Enhanced functional brain network integration in mild cognitive impairment during cognitive task performance: A compensatory mechanism or a result of neural disinhibition?

Although previous studies have observed increased global network integration during tasks in persons with mild cognitive impairment (MCI), the association between this integration and actual task performance has remained unexplored. Understanding this link is crucial for uncovering the underlying mechanism behind these changes in network integration and their potential role in MCI. Here, to find such a link, we investigated brain network integration derived from electroencephalography recordings during a visual motion discrimination task in older adults with MCI and those with normal cognition. We focused on a critical period just before stimulus presentation, which is known to be important for task performance. Our results revealed that during this period, MCI patients exhibited increased network integration compared to controls. Interestingly, increased integration was associated with worse task performance in the MCI group, suggesting it was not beneficial. No such association was found in the control group. Notably, this difference existed despite similar overall task performance between the groups. This suboptimal integration pattern during the cognitive task might reflect network de-differentiation due to disinhibition in MCI patients. Collectively, our study highlights the potential of analysing network integration during tasks to identify cognitive impairment and suggest a distinct role for network integration in MCI patients compared with healthy controls.

Construct validation of NIH Toolbox Cognition Battery premorbid cognitive functioning scores in Black and White older Americans with and without mild cognitive impairment.

OBJECTIVE: Valid estimates of premorbid cognitive functioning (PMIQ) are crucial for the assessment of older adults at risk for Alzheimer's disease. We investigated the relationship between the NIH Toolbox-Cognition Battery's (NIHTB-CB) Oral Reading Recognition (ORR) subtest and Wechsler Test of Adult Reading scores (WTAR, convergent validity). We also compared ORR to NIHTB-CB Flanker scores, where null relationships were expected (discriminant validity). METHODS: The WTAR and NIHTB-CB were administered to 130 cognitively normal (CN) and 113 participants with mild cognitive impairment (MCI). Participants were community-dwelling, older Black and White adults, ages 55-88 years. Data analysis used uncorrected standard scores and Bayesian bivariate correlations. Supplemental materials include intraclass correlations. RESULTS: ORR and WTAR scores were strongly positively associated, while ORR and Flanker scores were unrelated. This pattern held when restricting analyses to the two cognitive status groups, the two racial groups, and the four race-by-diagnosis subgroups. CONCLUSION: The findings demonstrate convergent and discriminant validity and support NIHTB-CB ORR scores as valid estimates of scores on a PMIQ measure in older Black and White adults with and without MCI.

Identification of amnestic mild cognitive impairment among Black and White community-dwelling older adults using NIH Toolbox Cognition tablet battery.

OBJECTIVES: Identify which NIH Toolbox Cognition Battery (NIHTB-CB) subtest(s) best differentiate healthy controls (HC) from those with amnestic mild cognitive impairment (aMCI) and compare the discriminant accuracy between a model using a priori "Norm Adjusted" scores versus "Unadjusted" standard scores with age, sex, race/ethnicity, and education controlled for within the model. Racial differences were also examined. METHODS: Participants were Black/African American (B/AA) and White consensus-confirmed (HC = 96; aMCI = 62) adults 60-85 years old that completed the NIHTB-CB for tablet. Discriminant function analysis (DFA) was used in the Total Sample and separately for B/AA (n = 80) and White participants (n = 78). RESULTS: Picture Sequence Memory (an episodic memory task) was the highest loading coefficient across all DFA models. When stratified by race, differences were noted in the pattern of the highest loading coefficients within the DFAs. However, the overall discriminant accuracy of the DFA models in identifying HCs and those with aMCI did not differ significantly by race (B/AA, White) or model/score type (Norm Adjusted versus Unadjusted). CONCLUSIONS: Racial differences were noted despite the use of normalized scores or demographic covariates-highlighting the importance of including underrepresented groups in research. While the models were fairly accurate at identifying consensus-confirmed HCs, the models proved less accurate at identifying White participants with an aMCI diagnosis. In clinical settings, further work is needed to optimize computerized batteries and the use of NIHTB-CB norm adjusted scores is recommended. In research settings, demographically corrected scores or within model correction is suggested.

Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG.

BACKGROUND: Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency. METHODS: Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score. RESULTS: The leave-one-out cross-validation accuracy is 91.97% and 3-fold accuracy is 91.17%. The 9 to 18 months' progression trend prediction accuracy over an availability-limited subset sample is 84.61%. CONCLUSION: The EEG-based soft discrimination model demonstrates high sensitivity and reliability for MCI detection and shows promising capability in proactive prediction of people at risk of MCI before clinical symptoms may occur.

Parallel electrophysiological abnormalities due to COVID-19 infection and to Alzheimer's disease and related dementia.

Many coronavirus disease 2019 (COVID-19) positive individuals exhibit abnormal electroencephalographic (EEG) activity reflecting "brain fog" and mild cognitive impairments even months after the acute phase of infection. Resting-state EEG abnormalities include EEG slowing (reduced alpha rhythm; increased slow waves) and epileptiform activity. An expert panel conducted a systematic review to present compelling evidence that cognitive deficits due to COVID-19 and to Alzheimer's disease and related dementia (ADRD) are driven by overlapping pathologies and neurophysiological abnormalities. EEG abnormalities seen in COVID-19 patients resemble those observed in early stages of neurodegenerative diseases, particularly ADRD. It is proposed that similar EEG abnormalities in Long COVID and ADRD are due to parallel neuroinflammation, astrocyte reactivity, hypoxia, and neurovascular injury. These neurophysiological abnormalities underpinning cognitive decline in COVID-19 can be detected by routine EEG exams. Future research will explore the value of EEG monitoring of COVID-19 patients for predicting long-term outcomes and monitoring efficacy of therapeutic interventions. HIGHLIGHTS: Abnormal intrinsic electrophysiological brain activity, such as slowing of EEG, reduced alpha wave, and epileptiform are characteristic findings in COVID-19 patients. EEG abnormalities have the potential as neural biomarkers to identify neurological complications at the early stage of the disease, to assist clinical assessment, and to assess cognitive decline risk in Long COVID patients. Similar slowing of intrinsic brain activity to that of COVID-19 patients is typically seen in patients with mild cognitive impairments, ADRD. Evidence presented supports the idea that cognitive deficits in Long COVID and ADRD are driven by overlapping neurophysiological abnormalities resulting, at least in part, from neuroinflammatory mechanisms and astrocyte reactivity. Identifying common biological mechanisms in Long COVID-19 and ADRD can highlight critical pathologies underlying brain disorders and cognitive decline. It elucidates research questions regarding cognitive EEG and mild cognitive impairment in Long COVID that have not yet been adequately investigated.

Mild Cognitive Impairment Subtype Performance in Comparison to Healthy Older Controls on the NIH Toolbox and Cogstate.

BACKGROUND: Early detection is necessary for the treatment of dementia. Computerized testing has become more widely used in clinical trials; however, it is unclear how sensitive these measures are to early signs of neurodegeneration. We investigated the use of the NIH Toolbox-Cognition (NIHTB-CB) and Cogstate-Brief computerized neuropsychological batteries in the identification of mild cognitive impairment (MCI) versus healthy older adults [healthy control (HC)] and amnestic (aMCI) versus nonamnestic MCI (naMCI). Exploratory analyses include investigating potential racial differences. METHODS: Two hundred six older adults were diagnosed as aMCI (n = 58), naMCI (n = 15), or cognitively healthy (HC; n = 133). RESULTS: The NIH Toolbox-CB subtests of Flanker, Picture Sequence Memory, and Picture Vocabulary significantly differentiated MCI from HC. Further, subtests from both computerized batteries differentiated patients with aMCI from those with naMCI. Although the main effect of race differences was noted on tests and in diagnostic groups was significant, there were no significant race-by-test interactions. CONCLUSIONS: Computer-based subtests vary in their ability to help distinguish MCI subtypes, though these tests provide less expensive and easier-to-administer clinical screeners to help identify patients early who may qualify for more comprehensive evaluations. Further work is needed, however, to refine computerized tests to achieve better precision in distinguishing impairment subtypes.

Laptop-Administered NIH Toolbox and Cogstate Brief Battery in Community-Dwelling Black Adults: Unexpected Pattern of Cognitive Performance between MCI and Healthy Controls.

OBJECTIVE: Black adults are approximately twice as likely to develop Alzheimer's disease (AD) than non-Hispanic Whites and access diagnostic services later in their illness. This dictates the need to develop assessments that are cost-effective, easily administered, and sensitive to preclinical stages of AD, such as mild cognitive impairment (MCI). Two computerized cognitive batteries, NIH Toolbox-Cognition and Cogstate Brief Battery, have been developed. However, utility of these measures for clinical characterization remains only partially determined. We sought to determine the convergent validity of these computerized measures in relation to consensus diagnosis in a sample of MCI and healthy controls (HC). METHOD: Participants were community-dwelling Black adults who completed the neuropsychological battery and other Uniform Data Set (UDS) forms from the AD centers program for consensus diagnosis (HC = 61; MCI = 43) and the NIH Toolbox-Cognition and Cogstate batteries. Discriminant function analysis was used to determine which cognitive tests best differentiated the groups. RESULTS: NIH Toolbox crystallized measures, Oral Reading and Picture Vocabulary, were the most sensitive in identifying MCI apart from HC. Secondarily, deficits in memory and executive subtests were also predictive. UDS neuropsychological test analyses showed the expected pattern of memory and executive functioning tests differentiating MCI from HC. CONCLUSIONS: Contrary to expectation, NIH Toolbox crystallized abilities appeared preferentially sensitive to diagnostic group differences. This study highlights the importance of further research into the validity and clinical utility of computerized neuropsychological tests within ethnic minority populations.

Sex differences and psychological stress: responses to the COVID-19 pandemic in China.

BACKGROUND: About 83,000 COVID-19 patients were confirmed in China up to May 2020. Amid the well-documented threats to physical health, the effects of this public health crisis - and the varied efforts to contain its spread - have altered individuals' "normal" daily functioning. These impacts on social, psychological, and emotional well-being remain relatively unexplored - in particular, the ways in which Chinese men and women experience and respond to potential behavioral stressors. Our study investigated sex differences in psychological stress, emotional reactions, and behavioral responses to COVID-19 and related threats among Chinese residents. METHODS: In late February (2020), an anonymous online questionnaire was disseminated via WeChat, a popular social media platform in China. The cross-sectional study utilized a non-probabilistic "snowball" or convenience sampling of residents from various provinces and regions of China. Basic demographic characteristics (e.g., age and gender) - along with residential living arrangements and conditions - were measured along with psychological stress and emotional responses to the COVID-19 pandemic. RESULTS: Three thousand eighty-eight questionnaires were returned: 1749 females (56.6%) and 1339 males (43.4%). The mean stress level,as measured by a visual analog scale, was 3.4 (SD = 2.4) - but differed significantly by sex. Besides sex, factors positively associated with stress included: age (< 45 years), employment (unsteady income, unemployed), risk of infection (exposureto COVID-19, completed medical observation), difficulties encountered (diseases, work/study, financial, mental), and related behaviors (higher desire for COVID-19 knowledge, more time concerning on the COVID-19 outbreak). "Protective" factors included frequent contact with colleagues, calmness of mood comparing with the pre-pandemic, and psychological resilience. Males and females also differed significantly in adapting to current living/working, conditions, responding to run a fever, and needing psychological support services. CONCLUSIONS: The self-reported stress of Chinese residents related to the COVID-19 pandemic was significantly related to sex, age, employment, resilience and coping styles. Future responses to such public health threats may wish to provide sex- and/or age-appropriate supports for psychological health and emotional well-being to those at greatest risk of experiencing stress.

Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel.

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.

Relationship of Depression With Executive Functions and Visuospatial Memory in Elderly.

Cognitive deficits are a potential part of the clinical picture of depression, especially when it comes to late-life depression. The present study was carried out to establish whether distinctive cognitive deficiencies can be linked with depression in the late-life period, especially in executive functioning, working memory, and visuospatial memory. Our sample consisted of 71 seniors in the age range between 69 and 85 years. A battery of neurocognitive tests was used, including tests of executive functioning (Trail Making Test [TMT], part B, Stroop color word test, semantic word fluency test, and partially Rey-Osterrieth Complex Figure test [ROCF]), tests of attention and working memory (TMT, part A and digit span), and test of visuospatil ability and memory (ROCF). Results demonstrated that depression scores were significantly negatively correlated with scores on Verbal Fluency test, Stroop test, and ROCF immediate copy and recall. Depression was also linked to slower functioning on Trail Making A and Trail Making B subtest. In general, higher depression scores were correlated with lower performance on neuropsychological tests. However, digit span showed no significant correlation with depression. In addition, results of regression analyses revealed that the strongest predictors of depression were performance on the Rey-Osterrieth test-immediate recall and Stroop test. Thus, we could ascertain that difficulties in executive functioning and visuospatial memory are the best predictors of depression in elderly.

Meaning in challenging times: Sense of meaning supports wellbeing despite pandemic stresses.

The COVID-19 pandemic created stress and trauma for many individuals. Traumatic experiences often trigger reflection on meaning in life, with subsequent growth or despair. This study evaluates the role of meaning in life in buffering stressors in the early stages of the COVID-19 pandemic. The purpose of this study was to determine the extent to which the negative effects of COVID-19 stressors (self-perceived stress, emotional state, and cognitive adaptation to stress in the pandemic) are influenced by meaning in life in the context of the early stages of the pandemic. Further, this study described differences in meaning in life observed across demographic groups. Web-based surveys were completed by 831 Slovenian participants in April of 2020. Demographic data; perceptions of stressors related to lacking necessities, movement restrictions, and concerns at home; meaning in life; perceived overall health status; anxiety; emotional state; and perceived stress were measured. A moderately strong sense of meaning in life (M = 5.0, SD = 0.74, range 1-7) was reported by participants, and meaning in life was associated with enhanced wellbeing (B = 0.06-.28, p < .01). Both direct and indirect relationships were observed between stressors and wellbeing outcomes. The indirect effects of meaning in life were especially prominent in the relationship between stressors related to lacking necessities and concerns at home and outcomes of anxiety, perceived stress, and negative emotions, contributing 13-27% of the total observed effects. Increased meaning in life was observed across older age groups (F(5, 825) = 4.8, p < .001) and for those in partnered relationships (t(829) = -3.397, p <.001). A strong sense of meaning in life was associated with improved well-being, even for individuals who experienced pandemic-related stressors. Public health initiatives and media may help improve resilience to pandemic trauma by emphasizing the collective meaning in challenging situations.

On the Influence of Aging on Classification Performance in the Visual EEG Oddball Paradigm Using Statistical and Temporal Features.

The utilization of a non-invasive electroencephalogram (EEG) as an input sensor is a common approach in the field of the brain-computer interfaces (BCI). However, the collected EEG data pose many challenges, one of which may be the age-related variability of event-related potentials (ERPs), which are often used as primary EEG BCI signal features. To assess the potential effects of aging, a sample of 27 young and 43 older healthy individuals participated in a visual oddball study, in which they passively viewed frequent stimuli among randomly occurring rare stimuli while being recorded with a 32-channel EEG set. Two types of EEG datasets were created to train the classifiers, one consisting of amplitude and spectral features in time and another with extracted time-independent statistical ERP features. Among the nine classifiers tested, linear classifiers performed best. Furthermore, we show that classification performance differs between dataset types. When temporal features were used, maximum individuals' performance scores were higher, had lower variance, and were less affected overall by within-class differences such as age. Finally, we found that the effect of aging on classification performance depends on the classifier and its internal feature ranking. Accordingly, performance will differ if the model favors features with large within-class differences. With this in mind, care must be taken in feature extraction and selection to find the correct features and consequently avoid potential age-related performance degradation in practice.

Mild Cognitive Impairment in African Americans Is Associated with Differences in EEG Theta/Beta Ratio.

BACKGROUND: Identification of older individuals with increased risk for cognitive decline can contribute not only to personal benefits (e.g., early treatment, evaluation of treatment), but could also benefit clinical trials (e.g., patient selection). We propose that baseline resting-state electroencephalography (rsEEG) could provide markers for early identification of cognitive decline. OBJECTIVE: To determine whether rsEEG theta/beta ratio (TBR) differed between mild cognitively impaired (MCI) and healthy older adults. METHODS: We analyzed rsEEG from a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling older African Americans (58 cognitively typical and 41 MCI). Eyes closed rsEEGs were acquired before and after participants engaged in a visual motion direction discrimination task. rsEEG TBR was calculated for four midline locations and assessed for differences as a function of MCI status. Hemispheric asymmetry of TBR was also analyzed at equidistant lateral electrode sites. RESULTS: Results showed that MCI participants had a higher TBR than controls (p = 0.04), and that TBR significantly differed across vertex location (p < 0.001) with the highest TBR at parietal site. MCI and cognitively normal controls also differed in hemispheric asymmetries, such that MCI show higher TBR at frontal sites, with TBR greater over right frontal electrodes in the MCI group (p = 0.003) and no asymmetries found in the cognitively normal group. Lastly, we found a significant task aftereffect (post-task compared to pre-task measures) with higher TBR at posterior locations (Oz p = 0.002, Pz p = 0.057). CONCLUSION: TBR and TBR asymmetries differ between MCI and cognitively normal older adults and may reflect neurodegenerative processes underlying MCI symptoms.

Utility of Diffusion Modeling of Cogstate Brief Battery Test Performance in Detecting Mild Cognitive Impairment.

Cognitive testing data are essential to the diagnosis of mild cognitive impairment (MCI), and computerized cognitive testing, such as the Cogstate Brief Battery, has proven helpful in efficiently identifying harbingers of dementia. This study provides a side-by-side comparison of traditional Cogstate outcomes and diffusion modeling of these outcomes in predicting MCI diagnosis. Participants included 257 older adults (160 = normal cognition; 97 = MCI). Results showed that both traditional Cogstate and diffusion modeling analyses predicted MCI diagnosis with acceptable accuracy. Cogstate measures of recognition learning and working memory accuracy and diffusion modeling variable of decision-making efficiency (drift rate) and nondecisional time were most predictive of MCI. While participants with normal cognition demonstrated a change in response caution (boundary separation) when transitioning tasks, participants with MCI did not evidence this change.

Metacognition in Community-Dwelling Older Black and African American Adults During the COVID-19 Pandemic.

BACKGROUND: Cognitive assessment of older adults typically includes symptom reports and objective evaluations. However, there is often poor agreement between these measures. Cultural norms, stress, and anxiety may also influence cognitive self-appraisal and performance. Little research describes how other factors affect the self-report/objective test discrepancies noted in the literature. OBJECTIVE: This study investigated whether the disparity between subjective cognitive concerns and objective cognitive performance is related to measures of anxiety and stress in older Black and African American adults. METHODS: Telephone screenings were administered to 206 older adults (ages 64-94) during the first year of the pandemic. Demographic data, objective memory (Telephone Interview for Cognitive Status [TICS-m]), an adaptation of the subjective memory measure, the Cognitive Change Questionnaire, emphasizing executive functioning in everyday life [CCQ-e]), Generalized Anxiety Disorder-7 (GAD-7), and Perceived Stress Scale-4 (PSS4) were measured. Metacognition Discrepancy Index (MDI) was calculated from the standardized residual after regressing TICS-m on CCQ-e scores to quantify the discrepancy between cognitive self-appraisal and objective cognitive functioning. RESULTS: Neither GAD-7 nor PSS-4 moderated the relationship between TICS-m and CCQ-e, and TICS-m scores weakly predicted subjective CCQ-e scores (F(1, 197)=4.37, p = 0.038, R2 = 0.022). The MDI correlated with stress and anxiety (rs = 0.294, 0.396, ps < 0.001). CONCLUSION: Discrepancies exist between objectively measured and self-evaluated cognition. Elevations in stress and anxiety are associated with greater overestimation of cognitive difficulties relative to objective performance. Pandemic-related stressors may have worsened anxiety and diminished self-appraisal of cognitive abilities for some individuals, while others may remain reluctant to acknowledge impairments. Social and emotional factors are meaningful considerations in assessing cognitive difficulties.

EEG asymmetry and cognitive testing in MCI identification.

BACKGROUND: Finding the baseline resting-state EEG markers for early identification of cognitive decline can contribute to the identification of individuals at risk of further change. Potential applications include identifying participants for clinical trials, early treatment, and evaluation of treatment, accessible even from a community setting. METHODS: Analyses were completed on a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling African Americans (58 cognitively typical/HC, and 41 mildly cognitively impaired/MCI), who were recruited from the Michigan Alzheimer's Disease Research Center (MADRC) and the Wayne State University Institute of Gerontology. In addition to neuropsychological testing with CogState and Toolbox computerized batteries, resting-state EEGs (rsEEG, eyes closed) were acquired before and after participants were engaged in a visual motion direction discrimination task. rsEEG frontal alpha asymmetry (FAA) and frontal beta asymmetry (FBA) were calculated. RESULTS: FAA showed no difference across groups for the pre-task resting state. FBA was significantly different between groups, with more asymmetric frontal beta in MCI. Both physiological indices, however, along with computerized neuropsychological tests were significant predictors in logistic regression classification of MCI vs. control participants. CONCLUSION: rsEEG asymmetries can contribute significantly to successful discrimination of older persons with MCI from those without, over and above cognitive testing, alone.

Task aftereffect reorganization of resting state functional brain networks in healthy aging and mild cognitive impairment.

The view of the human brain as a complex network has led to considerable advances in understanding the brain's network organization during rest and task, in both health and disease. Here, we propose that examining brain networks within the task aftereffect model, in which we compare resting-state networks immediately before and after a cognitive engagement task, may enhance differentiation between those with normal cognition and those with increased risk for cognitive decline. We validated this model by comparing the pre- and post-task resting-state functional network organization of neurologically intact elderly and those with mild cognitive impairment (MCI) derived from electroencephalography recordings. We have demonstrated that a cognitive task among MCI patients induced, compared to healthy controls, a significantly higher increment in global network integration with an increased number of vertices taking a more central role within the network from the pre- to post-task resting state. Such modified network organization may aid cognitive performance by increasing the flow of information through the most central vertices among MCI patients who seem to require more communication and recruitment across brain areas to maintain or improve task performance. This could indicate that MCI patients are engaged in compensatory activation, especially as both groups did not differ in their task performance. In addition, no significant group differences were observed in network topology during the pre-task resting state. Our findings thus emphasize that the task aftereffect model is relevant for enhancing the identification of network topology abnormalities related to cognitive decline, and also for improving our understanding of inherent differences in brain network organization for MCI patients, and could therefore represent a valid marker of cortical capacity and/or cortical health.

Neural Bases of Age-Related Sensorimotor Slowing in the Upper and Lower Limbs.

With advanced age, there is a loss of reaction speed that may contribute to an increased risk of tripping and falling. Avoiding falls and injuries requires awareness of the threat, followed by selection and execution of the appropriate motor response. Using event-related potentials (ERPs) and a simple visual reaction task (RT), the goal of our study was to distinguish sensory and motor processing in the upper- and lower-limbs while attempting to uncover the main cause of age-related behavioral slowing. Strength (amplitudes) as well as timing and speed (latencies) of various stages of stimulus- and motor-related processing were analyzed in 48 healthy individuals (young adults, n = 24, mean age = 34 years; older adults, n = 24, mean age = 67 years). The behavioral results showed a significant age-related slowing, where the younger compared to older adults exhibited shorter RTs for the upper- (222 vs. 255 ms; p = 0.006, respectively) and the lower limb (257 vs. 274 ms; p = 0.048, respectively) as well as lower variability in both modalities (p = 0.001). Using ERP indices, age-related slowing of visual stimulus processing was characterized by overall larger amplitudes with delayed latencies of endogenous potentials in older compared with younger adults. While no differences were found in the P1 component, the later components of recorded potentials for visual stimuli processing were most affected by age. This was characterized by increased N1 and P2 amplitudes and delayed P2 latencies in both upper and lower extremities. The analysis of motor-related cortical potentials (MRCPs) revealed stronger MRCP amplitude for upper- and a non-significant trend for lower limbs in older adults. The MRCP amplitude was smaller and peaked closer to the actual motor response for the upper- than for the lower limb in both age groups. There were longer MRCP onset latencies for lower- compared to upper-limb in younger adults, and a non-significant trend was seen in older adults. Multiple regression analyses showed that the onset of the MRCP peak consistently predicted reaction time across both age groups and limbs tested. However, MRCP rise time and P2 latency were also significant predictors of simple reaction time, but only in older adults and only for the upper limbs. Our study suggests that motor cortical processes contribute most strongly to the slowing of simple reaction time in advanced age. However, late-stage cortical processing related to sensory stimuli also appears to play a role in upper limb responses in the elderly. This process most likely reflects less efficient recruitment of neuronal resources required for the upper and lower extremity response task in older adults.

The Relationship Between Perceived Stress and Subjective Cognitive Decline During the COVID-19 Epidemic.

During the outbreak of the COVID-19 epidemic, fear of disease and its consequences, recommended lifestyle changes, and severe restrictions set by governments acted as stressors and affected people's mood, emotions, mental health, and wellbeing. Many studies conducted during this crisis focused on affective and physiological responses to stress, but few studies examined how the crisis affected cognition. The present cross-sectional study examined the relationship between physiological, affective, and cognitive responses to the epidemic. In an online survey conducted at the height of the first wave of the epidemic in Slovenia (April 15-25, 2020), 830 Slovenian residents aged 18-85 years reported the effects of stressors (confinement, problems at home, problems at work, lack of necessities, and increased workload), experienced emotions, generalized anxiety, perceived stress, changes in health, fatigue and sleep quality, and perceived changes in cognition during the epidemic. Risk factors for stress (neuroticism, vulnerability, general health, gender, and age) were also recorded. We hypothesized that stressors and stress risk factors will be related to subjective cognitive decline, with negative emotions, generalized anxiety, perceived stress, and physical symptoms acting as mediator variables. On average, the results showed a mild subjective cognitive decline during the epidemic. In structural equation modeling, 34% of its variance was predicted by the mediator variables, with negative emotions and physical symptoms having the largest contribution. Stress risk factors were predictably related to the four mediator variables. Among the stressors, confinement showed the strongest effect on the four mediator variables, implying the importance of thoughtful communication about necessary restrictive measures during emergency circumstances. The results of this study indicate that the possibility of altered cognitive function should be considered when planning work and study activities during the epidemic.

Post-task modulation of resting state EEG differentiates MCI patients from controls.

Background:  Early identification of cognitive decline is critical for identifying individuals for inclusion in clinical trials and for eventual care planning. Methods: A sample (ages 60-90 years) of consensus-diagnosed, community-dwelling Blacks (61 cognitively typical [HC], 28 amnestic mild cognitive impairment [aMCI], and 14 nonamnestic MCI [naMCI]) were recruited from the Michigan Alzheimer's Disease Research Center and the Wayne State University Institute of Gerontology. Participants received two resting state electroencephalograms (rsEEG, eyes closed) between which they engaged in a visual motion direction discrimination task. rsEEG %change current source densities across all frequency bands and regions of interest were calculated. Results: EEG current density was not different across groups for pre-task resting state. However, compared to HC, aMCI showed significantly greater declines at temporal and central cortical sites, while naMCI showed significant parietal declines. Conclusion: This novel approach of post-pre/cognitive challenge rsEEG successfully discriminated older persons with MCI from those without was sensitive to cognitive decline.