Brain health in diverse settings: How age, demographics and cognition shape brain function.

Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.

Taxonomically-related Word Pairs Evoke both N400 and LPC at Long SOA in Turkish.

Semantic priming in Turkish was examined in 36 right-handed healthy participants in a delayed lexical decision task via taxonomic relations using EEG. Prime-target relations included related- unrelated- and pseudo-words. Taxonomically related words at long stimulus onset asynchrony (SOA) were shown to modulate N400 and late positive component (LPC) amplitudes. N400 semantic priming effect in the time window of 300-500 ms was the largest for pseudo-words, intermediate for semantically-unrelated targets, and smallest for semantically-related targets as a reflection of lexical-semantic retrieval. This finding contributes to the ERP literature showing how remarkably universal the N400 brain potential is, with similar effects across languages and orthography. The ERP data also revealed different influences of related, unrelated, and pseudo-word conditions on the amplitude of the LPC. Attention scores and mean LPC amplitudes of related words in parietal region showed a moderate correlation, indicating LPC may be related to "relationship-detection process".

Meta-Analysis of Social Cognition in Mild Cognitive Impairment.

Social cognitive abilities are impaired in Alzheimer disease and other dementias. Recent studies suggested that social cognitive abilities might be also impaired in mild cognitive impairment (MCI). Current meta-analysis aimed to summarize available evidence for deficits in theory of mind (ToM) and emotion recognition in MCI. In this meta-analysis of 17 studies, facial emotion recognition and ToM performances of 513 individuals with MCI and 693 healthy controls were compared. Mild cognitive impairment was associated with significant impairments falling in the medium effect sizes range in ToM ( d = 0.63) and facial emotion recognition ( d = 0.58). Among individual emotions, recognition of fear and sadness were particularly impaired. There were no significant between-group differences in recognition of disgust, happiness, and surprise. Social cognitive deficits were more severe in multidomain MCI. There is a need for longitudinal studies investigating the potential role of social cognitive impairment in predicting conversion to dementia.

The impact of automated hippocampal volumetry on diagnostic confidence in patients with suspected Alzheimer's disease: A European Alzheimer's Disease Consortium study.

INTRODUCTION: Hippocampal volume is a core biomarker of Alzheimer's disease (AD). However, its contribution over the standard diagnostic workup is unclear. METHODS: Three hundred fifty-six patients, under clinical evaluation for cognitive impairment, with suspected AD and Mini-Mental State Examination ≥20, were recruited across 17 European memory clinics. After the traditional diagnostic workup, diagnostic confidence of AD pathology (DCAD) was estimated by the physicians in charge. The latter were provided with the results of automated hippocampal volumetry in standardized format and DCAD was reassessed. RESULTS: An increment of one interquartile range in hippocampal volume was associated with a mean change of DCAD of -8.0% (95% credible interval: [-11.5, -5.0]). Automated hippocampal volumetry showed a statistically significant impact on DCAD beyond the contributions of neuropsychology, 18F-fluorodeoxyglucose positron emission tomography/single-photon emission computed tomography, and cerebrospinal fluid markers (-8.5, CrI: [-11.5, -5.6]; -14.1, CrI: [-19.3, -8.8]; -10.6, CrI: [-14.6, -6.1], respectively). DISCUSSION: There is a measurable effect of hippocampal volume on DCAD even when used on top of the traditional diagnostic workup.

Brain clocks capture diversity and disparity in aging and dementia.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of multimodal diversity (geographical, socioeconomic, sociodemographic, sex, neurodegeneration) on the brain age gap (BAG) is unknown. Here, we analyzed datasets from 5,306 participants across 15 countries (7 Latin American countries -LAC, 8 non-LAC). Based on higher-order interactions in brain signals, we developed a BAG deep learning architecture for functional magnetic resonance imaging (fMRI=2,953) and electroencephalography (EEG=2,353). The datasets comprised healthy controls, and individuals with mild cognitive impairment, Alzheimer's disease, and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (fMRI: MDE=5.60, RMSE=11.91; EEG: MDE=5.34, RMSE=9.82) compared to non-LAC, associated with frontoposterior networks. Structural socioeconomic inequality and other disparity-related factors (pollution, health disparities) were influential predictors of increased brain age gaps, especially in LAC (R2=0.37, F2=0.59, RMSE=6.9). A gradient of increasing BAG from controls to mild cognitive impairment to Alzheimer's disease was found. In LAC, we observed larger BAGs in females in control and Alzheimer's disease groups compared to respective males. Results were not explained by variations in signal quality, demographics, or acquisition methods. Findings provide a quantitative framework capturing the multimodal diversity of accelerated brain aging.

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.

Biomarkers in Alzheimer's disease with a special emphasis on event-related oscillatory responses.

Alzheimer's disease (AD) is a devastating neurodegenerative dementing illness. Early diagnosis at the prodromal stage is an important topic of current research. Significant advances were recently made in the validation process of several biomarkers, including structural/amyloid imaging, cerebrospinal fluid measurements, and glucose positron emission tomography. Nevertheless, there remains a need to develop an efficient, low cost, potentially portable, noninvasive biomarker in the diagnosis, course, or treatment of AD. There is also a great need for a biomarker that would reflect functional brain dynamic changes within a very short time period, such as milliseconds, to provide information about cognitive deficits. Electrophysiological methods have the highest time resolution for reflecting brain dynamics in cognitive impairments. There are several strategies available for measuring cognitive changes, including spontaneous electroencephalography (EEG), sensory-evoked oscillations (SEOs), and event-related oscillations (EROs). The term "sensory-evoked" (SE) implies responses elicited upon simple sensory stimulation, whereas "event-related" (ER) indicates responses elicited upon a cognitive task, generally an oddball paradigm. Further selective connectivity deficit in sensory or cognitive networks is reflected by coherence measurements. When simple sensory stimulus is used, a sensory network becomes activated, whereas an oddball task initiates an activation in a sensory network and additionally in a related cognitive network. In AD, spontaneous activity reveals a topographically changed pattern of oscillations. In addition, the most common finding in spontaneous EEG of AD is decrease of fast and increase of slow frequencies. The hyperexcitability of motor and sensory cortices in AD has been demonstrated in many studies. The motor cortex hyperexcitability has been shown by transcranial magnetic stimulation studies. Also, the SEOs reflecting sensory network indicate a visual sensory cortex hyperexcitability in AD, as demonstrated by increased responses over posterior regions of the hemispheres. On the other hand, ERO studies reflecting activation of a cognitive network imply decreased responses in fronto-central regions of the brain in delta and theta frequencies. Coherence studies show the connectivity between different parts of the brain. Studies of SE coherence in mild AD subjects imply almost intact connectivity in all frequency ranges, whereas ER coherence is decreased in wide connections in alpha, theta, and delta frequency ranges. Moreover, alpha ER coherence seems to be sensitive to cholinergic treatment in AD. In further research in a search of AD biomarkers, multimodal methods should be introduced to electrophysiology in order to validate these methods. Standardization and harmonization of user-friendly acquisition and analysis protocols in larger cohort populations are also needed in order to incorporate electrophysiology as a part of the clinical criteria of AD.

Brain oscillations as biomarkers in neuropsychiatric disorders: following an interactive panel discussion and synopsis.

This survey covers the potential use of neurophysiological changes as a biomarker in four neuropsychiatric diseases (attention deficit hyperactivity disorder (ADHD), Alzheimer's disease (AD), bipolar disorder (BD), and schizophrenia (SZ)). Great developments have been made in the search of biomarkers in these disorders, especially in AD. Nevertheless, there is a tremendous need to develop an efficient, low-cost, potentially portable, non-invasive biomarker in the diagnosis, course, or treatment of the above-mentioned disorders. Electrophysiological methods would provide a tool that would reflect functional brain dynamic changes within milliseconds and also may be used as an ensemble of biomarkers that is greatly needed in the evaluation of cognitive changes seen in these disorders. The strategies for measuring cognitive changes include spontaneous electroencephalography (EEG), sensory evoked oscillation (SEO), and event-related oscillations (ERO). Further selective connectivity deficit in sensory or cognitive networks is reflected by coherence measurements. Possible candidate biomarkers discussed in an interactive panel can be summarized as follows: for ADHD: (a) elevation of delta and theta, (b) diminished alpha and beta responses in spontaneous EEG; for SZ: (a) decrease of ERO gamma responses, (b) decreased ERO in all other frequency ranges, (c) invariant ERO gamma response in relation to working memory demand; for euthymic BD: (a) decreased event-related gamma coherence, (b) decreased alpha in ERO and in spontaneous EEG; for manic BD: (a) lower alpha and higher beta in ERO, (b) decreased event-related gamma coherence, (c) lower alpha and beta in ERO after valproate; and for AD: (a) decreased alpha and beta, and increased theta and delta in spontaneous EEG, (b) hyperexcitability of motor cortices as shown by transcortical magnetic stimulation, (c) hyperexcitability of visual sensory cortex as indicated by increased SEO theta responses, (d) lower delta ERO, (e) lower delta, theta, and alpha event-related coherence, (f) higher theta synchrony and higher alpha event-related coherence in cholinergically treated AD subjects. In further research in the search for biomarkers, multimodal methods should be introduced to electrophysiology for validation purposes. Also, providing the protocols for standardization and harmonization of user-friendly acquisition or analysis methods that would be applied in larger cohort populations should be used to incorporate these electrophysiologic methods into the clinical criteria. In an extension to conventional anatomical, biochemical and brain imaging biomarkers, the use of neurophysiologic markers may lead to new applications for functional interpretrations and also the possibility to monitor treatments tailored for individuals.

Coherence in event-related EEG oscillations in patients with Alzheimer's disease dementia and amnestic mild cognitive impairment.

Objectives Working memory performances are based on brain functional connectivity, so that connectivity may be deranged in individuals with mild cognitive impairment (MCI) and patients with dementia due to Alzheimer's disease (ADD). Here we tested the hypothesis of abnormal functional connectivity as revealed by the imaginary part of coherency (ICoh) at electrode pairs from event-related electroencephalographic oscillations in ADD and MCI patients. Methods The study included 43 individuals with MCI, 43 with ADD, and 68 demographically matched healthy controls (HC). Delta, theta, alpha, beta, and gamma bands event-related ICoh was measured during an oddball paradigm. Inter-hemispheric, midline, and intra-hemispheric ICoh values were compared in ADD, MCI, and HC groups. Results The main results of the present study can be summarized as follows: (1) A significant increase of midline frontal and temporal theta coherence in the MCI group as compared to the HC group; (2) A significant decrease of theta, delta, and alpha intra-hemispheric coherence in the ADD group as compared to the HC and MCI groups; (3) A significant decrease of theta midline coherence in the ADD group as compared to the HC and MCI groups; (4) Normal inter-hemispheric coherence in the ADD and MCI groups. Conclusions Compared with the MCI and HC, the ADD group showed disrupted event-related intra-hemispheric and midline low-frequency band coherence as an estimate of brain functional dysconnectivity underlying disabilities in daily living. Brain functional connectivity during attention and short memory demands is relatively resilient in elderly subjects even with MCI (with preserved abilities in daily activities), and it shows reduced efficiency at multiple operating oscillatory frequencies only at an early stage of ADD. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09920-0.

Reduced power and phase-locking values were accompanied by thalamus, putamen, and hippocampus atrophy in Parkinson's disease with mild cognitive impairment: an event-related oscillation study.

Parkinson's disease (PD) is a multifaceted neurodegenerative disorder accompanied by mild cognitive impairment (MCI) as a crucial nonmotor manifestation. Event-related oscillations (EROs) are suggested to reflect cognitive status associated with subcortical structures in neurodegenerative conditions. In this study, 36 individuals with PD-MCI and 32 PD-CN were compared with 60 healthy control (HC) participants using visual EROs by measures of event-related spectral perturbation and inter-trial coherence, along with subcortical gray matter volumes based on the FIRST algorithm. Cross-correlations among electrophysiological, neuropsychological, and structural parameters were investigated exploratively. Both PD-MCI and PD-CN patients had diminished delta and alpha phase-locking than HC, however, electrophysiological abnormalities were more pronounced in PD-MCI over frontal, central, parietal, and temporal locations in almost all frequency bands, accompanied by bilateral thalamus, hippocampus, and right putamen atrophy. PD-CN had lower hippocampal volumes than HC, without exhibiting any subcortical differences from PD-MCI. Lastly, EROs showed low-to-high correlations with structural and neuropsychological measures. These findings may highlight the complex interplay between electrophysiological, neuropsychological, and structural parameters in detected abnormalities of PD-CN and PD-MCI.

Hyperconnectivity matters in early-onset Alzheimer's disease: a resting-state EEG connectivity study.

OBJECTIVES: The aim of this study was to differentiate individuals with early-onset Alzheimer's disease (EOAD) and identify differences of functional connectivity in resting-state EEG between individuals with EOAD and late-onset AD (LOAD) in comparison with both healthy young and elderly individuals. METHODS: Forty EOAD and 56 LOAD patients were included along with 51 demographically matched young, and 54 elderly healthy individuals as controls to the EOAD and LOAD groups. Four minutes of resting-state EEG were recorded during the eyes-closed condition. The absolute value of imaginary coherence (ICoh) was measured for connectivity. The maximum values of ICoh were measured at delta (0.5-3.5 Hz), theta (4-7.5Hz), alpha (8-13 Hz), alpha-1 (8-10 Hz), alpha-2 (10.5-13 Hz), beta (13-30 Hz), beta-1 (13-20 Hz), and beta-2 (20.5-30 Hz) frequency bands. RESULTS: Individuals with EOAD showed higher coherence values in all frequency bands than LOAD patients. Compared to young healthy controls (YHC), EOAD had increased ICoh values in theta and beta-2 bands, whereas LOAD had lower ICoh values in the alpha-1 band than elderly healthy controls (EHC). Lastly, patients with EOAD demonstrated negative moderate correlations between language domains and beta-1 ICoh values. CONCLUSION: To the authors' knowledge, this is the first study evaluating coherence alterations among early-and late-onset AD patients and the diagnostic value of coherence measures. It was suggested that EOAD patients had more severe pathological changes compared with LOAD.

The reliability of P300 and the influence of age, gender and education variables in a 50 years and older normative sample.

OBJECTIVES: The present study aims to investigate the effects of age, gender, and level of education on P300 in a healthy population, aged 50 years and over; and determine the reliability metrics for different conditions and measurement methods. METHOD: Auditory and visual oddball recordings of 171 healthy adults were investigated. A fully automated preprocessing was applied to elicit ERP P300. Maximum peak amplitude, latency and mean amplitudes were measured. Data were stratified by age, gender, and education to determine group-level differences by using repeat measures of ANOVA. The internal consistency of P300 was calculated by a split-half method using odd-even segments. Test-retest reliability was assessed by calculating the intraclass correlation coefficient (ICC). RESULTS: Maximum peak P300 amplitudes were higher in the 50-64 years age group compared to the >65 years age group; and females showed increased P300 amplitudes compared to males. P300 measures showed fair to good internal consistency and poor to good test-retest reliability. CONCLUSION: Age and gender should be taken into account when designing ERP studies with elderly individuals. P300 showed good internal consistency in general, between gender groups and age groups. Long-term test-retest reliability was lower but acceptable. These findings can be interpreted as the strength of P300 by being an objective and reliable method independent of cultural differences. Here we underline several factors that may affect P300 measures and discuss other possible factors that should be standardized for P300 to be used in clinical settings.

The effects of rasagiline on cognitive deficits in Parkinson's disease patients without dementia: a randomized, double-blind, placebo-controlled, multicenter study.

Cognitive impairment can occur at all stages of Parkinson's disease. Rasagiline is a selective monoamine oxidase type-B inhibitor that enhances central dopaminergic transmission. Dopamine is thought to be involved in certain cognitive processes such as working memory. We assessed the effects of rasagiline on cognitive deficits in cognitively impaired, nondemented patients with Parkinson's disease. This was a randomized, double-blind, placebo-controlled prospective study. Patients with Parkinson's disease receiving stable dopaminergic treatment were assigned to receive rasagiline 1 mg/day or placebo for 3 months. Patients were eligible if they had impairment in 2 of 4 cognitive domains (attention, executive functions, memory, visuospatial functions) in the screening neuropsychological tests, yet did not fulfill criteria for Parkinson's disease dementia. Fifty-five patients were randomized; 48 patients completed the study. Patients in the rasagiline group showed significant improvement in digit span-backward compared with the placebo group (P = .04), with trends favoring rasagiline in digit span total and digit-ordering tests. Verbal fluency total score showed a significant difference in favor of rasagiline (P = .038), with trends favoring rasagiline in semantic fluency test and Stroop spontaneous corrections. The composite cognitive domain Z scores revealed a significant difference in favor of rasagiline compared with placebo in the attentional Z score (P < .005). There were no significant differences between the 2 groups in the other cognitive tests or cognitive domain Z scores. The monoamine oxidase type-B inhibitor rasagiline may exert beneficial effects on certain aspects of attention and executive functions in nondemented patients with Parkinson's disease with cognitive impairment.

Resting-state EEG alpha/theta power ratio discriminates early-onset Alzheimer's disease from healthy controls.

OBJECTIVES: The present study aims to compare early-onset Alzheimer's disease (EOAD) patients with healthy controls (HC), and late-onset Alzheimer's disease (LOAD) patients using resting-state delta, theta, alpha, and beta oscillations and provide a cut-off score of alpha/theta ratio to discriminate individuals with EOAD and young HC. METHODS: Forty-seven individuals with EOAD, 51 individuals with LOAD, and demographically-matched 49 young and 51 older controls were included in the study. Spectral-power analysis using Fast-Fourier Transformation (FFT) is performed on resting-state electroencephalography (EEG) data. Delta, theta, alpha, and beta oscillations compared between groups and Receiver Operating Characteristic (ROC) curve analysis was conducted. RESULTS: Compared to healthy controls individuals with EOAD showed an increase in slow frequency bands and a decrease in fast frequency bands. Frontal alpha/theta power ratio is the best discriminating value between EOAD and young HC with the sensitivity and specificity greater than 80% with area under the curve (AUC) 0.881. CONCLUSIONS: EOAD display more widespread and severe electrophysiological abnormalities than LOAD and HC which may reflect more pronounced pathological burden and cholinergic deficits in EOAD. Additionally, the alpha/theta ratio can discriminate EOAD and young HC successfully. SIGNIFICANCE: This study is the first to report that resting-state EEG power can be a promising marker for diagnostic accuracy between EOAD and healthy controls.

Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis.

Brain-predicted age difference scores are calculated by subtracting chronological age from 'brain' age, which is estimated using neuroimaging data. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brain-predicted age difference scores and specific cognitive functions has not been systematically examined using appropriate statistical methods. First, applying machine learning to 1359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise grey matter data. This model was then applied to MRI data from three independent datasets, significantly predicting chronological age in each dataset: Dokuz Eylül University (n = 175), the Cognitive Reserve/Reference Ability Neural Network study (n = 380), and The Irish Longitudinal Study on Ageing (n = 487). Each independent dataset had rich neuropsychological data. Brain-predicted age difference scores were significantly negatively correlated with performance on measures of general cognitive status (two datasets); processing speed, visual attention, and cognitive flexibility (three datasets); visual attention and cognitive flexibility (two datasets); and semantic verbal fluency (two datasets). As such, there is firm evidence of correlations between increased brain-predicted age differences and reduced cognitive function in some domains that are implicated in cognitive ageing.

A new tool to assess amnestic mild cognitive impairment in Turkish older adults: virtual supermarket (VSM).

The purpose of this study was to investigate cognitive functioning by administering the Virtual Supermarket (VSM) test in patients with amnestic mild cognitive impairment (aMCI, N = 37) and age and education-matched healthy controls (HCs, N = 52). An extensive neuropsychological test battery and the VSM were administered to all participants. The aMCI group exhibited lower performance and required more time to complete the VSM compared to HCs. Also, aMCI-Multiple Domain (aMCI-MD) patients performed worse in the "Correct Types", "Correct Quantities", "Bought Unlisted", "Correct Money" variables compared to HCs. Moreover, aMCI-SD patients displayed lower performance in "Bought Unlisted" and "Correct Money" variables compared to HCs. The VSM variables correlated with established neuropsychological test scores. The VSM test was found to discriminate between aMCI and HCs with a correct classification rate (CCR) of 81%. This is a preliminary study showing that the VSM is a valid, brief and user-friendly test. .

Biological markers in cerebrospinal fluid (CSF) and evaluation of in vitro effect of CSF on PC12 cell line viability in Alzheimer's disease.

The definite diagnosis of Alzheimer's disease (AD) is based on post mortem pathological examination. To date, there is no laboratory test that can discriminate AD patients from healthy individuals. In the perspective of recent knowledge, there are three cerebrospinal fluid (CSF) markers which have the highest sensitivity and specificity: A beta(1-40), A beta(1-42), and p-tau. In the present study, 15 'Probable Alzheimer's Disease' (PAD) patients and 15 control subjects were included. PAD patients were selected from the patients of Dokuz Eylül University Neurology Department Dementia outpatient clinic and control subjects were selected from the patients who were undergone epidural anesthesia because of any surgical operation. The concentrations of Ab1-40, Ab1-42, and p-tau in CSF were quantified by using ELISA. Also, the effects of 'PAD patients' CSF on the survival of PC12 cell line were assessed. There was a significant decrease of Ab1-40 and increase of p-tau in patients with AD when compared with controls. Ab1-42 concentration was not significantly different between groups. There was a positive correlation between duration of the disease and CSF of p-tau concentration in patients with AD. There was no significant difference in cell line viability values between groups.

The neuropsychiatric inventory scores change across the mini mental state examination ranges in patients with Alzheimer's disease: a multicenter study in Turkey.

OBJECTIVE: To investigate neuropsychiatric manifestations in patients at various stages of Alzheimer's disease (AD). BACKGROUND: Several earlier studies reported high prevalence of neuropsychiatric symptoms in patients with AD; to date, no such study has been conducted in Turkey. METHOD: We evaluated 217 patients with AD from 18 referral centers across Turkey using a web-based dementia data registry. The Mini Mental State Examination and the Neuropsychiatric Inventory (NPI) were used to evaluate the global cognitive function, and assessment of neuropsychiatric symptoms, respectively. We classified the patients into mild, moderate, and severe stages on the basis of their Mini Mental State Examination scores. We assessed group differences and correlations between the degree of AD severity and NPI values. RESULTS: The highest NPI scores were seen in patients with severe AD. The mean composite scores for apathy, anxiety, and depression were the highest. The prevalence of any behavioral symptom was 86%. There was no difference in the behavioral domain between the groups or between the referral centers. Moderate correlation was found between the severity of AD and the total NPI score. The caregivers' NPI distress scores varied among referral centers. CONCLUSIONS: The prevalence of behavioral disturbance in AD is high and similar to earlier studies, yet regional differences are seen in caregivers' reactions to behavioral symptoms.

Mild cognitive impairment in Parkinson's disease is associated with decreased P300 amplitude and reduced putamen volume.

OBJECTIVE: Functional and structural brain alterations of cognitively normal Parkinson's disease (PD-CN) and Parkinson's disease mild cognitive impairment (PD-MCI) patients were investigated using event-related potentials (ERP) P300 and volumetric magnetic resonance imaging (MRI) parameters. METHODS: Twenty three patients with PD-CN, 21 with PD-MCI, and 23 demographically-matched healthy controls were included. EEGs were recorded using a visual oddball task and mean amplitude and peak latency values of P300 were measured. Gray matter volumes (GMV) of thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala and nucleus accumbens were obtained using FMRIB Integrated Registration and Segmentation Tool. Correlations among P300, subcortical GMV and cognitive performances were assessed. RESULTS: PD-CN patients demonstrated reduced P300 amplitudes compared to healthy controls. PD-MCI patients had lower P300 amplitudes than both PD-CN patients and controls and reduced volumes of the putamen compared to controls. Both putamen volumes and P300 amplitudes showed moderate associations with executive functions. CONCLUSIONS: Our findings support that P300 amplitude may be a useful marker for the detection of preclinical changes before the appearance of cognitive and structural deterioration in PD, as shown by decreased frontal P300 amplitudes in PD-CN. The reduction further spread to centro-parietal areas in PD-MCI patients, which was accompanied by lower putamen volumes. SIGNIFICANCE: This study is the first to report on changes in ERP P300 amplitude and subcortical volume in well-matched samples of PD-CN, PD-MCI and healthy controls.