Age-group differences between young and middle-aged adults in spatiotemporal EEG dynamics revealed by instantaneous frequency microstate analysis.

Background: Driving is associated with independence, but it also exposes a person to harmful situations while on road. Safety becomes an important aspect while assessing an individual's driving ability. This study examined the driving performance of Indian drivers, both young- and middle-aged adults on driving simulator (DS). Three tests were selected on the DS: Ability test 1: clutch, accelerator, brake, and steering assessment; Ability test 2: stopping, precise stopping, hard stopping, and reaction time; and Ability test 3: city driving for 5 min. Objective: The objective of the study was to assess and compare the driving performance in young- and middle-aged Indian adults. Study Design: Observational, analytical study design was chosen for the research - a pilot study on DS. Methods: A total of thirty normal adults were included in this study. Among them, 15 normal adults who were of 20-40 years were called young adults and other 15 who were of 40-60 years were called middle-aged. The inclusion criteria were normal adults with experience of driving four-wheeler for ≥1-year, both male and females, and age >20 years. Exclusion criteria were normal adults who had readily noticeable visual, cognitive, or locomotors impairment which can compromise on the driving ability. The outcome measures were scores from DS software. The test scores were analyzed using unpaired t-test. Results: There were 30 normal adults included in the study (n = 30). In Ability 1, performance on clutch (P = 0.13), brake (P = 0.90), and accelerator (P = 0.97) did not show significant difference between the young and middle age groups; steering (P = 0.00) performance had highly significant difference between young- and middle-aged adults. Middle-aged adults performed better than young adults. In Ability 2, performance for precise stopping (P = 0.01) has shown a significant difference, whereas reaction time (P = 0.008) is highly significant. On the other hand, stopping (P = 0.6) and hard stopping (P = 0.85) do not have a significant difference between the two groups.In city driving (P = 0.00), middle-aged adults performed better than young adults. The level of significance was set at α =0.05 and the confidence interval was at 95%, and the degree of freedom was 28. Conclusion: The performance of driving skills in normal Indian adults on DS is an achievable functional measure. Middle-aged adults are at par with young adults in the simulated operations when checked on the DS for Ability 1, Ability 2, and city driving.

BackgroundIntra-individual variability in reaction time (RT IIV) is considered to be an index of central nervous system functioning. Such variability is elevated in neurodegenerative diseases or following traumatic brain injury. It has also been suggested to increase with age in healthy ageing.ObjectivesTo investigate and quantify age differences in RT IIV in healthy ageing; to examine the effect of different tasks and procedures; to compare raw and mean-adjusted measures of RT IIV.Data SourcesFour electronic databases: PsycINFO, Medline, Web of Science and EMBASE, and hand searching of reference lists of relevant studies.Study EligibilityEnglish language journal articles, books or book chapters, containing quantitative empirical data on simple and/or choice RT IIV. Samples had to include younger (under 60 years) and older (60 years and above) human adults.Study Appraisal and SynthesisStudies were evaluated in terms of sample representativeness and data treatment. Relevant data were extracted, using a specially-designed form, from the published report or obtained directly from the study authors. Age-group differences in raw and RT-mean-adjusted measures of simple and choice RT IIV were quantified using random effects meta-analyses.ResultsOlder adults (60+ years) had greater RT IIV than younger (20–39) and middle-aged (40–59) adults. Age effects were larger in choice RT tasks than in simple RT tasks. For all measures of RT IIV, effect sizes were larger for the comparisons between older and younger adults than between older and middle-aged adults, indicating that the age-related increases in RT IIV are not limited to old age. Effect sizes were also larger for raw than for RT-mean-adjusted RT IIV measures.ConclusionsRT IIV is greater among older adults. Some (but not all) of the age-related increases in RT IIV are accounted for by the increased RT means.

Alzheimer disease: Florbetapir—a useful tool to image amyloid load and predict cognitive decline in Alzheimer disease

Alzheimer disease: Increased orexin level correlates with sleep disruption and cognitive decline in Alzheimer disease

To examine the age-specific prevalence, risk factors, and magnitude of the association between cognitive frailty and all-cause mortality in Chinese middle-aged and older adults. We used baseline (2011) and follow-up waves (2013, 2015, and 2018) data from the China Health and Retirement Longitudinal Study (CHARLS). The age group was categorized as middle-aged, old, and very old. Factors associated with cognitive frailty and the associations between cognitive frailty statuses and mortality were examined using multinomial logistic regression and Cox proportional hazards models, respectively. Totally 7947 participants were included in this study, and the overall prevalence of cognitive frailty was 12% (middle-aged, 11%; old, 10%; very old, 26%; P< 0.0001). Cognitive frailty was independently associated with rural residential status, long sleep duration, lack of social participation, depressive symptoms, and multimorbidity among all the age groups. Over the 7-year follow-up, participants with cognitive frailty were at a higher risk for all-cause mortality than the robust group (HR 1.70, 95%CI 1.12-2.57 for the middle-aged group, HR 1.70, 95%CI 1.02-2.84 for the old group, and HR 2.06, 95%CI 1.17-3.65 for the very old group). Pre-cognitive frailty was associated with a higher mortality risk in the middle-aged group only (HR 1.34, 95%CI 1.01-1.79). The prevalence of cognitive frailty in middle-aged adults was comparable with that in the old group. Cognitive frailty, a significant risk factor for mortality, was associated with multiple factors in middle-aged and older adults, calling for integrated cognitive frailty prevention strategies. Noticeably, pre-cognitive frailty in middle-aged people increases mortality risk and requires special attention.

Evoked and induced EEG oscillations to visual targets reveal a differential pattern of change along the spectrum of cognitive decline in Alzheimer's Disease

Background: The rate of cognitive decline in Alzheimer's disease (AD) varies considerably between individuals. Predicting rapid cognitive decline might help clinicians provide prognostic information, select subjects for trial intervention and/or reduce costs. Methods: PubMed and PsycINFO were searched for all the English written studies published until the end of 2010 on rapid cognitive decline in AD and factors associated with it. Results: More than 300 individual articles were retrieved. We selected 82 relevant studies. The main findings of these papers are that younger, more educated and more impaired patients are more likely to show rapid cognitive decline. ApoE alleles seem not to modify the velocity of clinical progression of dementia, or at most could have a very small effect. No inference can be made for all the other variables analysed. Conclusions: There are many studies on rapid cognitive decline. Results are heterogeneous and often contradictory. No reliable conclusions about factors that may be associated with rapid cognitive decline can yet be drawn.

Recently, natural herbs have gained increasing attention owing to their comparatively low toxicity levels and the abundance of historical medical documentation regarding their use. Nevertheless, owing to a lack of knowledge regarding these herbs and their compounds, attempts to find those that could be beneficial for treating diseases have often been ad hoc; thus, there is now a growing demand for an in silico method to identify beneficial herbs. In this study, we present a computational approach for identifying natural herbs specifically effective in treating cognitive decline in Alzheimer's disease (AD) sufferers, which analyzes the similarities between herbal compounds and known drugs targeting AD-related proteins. Our in silico method suggests that Corydalis ternata can improve cognitive decline in AD sufferers. Behavioral tests with an AD mouse model for the confirmation of the in silico prediction reveals that C. ternata significantly alleviated the cognitive decline (memory and motor functions) caused by neurodegeneration. Further pathology analyses reveal that C. ternata decreases the level of Aβ plaques, reduces neuroinflammation, and promotes autophagy flux, and thus C. ternata can be clinically effective for preventing mild cognitive impairment during the early stages of AD. These findings highlight the potential utility of our in silico method and the potential clinical application of the identified natural herb in treating and preventing AD.

ABSTRACTThis case study presents a patient with early-onset Alzheimer`s disease, who applied transcranial direct current stimulation (tDCS) daily for 8 consecutive months. This was a much higher frequency than previous tDCS studies. Neuropsychological assessments were conducted before the first tDCS session, after 5 months and after 8 months. After 8 months, the patient’s immediate recall improved with 39%, whereas delayed recall improved 23%. Overall, the results revealed that patient’s cognitive functions were stabilized. There may be slight possibility that tDCS could slow the cognitive decline in Alzheimer`s disease. This should be investigated in clinical trials.

Background: Alzheimer’s disease is characterized by progressive neurodegeneration and cognitive decline. Early diagnosis and monitoring are critical but remain challenging. Apelin-17 and Elabela, endogenous ligands of the apelin receptor (APJ), have emerged as neuroprotective peptides with potential biomarker utility. Objective: To evaluate circulating Apelin-17 and Elabela levels as predictive biomarkers of neurodegeneration and cognitive impairment in Alzheimer’s disease. Methods: We measured plasma Apelin-17 and Elabela in 60 Alzheimer’s disease patients and 60 cognitively normal controls. Correlations with cognitive scores, CSF AD biomarkers (Aβ42, total tau, phosphorylated tau), inflammatory markers (IL-6, TNF-α, CRP), and MRI volumetric data were assessed. A subset (n=30) was followed longitudinally for 12 months. Results: Alzheimer’s disease patients showed significantly reduced Apelin-17 (48.7 ± 15.3 pg/mL vs. 82.1 ± 20.4 pg/mL) and Elabela levels (31.5 ± 9.8 pg/mL vs. 57.3 ± 14.1 pg/mL; p < 0.001 for both). Peptide levels correlated positively with MMSE and specific cognitive domains and inversely with CSF tau, inflammatory markers, and brain atrophy (hippocampus, entorhinal, parietal cortex). Baseline peptides predicted 12-month cognitive decline and hippocampal volume loss. Combined biomarker models including Apelin-17, Elabela, and classical markers improved diagnostic accuracy (AUC=0.93). Conclusion: Circulating Apelin-17 and Elabela are promising predictive biomarkers for neurodegeneration and cognitive decline in Alzheimer’s disease, reflecting multiple pathological processes. They hold potential for early diagnosis, monitoring, and therapeutic targeting.

Rapid cognitive decline in Alzheimer's disease. Consensus paper.

Global synchronization index as a biological correlate of cognitive decline in Alzheimer's disease

The brain is known to be active even when not performing any overt cognitive tasks, and often it engages in involuntary mind wandering. This resting state has been extensively characterized in terms of fMRI-derived brain networks. However, an alternate method has recently gained popularity: EEG microstate analysis. Proponents of microstates postulate that the brain discontinuously switches between four quasi-stable states defined by specific EEG scalp topologies at peaks in the global field potential (GFP). These microstates are thought to be "atoms of thought," involved with visual, auditory, salience, and attention processing. However, this method makes some major assumptions by excluding EEG data outside the GFP peaks and then clustering the EEG scalp topologies at the GFP peaks, assuming that only one microstate is active at any given time. This study explores the evidence surrounding these assumptions by studying the temporal dynamics of microstates and its clustering space using tools from dynamical systems analysis, fractal, and chaos theory to highlight the shortcomings in microstate analysis. The results show evidence of complex and chaotic EEG dynamics outside the GFP peaks, which is being missed by microstate analysis. Furthermore, the winner-takes-all approach of only one microstate being active at a time is found to be inadequate since the dynamic EEG scalp topology does not always resemble that of the assigned microstate, and there is competition among the different microstate classes. Finally, clustering space analysis shows that the four microstates do not cluster into four distinct and separable clusters. Taken collectively, these results show that the discontinuous description of EEG microstates is inadequate when looking at nonstationary short-scale EEG dynamics.

Clinical characteristics and outcomes in middle-aged Fontan patients

Early cognitive decline in patients with Alzheimer’s (AD) is associated with quantifiable structural and functional connectivity changes in the brain. AD dysregulation of Aβ and tau metabolism progressively disrupt normal synaptic function, leading to loss of synapses, decreased hippocampal synaptic density and early hippocampal atrophy. Advances in brain imaging techniques in living patients have enabled the transition from clinical signs and symptoms-based AD diagnosis to biomarkers-based diagnosis, with functional brain imaging techniques, quantitative EEG, and body fluids sampling. The hippocampus has a central role in semantic and episodic memory processing. This cognitive function is critically dependent on normal intrahippocampal connections and normal hippocampal functional connectivity with many cortical regions, including the perirhinal and the entorhinal cortex, parahippocampal cortex, association regions in the temporal and parietal lobes, and prefrontal cortex. Therefore, decreased hippocampal synaptic density is reflected in the altered functional connectivity of intrinsic brain networks (aka large-scale networks), including the parietal memory, default mode, and salience networks. This narrative review discusses recent critical issues related to detecting AD-associated early cognitive decline with brain synaptic structural and functional markers in high-risk or neuropsychologically diagnosed patients with subjective cognitive impairment or mild cognitive impairment.