FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer's disease

Measuring transient functional connectivity is an important challenge in Electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of brain activity offered by high temporal resolution is confounded by the inherent noise of the medium and the spurious nature of correlations computed over short temporal windows. We propose a novel methodology to overcome these problems called Filter Average Short-Term (FAST) functional connectivity. First, long-term, stable, functional connectivity is averaged across an entire study cohort for a given pair of Visual Short Term Memory (VSTM) tasks. The resulting average connectivity matrix, containing information on the strongest general connections for the tasks, is used as a filter to analyse the transient high temporal resolution functional connectivity of individual subjects. In simulations, we show that this method accurately discriminates differences in noisy Event-Related Potentials (ERPs) between two conditions where standard connectivity and other comparable methods fail. We then apply this to analyse activity related to visual short-term memory binding deficits in two cohorts of familial and sporadic Alzheimer's disease. Reproducible significant differences were found in the binding task with no significant difference in the shape task in the P300 ERP range. This allows new sensitive measurements of transient functional connectivity, which can be implemented to obtain results of clinical significance.

Exploring the Association between Amyloid-β and Memory Markers for Alzheimer's Disease in Cognitively Unimpaired Older Adults

BACKGROUND

Memory tests vary in their sensitivity for detection of pre-symptomatic Alzheimer's disease (AD). The Visual Short-Term Memory Binding Test (VSTMBT) identifies AD-related performance deficits in older adults who are otherwise cognitively unimpaired.

OBJECTIVE

We investigated the association of this psychometric measure with brain amyloidosis and atrophy.

DESIGN

Cross-sectional mixed and correlational.

SETTING

Cognitive Reserve Study from Columbia University.

PARTICIPANTS

a sample of 39 cognitively unimpaired older adults (Age: M=65.3, SD=3.07) was obtained from the above study.

MEASUREMENTS

Extensive neuropsychological and neuroimaging (MRI and amyloid-β PET) assessments were carried out.

RESULTS

Performance on the VSTMBT allowed us to split the sample into Low Binding Cost (LBC, N=21) and High Binding Cost (HBC, N=18). Groups were matched according to age [p=0.702], years of education [0.071], and sex [p=0.291]. HBC's performance was comparable to that seen in symptomatic AD. Groups only differed in their amyloid-β deposition on PET in regions of the right ventral stream linked to visual cognition and affected early in AD pathogenesis (lateral-occipital cortex, p = 0.008; fusiform gyrus, p = 0.017; and entorhinal cortex, p = 0.046). Other regions known to be linked to low-level visual integration function also revealed increased amyloid-β deposition in HBC.

CONCLUSIONS

VSTMB deficits are associated with neuropathogenesis (i.e., amyloid-β deposition) in the earliest affected regions in pre-symptomatic AD. The VSTMB test holds potential for the identification of cognitively unimpaired older adults with very early AD pathogenesis and may thus be a useful tool for early intervention trials or other forms of clinical research.

The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds

The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21-89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research.

Age-related hearing loss associated with differences in the neural correlates of feature binding in visual working memory

The underlying neural mechanisms underpinning the association between age-related hearing loss (ARHL) and dementia remain unclear. A limitation has been the lack of functional neuroimaging studies in ARHL cohorts to help clarify this relationship. In the present study, we investigated the neural correlates of feature binding in visual working memory with ARHL (controls = 14, mild HL = 21, and moderate or greater HL = 23). Participants completed a visual change detection task assessing feature binding while their neural activity was synchronously recorded via high-density electroencephalography. There was no difference in accuracy scores for ARHL groups compared to controls. There was increased electrophysiological activity in those with ARHL, particularly in components indexing the earlier stages of visual cognitive processing. This activity was more pronounced with more severe ARHL and was associated with maintained feature binding. Source space (sLORETA) analyses indicated greater activity in networks modulated by frontoparietal and temporal regions. Our results demonstrate there may be increased involvement of neurocognitive control networks to maintain lower-order neurocognitive processing disrupted by ARHL.

The "when" matters: Evidence from memory markers in the clinical continuum of Alzheimer's disease

OBJECTIVE

Cognitive assessment able to detect impairments in the early neuropathological stages of Alzheimer's disease (AD) is urgently needed. The visual short-term memory binding task (VSTMBT) and the Free and Cued Selective Reminding Test (FCSRT) have been recommended by the neurodegenerative disease working group as promising tests to aid in the early detection of AD. In this study, we investigated their complementary value across the clinical stages of the AD continuum.

METHOD

One hundred and seventeen older adults with subjective cognitive complaint (SCC), 79 with mild cognitive impairment (MCI), 31 patients with AD dementia (ADD), and 37 cognitively unimpaired (CU) subjects, underwent assessment with the VSTMBT and the picture version of the Spanish FCSRT.

RESULTS

After controlling for multiple comparisons, significant differences were found across groups. The VSTMBT was the only test that "marginally" differentiated between CU and SCC (d = 0.47, p = .052). Moreover, whereas the FCSRT showed a gradient (CU = SCC) > MCI > ADD, the VSTMBT gradient was CU > SCC > (MCI = ADD) suggesting that conjunctive binding deficits assessed by the latter may be sensitive to the very early stages of the disease.

CONCLUSIONS

Our results suggest that the VSTMBT and the FCSRT are sensitive to the clinical continuum of AD. Whereas the former detects changes in the early prodromal stages, the latter is more sensitive to the advanced prodromal stages of AD. These novel tests can aid in the early detection, monitor disease progression and response to treatment, and thus support drug development programs. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Short-term memory conjunctive binding in Alzheimer's disease: A systematic review and meta-analysis

OBJECTIVE

Short-term memory (STM) binding tests assess the ability to temporarily hold conjunctions between surface features, such as objects and their colors (i.e., feature binding condition), relative to the ability to hold the individual features (i.e., single feature condition). Impairments in performance of these tests have been considered cognitive markers of Alzheimer's disease (AD). The objective of the present study was to conduct a meta-analysis of results from STM binding tests used in the assessment of samples mapped along the AD clinical continuum.

METHOD

We searched PubMed, Scopus, and Web of Science for articles that assessed patients with AD (from preclinical to dementia) using the STM binding tests and compared their results with those of controls. From each relevant article, we extracted the number of participants, the mean and standard deviations from single feature and of feature binding conditions. Results across studies were combined using standardized mean differences (effect sizes) to produce overall estimates of effect.

RESULTS

The feature binding condition of the STM binding showed large effects in all stages of AD. However, small sample sizes across studies, the presence of moderate to high heterogeneity and cross-sectional, case-controls designs decreased our confidence in the current evidence.

CONCLUSIONS

To be considered as a cognitive marker for AD, properly powered longitudinal designs and studies that clearly relate conjunctive memory tests with biomarkers (amyloid and tau) are still needed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The limitations and challenges in the assessment of executive dysfunction associated with real-world functioning: The opportunity of serious games

Nowadays, there is a broad range of methods for detecting and evaluating executive dysfunction ranging from clinical interview to neuropsychological evaluation. Nevertheless, a critical issue of these assessments is the lack of correspondence of the neuropsychological test's results with real-world functioning. This paper proposes serious games as a new framework to improve the neuropsychological assessment of real-world functioning. We briefly discuss the contribution and limitations of current methods of evaluation of executive dysfunction (paper-and-pencil tests, naturalistic observation methods, and Information and Communications Technologies) to inform on daily life functioning. Then, we analyze what are the limitations of these methods to predict real-world performance: (1) A lack of appropriate instruments to investigate the complexity of real-world functioning, (2) the vast majority of neuropsychological tests assess well-structured tasks, and (3) measurement of behaviors are based on simplistic data collection and statistical analysis. This work shows how serious games offer an opportunity to develop more efficient tools to detect executive dysfunction in everyday life contexts. Serious games provide meaningful narrative stories and virtual or real environments that immerse the user in natural and social environments with social interactions. In those highly interactive game environments, the player needs to adapt his/her behavioral performance to novel and ill-structured tasks which are suited for collecting user interaction evidence. Serious games offer a novel opportunity to develop better tools to improve diagnosis of the executive dysfunction in everyday life contexts. However, more research is still needed to implement serious games in everyday clinical practice.

Biomarkers for dementia in Latin American countries: Gaps and opportunities

Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we reported a survey to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The results show that neuroimaging is the most used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, the region holds a great potential to advance dementia biomarkers research. Considering the unique contributions that LAC could make to this growing field, we highlight the urgent need to expand biomarker research. These insights allowed us to propose an action plan that addresses the recommendations for a biomarker framework recently proposed by regional experts.

Memory-driven eye movements prospectively predict dementia in people at risk of Alzheimer's disease

Introduction

Oculomotor behaviors linked to cognitive performance revealed neurocognitive features of Alzheimer's disease (AD) that can enhance the accuracy of its assessment and diagnosis.

Methods

A sample of 107 participants (i.e., 65 mild cognitive impairment [MCI] and 42 controls) were recruited and followed up for 40 months. At baseline, they underwent assessment with the ViewMind digital biomarker, which draws cognitive-related patterns of eye movement while people perform the visual short-term memory binding task.

Results

Baseline data predicted that 36 patients with MCI would progress to the AD clinical syndrome (ADS Progressing). The remaining 29 MCI patients were predicted to remain as MCI or progress to other forms of dementia. After 40 months of follow-up, 94% of ADS Progressing patients had received a diagnosis of dementia, whereas none of the non-ADS Progressing had.

Discussion

The analysis of eye movement behavior combined with cognitive markers for AD can effectively predict progression to ADS among patients with MCI.

Memory markers in the continuum of the Alzheimer's clinical syndrome

BACKGROUND

The individual and complementary value of the Visual Short-Term Memory Binding Test (VSTMBT) and the Free and Cued Selective Reminding Test (FCSRT) as markers to trace the AD continuum was investigated. It was hypothesised that the VSTMBT would be an early indicator while the FCSRT would inform on imminent progression.

METHODS

Healthy older adults (n=70) and patients with mild cognitive impairment (MCI) (n=80) were recruited and followed up between 2012 and 2017. Participants with at least two assessment points entered the study. Using baseline and follow-up assessments four groups were defined: Older adults who were healthy (HOA), with very mild cognitive but not functional impairment (eMCI), and with MCI who did and did not convert to dementia (MCI converters and non-converters).

RESULTS

Only the VSTMBT predicted group membership in the very early stages (HOA vs eMCI). As the disease progressed, the FCSRT became a strong predictor excluding the VSTMB from the models. Their complementary value was high during the mid-prodromal stages and decreased in stages closer to dementia.

DISCUSSION

The study supports the notion that neuropsychological assessment for AD needs to abandon the notion of one-size-fits-all. A memory toolkit for AD needs to consider tools that are early indicators and tools that suggest imminent progression. The VSTMBT and the FSCRT are such tools.

Multi-feature computational framework for combined signatures of dementia in underrepresented settings

OBJECTIVE

The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.

APPROACH

We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, MRI, and EEG/fMRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).

MAIN RESULTS

The multimodal model yielded high AUC classification values (bvFTD patients vs. HCs: 0.93 (±0.01); AD patients vs. HCs: 0.95 (±0.01); bvFTD vs. AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens). Results proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.

SIGNIFICANCE

The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries.

Robust Assessment of EEG Connectivity Patterns in Mild Cognitive Impairment and Alzheimer's Disease

The prevalence of dementia, including Alzheimer's disease (AD), is on the rise globally with screening and intervention of particular importance and benefit to those with limited access to healthcare. Electroencephalogram (EEG) is an inexpensive, scalable, and portable brain imaging technology that could deliver AD screening to those without local tertiary healthcare infrastructure. We study EEG recordings of subjects with sporadic mild cognitive impairment (MCI) and prodromal familial, early-onset, AD for the same working memory tasks using high- and low-density EEG, respectively. A challenge in detecting electrophysiological changes from EEG recordings is that noise and volume conduction effects are common and disruptive. It is known that the imaginary part of coherency (iCOH) can generate functional connectivity networks that mitigate against volume conduction, while also erasing true instantaneous activity (zero or π-phase). We aim to expose topological differences in these iCOH connectivity networks using a global network measure, eigenvector alignment (EA), shown to be robust to network alterations that emulate the erasure of connectivities by iCOH. Alignments assessed by EA capture the relationship between a pair of EEG channels from the similarity of their connectivity patterns. Significant alignments-from comparison with random null models-are seen to be consistent across frequency ranges (delta, theta, alpha, and beta) for the working memory tasks, where consistency of iCOH connectivities is also noted. For high-density EEG recordings, stark differences in the control and sporadic MCI results are observed with the control group demonstrating far more consistent alignments. Differences between the control and pre-dementia groupings are detected for significant correlation and iCOH connectivities, but only EA suggests a notable difference in network topology when comparing between subjects with sporadic MCI and prodromal familial AD. The consistency of alignments, across frequency ranges, provides a measure of confidence in EA's detection of topological structure, an important aspect that marks this approach as a promising direction for developing a reliable test for early onset AD.

A novel deep learning approach using AlexNet for the classification of electroencephalograms in Alzheimer's Disease and Mild Cognitive Impairment

Alzheimer's Disease (AD) is the most common form of dementia. Mild Cognitive Impairment (MCI) is the term given to the stage describing prodromal AD and represents a 'risk factor' in early-stage AD diagnosis from normal cognitive decline due to ageing. The electroencephalogram (EEG) has been studied extensively for AD characterization, but reliable early-stage diagnosis continues to present a challenge. The aim of this study was to introduce a novel way of classifying between AD patients, MCI subjects, and age-matched healthy control (HC) subjects using EEG-derived feature images and deep learning techniques. The EEG recordings of 141 age-matched subjects (52 AD, 37 MCI, 52 HC) were converted into 2D greyscale images representing the Pearson correlation coefficients and the distance Lempel-Ziv Complexity (dLZC) between the 21 EEG channels. Each feature type was computed from EEG epochs of 1s, 2s, 5s and 10s segmented from the original recording. The CNN architecture AlexNet was modified and employed for this three-way classification task and a 70/30 split was used for training and validation with each of the different epoch lengths and EEG-derived images. Whilst a maximum classification accuracy of 73.49% was obtained using dLZC-derived images from 10s epochs as input to the model, the classification accuracy reached 98.13% using the images obtained from Pearson correlation coefficients and 5s epochs. Clinical Relevance- The preliminary findings from this study show that deep learning applied to the analysis of the EEG can classify subjects with accuracies close to 100.

Abnormal Functional Hierarchies of EEG Networks in Familial and Sporadic Prodromal Alzheimer's Disease During Visual Short-Term Memory Binding

Alzheimer's Disease (AD) shows both complex alterations of functional dependencies between brain regions and a decreased ability to perform Visual Short-Term Memory Binding (VSTMB) tasks. Recent advances in network neuroscience toward understanding the complexity of hierarchical brain function here enables us to establish a link between these two phenomena. Here, we study data on two types of dementia at Mild Cognitive Impairment (MCI) stage-familial AD patients (E280A mutation of the presenilin-1 gene) and elderly MCI patients at high risk of sporadic AD, both with age-matched controls. We analyzed Electroencephalogram (EEG) signals recorded during the performance of Visual Short-Term Memory (VSTM) tasks by these participants. Functional connectivity was computed using the phase-lag index in Alpha and Beta; and network analysis was employed using network indices of hierarchical spread (degree variance) and complexity. Hierarchical characteristics of EEG functional connectivity networks revealed abnormal patterns in familial MCI VSTMB function and sporadic MCI VSTMB function. The middle-aged familial MCI binding network displayed a larger degree variance in lower Beta compared to healthy controls (p = 0.0051, Cohen's d = 1.0124), while the elderly sporadic MCI binding network displayed greater hierarchical complexity in Alpha (p = 0.0140, Cohen's d = 1.1627). Characteristics in healthy aging were not shown to differ. These results indicate that activity in MCI exhibits cross-frequency network reorganization characterized by increased heterogeneity of node roles in the functional hierarchy. Aging itself is not found to cause VSTM functional hierarchy differences.

Barriers to Effective Memory Assessments for Alzheimer's Disease

Recently, Alzheimer's Disease International (ADI) stressed that around 75% of people living with dementia globally are still not receiving a diagnosis. In this commentary, I reflect on how efforts towards better cognitive assessments, particularly of memory, can be aligned and harmonized to contribute to such needs. I highlight some barriers that ongoing collaborations and trials are facing and their potential drivers. I suggest some strategies that can help overcome them and in so doing, integrate research agendas. We need to ignite the debate towards strategies that can help level the playfield to tackle Alzheimer's disease with true global solutions.

Addressing dementia challenges through international networks: Evidence from the Latin American and Caribbean Consortium on Dementia (LAC-CD)

BACKGROUND

LAC-CD has recently reported that challenges faced by LAC countries are very similar to those experienced by HIC, and that regional networks will be needed to bridge gaps. ReDLat is a US-LAC multi-partner consortium aimed at expanding dementia research in LAC. The UK-Latin America Brain Connectivity Research Network (UL-BCRN) focuses on developing new affordable EEG-based biomarkers for dementia. The Language and Brain Health Network (LBHN) integrate international multidisciplinary efforts to reveal linguistic markers of neurodegenerative diseases.

METHODS

ReDLat is collecting genomic, neuroimaging, clinical, cognitive, and socioeconomic data from a first-in-class cohort anchored in six LAC (Argentina, Chile, Colombia, Brazil, Mexico, and Peru) and will compare these to US data (> 4200 participants, including 2100 controls, 1050 AD patients, and 1050 FTD patients). The 5-year project will develop innovative, harmonized, and cross-nation approaches on two of the most prevalent neurodegenerative diseases, Alzheimer's disease (AD) and Frontotemporal Dementia (FTD). The UL-BCRN currently links seven EEG labs from Colombia, Argentina, Chile, Brazil and the UK. The network's vision is to forge strong relationships between labs through which new methodologies, EEG plus multidimensional datasets, and experience will be developed and shared. The LBHN will analyze speech samples from massive AD, FTD, and control cohorts across LAC, Spain, and the US. This effort aims to identify low-cost disease-specific markers in diverse Latino and English-speaking patients.

RESULTS

ReDLat will aims to reveal unique risk factors for AD and FTD in LAC compared to US populations. Data collection strategies have been adapted to face the challenges brought by the COVID-19 pandemic. The UL-BCRN has now standardised recording protocols across LAC and UK labs and is collecting data from longitudinal cohorts of patients at risk of dementia relying on novel culture-free cognitive paradigms. Preliminary LBHN data shows that, automated speech analyses can identify Latinos with AD and FTD, with good generalization across socio-biological profiles, dialects, and languages.

CONCLUSION

By broadening our understanding of dementia phenotypes, risk factors, and affordable diagnostic approaches in LAC, adding new evidence on variability across HIC and LMIC, the above networks will contribute unique knowledge that will help enhance future global dementia strategies.

Factors influencing acceptance of technology across age: Amid the COVID‐19 pandemic

Background

Digital technologies are creating unprecedented opportunities to improve and increase support to older people with cognitive and mental health problems, and to their family and carers. However, barriers that preclude the implementation of technology driven programs for the assessment and intervention of adults at risk of cognitive decline need to be better understood. This study investigated these outstanding issues, as well as considering the impact that the COVID‐19 Pandemic has had on such barriers.

Methods

A sample of 105 participants completed an online survey. Their ages ranged from 18 to 92 years. Of these, 72% were female, 83% had higher education and beyond, 42% were working, 42% were retired, and 14% were unemployed. The questionnaires assessed IT experience alongside awareness, attitudes, and stigmas regarding the use of technologies, particularly those used to support cognitive and mental health. Questionnaires also explored the impact of the COVID‐19 pandemic on these technology‐related factors. We compared these across groups of young (n=45), middle age (n=12) and older adults (n=48).

Results

Relative to younger participants, older participants were less aware of, and held stronger stigmas against healthcare technologies, even though they reported more IT experience. IT awareness was associated to more positive (r=0.619, p<0.001) and less negative IT Attitudes (r=‐0.271, p=0.015), more acceptability (r=‐0.374, p=0.001) and receptiveness towards technologies (r=‐0.610, p<0.001). Male participants appeared to be more aware of such technologies than female participants. However, relative to men, women had increased the number of ways and frequency with which they used technologies since the COVID‐19 pandemic started, and older people in general felt more inclined to endorse the need to learn more about healthcare technologies.

Conclusions

Having more accumulated IT experience throughout our lives may not necessarily lead to better acceptance of healthcare technologies. More awareness about such specific technologies will help overcome stigmas, and challenging environments such as those imposed by the COVID‐19 pandemic may lead to positive changes in perception and acceptance of such technologies. These are necessary steps towards the personalisation of healthcare technologies to support vulnerable adults at risk of dementia.

Oculomotor Behaviors and Integrative Memory Functions in the Alzheimer's Clinical Syndrome

BACKGROUND

Biological information drawn from eye-tracking metrics is providing evidence regarding drivers of cognitive decline in Alzheimer's disease. In particular, pupil size has proved useful to investigate cognitive performance during online activities.

OBJECTIVE

To investigate the oculomotor correlates of impaired performance of patients with mild Alzheimer's Clinical Syndrome (ACS) on a recently developed memory paradigm, namely the Short-Term Memory Binding Test (STMBT).

METHODS

We assessed a sample of eighteen healthy controls (HC) and eighteen patients with a diagnosis of mild ACS with the STMBT while we recorded their oculomotor behaviors using pupillometry and eye-tracking.

RESULTS

As expected, a group (healthy controls versus ACS) by condition (Unbound Colours versus Bound Colours) interaction was found whereby behavioral group differences were paramount in the Bound Colours condition. Healthy controls' pupils dilated significantly more in the Bound Colours than in the Unbound Colours condition, a discrepancy not observed in ACS patients. Furthermore, ROC analysis revealed the abnormal pupil behaviors distinguished ACS patients from healthy controls with values of sensitivity and specify of 100%, thus outperforming both recognition scores and gaze duration.

CONCLUSION

The biological correlates of Short-Term Memory Binding impairments appear to involve a network much wider than we have thought to date, which expands across cortical and subcortical structures. We discuss these findings focusing on their implications for our understanding of neurocognitive phenotypes in the preclinical stages of Alzheimer's disease and potential development of cognitive biomarkers that can support ongoing initiatives to prevent dementia.

The Latin America and the Caribbean Consortium on Dementia (LAC-CD): From Networking to Research to Implementation Science

In comparison with other regions, dementia prevalence in Latin America is growing rapidly, along with the consequent clinical, social, and economic burden upon patients and their families. The combination of fragile health care systems, large social inequalities, and isolated clinical and research initiatives makes the coordination of efforts imperative. The Latin America and the Caribbean Consortium on Dementia (LAC-CD) is a regional organization overseeing and promoting clinical and research activities on dementia. Here, we first provide an overview of the consortium, highlighting the antecedents and current mission. Then, we present the consortium’s regional research, including the multi-partner consortium to expand dementia research in Latin America (ReDLat), which aims to identify the unique genetic, social, and economic factors that drive Alzheimer’s and frontotemporal dementia presentation in LAC relative to the US. We describe an extension of ReDLat which aims to develop affordable markers of disease subtype and severity using high density EEG. We introduce current initiatives promoting regional diagnosis, visibility, and capacity, including the forthcoming launch of the Latin American Brain Health Institute (BrainLat). We discuss LAC-CD-led advances in brain health diplomacy, including an assessment of responses to the impact of COVID-19 on people with dementia and examining the knowledge of public policies among experts in the region. Finally, we present the current knowledge-to-action framework, which paves the way for a future regional action plan. Coordinated actions are crucial to forging strong regional bonds, supporting the implementation of regional dementia plans, improving health systems, and expanding research collaborations across Latin America.

Challenges to recruitment of participants with MCI in a multicentric neuropsychological study

BACKGROUND

Data on recruitment of Mild Cognitive Impairment (MCI) samples are seldom reported and this issue can be an important source of research waste.

AIM

To describe the recruitment challenges and reasons for non-eligibility faced during a bi-centre clinical study assessing the predictive value of a neuropsychological battery of the progression to dementia.

METHODS

Potential MCI participants were identified from databases of the two memory clinics based in Milan (Italy) and invited to the screening assessment.

RESULTS

About 50% of the cases initially identified were ineligible according to inclusion/exclusion criteria and the two sites took 22 months to recruit the planned 150 people. The main reasons for non-eligibility were the MMSE score (41%), age (14%), presence of cerebrovascular disorders (9%), perceptual deficits (6%), neurological (6%) or psychiatric (4%) comorbidities and low education (5%).

CONCLUSION

Awareness of the reasons for exclusion and of the time needed to recruit the planned sample would provide hints for the planning of future studies on MCI.

Systematic Review: Genetic, Neuroimaging, and Fluids Biomarkers for Frontotemporal Dementia Across Latin America Countries

Frontotemporal dementia (FTD) includes a group of clinically, genetically, and pathologically heterogeneous neurodegenerative disorders, affecting the fronto-insular-temporal regions of the brain. Clinically, FTD is characterized by progressive deficits in behavior, executive function, and language and its diagnosis relies mainly on the clinical expertise of the physician/consensus group and the use of neuropsychological tests and/or structural/functional neuroimaging, depending on local availability. The modest correlation between clinical findings and FTD neuropathology makes the diagnosis difficult using clinical criteria and often leads to underdiagnosis or misdiagnosis, primarily due to lack of recognition or awareness of FTD as a disease and symptom overlap with psychiatric disorders. Despite advances in understanding the underlying neuropathology of FTD, accurate and sensitive diagnosis for this disease is still lacking. One of the major challenges is to improve diagnosis in FTD patients as early as possible. In this context, biomarkers have emerged as useful methods to provide and/or complement clinical diagnosis for this complex syndrome, although more evidence is needed to incorporate most of them into clinical practice. However, most biomarker studies have been performed using North American or European populations, with little representation of the Latin American and the Caribbean (LAC) region. In the LAC region, there are additional challenges, particularly the lack of awareness and knowledge about FTD, even in specialists. Also, LAC genetic heritage and cultures are complex, and both likely influence clinical presentations and may modify baseline biomarker levels. Even more, due to diagnostic delay, the clinical presentation might be further complicated by both neurological and psychiatric comorbidity, such as vascular brain damage, substance abuse, mood disorders, among others. This systematic review provides a brief update and an overview of the current knowledge on genetic, neuroimaging, and fluid biomarkers for FTD in LAC countries. Our review highlights the need for extensive research on biomarkers in FTD in LAC to contribute to a more comprehensive understanding of the disease and its associated biomarkers. Dementia research is certainly reduced in the LAC region, highlighting an urgent need for harmonized, innovative, and cross-regional studies with a global perspective across multiple areas of dementia knowledge.

Deep learning of resting-state electroencephalogram signals for three-class classification of Alzheimer's disease, mild cognitive impairment and healthy ageing

Objective.This study aimed to produce a novel deep learning (DL) model for the classification of subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI) subjects and healthy ageing (HA) subjects using resting-state scalp electroencephalogram (EEG) signals.Approach.The raw EEG data were pre-processed to remove unwanted artefacts and sources of noise. The data were then processed with the continuous wavelet transform, using the Morse mother wavelet, to create time-frequency graphs with a wavelet coefficient scale range of 0-600. The graphs were combined into tiled topographical maps governed by the 10-20 system orientation for scalp electrodes. The application of this processing pipeline was used on a data set of resting-state EEG samples from age-matched groups of 52 AD subjects (82.3 ± 4.7 years of age), 37 MCI subjects (78.4 ± 5.1 years of age) and 52 HA subjects (79.6 ± 6.0 years of age). This resulted in the formation of a data set of 16197 topographical images. This image data set was then split into training, validation and test images and used as input to an AlexNet DL model. This model was comprised of five hidden convolutional layers and optimised for various parameters such as learning rate, learning rate schedule, optimiser, and batch size.Main results.The performance was assessed by a tenfold cross-validation strategy, which produced an average accuracy result of 98.9 ± 0.4% for the three-class classification of AD vs MCI vs HA. The results showed minimal overfitting and bias between classes, further indicating the strength of the model produced.Significance.These results provide significant improvement for this classification task compared to previous studies in this field and suggest that DL could contribute to the diagnosis of AD from EEG recordings.

Deficits in short-term memory binding are detectable in individuals with brain amyloid deposition in the absence of overt neurodegeneration in the Alzheimer's disease continuum

The short-term memory binding (STMB) test involves the ability to hold in memory the integration between surface features, such as shapes and colours. The STMB test has been used to detect Alzheimer's disease (AD) at different stages, from preclinical to dementia, showing promising results. The objective of the present study was to verify whether the STMB test could differentiate patients with distinct biomarker profiles in the AD continuum. The sample comprised 18 cognitively unimpaired (CU) participants, 30 mild cognitive impairment (MCI) and 23 AD patients. All participants underwent positron emission tomography (PET) with Pittsburgh compound-B labelled with carbon-11 ([¹¹C]PIB) assessing amyloid beta (Aβ) aggregation (A) and 18fluorine-fluorodeoxyglucose ([¹⁸F]FDG)-PET assessing neurodegeneration (N) (A-N- [n = 35]); A+N- [n = 11]; A+ N+ [n = 19]). Participants who were negative and positive for amyloid deposition were compared in the absence (A-N- vs. A+N-) of neurodegeneration. When compared with the RAVLT and SKT memory tests, the STMB was the only cognitive task that differentiated these groups, predicting the group outcome in logistic regression analyses. The STMB test showed to be sensitive to the signs of AD pathology and may represent a cognitive marker within the AD continuum.

Alzheimer's Disease and Parkinson Dementia Distinguished by Cognitive Marker

BACKGROUND

Temporary memory binding (TMB) has been shown to be specifically affected by Alzheimer's disease (AD) when it is assessed via free recall and titrating the task demands to equate baseline performance across patients.

METHODS

Patients with Parkinson's disease (PD) were subdivided into patients with and without cognitive impairment and compared with AD and amnestic mild cognitive impairment (aMCI) patients on their performance on the TMB.

RESULTS

The results show that only patients with AD dementia present with impaired TMB performance. Receiver operating characteristic curve analyses showed that TMB holds high sensitivity and specificity for aMCI and AD relative to PD groups and healthy controls.

CONCLUSION

The TMB is sensitive to the neurodegenerative mechanisms leading to AD dementia but not to those underpinning PD dementia. As such, TMB task can aid the differential diagnosis of these common forms of dementia.

Attentional bias during emotional processing: Behavioral and electrophysiological evidence from an Emotional Flanker Task

Threatening stimuli seem to capture attention more swiftly than neutral stimuli. This attention bias has been observed under different experimental conditions and with different types of stimuli. It remains unclear whether this adaptive behaviour reflects the function of automatic or controlled attention mechanisms. Additionally, the spatiotemporal dynamics of its neural correlates are largely unknown. The present study investigates these issues using an Emotional Flanker Task synchronized with EEG recordings. A group of 32 healthy participants saw response-relevant images (emotional scenes from IAPS or line drawings of objects) flanked by response-irrelevant distracters (i.e., emotional scenes flanked by line drawings or vice versa). We assessed behavioural and ERP responses drawn from four task conditions (Threat-Central, Neutral-Central, Threat-Peripheral, and Neutral-Peripheral) and subjected these responses to repeated-measures ANOVA models. When presented as response-relevant targets, threatening images attracted faster and more accurate responses. They did not affect response accuracy to targets when presented as response-irrelevant flankers. However, response times were significantly slower when threatening images flanked objects than when neutral images were shown as flankers. This result replicated the well-known Emotional Flanker Effect. Behavioural responses to response-relevant threatening targets were accompanied by significant modulations of ERP activity across all time-windows and regions of interest and displayed some meaningful correlations. The Emotional Flanker Effect was accompanied by a modulation over parietal and central-parietal regions within a time-window between 550-690ms. Such a modulation suggests that the attentional disruption to targets caused by response-irrelevant threatening flankers appears to reflect less neural resources available, which are seemingly drawn away by distracting threatening flankers. The observed spatiotemporal dynamics seem to concur with understanding of the important adaptive role attributed to threat-related attention bias.

GERO Cohort Protocol, Chile, 2017-2022: Community-based Cohort of Functional Decline in Subjective Cognitive Complaint elderly

BACKGROUND

With the global population aging and life expectancy increasing, dementia has turned a priority in the health care system. In Chile, dementia is one of the most important causes of disability in the elderly and the most rapidly growing cause of death in the last 20 years. Cognitive complaint is considered a predictor for cognitive and functional decline, incident mild cognitive impairment, and incident dementia. The GERO cohort is the Chilean core clinical project of the Geroscience Center for Brain Health and Metabolism (GERO). The objective of the GERO cohort is to analyze the rate of functional decline and progression to clinical dementia and their associated risk factors in a community-dwelling elderly with subjective cognitive complaint, through a population-based study. We also aim to undertake clinical research on brain ageing and dementia disorders, to create data and biobanks with the appropriate infrastructure to conduct other studies and facilitate to the national and international scientific community access to the data and samples for research.

METHODS

The GERO cohort aims the recruitment of 300 elderly subjects (> 70 years) from Santiago (Chile), following them up for at least 3 years. Eligible people are adults not diagnosed with dementia with subjective cognitive complaint, which are reported either by the participant, a proxy or both. Participants are identified through a household census. The protocol for evaluation is based on a multidimensional approach including socio-demographic, biomedical, psychosocial, neuropsychological, neuropsychiatric and motor assessments. Neuroimaging, blood and stool samples are also obtained. This multidimensional evaluation is carried out in a baseline and 2 follow-ups assessments, at 18 and 36 months. In addition, in months 6, 12, 24, and 30, a telephone interview is performed in order to keep contact with the participants and to assess general well-being.

DISCUSSION

Our work will allow us to determine multidimensional risks factors associated with functional decline and conversion to dementia in elderly with subjective cognitive complain. The aim of our GERO group is to establish the capacity to foster cutting edge and multidisciplinary research on aging in Chile including basic and clinical research.

TRIAL REGISTRATION

NCT04265482 in ClinicalTrials.gov. Registration Date: February 11, 2020. Retrospectively Registered.

Profiles of cognitive impairment in the continuum from normal cognition to Alzheimer's clinical syndrome: Contributions of the short-term memory binding tests

BACKGROUND

Short-term memory binding (STMB) tests assess conjunctive binding, in which participants should remember the integration of features, such as shapes (or objects) and colors, forming a unique representation in memory. In this study, we investigated two STMB paradigms: change detection (CD) and free recall (FR).

OBJECTIVE

To investigate the cognitive profile in the CD and FR tasks of three diagnostic groups: cognitively unimpaired (CU), mild cognitive impairment (MCI), and Alzheimer's clinical syndrome (ACS). In addition, we aimed to calculate and compare the accuracy of the CD and FR tasks to identify MCI and ACS.

METHODS

Participants were 24 CU, 24 MCI, and 37 ACS. The cognitive scores of the clinical groups were compared using analysis of variance (ANOVA) and receiver-operating characteristic (ROC) analyses were carried out to verify the accuracy of the STMB tasks.

RESULTS

In the CD task, CU was different from MCI and ACS (CU > MCI = ACS), while in the FR task all groups were different (CU > MCI > ACS). The ROC analyses showed an area under the curve (AUC) of 0.855 comparing CU with MCI for the CD task and 0.975 for the FR. The AUC comparing CU and ACS was 0.924 for the CD and 0.973 for the FR task. The FR task showed better accuracy to identify MCI patients, and the same accuracy to detect ACS.

CONCLUSION

The present findings indicate that impairments in CD and FR of bound representations are features of the cognitive profiles of MCI and ACS patients.

Role of Executive Functions in the Conversion from Mild Cognitive Impairment to Dementia

Background: Recent research pointed to executive dysfunction as a potential early predictor of the progression of mild cognitive impairment (MCI) to dementia in Alzheimer’s clinical syndrome (ACS). Such cognitive impairments account for functional impairments in instrumental activities of daily living (IADL). Objective: The present study analyzes the contributions of executive functions to predict MCI–dementia progression in ACS. Methods: We assessed 145 participants, 51 cognitively unimpaired and 94 MCI. The latter were divided using the traditional, memory-based MCI classification (single domain amnestic, multidomain amnestic, and non-amnestic). Eight tests assessing executive functions were administered at baseline and at 1-year follow-up, together with cognitive screening tools and IADL measures. MCI patients were reclassified based on the outcomes from a K-mean cluster analysis which identified three groups. A simple lineal regression model was used to examine whether the classification based on executive functioning could more accurately predict progression to dementia a year later. Results: Clusters based on executive function deficits explained a significant proportion of the variance linked to MCI–dementia conversion, even after controlling for the severity of MCI at baseline (F(1, 68) = 116.25, p = 0.000, R2 = 0.63). Classical memory-based MCI classification failed to predict such a conversion (F(1, 68) = 5.09, p = 0.955, R2 = 0.07). Switching, categories generation, and planning were the executive functions that best distinguished between MCI converters and stable. Conclusion: MCI with a dysexecutive phenotype significantly predicts conversion to dementia in ACS a year later. Switching abilities and verbal fluency (categories) must be evaluated in MCI patients to assess risk of future dementia.

Visual short-term memory relates to tau and amyloid burdens in preclinical autosomal dominant Alzheimer's disease

Background

Over the past decade, visual short-term memory (VSTM) binding tests have been shown to be one of the most sensitive behavioral indicators of Alzheimer’s disease (AD), especially when they require the binding of multiple features (e.g., color and shape). Recently, it has become possible to directly measure amyloid and tau levels in vivo via positron emission tomography (PET). To this point, these behavioral and neurochemical markers have not been compared in humans with AD or at risk for it.

Methods

In a cross-sectional study, we compared VSTM performance to tau and amyloid concentrations, measured by PET, in individuals certain to develop AD by virtue of their inheritance of the presenilin-1 E280A mutation. These included 21 clinically unimpaired subjects and 7 subjects with early mild cognitive impairment (MCI), as well as 30 family members who were not carriers of the mutation.

Results

We found that VSTM performance correlated strongly with tau in entorhinal cortex and inferior temporal lobe, and also with amyloid when examining asymptomatic carriers only. The condition requiring binding was not preferentially linked to tau—in fact, the non-binding “shape only” condition showed a stronger relationship.

Conclusions

The results confirm VSTM’s status as an early marker of AD pathology and raise interesting questions as to the course of binding-specific versus non-binding aspects of VSTM in early AD.

Neurocognitive mechanisms underlying working memory encoding and retrieval in Attention-Deficit/Hyperactivity Disorder

Working memory (WM) impairments in ADHD have been consistently reported along with deficits in attentional control. Yet, it is not clear which specific WM processes are affected in this condition. A deficient coupling between attention and WM has been reported. Nevertheless, most studies focus on the capacity to retain information rather than on the attention-dependent stages of encoding and retrieval. The current study uses a visual short-term memory binding task, measuring both behavioral and electrophysiological responses to characterize WM encoding, binding and retrieval comparing ADHD and non-ADHD matched adolescents. ADHD exhibited poorer accuracy and larger reaction times than non-ADHD on all conditions but especially when a change across encoding and test displays occurred. Binding manipulation affected equally both groups. Encoding P3 was larger in the non-ADHD group. Retrieval P3 discriminated change only in the non-ADHD group. Binding-dependent ERP modulations did not reveal group differences. Encoding and retrieval P3 were significantly correlated only in non-ADHD. These results suggest that while binding processes seem to be intact in ADHD, attention-related encoding and retrieval processes are compromised, resulting in a failure in the prioritization of relevant information. This new evidence can also inform recent theories of binding in visual WM.

Neurocognitive reorganization of emotional processing following a socio-cognitive intervention in Colombian ex-combatants

Ex-combatants often exhibit atypical Emotional Processing (EP) such as reduced emphatic levels and higher aggressive attitudes. Social Cognitive Training (SCT) addressing socio-emotional components powerfully improve social interaction among Colombian ex-combatants. However, with narrow neural evidence, this study offers a new testimony. A sample of 28 ex-combatants from Colombian illegal armed groups took part in this study, split into 15 for SCT and 13 for the conventional program offered by the Governmental Reintegration Route. All of them were assessed before and after the intervention with a protocol that included an EP task synchronized with electroencephalographic recordings. We drew behavioral scores and brain connectivity (Coherency) metrics from task performance. Behavioral scores yielded no significant effects. Increased post-intervention connectivity in the delta band was observed during negative emotional processing only SCT group. Positive emotions exposed distinctive gamma band connectivity that differentiate groups. These results suggest that SCT can trigger covert neurofunctional reorganization in ex-combatants embarked on the reintegration process even when overt behavioral improvements are not yet apparent. Such covert functional changes may be the neural signature of compensatory mechanisms necessary to reshape behaviors adaptively. This novel framework may inspire cutting-edge translational research at the crossing of neuroscience, sociology, and public policy-making.

Visual short-term memory binding deficit with age-related hearing loss in cognitively normal older adults

Age-related hearing loss (ARHL) has been posited as a possible modifiable risk factor for neurocognitive impairment and dementia. Measures sensitive to early neurocognitive changes associated with ARHL would help to elucidate the mechanisms underpinning this relationship. We hypothesized that ARHL might be associated with decline in visual short-term memory binding (VSTMB), a potential biomarker for preclinical dementia due to Alzheimer’s disease (AD). We examined differences in accuracy between older adults with hearing loss and a control group on the VSTMB task from a single feature (shapes) condition to a feature binding (shapes-colors) condition. Hearing loss was associated with a weaker capacity to process bound features which appeared to be accounted for by a weaker sensitivity for change detection (A’). Our findings give insight into the neural mechanisms underpinning neurocognitive decline with ARHL and its temporal sequence.

Predictors of Performance in Real and Virtual Scenarios across Age

BACKGROUND

Virtual reality applications to assist older adult with cognitive and functional decline are fast growing. However, such technological developments face limitations such as due to limited constructs and ecological validity. This study was aimed at investigating age-related changes in functional abilities and their associated cognitive underpinnings during task performance in virtual and real environments.

METHOD

Twenty-two younger adults (university students) and 22 older adults (aged 58-74) performed a multiple errands task twice, once in the "Discoveries" section of the National Museum of Scotland and once in the same room as a virtual environment. Accuracy and distance traveled were measured in both groups. Cognitive and daily living abilities were recorded in older adults using standard and novel questionnaires.

RESULTS

The testing environment had a significant effect on how efficient individuals performed the task. Older and younger adults' performance was alike but older adults relied on more cognitive resources. Older adults struggled in the virtual but not in the real environment. Younger but not older adults could transfer knowledge between environments.

CONCLUSION

The use of technology to assist frail older adults and those affected by dementia is growing rapidly. For these novel tools to be theoretically valid, they need to incorporate knowledge of the challenges they pose to these vulnerable groups. Here we present evidence of such challenges and their cognitive underpinnings. This theory may be considered by future applications aimed at enhancing functional abilities in these populations.

Perspectives on ethnic and racial disparities in Alzheimer's disease and related dementias: Update and areas of immediate need

Alzheimer's disease and related dementias (ADRDs) are a global crisis facing the aging population and society as a whole. With the numbers of people with ADRDs predicted to rise dramatically across the world, the scientific community can no longer neglect the need for research focusing on ADRDs among underrepresented ethnoracial diverse groups. The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART; alz.org/ISTAART) comprises a number of professional interest areas (PIAs), each focusing on a major scientific area associated with ADRDs. We leverage the expertise of the existing international cadre of ISTAART scientists and experts to synthesize a cross-PIA white paper that provides both a concise "state-of-the-science" report of ethnoracial factors across PIA foci and updated recommendations to address immediate needs to advance ADRD science across ethnoracial populations.