Analyses were conducted for all MCI, as well as for aMCI and naMCI sub-types. The CSA-Q was found to have concurrent validity with cognitive reserve proxies. Among all MCI, the CSA-Q dimensions of intensity and mental engagement had moderate associations with left hippocampal volume, but not with neuropsychological performance. For naMCI, the CSA-Q had moderate associations with left hippocampal volume, and small associations with aspects of executive functioning and processing speed. No equivalent associations emerged for the aMCI subtype. Our findings show that the CSA-Q may be particularly useful for older adults with non-amnestic cognitive deficits.

Characterizing Global and Regional Brain Structures in Amnestic Mild Cognitive Impairment Among Rural Residents: A Population-Based Study

Background: Structural brain magnetic resonance imaging (MRI) scans may provide reliable neuroimaging markers for defining amnestic mild cognitive impairment (aMCI). Objective: We sought to characterize global and regional brain structures of aMCI among rural-dwelling older adults with limited education in China. Methods: This population-based study included 180 participants (aged≥65 years, 42 with aMCI and 138 normal controls) in the Shandong Yanggu Study of Aging and Dementia during 2014–2016. We defined aMCI following the Petersen’s criteria. Global and regional brain volumes were automatically segmented on MRI scans and compared using a region-of-interest approach. Data were analyzed using general linear regression models. Results: Multi-adjusted β-coefficient (95% confidence interval) of brain volumes (cm3) associated with aMCI was –12.07 (–21.49, –2.64) for global grey matter (GM), –18.31 (–28.45, –8.17) for global white matter (WM), 28.17 (12.83, 44.07) for cerebrospinal fluid (CSF), and 2.20 (0.24, 4.16) for white matter hyperintensities (WMH). Furthermore, aMCI was significantly associated with lower GM volumes in bilateral superior temporal gyri, thalamus and right cuneus, and lower WM volumes in lateral areas extending from the frontal to the parietal, temporal, and occipital lobes, as well as right hippocampus (p < 0.05). Conclusion: Brain structure of older adults with aMCI is characterized by reduced global GM and WM volumes, enlarged CSF volume, increased WMH burden, reduced GM volumes in bilateral superior temporal gyri, thalamus, and right cuneus, and widespread reductions of lateral WM volumes.

Gray Matter Atrophy in Amnestic Mild Cognitive Impairment: A Voxel-Based Meta-Analysis

Background: Voxel-based morphometry (VBM) has been widely used to investigate structural alterations in amnesia mild cognitive impairment (aMCI). However, inconsistent results have hindered our understanding of the exact neuropathology related to aMCI. Objectives: Our aim was to systematically review the literature reporting VBM on aMCI to elucidate consistent gray matter alterations, their functional characterization, and corresponding co-activation patterns. Methods: The PubMed, Web of Science, and EMBASE databases were searched for VBM studies on aMCI published from inception up to June 2020. Peak coordinates were extracted from clusters that showed significant gray matter differences between aMCI patients and healthy controls (HC). Meta-analysis was performed using seed-based d mapping with the permutation of subject images (SDM-PSI), a newly improved meta-analytic method. Functional characterization and task-based co-activation patterns using the BrainMap database were performed on significant clusters to explore their functional roles. Finally, VBM was performed based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to further support the findings. Results: A total of 31 studies with 681 aMCI patients and 837 HC were included in this systematic review. The aMCI group showed significant gray matter atrophy in the left amygdala and right hippocampus, which was consistent with results from the ADNI dataset. Functional characterization revealed that these regions were mainly associated with emotion, cognition, and perception. Further, meta-regression analysis demonstrated that gray matter atrophy in the left inferior frontal gyrus and the left angular gyrus was significantly associated with cognitive impairment in the aMCI group. Conclusions: The findings of gray matter atrophy in the left amygdala and right hippocampus are highly consistent and robust, and not only offer a better understanding of the underlying neuropathology but also provide accurate potential biomarkers for aMCI.

CD103 Deficiency Promotes Autism (ASD) and Attention-Deficit Hyperactivity Disorder (ADHD) Behavioral Spectra and Reduces Age-Related Cognitive Decline

The incidence of autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD), which frequently co-occur, are both rising. The causes of ASD and ADHD remain elusive, even as both appear to involve perturbation of the gut-brain-immune axis. CD103 is an integrin and E-cadherin receptor most prominently expressed on CD8 T cells that reside in gut, brain, and other tissues. CD103 deficiency is well-known to impair gut immunity and resident T cell function, but it's impact on neurodevelopmental disorders has not been examined. We show here that CD8 T cells influence neural progenitor cell function, and that CD103 modulates this impact both directly and potentially by controlling CD8 levels in brain. CD103 knockout (CD103KO) mice exhibited a variety of behavioral abnormalities, including superior cognitive performance coupled with repetitive behavior, aversion to novelty and social impairment in females, with hyperactivity with delayed learning in males. Brain protein markers in female and male CD103KOs coincided with known aspects of ASD and ADHD in humans, respectively. Surprisingly, CD103 deficiency also decreased age-related cognitive decline in both sexes, albeit by distinct means. Together, our findings reveal a novel role for CD103 in brain developmental function, and identify it as a unique factor linking ASD and ADHD etiology. Our data also introduce a new animal model of combined ASD and ADHD with associated cognitive benefits, and reveal potential therapeutic targets for these disorders and age-related cognitive decline.

Voxelwise Meta-Analysis of Gray Matter Abnormalities in Mild Cognitive Impairment and Subjective Cognitive Decline Using Activation Likelihood Estimation

Background: Voxel-based morphometry studies have not yielded consistent results among patients with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Objective: Therefore, we aimed to conduct a meta-analysis of gray matter (GM) abnormalities acquired from these studies to determine their respective neuroanatomical changes. Methods: We systematically searched for voxel-based whole-brain morphometry studies that compared MCI or SCD subjects with healthy controls in PubMed, Web of Science, and EMBASE databases. We used the coordinate-based method of activation likelihood estimation to determine GM changes in SCD, MCI, and MCI sub-groups (amnestic MCI and non-amnestic MCI). Results: A total of 45 studies were included in our meta-analysis. In the MCI group, we found structural atrophy of the bilateral hippocampus, parahippocampal gyrus (PHG), amygdala, right lateral globus pallidus, right insula, and left middle temporal gyrus. The aMCI group exhibited GM atrophy in the bilateral hippocampus, PHG, and amygdala. The naMCI group presented with structural atrophy in the right putamen, right insula, right precentral gyrus, left medial/superior frontal gyrus, and left anterior cingulate. The right lingual gyrus, right cuneus, and left medial frontal gyrus were atrophic GM regions in the SCD group. Conclusion: Our meta-analysis identified unique patterns of neuroanatomical alternations in both the MCI and SCD group. Structural changes in SCD patients provide new evidence for the notion that subtle impairment of visual function, perception, and cognition may be related to early signs of cognitive impairment. In addition, our findings provide a foundation for future targeted interventions at different stages of preclinical Alzheimer’s disease.

Association between Sleep Disturbances and Medial Temporal Lobe Volume in Older Adults with Mild Cognitive Impairment Free of Lifetime History of Depression

BACKGROUND

Previous studies examining the link between neuropsychiatric symptoms (NPS) and biomarkers of Alzheimer's disease (AD) may be confounded by remitted or past history of psychiatric illness, which in itself is associated with AD biomarkers such as reduced medial temporal lobe (MTL) volume.

OBJECTIVE

We examined associations between mood and anxiety-related NPS and MTL in older adults with mild cognitive impairment (MCI) free of lifetime history of depression. We hypothesized an inverse relationship between NPS severity and MTL.

METHODS

Forty-two MCI participants without current or past history of depression or other major psychiatric illness were assessed using the Neuropsychiatric Inventory-Questionnaire (NPI-Q). Correlation and regression analyses were performed between selected NPI-Q items and regional MTL volumes from structural magnetic resonance imaging.

RESULTS

Sleep disturbances were inversely associated with several regional volumes within the MTL. Sleep disturbances remained significantly correlated with left hippocampal and amygdala volume following correction for multiple comparisons. In contrast, depression and anxiety were not correlated with MTL.

CONCLUSIONS

The relationship between reduced MTL and sleep, but not with depressed or anxious states, in MCI free of lifetime history of depression, suggests a potential mechanism for sleep as a risk factor for AD. The current findings highlight the importance of accounting for remitted psychiatric conditions in studies of the link between NPS and AD biomarkers and support the need for further research on sleep as clinical biomarker of AD and target for AD prevention.

Cerebellar Grey Matter Volume in Older Persons Is Associated with Worse Cognitive Functioning

The cerebellum is increasingly recognised for its role in modulation of cognition, behaviour, and affect. The present study examined the relation between structural cerebellar damage (grey matter volume (GMV), white matter hyperintensities (WMHs), lacunar infarcts (LIs) and microbleeds (MBs)) and measures of cognitive, psychological (i.e. symptoms of depression and apathy) and general daily functioning in a population of community-dwelling older persons with mild cognitive deficits, but without dementia. In 194 participants of the Discontinuation of Antihypertensive Treatment in Elderly People (DANTE) Study Leiden, the association between cerebellar GMV, WMHs, LIs and MBs and measures of cognitive, psychological and general daily functioning was analysed with linear regression analysis, adjusted for age, sex, education and cerebral volume. Cerebellar GMV was associated with the overall cognition score (standardised beta 0.20 [95% CI, 0.06-0.33]). Specifically, posterior cerebellar GMV was associated with executive function (standardised beta 0.18 [95% CI, 0.03-0.16]). No relation was found between vascular pathology and cognition. Also, no consistent associations were found on the cerebellar GMV and vascular pathology measures and psychological and general daily functioning. In this population of community-dwelling elderly, less posterior cerebellar GMV but not vascular pathology was associated with worse cognitive function, specifically with poorer executive function. No relation was found between cerebellar pathology and psychological and general daily functioning.

Cortical atrophy patterns of incident MCI subtypes in the Mayo Clinic Study of Aging

INTRODUCTION

We examined differences in cortical thickness in empirically derived mild cognitive impairment (MCI) subtypes in the Mayo Clinic Study of Aging.

METHODS

We compared cortical thickness of four incident MCI subtypes (n = 192) to 1257 cognitive unimpaired individuals.

RESULTS

The subtle cognitive impairment cluster had atrophy in the entorhinal and parahippocampal cortex. The amnestic, dysnomic, and dysexecutive clusters also demonstrated entorhinal cortex atrophy as well as thinning in temporal, parietal, and frontal isocortex in somewhat different patterns.

DISCUSSION

We found patterns of atrophy in each of the incident MCI clusters that corresponded to their patterns of cognitive impairment. The identification of MCI subtypes based on cognitive and structural features may allow for more efficient trial and study designs. Given individuals in the subtle cognitive impairment cluster have less structural changes and cognitive decline and may represent the earliest group, this could be a unique group to target with early interventions.

A combination of 3-D discrete wavelet transform and 3-D local binary pattern for classification of mild cognitive impairment

BACKGROUND

The detection of Alzheimer's Disease (AD) in its formative stages, especially in Mild Cognitive Impairments (MCI), has the potential of helping the clinicians in understanding the condition. The literature review shows that the classification of MCI-converts and MCI-non-converts has not been explored profusely and the maximum classification accuracy reported is rather low. Thus, this paper proposes a Machine Learning approach for classifying patients of MCI into two groups one who converted to AD and the others who are not diagnosed with any signs of AD. The proposed algorithm is also used to distinguish MCI patients from controls (CN). This work uses the Structural Magnetic Resonance Imaging data.

METHODS

This work proposes a 3-D variant of Local Binary Pattern (LBP), called LBP-20 for extracting features. The method has been compared with 3D-Discrete Wavelet Transform (3D-DWT). Subsequently, a combination of 3D-DWT and LBP-20 has been used for extracting features. The relevant features are selected using the Fisher Discriminant Ratio (FDR) and finally the classification has been carried out using the Support Vector Machine.

RESULTS

The combination of 3D-DWT with LBP-20 results in a maximum accuracy of 88.77. Similarly, the proposed combination of methods is also applied to distinguish MCI from CN. The proposed method results in the classification accuracy of 90.31 in this data.

CONCLUSION

The proposed combination is able to extract relevant distribution of microstructures from each component, obtained with the use of DWT and thereby improving the classification accuracy. Moreover, the number of features used for classification is significantly less as compared to those obtained by 3D-DWT. The performance of the proposed method is measured in terms of accuracy, specificity and sensitivity and is found superior in comparison to the existing methods. Thus, the proposed method may contribute to effective diagnosis of MCI and may prove advantageous in clinical settings.

The efficacy of gray matter atrophy and cognitive assessment in differentiation of aMCI and naMCI

Background: Mild cognitive impairment (MCI) is a heterogeneous entity that can be categorized into related but different subtypes. In this study, we analyzed the gray matter structural changes of amnestic MCI (aMCI) and non-amnestic MCI (naMCI), and how it resulted in diverse cognitive impairment.Methods: Altogether 77 individuals were recruited, including 28 cognitively normal controls (NC), 25 naMCI subjects, and 24 aMCI subjects. All participants underwent a 3.0 T magnetic resonance (MR) scan and a detailed neuropsychological examination. Cortical thickness and subcortical nuclei volume were extracted by Freesurfer software and compared among groups. The areas with significant differences were further analyzed by general linear regression to identify the risk factors of each cognitive impairment subtypes.Results: Significant differences were observed in bilateral hippocampi, amygdala, thalamus, accumbens, left transverse temporal gyrus and left precuneus among groups. AMCI and naMCI were significantly different in the right hippocampus, bilateral amygdala, left precuneus, and left transverse temporal gyrus. Linear regression analysis revealed that the atrophy of left precuneus was a risk factor of memory, executive function (EF) and visuospatial impairment (p < 0.001). The atrophy of left amygdala, right accumbens and left thalamus were risk factors of memory, EF and language impairment respectively (p < 0.05).Conclusions: These findings confirmed that different gray matter structural changes could lead to specific neuropsychological features in MCI subtypes. Thorough understanding of MCI subtypes and the underlying pathology would be beneficial for precise diagnosis and intervention.

Amnestic mild cognitive impairment in Parkinson's disease: White matter structural changes and mechanisms

Mild cognitive impairment (MCI) is a heterogeneous cognitive disorder that is often comorbid with Parkinson's diseases (PD). The amnestic subtype of PD-MCI (PD-aMCI) has a higher risk to develop dementia. However, there is a lack of studies on the white matter (WM) structural changes of PD-aMCI. We characterized the WM structural changes of PD-aMCI (n = 17) with cognitively normal PD (PD-CN, n = 19) and normal controls (n = 20), using voxel-based and tract-based spatial statistics (TBSS) analyses on fractional anisotropy (FA) axial diffusivity (AD), and radial diffusivity (RD). By excluding and then including the motor performance as a covariate in the comparison analysis between PD-aMCI and PD-CN, we attempted to discern the influences of two neuropathological mechanisms on the WM structural changes of PD-aMCI. The correlation analyses between memory and voxel-based WM measures in all PD patients were also performed (n = 36). The results showed that PD-aMCI had smaller FA values than PD-CN in the diffuse WM areas, and PD-CN had higher AD and RD values than normal controls in the right caudate. Most FA difference between PD-aMCI and PD-CN could be weakened by the motor adjustment. The FA differences between PD-aMCI and PD-CN were largely spatially overlapped with the memory-correlated FA values. Our findings demonstrated that the WM structural differences between PD-aMCI and PD-CN were mainly memory-related, and the influence of motor adjustment might indicate a common mechanism underlying both motor and memory impairment in PD-aMCI, possibly reflecting a predominant influence of dopaminergic neuropathology.

A Deep Learning approach for Diagnosis of Mild Cognitive Impairment Based on MRI Images

Mild cognitive impairment (MCI) is an intermediary stage condition between healthy people and Alzheimer's disease (AD) patients and other dementias. AD is a progressive and irreversible neurodegenerative disorder, which is a significant threat to people, age 65 and older. Although MCI does not always lead to AD, an early diagnosis at the stage of MCI can be very helpful in identifying people who are at risk of AD. Moreover, the early diagnosis of MCI can lead to more effective treatment, or at least, significantly delay the disease's progress, and can lead to social and financial benefits. Magnetic resonance imaging (MRI), which has become a significant tool for the diagnosis of MCI and AD, can provide neuropsychological data for analyzing the variance in brain structure and function. MCI is divided into early and late MCI (EMCI and LMCI) and sadly, there is no clear differentiation between the brain structure of healthy people and MCI patients, especially in the EMCI stage. This paper aims to use a deep learning approach, which is one of the most powerful branches of machine learning, to discriminate between healthy people and the two types of MCI groups based on MRI results. The convolutional neural network (CNN) with an efficient architecture was used to extract high-quality features from MRIs to classify people into healthy, EMCI, or LMCI groups. The MRIs of 600 individuals used in this study included 200 control normal (CN) people, 200 EMCI patients, and 200 LMCI patients. This study randomly selected 70 percent of the data to train our model and 30 percent for the test set. The results showed the best overall classification between CN and LMCI groups in the sagittal view with an accuracy of 94.54 percent. In addition, 93.96 percent and 93.00 percent accuracy were reached for the pairs of EMCI/LMCI and CN/EMCI, respectively.

The cerebellum in Alzheimer's disease: evaluating its role in cognitive decline

The cerebellum has long been regarded as essential only for the coordination of voluntary motor activity and motor learning. Anatomical, clinical and neuroimaging studies have led to a paradigm shift in the understanding of the cerebellar role in nervous system function, demonstrating that the cerebellum appears integral also to the modulation of cognition and emotion. The search to understand the cerebellar contribution to cognitive processing has increased interest in exploring the role of the cerebellum in neurodegenerative and neuropsychiatric disorders. Principal among these is Alzheimer's disease. Here we review an already sizeable existing literature on the neuropathological, structural and functional neuroimaging studies of the cerebellum in Alzheimer's disease. We consider these observations in the light of the cognitive deficits that characterize Alzheimer's disease and in so doing we introduce a new perspective on its pathophysiology and manifestations. We propose an integrative hypothesis that there is a cerebellar contribution to the cognitive and neuropsychiatric deficits in Alzheimer's disease. We draw on the dysmetria of thought theory to suggest that this cerebellar component manifests as deficits in modulation of the neurobehavioural deficits. We provide suggestions for future studies to investigate this hypothesis and, ultimately, to establish a comprehensive, causal clinicopathological disease model.

Neural correlates of domain-specific cognitive decline: The ARIC-NCS Study

OBJECTIVE

To evaluate the association of cognitive declines in the domains of memory, language, and executive function with brain gray matter (GM) volume in old age.

METHODS

This was a prospective study of 1,846 participants in the Atherosclerosis Risk in Communities (ARIC) Study who underwent 3T brain MRI scans in 2011 to 2013. Participants were categorized by cognitive domain performance trajectory over the prior 20 years (cut point to define decline: 20th percentile). Associations between GM volume and cognitive declines were assessed at the voxel level with voxel-based morphometry and at the regional level with atlas-defined GM volumes of specific regions of interest.

RESULTS

Participants were an average age of 76 years; 60% were female; and 28% were black. Participants in the top 20th percentile for decline in the memory domain had smaller GM volumes in the medial temporal lobe (-3.3%, 95% confidence interval [CI] -4.6% to -2.1%), amygdala (-2.7%, 95% CI -4.1% to -1.3%), entorhinal cortex (-4.1%, 95% CI -6.0% to -2.2%), and hippocampus (-3.8%, 95% CI -5.2% to -2.4%) compared to participants who were in the lowest 80th percentile for decline in all domains. In contrast, among participants who were in the top 20th percentile for decline in the language or executive function domains, GM volumes were smaller in more brain regions.

CONCLUSIONS

Declines in memory function were associated with brain volume loss in the medial temporal and hippocampal formations. Declines in language and executive function were associated with decreases in brain volumes across more noncontiguous brain regions.

Alteration of regional homogeneity and white matter hyperintensities in amnestic mild cognitive impairment subtypes are related to cognition and CSF biomarkers

Amnestic mild cognitive impairment can be further classified as single-domain aMCI (SD-aMCI) with isolated memory deficit, or multi-domain aMCI (MD-aMCI) if memory deficit is combined with impairment in other cognitive domains. Prior studies reported these clinical subtypes presumably differ in etiology. Thus, we aimed to explore the possible mechanisms between different aMCI subtypes by assessing alteration in brain activity and brain vasculature, and their relations with CSF AD biomarkers. 49 healthy controls, 32 SD-aMCI, and 32 MD-aMCI, who had undergone structural scans, resting-state functional MRI (rsfMRI) scans and neuropsychological evaluations, were identified. Regional homogeneity (ReHo) was employed to analyze regional synchronization. Periventricular white matter hyperintensities (PWMH) and deep WMH (DWMH) volume of each participant was quantitatively assessed. AD biomarkers from CSF were also measured. SD-aMCI showed decreased ReHo in medial temporal gyrus (MTG), and increased ReHo in lingual gyrus (LG) and superior temporal gyrus (STG) relative to controls. MD-aMCI showed decreased ReHo, mostly located in precuneus (PCu), LG and postcentral gyrus (PCG), relative to SD-aMCI and controls. As for microvascular disease, MD-aMCI patients had more PWMH burden than SD-aMCI and controls. Correlation analyses indicated mean ReHo in differenced regions were related with memory, language, and executive function in aMCI patients. However, no significant associations between PWMH and behavioral data were found. The Aβ level was related with the ReHo value of STG in SD-aMCI. MD-aMCI displayed different patterns of abnormal regional synchronization and more severe PWMH burden compared with SD-aMCI. Therefore aMCI is not a uniform disease entity, and MD-aMCI group may show more complicated pathologies than SD-aMCI group.

Decreased Bilateral FDG-PET Uptake and Inter-Hemispheric Connectivity in Multi-Domain Amnestic Mild Cognitive Impairment Patients: A Preliminary Study

Background: Amnestic mild cognitive impairment (aMCI) is a heterogeneous condition. Based on clinical symptoms, aMCI could be categorized into single-domain aMCI (SD-aMCI, only memory deficit) and multi-domain aMCI (MD-aMCI, one or more cognitive domain deficit). As core intrinsic functional architecture, inter-hemispheric connectivity maintains many cognitive abilities. However, few studies investigated whether SD-aMCI and MD-aMCI have different inter-hemispheric connectivity pattern. Methods: We evaluated inter-hemispheric connection pattern using fluorine-18 positron emission tomography - fluorodeoxyglucose (¹⁸F PET-FDG), resting-state functional MRI and structural T1 in 49 controls, 32 SD-aMCI, and 32 MD-aMCI patients. Specifically, we analyzed the 18^F PET-FDG (intensity normalized by cerebellar vermis) in a voxel-wise manner. Then, we estimated inter-hemispheric functional and structural connectivity by calculating the voxel-mirrored homotopic connectivity (VMHC) and corpus callosum (CC) subregions volume. Further, we correlated inter-hemispheric indices with the behavioral score and pathological biomarkers. Results: We found that MD-aMCI exhibited more several inter-hemispheric connectivity damages than SD-aMCI. Specifically, MD-aMCI displayed hypometabolism in the bilateral middle temporal gyrus (MTG), inferior parietal lobe, and left precuneus (PCu) (p < 0.001, corrected). Correspondingly, MD-aMCI showed decreased VMHC in MTG, PCu, calcarine gyrus, and postcentral gyrus, as well as smaller mid-posterior CC than the SD-aMCI and controls (p < 0.05, corrected). Contrary to MD-aMCI, there were no neuroimaging indices with significant differences between SD-aMCI and controls, except reduced hypometabolism in bilateral MTG. Within aMCI patients, hypometabolism and reduced inter-hemispheric connectivity correlated with worse executive ability. Moreover, hypometabolism indices correlated to increased amyloid deposition. Conclusion: In conclusion, patients with MD-aMCI exhibited the more severe deficit in inter-hemispheric communication than SD-aMCI. This long-range connectivity deficit may contribute to cognitive profiles and potentially serve as a biomarker to estimate disease progression of aMCI patients.

Altered Whole-Brain Structural Covariance of the Hippocampal Subfields in Subcortical Vascular Mild Cognitive Impairment and Amnestic Mild Cognitive Impairment Patients

The hippocampus plays important roles in memory processing. However, the hippocampus is not a homogeneous structure, which consists of several subfields. The hippocampal subfields are differently affected by many neurodegenerative diseases, especially mild cognitive impairment (MCI). Amnestic mild cognitive impairment (aMCI) and subcortical vascular mild cognitive impairment (svMCI) are the two subtypes of MCI. aMCI is characterized by episodic memory loss, and svMCI is characterized by extensive white matter hyperintensities and multiple lacunar infarctions on magnetic resonance imaging. The primary cognitive impairment in svMCI is executive function, attention, and semantic memory. Some variations or disconnections within specific large-scale brain networks have been observed in aMCI and svMCI patients. The aim of this study was to investigate abnormalities in structural covariance networks (SCNs) between hippocampal subfields and the whole cerebral cortex in aMCI and svMCI patients, and whether these abnormalities are different between the two groups. Automated segmentation of hippocampal subfields was performed with FreeSurfer 5.3, and we selected five hippocampal subfields as the seeds of SCN analysis: CA1, CA2/3, CA4/dentate gyrus (DG), subiculum, and presubiculum. SCNs were constructed based on these hippocampal subfield seeds for each group. Significant correlations between hippocampal subfields, fusiform gyrus (FFG), and entorhinal cortex (ERC) in gray matter volume were found in each group. We also compared the differences in the strength of structural covariance between any two groups. In the aMCI group, compared to the normal controls (NC) group, we observed an increased association between the left CA1/CA4/DG/subiculum and the left temporal pole. Additionally, the hippocampal subfields (bilateral CA1, left CA2/3) significantly covaried with the orbitofrontal cortex in the svMCI group compared to the NC group. In the aMCI group compared to the svMCI group, we observed decreased association between hippocampal subfields and the right FFG, while we also observed an increased association between the bilateral subiculum/presubiculum and bilateral ERC. These findings provide new evidence that there is altered whole-brain structural covariance of the hippocampal subfields in svMCI and aMCI patients and provide insights to the pathological mechanisms of different MCI subtypes.

Gray matter volume and dual-task gait performance in mild cognitive impairment

Dual-task gait performance is impaired in older adults with mild cognitive impairment, but the brain substrates associated with dual-task gait performance are not well-established. The relationship between gray matter and gait speed under single-task and dual-task conditions (walking while counting backward) was examined in 560 seniors with mild cognitive impairment (non-amnestic mild cognitive impairment: n = 270; mean age = 72.4 yrs., 63.6 % women; amnestic mild cognitive impairment: n = 290; mean age = 73.4 yrs., 45.4 % women). Multivariate covariance-based analyses of magnetic resonance imaging data, adjusted for potential confounders including single-task gait speed, were performed to identify gray matter patterns associated with dual-task gait speed. There were no differences in gait speed or cognitive performance during dual-task gait between individuals with non-amnestic mild cognitive impairment and amnestic mild cognitive impairment. Overall, increased dual-task gait speed was associated with a gray matter pattern of increased volume in medial frontal gyrus, superior frontal gyrus, anterior cingulate, cingulate, precuneus, fusiform gyrus, middle occipital gyrus, inferior temporal gyrus and middle temporal gyrus. The relationship between dual-task gait speed and brain substrates also differed by mild cognitive impairment subtype. Our study revealed a pattern of gray matter regions associated with dual-task performance. Although dual-task gait performance was similar in amnestic and non-amnestic mild cognitive impairment, the gray matter patterns associated with dual-task gait performance differed by mild cognitive impairment subtype. These findings suggest that the brain substrates supporting dual-task gait performance in amnestic and non-amnestic subtypes are different, and consequently may respond differently to interventions, or require different interventions.

Up-regulation of DMN Connectivity in Mild Cognitive Impairment Via Network-based Cognitive Training

BACKGROUND

Previous work designed a network-based protocol of cognitive training. This programme exploits a mechanism of induced task-oriented co-activation of multiple regions that are part of the default mode network (DMN), to induce functional rewiring and increased functional connectivity within this network.

OBJECTIVE

In this study, the programme was administered to patients with a diagnosis of mild cognitive impairment to test its effects in a clinical sample.

METHOD

Twenty-three patients with mild cognitive impairment (mean age: 73.74 years, standard deviation 5.13, female/male ratio 13/10) allocated to the experimental condition, underwent one month of computerised training, while fourteen patients (mean age: 73.14 years, standard deviation 6.16, female/ male ratio 7/7) assigned to the control condition underwent a regime of intense social engagement. Patients were in the prodromal stage of Alzheimer's disease (AD) as confirmed by clinical follow ups for at least two years. The DMN was computed at baseline and retest, together with other, control patterns of connectivity, grey matter maps and neuropsychological profiles.

RESULTS

A condition-by-timepoint interaction indicating increased connectivity triggered by the programme was found in left parietal DMN regions. No decreases as well as no changes in the other networks or morphology were found. Although between-condition cognitive changes did not reach statistical significance, they correlated positively with changes in DMN connectivity in the left parietal region, supporting the hypothesis that parietal changes were beneficial.

CONCLUSION

This programme of cognitive training up-regulates a pattern of connectivity which is pathologically down-regulated in AD. We argue that, when cognitive interventions are conceptualised as tools to induce co-activation repeatedly, they can lead to clinically relevant improvements in brain functioning, and can be of aid in support of pharmacological and other interventions in the earliest stages of AD.

Classifying MCI Subtypes in Community-Dwelling Elderly Using Cross-Sectional and Longitudinal MRI-Based Biomarkers

Amnestic MCI (aMCI) and non-amnestic MCI (naMCI) are considered to differ in etiology and outcome. Accurately classifying MCI into meaningful subtypes would enable early intervention with targeted treatment. In this study, we employed structural magnetic resonance imaging (MRI) for MCI subtype classification. This was carried out in a sample of 184 community-dwelling individuals (aged 73-85 years). Cortical surface based measurements were computed from longitudinal and cross-sectional scans. By introducing a feature selection algorithm, we identified a set of discriminative features, and further investigated the temporal patterns of these features. A voting classifier was trained and evaluated via 10 iterations of cross-validation. The best classification accuracies achieved were: 77% (naMCI vs. aMCI), 81% (aMCI vs. cognitively normal (CN)) and 70% (naMCI vs. CN). The best results for differentiating aMCI from naMCI were achieved with baseline features. Hippocampus, amygdala and frontal pole were found to be most discriminative for classifying MCI subtypes. Additionally, we observed the dynamics of classification of several MRI biomarkers. Learning the dynamics of atrophy may aid in the development of better biomarkers, as it may track the progression of cognitive impairment.

Disrupted functional connectivity between perirhinal and parahippocampal cortices with hippocampal subfields in patients with mild cognitive impairment and Alzheimer's disease

Most patients with mild cognitive impairment and Alzheimer's disease can initially present memory loss. The medial temporal lobes are the brain regions most associated with declarative memory function. As sub-components of the MTL, the perirhinal cortex, parahippocampal cortex and hippocampus have also been identified as playing important roles in memory. The functional connectivity between hippocampus subfields and perirhnial cortices as well as parahippocampal cortices among normal cognition controls (NC group, n=33), mild cognitive impairment (MCI group, n=31) and Alzheimer's disease (AD group, n=27) was investigated in this study. The result shows significant differences of functional connectivity in 3 pairs of regions among NC group, MCI group and AD group: right perirhinal cortex with right hippocampus tail, left perirhinal cortex with right hippocampus tail, and right parahippocampal cortex with right hippocampus head. Clustering methods were used to classify NC group, MCI group and AD group (accuracy=100%) as well as different subtypes of mild cognitive impairment patients based on functional alterations. Functional connectivity disrupted between perirhinal and parahippocampal cortex with hippocampal subfields, which may provide a better understanding of the neurodegenerative progress of MCI and AD.

Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

OBJECTIVE

We investigated differences in regional cortical thickness between previously identified empirically derived mild cognitive impairment (MCI) subtypes (amnestic MCI, dysnomic MCI, dysexecutive/mixed MCI, and cluster-derived normal) in order to determine whether these cognitive subtypes would show different patterns of cortical atrophy.

METHODS

Participants were 485 individuals diagnosed with MCI and 178 cognitively normal individuals from the Alzheimer's Disease Neuroimaging Initiative. Cortical thickness estimates were computed for 32 regions of interest per hemisphere. Statistical group maps compared each MCI subtype to cognitively normal participants and to one another.

RESULTS

The pattern of cortical thinning observed in each MCI subtype corresponded to their cognitive profile. No differences in cortical thickness were found between the cluster-derived normal MCI subtype and the cognitively normal group. Direct comparison between MCI subtypes suggested that the cortical thickness patterns reflect increasing disease severity.

CONCLUSIONS

There is an ordered pattern of cortical atrophy among patients with MCI that coincides with their profiles of increasing cognitive dysfunction. This heterogeneity is not captured when patients are grouped by conventional diagnostic criteria. Results in the cluster-derived normal group further support the premise that the conventional MCI diagnostic criteria are highly susceptible to false-positive diagnostic errors. Findings suggest a need to (1) improve the diagnostic criteria by reducing reliance on conventional screening measures, rating scales, and a single memory measure in order to avoid false-positive errors; and (2) divide MCI samples into meaningful subgroups based on cognitive and biomarkers profiles-a method that may provide better staging of MCI and inform prognosis.

Hippocampal complex atrophy in poststroke and mild cognitive impairment

To investigate putative interacting or distinct pathways for hippocampal complex substructure (HCS) atrophy and cognitive affection in early-stage Alzheimer's disease (AD) and cerebrovascular disease (CVD), we recruited healthy controls, patients with mild cognitive impairment (MCI) and poststroke patients. HCSs were segmented, and quantitative white-matter hyperintensity (WMH) load and cerebrospinal fluid (CSF) amyloid-β concentrations were determined. The WMH load was higher poststroke. All examined HCSs were smaller in amyloid-positive MCI than in controls, and the subicular regions were smaller poststroke. Memory was reduced in amyloid-positive MCI, and psychomotor speed and executive function were reduced in poststroke and amyloid-positive MCI. Size of several HCS correlated with WMH load poststroke and with CSF amyloid-β concentrations in MCI. In poststroke and amyloid-positive MCI, neuropsychological function correlated with WMH load and hippocampal volume. There are similar patterns of HCS atrophy in CVD and early-stage AD, but different HCS associations with WMH and CSF biomarkers. WMHs add to hippocampal atrophy and the archetypal AD deficit delayed recall. In line with mounting evidence of a mechanistic link between primary AD pathology and CVD, these additive effects suggest interacting pathologic processes.

The relationship between inflammatory markers and voxel-based gray matter volumes in nondemented older adults

Ageing is characterized by chronically elevated inflammatory markers (IMs). Peripheral IM levels have been found in negative correlations with brain structural measures including global and lobar volumes and the hippocampus. This study investigated the relationship between 10 peripheral IMs and voxel-based gray matter (GM) volumes in nondemented older adults (n = 463). Two proinflammatory cytokines (tumor necrosis factor-α [TNF-α] and interleukin-1β) and 2 vascular IMs (vascular cellular adhesion molecule-1 and plasminogen activator inhibitor-1) were negatively correlated with regional GM volumes. TNF-α and interleukin-1β were both significantly correlated with GM volumes in the left occipitotemporal area, left superior occipital gyrus, and left inferior parietal lobule; TNF-α was also significantly correlated with the bilateral medial prefrontal cortices and approached significance for the correlations with the bilateral hippocampi. Significant GM correlations with vascular cellular adhesion molecule-1 were located in the bilateral anterior cingulate cortices, and with plasminogen activator inhibitor-1 in the cerebellum and right hippocampus. The neuroanatomical correlation patterns of 2 proinflammatory cytokines and 2 vascular IMs might be reflective of the effects of neurodegenerative and vascular pathological processes in the ageing brain.

Neuropsychological and neuroimaging characteristics of amnestic mild cognitive impairment subtypes: a selective overview

Alzheimer's disease (AD) is a progressive age-related neurodegenerative disease. Amnestic mild cognitive impairment (aMCI) is considered to represent early AD. Various aMCI clinical subtypes have been identified as either single domain (SD) or multidomain (MD). The various subtypes represent heterogeneous syndrome, indicating the different probability of progression to AD. Understanding the heterogeneous concept of aMCI can help to construct potential biomarkers to monitor the progression of aMCI to AD. This review provides an overview of various neuroimaging measures for subtypes of aMCI. Focusing on neuropsychological, structural, and functional neuroimaging findings, we found that aMCI showed differences in clinical progression and the abnormalities in MD-aMCI were distributed across temporal, frontal, and parietal cortices, which is similar to AD. This is also compatible with the notion that MD-aMCI is a transition stage between SD-aMCI and AD. Our review provided a framework for the diagnosis of clinical subtypes of aMCI and early detection and intervention of the progression from aMCI to AD.

Hippocampal atrophy in people with memory deficits: results from the population-based IPREA study

BACKGROUND

Clinical studies have shown that hippocampal atrophy is present before dementia in people with memory deficits and can predict dementia development. The question remains whether this association holds in the general population. This is of interest for the possible use of hippocampal atrophy to screen population for preventive interventions. The aim of this study was to assess hippocampal volume and shape abnormalities in elderly adults with memory deficits in a cross-sectional population-based study.

METHODS

We included individuals participating in the Italian Project on the Epidemiology of Alzheimer Disease (IPREA) study: 75 cognitively normal individuals (HC), 31 individuals with memory deficits (MEM), and 31 individuals with memory deficits not otherwise specified (MEMnos). Hippocampal volumes and shape were extracted through manual tracing and the growing and adaptive meshes (GAMEs) shape-modeling algorithm. We investigated between-group differences in hippocampal volume and shape, and correlations with memory deficits.

RESULTS

In MEM participants, hippocampal volumes were significantly smaller than in HC and were mildly associated with worse memory scores. Memory-associated shape changes mapped to the anterior hippocampus. Shape-based analysis detected no significant difference between MEM and HC, while MEMnos showed shape changes in the posterior hippocampus compared with HC and MEM groups.

CONCLUSIONS

These findings support the discriminant validity of hippocampal volumetry as a biomarker of memory impairment in the general population. The detection of shape changes in MEMnos but not in MEM participants suggests that shape-based biomarkers might lack sensitivity to detect Alzheimer's-like pathology in the general population.

Synchronization during an internally directed cognitive state in healthy aging and mild cognitive impairment: a MEG study

Mild cognitive impairment (MCI) is a stage between healthy aging and dementia. It is known that in this condition the connectivity patterns are altered in the resting state and during cognitive tasks, where an extra effort seems to be necessary to overcome cognitive decline. We aimed to determine the functional connectivity pattern required to deal with an internally directed cognitive state (IDICS) in healthy aging and MCI. This task differs from the most commonly employed ones in neurophysiology, since inhibition from external stimuli is needed, allowing the study of this control mechanism. To this end, magnetoencephalographic (MEG) signals were acquired from 32 healthy individuals and 38 MCI patients, both in resting state and while performing a subtraction task of two levels of difficulty. Functional connectivity was assessed with phase locking value (PLV) in five frequency bands. Compared to controls, MCIs showed higher PLV values in delta, theta, and gamma bands and an opposite pattern in alpha, beta, and gamma bands in resting state. These changes were associated with poorer neuropsychological performance. During the task, this group exhibited a hypersynchronization in delta, theta, beta, and gamma bands, which was also related to a lower cognitive performance, suggesting an abnormal functioning in this group. Contrary to controls, MCIs presented a lack of synchronization in the alpha band which may denote an inhibition deficit. Additionally, the magnitude of connectivity changes rose with the task difficulty in controls but not in MCIs, in line with the compensation-related utilization of neural circuits hypothesis (CRUNCH) model.

MEG spectral analysis in subtypes of mild cognitive impairment

Mild cognitive impairment (MCI) has been described as an intermediate stage between normal aging and dementia. Previous studies characterized the alterations of brain oscillatory activity at this stage, but little is known about the differences between single and multidomain amnestic MCI patients. In order to study the patterns of oscillatory magnetic activity in amnestic MCI subtypes, a total of 105 subjects underwent an eyes-closed resting-state magnetoencephalographic recording: 36 healthy controls, 33 amnestic single domain MCIs (a-sd-MCI), and 36 amnestic multidomain MCIs (a-md-MCI). Relative power values were calculated and compared among groups. Subsequently, relative power values were correlated with neuropsychological tests scores and hippocampal volumes. Both MCI groups showed an increase in relative power in lower frequency bands (delta and theta frequency ranges) and a decrease in power values in higher frequency bands (alpha and beta frequency ranges), as compared with the control group. More importantly, clear differences emerged from the comparison between the two amnestic MCI subtypes. The a-md-MCI group showed a significant power increase within delta and theta ranges and reduced relative power within alpha and beta ranges. Such pattern correlated with the neuropsychological performance, indicating that the a-md-MCI subtype is associated not only with a "slowing" of the spectrum but also with a poorer cognitive status. These results suggest that a-md-MCI patients are characterized by a brain activity profile that is closer to that observed in Alzheimer disease. Therefore, it might be hypothesized that the likelihood of conversion to dementia would be higher within this subtype.

Sub-cortical infarcts and the risk of falls in older people: combined results of TASCOG and Sydney MAS studies

BACKGROUND

White matter hyperintensities increase the risk of multiple falls in older people, but the effect of sub-cortical infarcts is unknown.

AIMS

By pooling data from two Australian population-based studies, we aimed to investigate the association between sub-cortical infarcts and multiple falls and whether this relationship, and that of white matter hyperintensities, is mediated or modified by cognitive or sensorimotor factors.

METHODS

Participants underwent structural magnetic resonance imaging and cognitive and sensorimotor assessments. Falls were prospectively measured over 12 months. Sub-cortical infarcts were detected visually. Total white matter hyperintensity volume was quantified using automated segmentation methods. Generalized linear models were used to examine if sub-cortical infarcts and white matter hyperintensities predicted falls.

RESULTS

The mean age of the sample (n = 655) was 74·5 (standard deviation 6·7) years, 336 (51·3%) males. Overall, 114 (17·4%) had multiple falls. The majority had no sub-cortical infarcts (n = 491, 75·0%), while 90 had one (13·7%), 41 had two (6·3%), and 33 had more than or equal to three sub-cortical infarcts (5·0%). The risk of multiple falls was elevated in people with more than or equal to three sub-cortical infarcts (adjusted relative risk 1·89, 95% confidence interval 1·03, 3·46) and in the highest quarter of white matter hyperintensity volume (adjusted relative risk 1·46, 95% confidence interval 1·00, 2·13). The effect of sub-cortical infarcts on falls was amplified by poorer vision (P = 0·03). The effect of white matter hyperintensities was amplified by poorer vision (P = 0·008), proprioception (P = 0·03), and muscle strength (P = 0·008). There was no modifying effect of cognitive function.

CONCLUSIONS

Increasing burdens of sub-cortical infarcts and white matter hyperintensities are associated with a risk of falling. Interventions targeting sensorimotor factors along with strategies to prevent sub-cortical infarcts and white matter hyperintensities may reduce the risk of falls.

The impact of glucose disorders on cognition and brain volumes in the elderly: the Sydney Memory and Ageing Study

Type 2 diabetes predicts accelerated cognitive decline and brain atrophy. We hypothesized that impaired fasting glucose (IFG) and incident glucose disorders have detrimental effects on global cognition and brain volume. We further hypothesized that metabolic and inflammatory derangements accompanying hyperglycaemia contribute to change in brain structure and function. This was a longitudinal study of a community-dwelling elderly cohort with neuropsychological testing (n = 880) and brain volumes by magnetic resonance imaging (n = 312) measured at baseline and 2 years. Primary outcomes were global cognition and total brain volume. Secondary outcomes were cognitive domains (processing speed, memory, language, visuospatial and executive function) and brain volumes (hippocampal, parahippocampal, precuneus and frontal lobe). Participants were categorised as normal, impaired fasting glucose at both assessments (stable IFG), baseline diabetes or incident glucose disorders (incident diabetes or IFG at 2 years). Measures included inflammatory cytokines and oxidative metabolites. Covariates were age, sex, education, non-English speaking background, smoking, blood pressure, lipid-lowering or antihypertensive medications, mood score, apolipoprotein E genotype and baseline cognition or brain volume. Participants with incident glucose disorders had greater decline in global cognition and visuospatial function compared to normal, similar to that observed in baseline diabetes. Homocysteine was independently associated with the observed effect of diabetes on executive function. Apolipoprotein E genotype did not influence the observed effects of diabetes on cognition. Incident glucose disorders and diabetes were also associated with greater 2-year decline in total brain volume, compared to normal (40.0 ± 4.2 vs. 46.7 ± 5.7 mm(3) vs. 18.1 ± 6.2, respectively, p < 0.005). Stable IFG did not show greater decline in global cognition or brain volumes compared to normal. Incident glucose disorders, like diabetes, are associated with accelerated decline in global cognition and brain volumes in non-demented elderly, whereas stable IFG is not. Preventing deterioration in glucose metabolism in the elderly may help preserve brain structure and function.

Sydney Memory and Ageing Study: an epidemiological cohort study of brain ageing and dementia

Non-demented community-dwelling older adults aged 70-90 years (n = 1,037) randomly recruited from the electoral roll completed neuropsychological and medical assessments over six years. The overall prevalence of mild cognitive impairment (MCI) at baseline was 36.7%. Risk factors for MCI include APOE ε4 allele carrier status, high homocysteine, heart disease, poor odour identification, low visual acuity and low mental activity, but notable age and sex differences were observed. Neuropsychiatric symptoms were rare; depression was the most common and was associated with cognitive impairment in at least one domain as well as subsequent dementia 2 years later. Poorer cognitively demanding functional abilities were associated with cognitive impairment. Biomarkers for cognitive impairment and decline were identified. Inflammatory markers and plasma apolipoprotein levels were associated with poorer performance in the attention/processing speed domain. Measures of white matter lesions, white matter integrity, sulcal morphology and tractography were identified as novel biomarkers of early cognitive decline. Stronger deactivation in the posteromedial cortex with increasing memory load on functional MRI predicted future decline. Compared to previous reports, our prevalence rates of MCI were higher but rates of progression to dementia and reversion to normal were similar, as were risk factors for progression to dementia.