The neural correlates of verbal short-term memory in Alzheimer's disease: an fMRI study

Alterations of Structural Network Efficiency in Early-Onset and Late-Onset Alzheimer's Disease

BACKGROUND AND PURPOSE

Early- and late-onset Alzheimer's disease (EOAD and LOAD, respectively) share the same neuropathological hallmarks of amyloid and neurofibrillary tangles but have distinct cognitive features. We compared structural brain connectivity between the EOAD and LOAD groups using structural network efficiency and evaluated the association of structural network efficiency with the cognitive profile and pathological markers of Alzheimer's disease (AD).

METHODS

The structural brain connectivity networks of 80 AD patients (47 with EOAD and 33 with LOAD) and 57 healthy controls were reconstructed using diffusion-tensor imaging. Graph-theoretic indices were calculated and intergroup differences were evaluated. Correlations between network parameters and neuropsychological test results were analyzed. The correlations of the amyloid and tau burdens with network parameters were evaluated for the patients and controls.

RESULTS

Compared with the age-matched control group, the EOAD patients had increased global path length and decreased global efficiency, averaged local efficiency, and averaged clustering coefficient. In contrast, no significant differences were found in the LOAD patients. Locally, the EOAD patients showed decreases in local efficiency and the clustering coefficient over a wide area compared with the control group, whereas LOAD patients showed such decreases only within a limited area. Changes in network parameters were significantly correlated with multiple cognitive domains in EOAD patients, but only with Clinical Dementia Rating Sum-of-Boxes scores in LOAD patients. Finally, the tau burden was correlated with changes in network parameters in AD signature areas in both patient groups, while there was no correlation with the amyloid burden.

CONCLUSIONS

The impairment of structural network efficiency and its effects on cognition may differ between EOAD and LOAD.

Constructing hierarchical attentive functional brain networks for early AD diagnosis

Analyzing functional brain networks (FBN) with deep learning has demonstrated great potential for brain disorder diagnosis. The conventional construction of FBN is typically conducted at a single scale with a predefined brain region atlas. However, numerous studies have identified that the structure and function of the brain are hierarchically organized in nature. This urges the need of representing FBN in a hierarchical manner for more effective analysis of the complementary diagnostic insights at different scales. To this end, this paper proposes to build hierarchical FBNs adaptively within the Transformer framework. Specifically, a sparse attention-based node-merging module is designed to work alongside the conventional network feature extraction modules in each layer. The proposed module generates coarser nodes for further FBN construction and analysis by combining fine-grained nodes. By stacking multiple such layers, a hierarchical representation of FBN can be adaptively learned in an end-to-end manner. The hierarchical structure can not only integrate the complementary information from multiscale FBN for joint analysis, but also reduce the model complexity due to decreasing node sizes. Moreover, this paper argues that the nodes defined by the existing atlases are not necessarily the optimal starting level to build FBN hierarchy and exploring finer nodes may further enrich the FBN representation. In this regard, each predefined node in an atlas is split into multiple sub-nodes, overcoming the scale limitation of the existing atlases. Extensive experiments conducted on various data sets consistently demonstrate the superior performance of the proposed method over the competing methods.

Unveiling the influence of daily dietary patterns on brain cortical structure: insights from bidirectional Mendelian randomization

Cognitive impairment is a significant concern in aging populations. This study utilized Mendelian randomization analysis to explore the impact of dietary habits and macro-nutrients on cortical structure. A bidirectional Mendelian randomization approach was employed, incorporating large-scale genetic data on dietary habits and brain cortical structure. The results did not reveal significant causal relationships between dietary factors and overall cortical structure and thickness. However, specific dietary factors showed associations with cortical structure in certain regions. For instance, fat intake affected six cortical regions, while milk, protein, fruits, and water were associated with changes in specific regions. Reverse analysis suggested that cortical thickness influenced the consumption of alcohol, carbohydrates, coffee, and fish. These findings contribute to understanding the potential mechanisms underlying the role of dietary factors in cognitive function changes and provide evidence supporting the existence of the gut-brain axis.

Untangling Tau: Molecular Insights into Neuroinflammation, Pathophysiology, and Emerging Immunotherapies

Neuroinflammation, a core pathological feature observed in several neurodegenerative diseases, including Alzheimer's disease (AD), is rapidly gaining attention as a target in understanding the molecular underpinnings of these disorders. Glial cells, endothelial cells, peripheral immune cells, and astrocytes produce a variety of pro-inflammatory mediators that exacerbate the disease progression. Additionally, microglial cells play a complex role in AD, facilitating the clearance of pathological amyloid-beta peptide (Aβ) plaques and aggregates of the tau protein. Tau proteins, traditionally associated with microtubule stabilization, have come under intense scrutiny for their perturbed roles in neurodegenerative conditions. In this narrative review, we focus on recent advances from molecular insights that have revealed aberrant tau post-translational modifications, such as phosphorylation and acetylation, serving as pathological hallmarks. These modifications also trigger the activation of CNS-resident immune cells, such as microglia and astrocytes substantially contributing to neuroinflammation. This intricate relationship between tau pathologies and neuroinflammation fosters a cascading impact on neural pathophysiology. Furthermore, understanding the molecular mechanisms underpinning tau's influence on neuroinflammation presents a frontier for the development of innovative immunotherapies. Neurodegenerative diseases have been relatively intractable to conventional pharmacology using small molecules. We further comprehensively document the many alternative approaches using immunotherapy targeting tau pathological epitopes and structures with a wide array of antibodies. Clinical trials are discussed using these therapeutic approaches, which have both promising and disappointing outcomes. Future directions for tau immunotherapies may include combining treatments with Aβ immunotherapy, which may result in more significant clinical outcomes for neurodegenerative diseases.

Spoken discourse in episodic autobiographical and verbal short-term memory in Chinese people with dementia: the roles of global coherence and informativeness

Introduction

Memory and discourse production are closely related in healthy populations. A few studies in people with amnestic mild cognitive impairment and people with dementia (PWD) suggested similar links, although empirical evidence is insufficient to inform emerging intervention design and natural language processing research. Fine-grained discourse assessment is needed to understand their complex relationship in PWD.

Methods

Spoken samples from 104 PWD were elicited using personal narrative and sequential picture description and assessed using Main Concept Analysis and other content-based analytic methods. Discourse and memory performance data were analyzed in bivariate correlation and linear multiple regression models to determine the relationship between discourse production and episodic autobiographical memory and verbal short-term memory (vSTM).

Results

Global coherence was a significant predictor of episodic autobiographical memory, explaining over half of the variance. Both episodic autobiographical memory and vSTM were positively correlated with global coherence and informativeness, and negatively with empty speech indices.

Discussion

Coherence in personal narrative may be supported by episodic autobiographical memory and vice versa, suggesting potential mechanism of interventions targeting personhood through conversation. Indices of global coherence, informativeness, and empty speech can be used as markers of memory functions in PWD.

Comprehensive review of task-based neuroimaging studies of cognitive deficits in Alzheimer's disease using electrophysiological methods

With an aging population, cognitive decline and neurodegenerative disorders are an emerging public health crises with enormous, yet still under-recognized burdens. Alzheimer's disease (AD) is the most common type of dementia, and the number of cases is expected to dramatically rise in the upcoming decades. Substantial efforts have been placed into understanding the disease. One of the primary avenues of research is neuroimaging, and while positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) are most common, crucial recent advancements in electrophysiological methods such as magnetoencephalography (MEG) and electroencephalography (EEG) have provided novel insight into the aberrant neural dynamics at play in AD pathology. In this review, we outline task-based M/EEG studies published since 2010 using paradigms probing the cognitive domains most affected by AD, including memory, attention, and executive functioning. Furthermore, we provide important recommendations for adapting cognitive tasks for optimal use in this population and adjusting recruitment efforts to improve and expand future neuroimaging work.

Changes in Cognition and Brain Function After 26 Weeks of Progressive Resistance Training in Older Adults at Risk for Diabetes: A Pilot Randomized Controlled Trial

OBJECTIVES

Type 2 diabetes is associated with deficits in cognition and brain health. Individuals with at least 1 risk factor for diabetes (i.e. obesity, prediabetes) already experience some neurocognitive impairment and are at risk for further decline. One way to combat these deficits is through exercise, but its is unknown whether resistance exercise can improve these functions in this at-risk group.

METHODS

This study was a pilot randomized controlled trial. Participants were 60 to 80 years of age and had prediabetes (fasting capillary glucose 6.1 to 6.9 mmol/L) and/or were overweight or obese (body mass index ≥25). Participants completed resistance training or balance and stretching exercise (control) thrice weekly for 6 months. Neuropsychological tests were used to assess cognitive ability, whereas functional magnetic resonance imaging was used to examine brain activation patterns.

RESULTS

Resistance training led to improvements in task-switching, attention and conflict resolution, as well as improved patterns of brain activation that may mimic healthy older adults.

CONCLUSIONS

Resistance exercise may serve as an effective behavioural strategy to improve neurocognition in older adults at risk for type 2 diabetes. A large-scale powered trial is needed to further explore these findings.

Structural Correlates of Overt Sentence Reading in Mild Cognitive Impairment and Mild-to-Moderate Alzheimer's Disease

BACKGROUND

Overt sentence reading in mild cognitive impairment (MCI) and mild-tomoderate Alzheimer's disease (AD) has been associated with slowness of speech, characterized by a higher number of pauses, shorter speech units and slower speech rate and attributed to reduced working memory/ attention and language capacity.

OBJECTIVE

This preliminary case-control study investigates whether the temporal organization of speech is associated with the volume of brain regions involved in overt sentence reading and explores the discriminative ability of temporal speech parameters and standard volumetric MRI measures for the classification of MCI and AD.

METHODS

Individuals with MCI, mild-to-moderate AD, and healthy controls (HC) had a structural MRI scan and read aloud sentences varying in cognitive-linguistic demand (length). The association between speech features and regional brain volumes was examined by linear mixed-effect modeling. Genetic programming was used to explore the discriminative ability of temporal and MRI features.

RESULTS

Longer sentences, slower speech rate, and a higher number of pauses and shorter interpausal units were associated with reduced volumes of the reading network. Speech-based classifiers performed similarly to the MRI-based classifiers for MCI-HC (67% vs. 68%) and slightly better for AD-HC (80% vs. 64%) and AD-MCI (82% vs. 59%). Adding the speech features to the MRI features slightly improved the performance of MRI-based classification for AD-HC and MCI-HC but not HC-MCI.

CONCLUSION

The temporal organization of speech in overt sentence reading reflects underlying volume reductions. It may represent a sensitive marker for early assessment of structural changes and cognitive- linguistic deficits associated with healthy aging, MCI, and AD.

Multiview Feature Learning With Multiatlas-Based Functional Connectivity Networks for MCI Diagnosis

Functional connectivity (FC) networks built from resting-state functional magnetic resonance imaging (rs-fMRI) has shown promising results for the diagnosis of Alzheimer's disease and its prodromal stage, that is, mild cognitive impairment (MCI). FC is usually estimated as a temporal correlation of regional mean rs-fMRI signals between any pair of brain regions, and these regions are traditionally parcellated with a particular brain atlas. Most existing studies have adopted a predefined brain atlas for all subjects. However, the constructed FC networks inevitably ignore the potentially important subject-specific information, particularly, the subject-specific brain parcellation. Similar to the drawback of the "single view" (versus the "multiview" learning) in medical image-based classification, FC networks constructed based on a single atlas may not be sufficient to reveal the underlying complicated differences between normal controls and disease-affected patients due to the potential bias from that particular atlas. In this study, we propose a multiview feature learning method with multiatlas-based FC networks to improve MCI diagnosis. Specifically, a three-step transformation is implemented to generate multiple individually specified atlases from the standard automated anatomical labeling template, from which a set of atlas exemplars is selected. Multiple FC networks are constructed based on these preselected atlas exemplars, providing multiple views of the FC network-based feature representations for each subject. We then devise a multitask learning algorithm for joint feature selection from the constructed multiple FC networks. The selected features are jointly fed into a support vector machine classifier for multiatlas-based MCI diagnosis. Extensive experimental comparisons are carried out between the proposed method and other competing approaches, including the traditional single-atlas-based method. The results indicate that our method significantly improves the MCI classification, demonstrating its promise in the brain connectome-based individualized diagnosis of brain diseases.

Effect of Denoising and Deblurring 18F-Fluorodeoxyglucose Positron Emission Tomography Images on a Deep Learning Model’s Classification Performance for Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common progressive neurodegenerative disease. 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) is widely used to predict AD using a deep learning model. However, the effects of noise and blurring on 18F-FDG PET images were not considered. The performance of a classification model trained using raw, deblurred (by the fast total variation deblurring method), or denoised (by the median modified Wiener filter) 18F-FDG PET images without or with cropping around the limbic system area using a 3D deep convolutional neural network was investigated. The classification model trained using denoised whole-brain 18F-FDG PET images achieved classification performance (0.75/0.65/0.79/0.39 for sensitivity/specificity/F1-score/Matthews correlation coefficient (MCC), respectively) higher than that with raw and deblurred 18F-FDG PET images. The classification model trained using cropped raw 18F-FDG PET images achieved higher performance (0.78/0.63/0.81/0.40 for sensitivity/specificity/F1-score/MCC) than the whole-brain 18F-FDG PET images (0.72/0.32/0.71/0.10 for sensitivity/specificity/F1-score/MCC, respectively). The 18F-FDG PET image deblurring and cropping (0.89/0.67/0.88/0.57 for sensitivity/specificity/F1-score/MCC) procedures were the most helpful for improving performance. For this model, the right middle frontal, middle temporal, insula, and hippocampus areas were the most predictive of AD using the class activation map. Our findings demonstrate that 18F-FDG PET image preprocessing and cropping improves the explainability and potential clinical applicability of deep learning models.

Whole-Brain Functional Connectivity Dynamics Associated With Electroconvulsive Therapy Treatment Response

BACKGROUND

Depressive episodes (DEPs), characterized by abnormalities in cognitive functions and mood, are a leading cause of disability. Electroconvulsive therapy (ECT), which involves a brief electrical stimulation of the anesthetized brain, is one of the most effective treatments used in patients with DEP due to its rapid efficacy.

METHODS

In this work, we investigated how dynamic brain functional connectivity responds to ECT and whether the dynamic responses are associated with treatment outcomes and side effects in patients. We applied a fully automated independent component analysis-based pipeline to 110 patients with DEP (including diagnosis of unipolar depression or bipolar depression) and 60 healthy control subjects. The dynamic functional connectivity was analyzed by a combination of the sliding window approach and clustering analysis.

RESULTS

Five recurring connectivity states were identified, and patients with DEPs had fewer occurrences in one brain state (state 1) with strong positive and negative connectivity. Patients with DEP changed the occupancy of two states (states 3 and 4) after ECT, resulting in significantly different occurrences of one additional state (state 3) compared with healthy control subjects. We further found that patients with DEP had diminished global metastate dynamism, two of which recovered to normal after ECT. The changes in dynamic connectivity characteristics were associated with the changes in memory recall and Hamilton Depression Rating Scale of DEP after ECT.

CONCLUSIONS

These converging results extend current findings on subcortical-cortical dysfunction and dysrhythmia in DEP and demonstrate that ECT might cause remodeling of brain functional dynamics that enhance the neuroplasticity of the diseased brain.

Potential Roles of Glucagon-Like Peptide-1 and Its Analogues in Dementia Targeting Impaired Insulin Secretion and Neurodegeneration

Dementia is a chronic, irreversible condition marked by memory loss, cognitive decline, and mental instability. It is clinically related to various progressive neurological diseases, including Parkinson’s disease, Alzheimer’s disease, and Huntington’s. The primary cause of neurological disorders is insulin desensitization, demyelination, oxidative stress, and neuroinflammation accompanied by various aberrant proteins such as amyloid-β deposits, Lewy bodies accumulation, tau formation leading to neurofibrillary tangles. Impaired insulin signaling is directly associated with amyloid-β and α-synuclein deposition, as well as specific signaling cascades involved in neurodegenerative diseases. Insulin dysfunction may initiate various intracellular signaling cascades, including phosphoinositide 3-kinase (PI3K), c-Jun N-terminal kinases (JNK), and mitogen-activated protein kinase (MAPK). Neuronal death, inflammation, neuronal excitation, mitochondrial malfunction, and protein deposition are all influenced by insulin. Recent research has focused on GLP-1 receptor agonists as a potential therapeutic target. They increase glucose-dependent insulin secretion and are beneficial in neurodegenerative diseases by reducing oxidative stress and cytokine production. They reduce the deposition of abnormal proteins by crossing the blood-brain barrier. The purpose of this article is to discuss the role of insulin dysfunction in the pathogenesis of neurological diseases, specifically dementia. Additionally, we reviewed the therapeutic target (GLP-1) and its receptor activators as a possible treatment of dementia.

Altered dynamic functional architecture in type 2 diabetes mellitus

INTRODUCTION

Type 2 diabetes mellitus (T2DM) can accelerate cognitive decline and even dementia so that the underlying mechanism deserves further exploration. In the resting state, brain function is still changing dynamically. At present, it is still unknown whether the dynamic functional connectivity (dFC) between various brain regions is in a stable state. It is necessary to interpret brain changes from a new perspective, that is, the stability of brain architecture.

METHODS

In this study, we used a fixed dynamic time scale to explore the stability of dynamic functional architecture in T2DM, then the dynamic effective connectivity (dEC) was used to further explain how information flows through dynamically fluctuating brain architecture in T2DM.

RESULT

Two brain regions with decreased stability were found including the right supra-marginal gyrus (SMG) and the right median cingulate gyrus (MCG) in T2DM subjects. The dEC variation has increased between the left inferior frontal gyrus (IFG) and the right MCG. The direction of causal flow is from the right MCG to the left IFG.

CONCLUSION

The combination of stability and dEC can not only show the stability of dynamic functional architecture in brain but also reflect the fluidity of brain information, which is an innovative and interesting attempt in the field of neuroimaging. The changes of dynamic architecture in T2DM patients may present an innovative perspective and explanation for their cognitive decline.

Near-Lifespan Tracking of Cerebral Microvascular Degeneration in Aging to Alzheimer’s Continuum

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder affecting millions of people worldwide and is currently incurable. As the population ages, AD and related dementia are becoming the biggest epidemic in medical history: the number of people aged 65 and older with AD is projected to increase between two- and three-fold by 2050. Imaging and biomarker studies suggest that the pathophysiological processes of AD begin more than a decade before the diagnosis of dementia, opening the possibility of early, preemptive prediction. For accurate prediction, it is important although challenging to fully understand how multiple etiologies and age-related prodromal processes contribute to the onset of Alzheimer’s continuum, across a long period comparable to the lifespan. Addressing this challenge was one of the overarching transformative concepts at the 2015 AD Research Summit, “to develop new programs on systems biology and integrative physiology to gain a deeper understanding of the complex biology of the disease.”

Among other factors, cerebral microvascular degeneration (CMD) may play a key role in the onset and development of Alzheimer’s continuum, potentially prior to, along with, or independently of the beta-amyloid (Aβ) accumulation. Despite its importance for early detection and as a therapeutic target for early intervention, it is unknown whether CMD is a causal factor for AD pathogenesis or an early consequence of multifactorial conditions that lead to AD at a later stage. Here, this Viewpoint suggests that we should fill two critical knowledge gaps: (1) Temporal relationships between various CMDs and other key factors before/during/after the onset of Alzheimer’s continuum have not been established; (2) Little integrative study down to the capillary vessel level has been conducted on how individual defects in various microvascular structural and flow properties distinctly correlate with and/or contribute to neuronal degeneration. As the first step toward filling these gaps, I propose utilizing recent advances in microscopic imaging and image analysis techniques to longitudinally track a comprehensive set of CMDs over the lifespan in model animals, along with Aβ, tau, neuronal degeneration, and cognitive impairment when possible.

Planning in amnestic mild cognitive impairment: an fMRI study

INTRODUCTION

The memory impairment that is characteristic of amnestic mild cognitive impairment (aMCI) is often accompanied by difficulties in executive functioning, including planning. Though planning deficits in aMCI are well documented, their neural correlates are largely unknown, and have not yet been investigated with functional magnetic resonance imaging (fMRI).

OBJECTIVES

The aim of this study was to: (1) identify differences in brain activity and connectivity during planning in people with aMCI and cognitively healthy older adults, and (2) find whether planning-related activity and connectivity are associated with cognitive performance and symptoms of apathy.

METHODS

Twenty-five people with aMCI and 15 cognitively healthy older adults performed a visuospatial planning task (Tower of London; ToL) during fMRI. Task-related brain activation, spatial maps of task-related independent components, and seed-to-voxel functional connectivity were compared between the two groups and regressed against measures of executive functions (Trail Making Test difference score, TMT B-A; Digit Symbol Substitution Test, DSST), delayed recall (Rey Auditory Verbal Learning Test), and apathy (Apathy Evaluation Scale).

RESULTS

People with aMCI scored lower on task-switching (TMT B-A), working memory (DSST), and planning (ToL). During planning, people with aMCI had less activation in the bilateral anterior calcarine sulcus/cuneus, the bilateral temporal cortices, the left precentral gyrus, the thalamus, and the right cerebellum. Across all participants, higher planning-related activity in the supplementary motor area, the retrosplenial cortex and surrounding areas, and the right temporal cortex was related to better delayed recall. There were no between-group differences in functional connectivity, nor were there any associations between connectivity and cognition. We also did not find any associations between brain activity or connectivity and apathy.

CONCLUSION

Impaired planning in people with aMCI appears to be accompanied by lower activation in a diffuse cortico-thalamic network. Across all participants, higher planning-related activity in parieto-occipital, temporal, and frontal areas was related to better memory performance. The results point to the relevance of planning deficits for understanding aMCI and extend its clinical and neurobiological signature.

Preservation Analysis on Spatiotemporal Specific Co-expression Networks Suggests the Immunopathogenesis of Alzheimer's Disease

The occurrence and development of Alzheimer’s disease (AD) is a continuous clinical and pathophysiological process, molecular biological, and brain functional change often appear before clinical symptoms, but the detailed underlying mechanism is still unclear. The expression profiling of postmortem brain tissue from AD patients and controls provides evidence about AD etiopathogenesis. In the current study, we used published AD expression profiling data to construct spatiotemporal specific coexpression networks in AD and analyzed the network preservation features of each brain region in different disease stages to identify the most dramatically changed coexpression modules and obtained AD-related biological pathways, brain regions and circuits, cell types and key genes based on these modules. As result, we constructed 57 spatiotemporal specific networks (19 brain regions by three disease stages) in AD and observed universal expression changes in all 19 brain regions. The eight most dramatically changed coexpression modules were identified in seven brain regions. Genes in these modules are mostly involved in immune response-related pathways and non-neuron cells, and this supports the immune pathology of AD and suggests the role of blood brain barrier (BBB) injuries. Differentially expressed genes (DEGs) meta-analysis and protein–protein interaction (PPI) network analysis suggested potential key genes involved in AD development that might be therapeutic targets. In conclusion, our systematical network analysis on published AD expression profiling data suggests the immunopathogenesis of AD and identifies key brain regions and genes.

Cortical structure and the risk for Alzheimer's disease: a bidirectional Mendelian randomization study

Progressive loss of neurons in a specific brain area is one of the manifestations of Alzheimer's disease (AD). Much effort has been devoted to investigating brain atrophy and AD. However, the causal relationship between cortical structure and AD is not clear. We conducted a bidirectional two-sample Mendelian randomization analysis to investigate the causal relationship between cortical structure (surface area and thickness of the whole cortex and 34 cortical regions) and AD risk. Genetic variants used as instruments came from a large genome-wide association meta-analysis of cortical structure (33,992 participants of European ancestry) and AD (AD and AD-by-proxy, 71,880 cases, 383,378 controls). We found suggestive associations of the decreased surface area of the temporal pole (OR (95% CI): 0.95 (0.9, 0.997), p = 0.04), and decreased thickness of cuneus (OR (95% CI): 0.93 (0.89, 0.98), p = 0.006) with higher AD risk. We also found a suggestive association of vulnerability to AD with the decreased surface area of precentral (β (SE): -43.4 (21.3), p = 0.042) and isthmus cingulate (β (SE): -18.5 (7.3), p = 0.011). However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and AD met the threshold. We show suggestive evidence of an association of the atrophy of the temporal pole and cuneus with higher AD risk. In the other direction, there was a suggestive causal relationship between vulnerability to AD and the decreased surface area of the precentral and isthmus cingulate. Our findings shed light on the associations of cortical structure with the occurrence of AD.

Increased resting state functional irregularity of T2DM brains with high HbA1c: sign for impaired verbal memory function?

Glycosylated hemoglobin A1c (HbA1c) has been considered as a key contributor to impaired cognition in type 2 diabetes mellitus (T2DM) brains. However, how does it affect the brain and whether the glucose controlling can slow down the process are still unknown. In the current study, T2DM patients with high glycosylated hemoglobin level (HGL) and controls with normal glycosylated hemoglobin level (NGL) were enrolled to investigate the relationships between HbA1c, brain imaging characteristics and cognitive function. First, a series of cognitive tests including California Verbal Learning Test (CVLT) were conducted. Then, the functional irregularity based on resting state functional magnetic resonance imaging data was evaluated via a new data-driven brain entropy (BEN) mapping analysis method. We found that the HGLs exhibited significantly increased BEN in the right precentral gyrus (PreCG.R), the right middle frontal gyrus (MFG.R), the triangular and opercular parts of the right inferior frontal gyrus (IFGtriang.R and IFGoperc.R). The strengths of the functional connections of PreCG.R with the brainstem/cerebellum were decreased. Partial correlation analysis showed that HbA1c had a strong positive correlation to regional BEN and negatively correlated with some CVLT scores. Negative correlations also existed between the BEN of PreCG.R/IFGoperc.R and some CVLT scores, suggesting the correspondence between higher HbA1c, increased BEN and decreased verbal memory function. This study demonstrated the potential of BEN in exploring the functional alterations affected by HbA1c and interpreting the verbal memory function decline. It will help understanding the neurophysiological mechanism of T2DM-induced cognitive decline and taking effective prevention or treatment measures.

Neuroplastic effects of a selective serotonin reuptake inhibitor in relearning and retrieval

Animal studies using selective serotonin reuptake inhibitors (SSRIs) and learning paradigms have demonstrated that serotonin is important for flexibility in executive functions and learning. SSRIs might facilitate relearning through neuroplastic processes and thus exert their clinical effects in psychiatric diseases where cognitive functioning is affected. However, translation of these mechanisms to humans is missing. In this randomized placebo-controlled trial, we assessed functional brain activation during learning and memory retrieval in healthy volunteers performing associative learning tasks aiming to translate facilitated relearning by SSRIs.

To this extent, seventy-six participants underwent three MRI scanning sessions: (1) at baseline, (2) after three weeks of daily associative learning and subsequent retrieval (face-matching or Chinese character–noun matching) and (3) after three weeks of relearning under escitalopram (10 mg/day) or placebo. Associative learning and retrieval tasks were performed during each functional MRI (fMRI) session. Statistical modeling was done using a repeated-measures ANOVA, to test for content-by-treatment-by-time interaction effects.

During the learning task, a significant substance-by-time interaction was found in the right insula showing a greater deactivation in the SSRI cohort after 21 days of relearning compared to the learning phase. In the retrieval task, there was a significant content-by-time interaction in the left angular gyrus (AG) with an increased activation in face-matching compared to Chinese-character matching for both learning and relearning phases. A further substance-by-time interaction was found in task performance after 21 days of relearning, indicating a greater decrease of performance in the placebo group.

Our findings that escitalopram modulate insula activation demonstrates successful translation of relearning as a mechanism of SSRIs in human. Furthermore, we show that the left AG is an active component of correct memory retrieval, which coincides with previous literature. We extend the function of this region by demonstrating its activation is not only stimulus dependent but also time constrained. Finally, we were able to show that escitalopram aids in relearning, irrespective of content.

Hypertensive Disorders of Pregnancy and Cognitive Impairment: A Prospective Cohort Study

OBJECTIVE

To determine the association between hypertensive disorders of pregnancy (HDP) and cognitive impairment 15 years after pregnancy, we measured cognitive performance in 115 women with a history of HDP and in 481 women with a previous normotensive pregnancy.

METHODS

This was a nested cohort study embedded in a population-based prospective cohort from early pregnancy onwards. Cognitive function was assessed with cognitive tests 15 years after the index pregnancy (median 14.7 years, 90% range [13.9-16.1]). Cognitive performance was measured in different cognitive domains: executive function, processing speed, verbal memory, motor function, and visuospatial ability. A global cognition factor (g-factor) was derived from principal component analysis.

RESULTS

Of the women with HDP, 80 (69.6%) had gestational hypertension (GH) and 35 (30.4%) had preeclampsia. Women with HDP had a lower g-factor than women with a previous normotensive pregnancy (mean -0.22, 90% range [-2.06-1.29]). HDP was negatively associated with the 15-word learning test: immediate recall (-0.25, 95% CI [-0.44 to -0.06]) and delayed recall (-0.30, 95% CI [-0.50 to -0.10]). Women with GH perform significantly worse on their 15-word learning test than women with a previous normotensive pregnancy.

CONCLUSION

A history of HDP is independently associated with poorer working memory and verbal learning 15 years after pregnancy. This association is mainly driven by women with GH. Clinicians and women who experienced HDP should be aware of this risk.

Altered Patterns of Functional Connectivity and Causal Connectivity in Salience Subnetwork of Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment

The subjective cognitive decline (SCD) may last for decades prior to the onset of dementia and has been proposed as a risk population for development to amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD). Disruptions of functional connectivity and causal connectivity (CC) in the salience network (SN) are generally perceived as prominent hallmarks of the preclinical AD. Nevertheless, the alterations in anterior SN (aSN), and posterior SN (pSN) remain unclear. Here, we hypothesized that both the functional connectivity (FC) and CC of the SN subnetworks, comprising aSN and pSN, were distinct disruptive in the SCD and aMCI. We utilized resting-state functional magnetic resonance imaging to investigate the altered FC and CC of the SN subnetworks in 28 healthy controls, 23 SCD subjects, and 29 aMCI subjects. In terms of altered patterns of FC in SN subnetworks, aSN connected to the whole brain was significantly increased in the left orbital superior frontal gyrus, left insula lobule, right caudate lobule, and left rolandic operculum gyrus (ROG), whereas decreased FC was found in the left cerebellum superior lobule and left middle temporal gyrus when compared with the HC group. Notably, no prominent statistical differences were obtained in pSN. For altered patterns of CC in SN subnetworks, compared to the HC group, the aberrant connections in aMCI group were separately involved in the right cerebellum inferior lobule (CIL), right supplementary motor area (SMA), and left ROG, whereas the SCD group exhibited more regions of aberrant connection, comprising the right superior parietal lobule, right CIL, left inferior parietal lobule, left post-central gyrus (PG), and right angular gyrus. Especially, SCD group showed increased CC in the right CIL and left PG, whereas the aMCI group showed decreased CC in the left pre-cuneus, corpus callosum, and right SMA when compared to the SCD group. Collectively, our results suggest that analyzing the altered FC and CC observed in SN subnetworks, served as impressible neuroimaging biomarkers, may supply novel insights for designing preclinical interventions in the preclinical stages of AD.

Alzheimer's and Hyperglycemia: Role of the Insulin Signaling Pathway and GSK-3 Inhibition in Paving a Path to Dementia

In this project, we are trying to review the articles that discuss the relationship between insulin signaling and Alzheimer's disease (AD). Another focus of this project is to find the best treatment regimen that can reduce the progression of AD in patients with impaired glucose metabolism. We used Pubmed database to collect our data and used the following keywords: Alzheimer’s disease, insulin signaling pathway, type 3 diabetes, type 2 diabetes, insulin, and insulin resistance in our revision; we included free articles that were published in the last 10 years and excluded articles that were written in any language other than English. We reviewed 68 articles. Forty-nine out of 68 articles were containing materials that are relevant for this project. We found that there is a relation between AD and the insulin signaling pathway. Insulin signaling pathway impairment leads to hyperphosphorylation of Tau protein, which plays a vital role in AD pathology. The effect of insulin on cognition is bidirectional; the intranasal route of insulin showed to have a promising effect on cognition improvement. Subcutaneous and intravenous insulin can increase the risk of dementia. Further studies are encouraged to use a specific anti-diabetic medication that can reduce the progression of AD.

Identifying Morphological Patterns of Hippocampal Atrophy in Patients With Mesial Temporal Lobe Epilepsy and Alzheimer Disease

Purpose: Mesial temporal lobe epilepsy (MTLE) and Alzheimer's disease (AD) are two distinct neurological disorders associated with hippocampal atrophy. Our goal is to analyze the morphologic patterns of hippocampal atrophy to better understand the underlying pathological and clinical characteristics of the two conditions.

Methods: Twenty-five patients with AD and 20 healthy controls with matched age and gender were recruited into the AD group. Twenty-three MTLE patients and 28 healthy controls with matched age and gender were recruited into the MTLE group. All subjects were scanned on 3T-MRI scanner. Automated volumetric analysis was applied to measure and compare the hippocampal volume of the two respective groups. Vertex-based morphologic analysis was applied to characterize the morphologic patterns of hippocampal atrophy within and between groups, and a correlation analysis was performed.

Results: Volumetric analysis revealed significantly decreased hippocampal volume in both AD and MTLE patients compared to the controls. In the patients with AD, the mean total hippocampal volume was 32.70% smaller than that of healthy controls, without a significant difference between the left and the right hippocampus (p < 0.05). In patients with MTLE, a significant reduction in unilateral hippocampal volume was observed, with a mean volume reduction of 28.38% as compared with healthy controls (p < 0.05). Vertex-based morphologic analysis revealed a generalized shrinkage of the hippocampi in AD patients, especially in bilateral medial and lateral regions. In MTLE group, atrophy was seen in the ipsilateral head, ipsilateral lateral body and slightly contralateral tail of the hippocampus (FWE-corrected, p < 0.05).

Conclusions: MTLE and AD have distinctive morphologic patterns of hippocampal atrophy, which provide new insight into the radiology-pathology correlation in these diseases.

Short-Term Classification Learning Promotes Rapid Global Improvements of Information Processing in Human Brain Functional Connectome

Classification learning is a preeminent human ability within the animal kingdom but the key mechanisms of brain networks regulating learning remain mostly elusive. Recent neuroimaging advancements have depicted human brain as a complex graph machinery where brain regions are nodes and coherent activities among them represent the functional connections. While long-term motor memories have been found to alter functional connectivity in the resting human brain, a graph topological investigation of the short-time effects of learning are still not widely investigated. For instance, classification learning is known to orchestrate rapid modulation of diverse memory systems like short-term and visual working memories but how the brain functional connectome accommodates such modulations is unclear. We used publicly available repositories (openfmri.org) selecting three experiments, two focused on short-term classification learning along two consecutive runs where learning was promoted by trial-by-trial feedback errors, while a further experiment was used as supplementary control. We analyzed the functional connectivity extracted from BOLD fMRI signals, and estimated the graph information processing in the cerebral networks. The information processing capability, characterized by complex network statistics, significantly improved over runs, together with the subject classification accuracy. Instead, null-learning experiments, where feedbacks came with poor consistency, did not provoke any significant change in the functional connectivity over runs. We propose that learning induces fast modifications in the overall brain network dynamics, definitely ameliorating the short-term potential of the brain to process and integrate information, a dynamic consistently orchestrated by modulations of the functional connections among specific brain regions.

Alzheimer's Disease: The Link Between Amyloid-β and Neurovascular Dysfunction

While prevailing evidence supports that the amyloid cascade hypothesis is a key component of Alzheimer's disease (AD) pathology, many recent studies indicate that the vascular system is also a major contributor to disease progression. Vascular dysfunction and reduced cerebral blood flow (CBF) occur prior to the accumulation and aggregation of amyloid-β (Aβ) plaques and hyperphosphorylated tau tangles. Although research has predominantly focused on the cellular processes involved with Aβ-mediated neurodegeneration, effects of Aβ on CBF and neurovascular coupling are becoming more evident. This review will describe AD vascular disturbances as they relate to Aβ, including chronic cerebral hypoperfusion, hypertension, altered neurovascular coupling, and deterioration of the blood-brain barrier. In addition, we will describe recent findings about the relationship between these vascular defects and Aβ accumulation with emphasis on in vivo studies utilizing rodent AD models.

Alzheimer's disease patients activate attention networks in a short-term memory task

Network functioning during cognitive tasks is of major interest in Alzheimer's disease (AD). Cognitive functioning in AD includes variable performance in short-term memory (STM). In most studies, the verbal STM functioning in AD patients has been interpreted within the phonological loop subsystem of Baddeley's working memory model. An alternative account considers that domain-general attentional processes explain the involvement of frontoparietal networks in verbal STM beside the functioning of modality-specific subsystems. In this study, we assessed the functional integrity of the dorsal attention network (involved in task-related attention) and the ventral attention network (involved in stimulus-driven attention) by varying attentional control demands in a STM task. Thirty-five AD patients and twenty controls in the seventies performed an fMRI STM task. Variation in load (five versus two items) allowed the dorsal (DAN) and ventral attention networks (VAN) to be studied. ANOVA revealed that performance decreased with increased load in both groups. AD patients performed slightly worse than controls, but accuracy remained above 70% in all patients. Statistical analysis of fMRI brain images revealed DAN activation for high load in both groups. There was no between-group difference or common activation for low compared to high load conditions. Psychophysiological interaction showed a negative relationship between the DAN and the VAN for high versus low load conditions in patients. In conclusion, the DAN remained activated and connected to the VAN in mild AD patients who succeeded in performing an fMRI verbal STM task. DAN was necessary for the task, but not sufficient to reach normal performance. Slightly lower performance in early AD patients compared to controls might be related to maintained bottom-up attention to distractors, to decrease in executive functions, to impaired phonological processing or to reduced capacity in serial order processing.

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Patients with early AD succeeded in performing an fMRI short-term memory task.

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Dorsal attention network activation did not differ between patients and controls.

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Dorsal and ventral attention networks remained connected in high load task in AD.

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DAN was necessary for the task, but not sufficient to reach normal performance.

In-Out-Test: A New Paradigm for Sorting the Wheat from the Chaff in Prodromal Alzheimer's Disease

BACKGROUND

Assessment of hippocampal amnesia is helpful to distinguish between normal cognition and mild cognitive impairment (MCI), but not for identifying converters to dementia. Here biomarkers are useful but novel neuropsychological approaches are needed in their absence. The In-out-test assesses episodic memory using a new paradigm hypothesized to avoid reliance on executive function, which may compensate for damaged memory networks.

OBJECTIVE

To assess the validity of the In-out-test in identifying prodromal Alzheimer's disease (PAD) in a clinical setting, by comparing this to the Free and Cued Selective Reminding Test (FCSRT) and cerebrospinal fluid biomarkers.

METHODS

A cross-sectional study of 32 cognitively healthy, 32 MCI, and 30 progressive dementia subjects. All participants were given both the In-out-test and the FCSRT; 40 of them also received a lumbar puncture.

RESULTS

Internal consistency was demonstrated using Cronbach Alpha (r = 0.81) and Inter-rater reliability with Kappa (k = 0.94). Intraclass correlation (ICC) for test-retest reliability: r = 0.57 (p = 0.57). ICC between the In-out-test and FCSRT r = 0.87 (p = 0.001). ICC between the In-out-test and Aβ42 and P-tau/Aβ42 for controls: 0.73 and 0.75, respectively; P-tau for MCI: 0.77 and total sample: 0.70; Aβ42 for dementia: 0.71. All ICC measures between FCSRT and biomarkers were ≤0.264. AD diagnosis: In-out-test k = 0.71; FCSRT k = 0.49. PAD diagnosis (N = 35): In-out-test k = 0.69; FCSRT k = 0.44.

CONCLUSIONS

The In-out-test detected prodromal AD with a higher degree of accuracy than a conventional hippocampal-based memory test. These results suggest that this new paradigm could be of value in clinical settings, predicting which patients with MCI will go on to develop AD.

Current understanding of magnetic resonance imaging biomarkers and memory in Alzheimer's disease

Alzheimer's disease (AD) is caused by a cascade of changes to brain integrity. Neuroimaging biomarkers are important in diagnosis and monitoring the effects of interventions. As memory impairments are among the first symptoms of AD, the relationship between imaging findings and memory deficits is important in biomarker research. The most established magnetic resonance imaging (MRI) finding is hippocampal atrophy, which is related to memory decline and currently used as a diagnostic criterion for AD. While the medial temporal lobes are impacted early by the spread of neurofibrillary tangles, other networks and regional changes can be found quite early in the progression. Atrophy in several frontal and parietal regions, cortical thinning, and white matter alterations correlate with memory deficits in early AD. Changes in activation and connectivity have been detected by functional MRI (fMRI). Task-based fMRI studies have revealed medial temporal lobe hypoactivation, parietal hyperactivation, and frontal hyperactivation in AD during memory tasks, and activation patterns of these regions are also altered in preclinical and prodromal AD. Resting state fMRI has revealed alterations in default mode network activity related to memory in early AD. These studies are limited in part due to the historic inclusion of patients who had suspected AD but likely did not have the disorder. Modern biomarkers allow for more diagnostic certainty, allowing better understanding of neuroimaging markers in true AD, even in the preclinical stage. Larger patient cohorts, comparison of candidate imaging biomarkers to more established biomarkers, and inclusion of more detailed neuropsychological batteries to assess multiple aspects of memory are needed to better understand the memory deficit in AD and help develop new biomarkers. This article reviews MRI findings related to episodic memory impairments in AD and introduces a new study with multimodal imaging and comprehensive neuropsychiatric evaluation to overcome current limitations.

Altered functional brain networks in amnestic mild cognitive impairment: a resting-state fMRI study

Amnestic mild cognitive impairment MCI (aMCI) has a high progression to Alzheimer's disease (AD). Recently, resting-state functional MRI (RS-fMRI) has been increasingly utilized in studying the pathogenesis of aMCI, especially in resting-state networks (RSNs). In the current study, we aimed to explore abnormal RSNs related to memory deficits in aMCI patients compared to the aged-matched healthy control group using RS-fMRI techniques. Firstly, we used ALFF (amplitude of low-frequency fluctuation) method to define the regions of interest (ROIs) which exhibited significant changes in aMCI compared with the control group. Then, we divided these ROIs into different networks in line with prior studies. The aim of this study is to explore the functional connectivity between these ROIs within networks and also to investigate the connectivity between networks. Comparing aMCI to the control group, our results showed that 1) the hippocampus (HIPP) had decreased FC with the medial prefrontal cortex (mPFC) and inferior parietal lobe (IPL), and the mPFC showed increased connectivity to IPL in the default mode network; 2) the thalamus showed decreased FC with the putamen and HIPP, and the HIPP showed increased connectivity to the putamen in the limbic system; 3) the supplementary motor area had decreased FC with the middle temporal gyrus and increased FC with the superior parietal lobe in the sensorimotor network; 4) increased connectivity between the lingual gyrus and middle occipital gyrus in the visual network; and 5) the DMN has reduced inter-network connectivities with the SMN and VN. These findings indicated that functional brain networks involved in cognition such as episodic memory, sensorimotor and visual cognition in aMCI were altered, and provided a new sight in understanding the important subtype of aMCI.

The Relationship of Cognitive Performance and the Theta-Alpha Power Ratio Is Age-Dependent: An EEG Study of Short Term Memory and Reasoning during Task and Resting-State in Healthy Young and Old Adults

Objective: The Theta-Alpha ratio (TAR) is known to differ based upon age and cognitive ability, with pathological electroencephalography (EEG) patterns routinely found within neurodegenerative disorders of older adults. We hypothesized that cognitive ability would predict EEG metrics differently within healthy young and old adults, and that healthy old adults not showing age-expected EEG activity may be more likely to demonstrate cognitive deficits relative to old adults showing these expected changes. Methods: In 216 EEG blocks collected in 16 young and 20 old adults during rest (eyes open, eyes closed) and cognitive tasks (short-term memory [STM]; matrix reasoning [RM; Raven's matrices]), models assessed the contributing roles of cognitive ability, age, and task in predicting the TAR. A general linear mixed-effects regression model was used to model this relationship, including interaction effects to test whether increased cognitive ability predicted TAR differently for young and old adults at rest and during cognitive tasks. Results: The relationship between cognitive ability and the TAR across all blocks showed age-dependency, and cognitive performance at the CZ midline location predicted the TAR measure when accounting for the effect of age (p < 0.05, chi-square test of nested models). Age significantly interacted with STM performance in predicting the TAR (p < 0.05); increases in STM were associated with increased TAR in young adults, but not in old adults. RM showed similar interaction effects with aging and TAR (p < 0.10). Conclusion: EEG correlates of cognitive ability are age-dependent. Adults who did not show age-related EEG changes were more likely to exhibit cognitive deficits than those who showed age-related changes. This suggests that healthy aging should produce moderate changes in Alpha and TAR measures, and the absence of such changes signals impaired cognitive functioning.

Vulnerability of the frontal and parietal regions in hypertensive patients during working memory task

BACKGROUND

Hypertension is related with cognitive decline in the elderly. The frontal-parietal executive system plays an important role in cognitive aging and is also vulnerable to damage in elderly patients with hypertension. Examination of the brain's functional characteristics in frontal-parietal regions of hypertension is likely to be important for understanding the neural mechanisms of hypertension's effect on cognitive aging.

METHODS

We address this issue by comparing hypertension and control-performers in a functional MRI study. Twenty-eight hypertensive patients and 32 elderly controls were tested with n-back task with two load levels.

RESULTS

The hypertensive patients exhibited worse executive and memory abilities than control subjects. The patterns of brain activation changed under different working memory loads in the hypertensive patients, who exhibited reduced activation only in the precentral gyrus under low loads and reduced activation in the middle frontal gyrus, left medial superior frontal gyrus and right precuneus under high loads. Thus, more regions of diminished activation were observed in the frontal and parietal regions with increasing task difficulty. More importantly, we found that lower activation in changed frontal and parietal regions was associated with worse cognitive function in high loads.

CONCLUSION

The results demonstrate the relationship between cognitive function and frontoparietal functional activation in hypertension and their relevance to cognitive aging risk. Our findings provide a better understanding of the mechanism of cognitive decline in hypertension and highlight the importance of brain protection in hypertension.

Hybrid High-order Functional Connectivity Networks Using Resting-state Functional MRI for Mild Cognitive Impairment Diagnosis

Conventional functional connectivity (FC), referred to as low-order FC, estimates temporal correlation of the resting-state functional magnetic resonance imaging (rs-fMRI) time series between any pair of brain regions, simply ignoring the potentially high-level relationship among these brain regions. A high-order FC based on “correlation’s correlation” has emerged as a new approach for abnormality detection of brain disease. However, separate construction of the low- and high-order FC networks overlooks information exchange between the two FC levels. Such a higher-level relationship could be more important for brain diseases study. In this paper, we propose a novel framework, namely “hybrid high-order FC networks” by exploiting the higher-level dynamic interaction among brain regions for early mild cognitive impairment (eMCI) diagnosis. For each sliding window-based rs-fMRI sub-series, we construct a whole-brain associated high-order network, by estimating the correlations between the topographical information of the high-order FC sub-network from one brain region and that of the low-order FC sub-network from another brain region. With multi-kernel learning, complementary features from multiple time-varying FC networks constructed at different levels are fused for eMCI classification. Compared with other state-of-the-art methods, the proposed framework achieves superior diagnosis accuracy, and hence could be promising for understanding pathological changes of brain connectome.

Old Maids: Aging and Its Impact on Microglia Function

Microglia are highly active and vigilant housekeepers of the central nervous system that function to promote neuronal growth and activity. With advanced age, however, dysregulated inflammatory signaling and defects in phagocytosis impede their ability to perform the most essential of homeostatic functions, including immune surveillance and debris clearance. Microglial activation is one of the hallmarks of the aging brain and coincides with age-related neurodegeneration and cognitive decline. Age-associated microglial dysfunction leads to cellular senescence and can profoundly alter the response to sterile injuries and immune diseases, often resulting in maladaptive responses, chronic inflammation, and worsened outcomes after injury. Our knowledge of microglia aging and the factors that regulate age-related microglial dysfunction remain limited, as the majority of pre-clinical studies are performed in young animals, and human brain samples are difficult to obtain quickly post-mortem or in large numbers. This review outlines the impact of normal aging on microglial function, highlights the potential mechanisms underlying age-related changes in microglia, and discusses how aging can shape the recovery process following injury.

APOE Genotype Effects on Intrinsic Brain Network Connectivity in Patients with Amnestic Mild Cognitive Impairment

Whether and how the apolipoprotein E (APOE) ε4 genotype specifically modulates brain network connectivity in patients with amnestic mild cognitive impairment (aMCI) remain largely unknown. Here, we employed resting-state (‘task-free’) functional MRI and network centrality approaches to investigate local (degree centrality, DC) and global (eigenvector centrality, EC) functional integrity in the whole-brain connectome in 156 older adults, including 66 aMCI patients (27 ε4-carriers and 39 non-carriers) and 90 healthy controls (45 ε4-carriers and 45 non-carriers). We observed diagnosis-by-genotype interactions on DC in the left superior/middle frontal gyrus, right middle temporal gyrus and cerebellum, with higher values in the ε4-carriers than non-carriers in the aMCI group. We further observed diagnosis-by-genotype interactions on EC, with higher values in the right middle temporal gyrus but lower values in the medial parts of default-mode network in the ε4-carriers than non-carriers in the aMCI group. Notably, these genotype differences in DC or EC were absent in the control group. Finally, the network connectivity DC values were negatively correlated with cognitive performance in the aMCI ε4-carriers. Our findings suggest that the APOE genotype selectively modulates the functional integration of brain networks in patients with aMCI, thus providing important insight into the gene-connectome interaction in this disease.

Dissociating Normal Aging from Alzheimer's Disease: A View from Cognitive Neuroscience

Both normal aging and Alzheimer's disease (AD) are associated with changes in cognition, grey and white matter volume, white matter integrity, neural activation, functional connectivity, and neurotransmission. Obviously, all of these changes are more pronounced in AD and proceed faster providing the basis for an AD diagnosis. Since these differences are quantitative, however, it was hypothesized that AD might simply reflect an accelerated aging process. The present article highlights the different neurocognitive changes associated with normal aging and AD and shows that, next to quantitative differences, there are multiple qualitative differences as well. These differences comprise different neurocognitive dissociations as different cognitive deficit profiles, different weights of grey and white matter atrophy, and different gradients of structural decline. These qualitative differences clearly indicate that AD cannot be simply described as accelerated aging process but on the contrary represents a solid entity.

The nature of working memory gating in Parkinson's disease: A multi-domain signal detection examination

Distractions are ubiquitous; our brains are inundated with task-irrelevant information. Thus, to remember successfully, one must actively maintain relevant information and prevent distraction from entering working memory. Researchers suggest the basal ganglia-prefrontal pathways are vital to this process by acting as a working memory gate. Using Parkinson's disease as a model of frontostriatal functioning and with signal detection analyses, the present study aims to better characterize the contribution of frontostriatal pathways of this gating process and to determine how it operates across multiple domains. To achieve this, Parkinson's disease patients and healthy controls completed verbal and spatial working memory tasks consisting of three conditions: low-load without distraction; low-load with distraction; and high-load without distraction. Patients were tested both ON and OFF dopaminergic medication, allowing for assessment of the contribution of dorsal and ventral frontostriatal pathways. The results demonstrate that when medication is withheld, Parkinson's patients have a response bias to answer "NO" across all conditions and domains, supporting our hypothesis that the basal ganglia-prefrontal pathways allow or prevent updates of working memory. Contrastingly, medication status affects d' in the distraction condition but not in the high- or low-load conditions. We attribute this to stimulus valuation processes that were impaired by dopaminergic medication overdosing the ventral pathway. These findings are both consistent with the hypothesis that the working memory gate filters spatial and verbal information before it enters into the working memory system, adding support for the gate being a domain-general mechanism of the central executive.

Linking Resting-State Networks in the Prefrontal Cortex to Executive Function: A Functional Near Infrared Spectroscopy Study

Executive function (EF) plays vital roles in our everyday adaptation to the ever-changing environment. However, limited existing studies have linked EF to the resting-state brain activity. The functional connectivity in the resting state between the sub-regions of the brain can reveal the intrinsic neural mechanisms involved in cognitive processing of EF without disturbance from external stimuli. The present study investigated the relations between the behavioral executive function (EF) scores and the resting-state functional network topological properties in the Prefrontal Cortex (PFC). We constructed complex brain functional networks in the PFC from 90 healthy young adults using functional near infrared spectroscopy (fNIRS). We calculated the correlations between the typical network topological properties (regional topological properties and global topological properties) and the scores of both the Total EF and components of EF measured by computer-based Cambridge Neuropsychological Test Automated Battery (CANTAB). We found that the Total EF scores were positively correlated with regional properties in the right dorsal superior frontal gyrus (SFG), whereas the opposite pattern was found in the right triangular inferior frontal gyrus (IFG). Different EF components were related to different regional properties in various PFC areas, such as planning in the right middle frontal gyrus (MFG), working memory mainly in the right MFG and triangular IFG, short-term memory in the left dorsal SFG, and task switch in the right MFG. In contrast, there were no significant findings for global topological properties. Our findings suggested that the PFC plays an important role in individuals' behavioral performance in the executive function tasks. Further, the resting-state functional network can reveal the intrinsic neural mechanisms involved in behavioral EF abilities.

Understanding the cognitive underpinnings of functional impairments in early dementia: a review

OBJECTIVES

Early dementia is marked by cognitive and functional impairments, and although studies indicate an association between these, detailed analyses exploring this relationship are rare. It is crucial to understand how specific cognitive deficits underlie functional deficits to develop successful cognitive interventions. This paper reviews the evidence of impairment in everyday functioning and in working, long-term and prospective memory in early dementia. Findings are evaluated with respect to the relationship between cognitive and functional impairments.

METHODS

From the literature searches, 17 studies on everyday functioning and 40 studies on memory were obtained. Studies were only included if patients had an official diagnosis and were in the early stages of dementia.

RESULTS

Complex instrumental activities of daily living were subject to greater impairment than basic activities of daily living. In particular, early dementia patients struggle with finance tasks; a deficit linked to impaired working memory. Regarding cognition, long-term memory is the earliest form of memory to decline as is well recognised. Evidence also indicates deficits in working and prospective memory, with inconsistent evidence about impairments of the former. A major limitation of the literature is a lack of studies assessing individual everyday activities and the associated error patterns that might occur.

CONCLUSION

This review critically assesses the status of translational research for everyday activities in early dementia, an area with critical implications for cognitive-based rehabilitation. Further research is required into the detailed assessment of individual everyday activity and specific memory deficits, in order to effectively map cognitive functions onto functional performance.

Functional neuroanatomy of spatial sound processing in Alzheimer's disease

Deficits of auditory scene analysis accompany Alzheimer's disease (AD). However, the functional neuroanatomy of spatial sound processing has not been defined in AD. We addressed this using a “sparse” fMRI virtual auditory spatial paradigm in 14 patients with typical AD in relation to 16 healthy age-matched individuals. Sound stimulus sequences discretely varied perceived spatial location and pitch of the sound source in a factorial design. AD was associated with loss of differentiated cortical profiles of auditory location and pitch processing at the prescribed threshold, and significant group differences were identified for processing auditory spatial variation in posterior cingulate cortex (controls > AD) and the interaction of pitch and spatial variation in posterior insula (AD > controls). These findings build on emerging evidence for altered brain mechanisms of auditory scene analysis and suggest complex dysfunction of network hubs governing the interface of internal milieu and external environment in AD. Auditory spatial processing may be a sensitive probe of this interface and contribute to characterization of brain network failure in AD and other neurodegenerative syndromes.

A Rotational Cylindrical fMRI Phantom for Image Quality Control

Purpose

A novel phantom for image quality testing for functional magnetic resonance imaging (fMRI) scans is described.

Methods

The cylindrical, rotatable, ~4.5L phantom, with eight wedge-shaped compartments, is used to simulate rest and activated states. The compartments contain NiCl₂ doped agar gel with alternating concentrations of agar (1.4%, 1.6%) to produce T₁ and T₂ values approximating brain grey matter. The Jacard index was used to compare the image distortions for echo planar imaging (EPI) and gradient recalled echo (GRE) scans. Contrast to noise ratio (_CNR) was compared across the imaging volume for GRE and EPI.

Results

The mean T₂ for the two agar concentrations were found to be 106.5±4.8, 94.5±4.7 ms, and T₁ of 1500±40 and 1485±30 ms, respectively. The Jacard index for GRE was generally found to be higher than for EPI (0.95 versus 0.8). The CNR varied from 20 to 50 across the slices and echo times used for EPI scans, and from 20 to 40 across the slices for the GRE scans. The phantom provided a reproducible CNR over 25 days.

Conclusions

The phantom provides a quantifiable signal change over a head-size imaging volume with EPI and GRE sequences, which was used for image quality assessment.

State-based functional connectivity changes associate with cognitive decline in amnestic mild cognitive impairment subjects

Episodic memory (EM) dysfunction is a central characteristic of amnestic mild cognitive impairment (aMCI) subjects, and has a high risk of converting to Alzheimer's disease (AD). However, it is unknown how the EM network is modulated when a situation is switched. Twenty-six aMCI and twenty-two cognitively normal (CN) subjects were enrolled in this study. All of the subjects completed multi-dimensional neuropsychological tests and underwent functional magnetic resonance imaging scans during a resting-state and an episodic memory retrieval task state. The EM network was constructed using a seed-based functional connectivity (FC) approach. AMCI subjects showed poorer cognitive performances in the episodic memory and executive function. We demonstrated that connectivity of the left posterior parahippocampal gyrus (LpPHG) connected to the left ventral medial prefrontal cortex and the right postcentral gyrus (RPCG) was significantly decreased in aMCI subjects compared to CN subjects. Meanwhile, there was increased connectivity of the LpPHG to the right dorsal medial prefrontal cortex (RDMPFC), RPCG, left inferior parietal cortex, and bilateral superior parietal lobe in all of the subjects that changed from a resting-state to a task-state. Interestingly, the changed LpPHG-RDMPFC connectivity strength was significantly correlated with EM scores and executive function in the aMCI subjects. As a result, general brain regions are functionally organized and integrated into the EM network, and this strongly suggests that more cognitive resources are mobilized to meet the challenge of cognitive demand in the task state. These findings extend our understanding of the underlying mechanisms of EM deficits in aMCI subjects.

Manipulating motor performance and memory through real-time fMRI neurofeedback

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Neurofeedback training of motor cortex shortens reaction times.

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Self-regulation of parahippocampal cortex activity interferes with memory encoding.

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Differential neurofeedback reveals double dissociation between neurofeedback target areas.

Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects.

Immediate rather than delayed memory impairment in older adults with latent toxoplasmosis

The neurotropic parasite Toxoplasma gondii infects one third of the world population, but its effect on memory remains ambiguous. To examine a potential relationship of the infection with immediate and delayed memory, a population-based study was conducted in 4485 participants of the Third National Health and Nutrition Examination Survey aged 60years and older. Serum anti-Toxoplasma IgG antibodies were measured by enzyme immune assay and verbal memory was assessed using the Mini-Mental State Examination and the East Boston Memory Test. The prevalence of latent toxoplasmosis was 41%; in one way analysis of variance, anti-Toxoplasma IgG antibody levels significantly differed across tertiles for immediate (P=0.006) but not delayed memory scores (P=0.22). In multinomial logistic regression adjusting for covariates, Toxoplasma seropositivity was associated with lower immediate memory performance (OR: 0.65, 95% CI: 0.44, 0.97 for medium tertile and OR: 0.61, 95% CI: 0.37, 0.98 for highest tertile in reference to the lowest tertile), especially in non-Hispanic Whites (OR: 0.56, 95% CI: 0.36, 0.88 for medium tertile and OR: 0.51, 95% CI: 0.30, 0.87 for highest tertile in reference to the lowest tertile). However, no relationship with delayed memory was observed. In conclusion, latent toxoplasmosis is widespread in older adults and may primarily affect immediate rather than delayed memory, particularly in White Americans.

Changes in thalamic connectivity in the early and late stages of amnestic mild cognitive impairment: a resting-state functional magnetic resonance study from ADNI

We used resting-state functional magnetic resonance imaging (fMRI) to investigate changes in the thalamus functional connectivity in early and late stages of amnestic mild cognitive impairment. Data of 25 late stages of amnestic mild cognitive impairment (LMCI) patients, 30 early stages of amnestic mild cognitive impairment (EMCI) patients and 30 well-matched healthy controls (HC) were analyzed from the Alzheimer’s disease Neuroimaging Initiative (ADNI). We focused on the correlation between low frequency fMRI signal fluctuations in the thalamus and those in all other brain regions. Compared to healthy controls, we found functional connectivity between the left/right thalamus and a set of brain areas was decreased in LMCI and/or EMCI including right fusiform gyrus (FG), left and right superior temporal gyrus, left medial frontal gyrus extending into supplementary motor area, right insula, left middle temporal gyrus (MTG) extending into middle occipital gyrus (MOG). We also observed increased functional connectivity between the left/right thalamus and several regions in LMCI and/or EMCI including left FG, right MOG, left and right precuneus, right MTG and left inferior temporal gyrus. In the direct comparison between the LMCI and EMCI groups, we obtained several brain regions showed thalamus-seeded functional connectivity differences such as the precentral gyrus, hippocampus, FG and MTG. Briefly, these brain regions mentioned above were mainly located in the thalamo-related networks including thalamo-hippocampus, thalamo-temporal, thalamo-visual, and thalamo-default mode network. The decreased functional connectivity of the thalamus might suggest reduced functional integrity of thalamo-related networks and increased functional connectivity indicated that aMCI patients could use additional brain resources to compensate for the loss of cognitive function. Our study provided a new sight to understand the two important states of aMCI and revealed resting-state fMRI is an appropriate method for exploring pathophysiological changes in aMCI.

Altered brain activation patterns under different working memory loads in patients with type 2 diabetes

OBJECTIVE

Type 2 diabetes mellitus (T2DM) has important effects on cognition and the risk for Alzheimer disease (AD). Working memory (WM) is a susceptible cognitive domain of mild cognitive impairment and AD. Thus, the identification of brain activation patterns under different WM loads can potentially enhance our understanding of the mechanisms underlying cognitive dysfunction in T2DM.

RESEARCH DESIGN AND METHODS

The current study assessed the effects of T2DM on cognitive performance and explored the related neuronal damage through a visual n-back task and functional magnetic resonance imaging.

RESULTS

We found that patients with T2DM exhibited worse executive and memory abilities than control subjects. Furthermore, the patterns of brain activation changed under different WM loads in the T2DM patients, who exhibited reduced activation in the left inferior frontal gyrus under low loads and reduced activation in the left middle frontal gyrus and superior frontal gyrus (SFG) under high loads. Thus, more regions of diminished activation were seen in the frontal cortex with increasing task difficulty. Furthermore, we found that lower SFG activation was associated with worse cognitive function.

CONCLUSIONS

The findings demonstrate deficient WM in patients with T2DM and the relation between cognitive function and degree of neuronal activity and their relevance to AD risk. Further longitudinal studies are needed to replicate these results and to evaluate the clinical value of brain imaging methods in the prediction of disease progress in these patients.