Reduced Activity in the Right Inferior Frontal Gyrus in Elderly APOE-E4 Carriers during a Verbal Fluency Task

Who am I with my Lewy bodies? The insula as a core region of the self-concept networks

BACKGROUND

Dementia with Lewy bodies (DLB) is characterized by insular atrophy, which occurs at the early stage of the disease. Damage to the insula has been associated with disorders reflecting impairments of the most fundamental components of the self, such as anosognosia, which is a frequently reported symptom in patients with Lewy bodies (LB). The purpose of this study was to investigate modifications of the self-concept (SC), another component of the self, and to identify neuroanatomical correlates, in prodromal to mild DLB.

METHODS

Twenty patients with prodromal to mild DLB were selected to participate in this exploratory study along with 20 healthy control subjects matched in terms of age, gender, and level of education. The Twenty Statements Test (TST) was used to assess the SC. Behavioral performances were compared between LB patients and control subjects. Three-dimensional magnetic resonance images (MRI) were acquired for all participants and correlational analyses were performed using voxel-based morphometry (VBM) in whole brain and using a mask for the insula.

RESULTS

The behavioral results on the TST showed significantly impaired performances in LB patients in comparison with control subjects (p < .0001). Correlational analyses using VBM revealed positive correlations between the TST and grey matter volume within insular cortex, right supplementary motor area, bilateral inferior temporal gyri, right inferior frontal gyrus, and left lingual gyrus, using a threshold of p = .001 uncorrected, including total intracranial volume (TIV), age, and MMSE as nuisance covariates. Additionally, correlational analysis using a mask for the insula revealed positive correlation with grey matter volume within bilateral insular cortex, using a threshold of p = .005.

CONCLUSIONS

The behavioral results confirm the existence of SC impairments in LB patients from the prodromal stage of the disease, compared to matched healthy controls. As we expected, VBM analyses revealed involvement of the insula, among that of other brain regions, already known to be involved in other self-components. While this study is exploratory, our findings provide important insights regarding the involvement of the insula within the self, confirming the insula as a core region of the self-networks, including for high-order self-representations such as the SC.

Illuminating neurodegeneration: a future perspective on near-infrared spectroscopy in dementia research

SIGNIFICANCE

Dementia presents a global healthcare crisis, and neuroimaging is the main method for developing effective diagnoses and treatments. Yet currently, there is a lack of sensitive, portable, and low-cost neuroimaging tools. As dementia is associated with vascular and metabolic dysfunction, near-infrared spectroscopy (NIRS) has the potential to fill this gap.

AIM

This future perspective aims to briefly review the use of NIRS in dementia to date and identify the challenges involved in realizing the full impact of NIRS for dementia research, including device development, study design, and data analysis approaches.

APPROACH

We briefly appraised the current literature to assess the challenges, giving a critical analysis of the methods used. To assess the sensitivity of different NIRS device configurations to the brain with atrophy (as is common in most forms of dementia), we performed an optical modeling analysis to compare their cortical sensitivity.

RESULTS

The first NIRS dementia study was published in 1996, and the number of studies has increased over time. In general, these studies identified diminished hemodynamic responses in the frontal lobe and altered functional connectivity in dementia. Our analysis showed that traditional (low-density) NIRS arrays are sensitive to the brain with atrophy (although we see a mean decrease of 22% in the relative brain sensitivity with respect to the healthy brain), but there is a significant improvement (a factor of 50 sensitivity increase) with high-density arrays.

CONCLUSIONS

NIRS has a bright future in dementia research. Advances in technology - high-density devices and intelligent data analysis-will allow new, naturalistic task designs that may have more clinical relevance and increased reproducibility for longitudinal studies. The portable and low-cost nature of NIRS provides the potential for use in clinical and screening tests.

Factors associated with dropout in the longitudinal Vogel study of cognitive decline

Dementia, including Alzheimer's disease, is a growing problem worldwide. Prevention or early detection of the disease or a prodromal cognitive decline is necessary. By means of our long-term follow-up 'Vogel study', we aim to predict the pathological cognitive decline of a German cohort (mean age was 73.9 ± 1.55 years at first visit) with three measurement time points within 6 years per participant. Especially in samples of the elderly and subjects with chronic or co-morbid diseases, dropouts are one of the biggest problems of long-term studies. In contrast to the large number of research articles conducted on the course of dementia, little research has been done on the completion of treatment. To ensure unbiased and reliable predictors of cognitive decline from study completers, our objective was to determine predictors of dropout. We conducted multivariate analyses of covariance and multinomial logistic regression analyses to compare and predict the subject's dropout behaviour at the second visit 3 years after baseline (full participation, partial participation and no participation/dropout) with neuropsychiatric, cognitive, blood and lifestyle variables. Lower performance in declarative memory, attention and visual-spatial processing predicted dropout rather than full participation. Lower performance in visual-spatial processing predicted partial participation as opposed to full participation. Furthermore, lower performance in mini-mental status examination predicted whether subjects dropped out or participated partially instead of full participation. Baseline cognitive parameters are associated with dropouts at follow-up with a loss of impaired participants. We expect a bias into a healthier sample over time.

The Effect of APOE ɛ4 on the Functional Connectivity in Frontoparietal Network in Hypertensive Patients

Allele 4 of the apolipoprotein E gene (APOE ε4) and hypertension are considered risk factors for Alzheimer’s Disease (AD). The detection of differences in cognitive function and brain networks between hypertensive patients who are APOE ε4 carriers and non-carriers may help in understanding how hypertension and risk genes cumulatively impair brain function, which could provide critical insights into the genetic mechanism by which hypertension serves as a potential risk factor for cognitive decline and even AD. Using behavioral data from 233 elderly hypertensive patients and neuroimaging data from 38 of them from Beijing, China; the study aimed to assess the effects of APOE ε4 on cognition and to explore related changes in functional connectivity. Cognitively, the patients with APOE ε4 showed decreased executive function, memory and language. In the MRI sub-cohort, the frontoparietal networks in the APOE ε4 carrier group exhibited an altered pattern, mainly in the left precentral regions, inferior frontal lobe and angular gyrus. More importantly, the decline of cognitive function was correlated with abnormal FC in the left precentral regions in APOE ε4 carriers. APOE ε4 aggravated the dysfunction in frontal and parietal regions in hypertensive patients. This highlights the importance of brain protection in hypertensive patients, especially those with a genetic risk of AD.

Reduced parietal activation in participants with mild cognitive impairments during visual-spatial processing measured with functional near-infrared spectroscopy

Functional Near Infrared Spectroscopy (fNIRS) may be a suitable, simple, and cost-effective brain imaging technique for detecting divergent neuronal patterns at an early stage of neurodegeneration. In course of Mild Cognitive Impairment (MCI) or Alzheimer's disease (AD), a deficit in visual-spatial processing, located in the parietal cortex, is a reliable risk factor. Earlier, we established the application of the clock-hand-angle-discrimination task (ADT) during fNIRS to identify neuronal correlates of the visual-spatial processing in a healthy elderly sample. In this analysis, we aimed to measure and find out differences in the hemodynamic response in MCI participants compared to matched healthy controls. As expected, MCI participants showed more errors over all conditions of pointer length and a higher reaction time in the long and middle pointer length condition. Moreover, results revealed a significant reduction of cortical activation in MCI patients. There was a generally increased activity in both the right as compared to the left hemisphere and the superior parietal brain region as compared to the inferior parietal brain region in both groups. In summary, fNIRS can be implemented in the measurement of visual-spatial processing in MCI patients and healthy elderly based on ADT. MCI participants had difficulties to cope with the ADT. Since neuronal hypoactivity occurs with concomitant behavioral deficits, an additional analysis was performed on a subgroup of MCI patients who performed as well as the control group in behavior. This subgroup analysis also showed a hypoactivation of the parietal cortex, without evidence of a compensatory activation. Therefore, we assume that MCI patients are characterized by a deficit in the parietal cortex. Overall, these findings confirm our hypothesis that hemodynamic deficits in visual-spatial processing, localized in the parietal cortex, are reliable and early diagnostic markers for cognitive decline in risk groups for the development of AD.

Measurement invariance testing of longitudinal neuropsychiatric test scores distinguishes pathological from normative cognitive decline and highlights its potential in early detection research

OBJECTIVE

Alzheimer's disease (AD) is a growing challenge worldwide, which is why the search for early-onset predictors must be focused as soon as possible. Longitudinal studies that investigate courses of neuropsychological and other variables screen for such predictors correlated to mild cognitive impairment (MCI). However, one often neglected issue in analyses of such studies is measurement invariance (MI), which is often assumed but not tested for. This study uses the absence of MI (non-MI) and latent factor scores instead of composite variables to assess properties of cognitive domains, compensation mechanisms, and their predictability to establish a method for a more comprehensive understanding of pathological cognitive decline.

METHODS

An exploratory factor analysis (EFA) and a set of increasingly restricted confirmatory factor analyses (CFAs) were conducted to find latent factors, compared them with the composite approach, and to test for longitudinal (partial-)MI in a neuropsychiatric test battery, consisting of 14 test variables. A total of 330 elderly (mean age: 73.78 ± 1.52 years at baseline) were analyzed two times (3 years apart).

RESULTS

EFA revealed a four-factor model representing declarative memory, attention, working memory, and visual-spatial processing. Based on CFA, an accurate model was estimated across both measurement timepoints. Partial non-MI was found for parameters such as loadings, test- and latent factor intercepts as well as latent factor variances. The latent factor approach was preferable to the composite approach.

CONCLUSION

The overall assessment of non-MI latent factors may pose a possible target for this field of research. Hence, the non-MI of variances indicated variables that are especially suited for the prediction of pathological cognitive decline, while non-MI of intercepts indicated general aging-related decline. As a result, the sole assessment of MI may help distinguish pathological from normative aging processes and additionally may reveal compensatory neuropsychological mechanisms.

Neuronal correlates of the visual-spatial processing measured with functional near-infrared spectroscopy in healthy elderly individuals

Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) are a globally rising issue. It is necessary to detect such diseases early to find strategies for prevention. Typically, patients with MCI or AD show deviant neuronal patterns, which could be detected early through brain imaging techniques enabling assumptions about pre-existing diseases. Functional Near-Infrared Spectroscopy (fNIRS) is an appropriate imaging method because of its easy and economical nature with hardly any drawbacks. An early measurable risk factor indicating neurodegenerative processes could be a deficit in visual-spatial processing, which is localized in the parietal cortex. In this study, we aimed to measure the hemodynamic response of the visual-spatial processing in the healthy elderly participants of our long-term Vogel Study with fNIRS during the clock-hand-angle-discrimination task (ADT) to deepen our understanding of healthy brain mechanisms. Our results revealed for our healthy sample a significantly increased neuronal brain activity with increasing task difficulties, namely from the long to the middle to the short clock hand during ADT and significantly higher activation in the right hemisphere compared to the left hemisphere as well as in the superior parietal cortex compared to the inferior parietal cortex. Additionally, our behavioral data demonstrated longer reaction times and more errors with an increasing task requirement. We, therefore, assume that visual-spatial processing can successfully be operationalized with fNIRS for healthy elderly people based on ADT. Further fNIRS analyses are planned to investigate pathological neuronal correlates of visual-spatial function in MCI or AD study participants.

A Systematic Review of the Application of Functional Near-Infrared Spectroscopy to the Study of Cerebral Hemodynamics in Healthy Aging

Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have shown that healthy aging is associated with functional brain deterioration that preferentially affects the prefrontal cortex. This article reviews the application of an alternative method, functional near-infrared spectroscopy (fNIRS), to the study of age-related changes in cerebral hemodynamics and factors that influence cerebral hemodynamics in the elderly population. We conducted literature searches in PudMed and PsycINFO, and selected only English original research articles that used fNIRS to study healthy individuals with a mean age of ≥ 55 years. All articles were published in peer-reviewed journals between 1977 and May 2019. We synthesized 114 fNIRS studies examining hemodynamic changes that occurred in the resting state and during the tasks of sensation and perception, motor control, semantic processing, word retrieval, attentional shifting, inhibitory control, memory, and emotion and motivation in healthy older adults. This review, which was not registered in a registry, reveals an age-related reduction in resting-state cerebral oxygenation and connectivity in the prefrontal cortex. It also shows that aging is associated with a reduction in functional hemispheric asymmetry and increased compensatory activity in the frontal lobe across multiple task domains. In addition, this article describes the beneficial effects of healthy lifestyles and the detrimental effects of cardiovascular disease risk factors on brain functioning among nondemented older adults. Limitations of this review include exclusion of gray and non-English literature and lack of meta-analysis. Altogether, the fNIRS literature provides some support for various neurocognitive aging theories derived from task-based PET and fMRI studies. Because fNIRS is relatively motion-tolerant and environmentally unconstrained, it is a promising tool for fostering the development of aging biomarkers and antiaging interventions.

Hemodynamics Analysis of Patients With Mild Cognitive Impairment During Working Memory Tasks

Diagnosis of dementia in early stage is important to prevent progression of dementia in the aging society. Mild cognitive impairment (MCI) denotes an early stage of Alzheimer disease (AD). In this paper, we aim to classify MCI patients from healthy controls (HC) during working memory tasks using functional near-infrared spectroscopy (fNIRS). To achieve this objective, t-values and correlation coefficients are calculated to find the region of interest (ROI) channels and brain connectivity. From the ROI channels averaged over subjects, features (mean and slope) of hemodynamic responses were extracted for classification. Extracted features were labelled as two classes and classified via two classifiers, linear discriminant analysis (LDA) and support vector machine (SVM). The classification accuracies were 73.08 % with LDA and 71.15 % with SVM. The results show that there are significant differences in the hemodynamic responses (HR) between MCI patients and healthy controls. Therefore, these results suggest a possibility of using fNIRS as a diagnostic tool for MCI patients.

Evaluation of Neural Degeneration Biomarkers in the Prefrontal Cortex for Early Identification of Patients With Mild Cognitive Impairment: An fNIRS Study

Mild cognitive impairment (MCI), a condition characterizing poor cognition, is associated with aging and depicts early symptoms of severe cognitive impairment, known as Alzheimer's disease (AD). Meanwhile, early detection of MCI can prevent progression to AD. A great deal of research has been performed in the past decade on MCI detection. However, availability of biomarkers for MCI detection requires greater attention. In our study, we evaluated putative and reliable biomarkers for diagnosing MCI by performing different mental tasks (i.e., N-back task, Stroop task, and verbal fluency task) using functional near-infrared spectroscopy (fNIRS) signals on a group of 15 MCI patients and 9 healthy control (HC). The 15 digital biomarkers (i.e., five means, seven slopes, peak, skewness, and kurtosis) and two image biomarkers (t-map, correlation map) in the prefrontal cortex (PFC) (i.e., left PFC, middle PFC, and right PFC) between the MCI and HC groups were investigated by the statistical analysis, linear discriminant analysis (LDA), and convolutional neural network (CNN) individually. The results reveal that the statistical analysis using digital biomarkers (with a p-value < 0.05) could not distinguish the MCI patients from the HC over 60% accuracy. Therefore, the current statistical analysis needs to be improved to be used for diagnosing the MCI patients. The best accuracy with LDA was 76.67% with the N-back and Stroop tasks. However, the CNN classification results trained by image biomarkers showed a high accuracy. In particular, the CNN results trained via t-maps revealed the best accuracy (90.62%) with the N-back task, whereas the CNN result trained by the correlation maps was 85.58% with the N-back task. Also, the results illustrated that investigating the sub-regions (i.e., right, middle, left) of the PFC for detecting MCI would be better than examining the whole PFC. The t-map (or/and the correlation map) is conclusively recommended as an image biomarker for early detection of AD. The combination of CNN and image biomarkers can provide a reliable clinical tool for diagnosing MCI patients.

Decreased hemodynamic response in inferior frontotemporal regions in elderly with mild cognitive impairment

The verbal fluency task (VFT) is a well-established cognitive marker for mild cognitive impairment (MCI) in the prodromal stage of Alzheimer´s dementia (AD). The behavioral VFT performance of patients allows the prediction of dementia two years later. But effective compensatory mechanism might cover or reduce the predictive value of the VFT. Therefore the aim of this study is to measure the hemodynamic response during VFT in patients with mild cognitive impairment (MCI) to establish the hemodynamic response during the VFT as a screening instrument for the prediction of dementia. One method which allows measuring the hemodynamic response during speech production without severe problems with moving artifacts like in functional magnetic resonance imaging (fMRI) is the functional near-infrared spectroscopy (fNIRS). It is optimal as a screening instrument, as it is easy to apply and without any contraindications. In this study we assessed the hemodynamic response in prefrontal and temporal regions in patients with MCI as well as matched healthy controls with fNIRS. We found a decreased hemodynamic response in the inferior frontotemporal cortex for the MCI group. Our results indicate that a frontotemporal decreased hemodynamic response could serve as a diagnostic biomarker for dementia.