Background: neuroinfiammation which occurs as a long-term latent activation of systemic infiammation in the central nervous system is currently considered as one of the main pathogenetic mechanisms of the neurodegeneration progression in the brain of patients with Alzheimer’s disease. The aim of study is to research the prognostic significance of clinical and immunological parameters determined in the blood serum of patients with amnestic Mild Cognitive Impairment (aMCI) and to form an immunological profile that determines the further dynamics of the syndrome. Patients and Methods : 261 outpatient with aMCI were followed up at the FSBSI “Mental Health Research Centre” in the period from 2014 to 2023. The study participants underwent a general clinical examination and assessment of cognitive functions using a battery of psychometric tests and scales (MMSE, MoCA, CDT, tests of 10 words and 5 geometric shapes memorization, the Hachinski ischemic scale). In addition, patients underwent an initial level of cytokines study (TNFa, IL-1, IL-1b, IL-1RA, IL-2, IL-4, IL-6, IL-8, IL-10) in blood serum by enzyme immunoassay (ELISA); the levels of leukocyte elastase enzymatic activity (LE) and α1-proteinase inhibitor functional activity were determined in blood plazma by the spectrophotometric method. The protease inhibitory index was calculated. Conclusion: the cytokines set and immune response indicators have been identified. The distinguishing levels of TNFa, IL-6, IL-1b, LE predict various variants of three year course of aMCI including the conversion to dementia.

Objective This study aims to utilize multimodal neuroimaging techniques to simultaneously analyze global topological properties of white matter structural networks and resting-state functional networks in aMCI patients, comparing them with healthy controls. By conducting independent and integrative analyses of topological impairments in both networks, we seek to systematically characterize the multimodal network disruption patterns in aMCI. Methods 45 aMCI patients and 42 healthy adults from the First Affiliated Hospital of Heilongjiang University of Chinese Medicine in Harbin, Heilongjiang Province, China, were enrolled. A case-control cross-sectional study was conducted. DTI and rs-fMRI data were collected for all participants. Global topological properties of structural and functional networks were constructed using PANDA and dpabi software and were calculated via graph-theoretical analysis in GRETNA software, followed by statistical comparisons between groups. Results In patients with aMCI, the small-world (C p , aC p , Lambda, aLambda) of the WM structural network were significantly higher than those in the HC group; Rich-club nodes showed redistribution, and the Rich-club coefficient was decreased; aE loc was significantly increased; the Assortativity index ( r < 0) indicated disassortativity; the Hierarchy index ( b > 0) exhibited a significant decrease in b within the sparsity range of 0.39∼0.4; the synchronization coefficient ( s ) was significantly reduced at sparsity levels ranging from 0.28 to 0.30. For the functional network, the small-world index aL p in the aMCI group was significantly lower than that in the HC group; Rich-club nodes showed redistribution, and the Rich-club coefficient was increased within a certain Degree range; aE g was significantly increased; the Assortativity index ( r > 0) indicated assortativity; the Hierarchy index ( b > 0) was observed within a specific sparsity range. Conclusion We identified a “structure-function dissociation” in aMCI, where the structural network suffers from fragmentation and hub disruption, while the functional network compensates through rigid, hyper-localized reorganization with elevated local efficiency. This divergence reveals a core pathological mechanism of the disease.

Background/Objectives: Amnestic mild cognitive impairment (aMCI) represents a transitional stage between normal aging and dementia, constituting a critical intervention window for Alzheimer's disease (AD). As a non-invasive intervention, neurofeedback training (NFT) has demonstrated potential in ameliorating cognitive deficits and clinical symptoms in aMCI patients; however, its mechanistic effects on functional brain connectivity remain inadequately elucidated. Methods: This study employed low- and high-order functional analytical approaches to comprehensively investigate the effects of NFT on dynamic brain functional networks in aMCI. Results: Our findings revealed that following NFT, aMCI patients exhibited enhanced connectivity strength, global efficiency, and nodal characteristics within the delta band, whereas connectivity was generally attenuated in the theta, alpha, and beta bands. Dynamic network analysis indicated increased entropy in short-time windows. Cognitive assessments showed a significant short-term improvement in MoCA scores among 92.9% of participants. Conclusions: These results suggest that NFT effectively remodels brain network activity patterns in aMCI patients, thereby facilitating cognitive improvement. These findings provide preliminary insights into the brain network mechanisms underlying NFT-mediated cognitive enhancement in aMCI.

Integrating [11C]methylreboxetine PET and MRI to map in vivo norepinephrine transporter distribution: A proof-of-concept study of noradrenergic vulnerability in neurodegeneration.

Amnestic mild cognitive impairment (aMCI) represents a critical prodromal stage of Alzheimer's disease (AD), yet effective therapeutic interventions to prevent or delay this conversion remain an unmet clinical need. Growing evidence implicates dysregulation of the microbiota-gut-brain axis (MGBA)-a complex bidirectional communication network involving neural, immune, and endocrine pathways-in the pathogenesis of neurodegenerative disorders. This perspective proposes that acupuncture, as a multi-target therapeutic approach, may modulate gut microbiota composition and restore MGBA homeostasis, thereby potentially decelerating the progression from aMCI to AD. A systematic understanding of the precise mechanisms through which acupuncture influences the MGBA carries substantial implications for both neuroscience and clinical practice. Future investigations should prioritize the elucidation of these mechanisms and the generation of robust clinical evidence through well-controlled experimental designs.

Elevated levels of total tau (t-tau) are a key biomarker of neurodegeneration, often seen in Alzheimer disease (AD). Identifying individuals at increased risk of AD using minimally invasive biomarkers can enable early intervention. We developed a polygenic risk score (PRS) for plasma t-tau and examined its association with the risk for developing clinical endophenotypes of AD pathology. This longitudinal cohort study used data from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) study, involving individuals aged 65 years or older, free of AD, or amnestic mild cognitive impairment (aMCI-an AD prodrome) at baseline. Our primary exposure was PRStau, a PRS based on common genetic variants linked to plasma tau levels. The primary outcome was aMCI or AD incidence. We assessed the association between PRStau levels and aMCI/AD risk using Cox regression models adjusted for age, sex, education, APOE ε4 allele carriership, and population structure. We sought replication in a sample of UK Biobank (UKB) participants aged 60 years or older without prevalent dementia. In the HELIAD sample, among 618 cognitively healthy participants (mean age 73.37 years, 58.4% female), followed for 2.92 ± 0.80 years, 73 developed AD/aMCI. A 1 SD increase in PRStau was linked to a 29% higher AD/aMCI risk (hazard ratio [HR] 1.290, 95% CI 1.006-1.654). Stratified analyses revealed greater effect estimates in women (HR 1.451, 95% CI 1.023-2.058) and younger participants (HR 1.866, 95% CI 1.175-2.962), whereas results in men and older participants did not reach statistical significance. In the UKB sample (n = 142,637, mean age 64.2 years, 52% female), 2,737 participants developed AD over 12.9 ± 2.4 years of follow-up. Higher PRStau was also linked to increased AD risk (HR 1.046, 95% CI 1.007-1.086). These results support the potential utility of PRS for plasma t-tau in predicting AD/aMCI incidence. The relationship between genetic predisposition for elevated plasma t-tau levels and AD pathology might be influenced by sex and age, suggesting that these factors should be considered in AD genetic risk modeling. PRS could serve as an early indicator of genetic propensity for tau pathology, enhancing existing AD diagnostic and risk stratification algorithms.

Background/Objectives: Sleep disturbances are increasingly recognized as dynamic biomarkers of cognitive decline; however, longitudinal and multimodal studies directly comparing amnestic (aMCI) and non-amnestic mild cognitive impairment (naMCI) remain limited. Methods: In a three-wave longitudinal design (~24 months), 179 older adults (46 healthy controls [HCs], 75 aMCI, 58 naMCI; mean age = 70.2 years, education = 12.3 years) were assessed with actigraphy and validated questionnaires (Athens Insomnia Scale, Pittsburgh Sleep Quality Index, STOP-BANG). Mixed ANOVAs and structural equation modeling tested group, time and mediation effects. Results: Subjective measures revealed a progressive worsening of insomnia and sleep quality in MCI, with naMCI exhibiting the steepest decline, while HCs remained largely stable. STOP-BANG trajectories indicated increasing sleep-disordered breathing risk across groups, most pronounced in naMCI. Objective indices corroborated these findings: total sleep time (TST) and sleep efficiency (SE) declined significantly in MCI, especially naMCI, while wake after sleep onset (WASO) increased longitudinally. By the third assessment, naMCI consistently showed the shortest TST and lowest SE. Mediation analyses identified SE as a central predictor of future subjective complaints, with indirect contributions from WASO and PSQI. Conclusions: Longitudinal trajectories, rather than cross-sectional comparisons, best differentiated MCI subtypes. NaMCI demonstrated the most aggressive deterioration in both objective and subjective sleep measures, highlighting its heightened vulnerability to sleep dysregulation and potential relevance for neurodegenerative progression. Clinically, sustained monitoring of SE, TST, and sleep-disordered breathing risk may provide prognostic value and inform early, targeted interventions in at-risk populations.

Introduction: Heart failure (HF) is associated with higher risk of developing cognitive impairment including mild cognitive impairment (MCI) and dementia. However, longitudinal changes in cognitive status in HF are less understood. Research questions: What percent of participants with HF have MCI or dementia at baseline using a rigorous diagnostic consensus? What percent develop MCI or dementia 16-36 months after baseline? Methods: A longitudinal descriptive study was conducted using supplement study data from a 3-arm randomized controlled trial. In the parent study, an 8-week cognitive training intervention (BrainHQ) was tested for efficacy compared with computerized crossword puzzles and usual care control conditions. There was no significant improvement in memory over 8 months of follow-up. Of 256 participants with HF (MoCA ≥ 19) randomized in the parent study, 144 were eligible and invited for the supplement study, and 96 consented. The supplement study added one additional follow-up interview between 16 and 36 months after baseline to assess long-term BrainHQ efficacy. Cognitive status (normal, MCI, or dementia) was determined by diagnostic consensus among a group of experts from neurology, neuropsychology, cardiology, and nursing who reviewed cognitive test scores, medical history, and supporting data (e.g., instrumental activities of daily living, depressive symptoms). A 100% consensus was reached for all 96 participants. Results: The sample was 51% women, mean age 65 ± 12 years. At baseline, 72 of 96 participants (75%) had normal cognition and 24 (25%) had MCI (Figure 1): 5 amnestic MCI , 15 non-amnestic MCI, and 4 multi-domain MCI. At the supplement follow-up, 74 (77%) retained their baseline cognitive status, 10 (11%) developed MCI, 5 (5%) developed dementia, and 7 (7%) converted from MCI to normal cognition. Of 72 with baseline normal cognition, 60 (83%) remained normal, 10 (14%) developed MCI, and 2 (3%) developed dementia. Of 24 with baseline MCI, 14 (58%) remained MCI, 3 (13%) developed dementia, and 7 (29%) improved to normal cognition. Conclusion: Using diagnostic consensus, MCI was identified among 25% of participants at baseline. Sixteen percent developed MCI or dementia at the follow-up. Notably, 29% of participants with baseline MCI improved to normal cognition at the follow-up. These findings highlight the need for interventions to identify, delay or reverse cognitive decline in HF.

Resting EEG partial coherence demonstrates increased γ range central functional connectivity in amnestic mild cognitive impairment.

Cortical functional connectivity changes in amnestic mild cognitive impairment.

A 67-year-old woman with myeloperoxidase (MPO)-antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis presented with progressive cognitive decline and was diagnosed with amnestic mild cognitive impairment. Brain magnetic resonance imaging (MRI) revealed chronic infarcts consistent with cerebral small vessel disease. Although conventional vascular risk factors were present, they were insufficient to fully account for the imaging and clinical findings. This case suggests that MPO-ANCA-associated vasculitis should be considered in the differential diagnosis of patients presenting with vascular cognitive impairment, particularly in the presence of systemic inflammatory features.

Bilateral oophorectomy and the probability of amnestic mild cognitive impairment among carriers of a pathogenic variant in BRCA1 or BRCA2.

Background: This study examined the impact of amnestic mild cognitive impairment (aMCI) on dynamic changes in cerebrocortical oxygen saturation (ScO2) and O2 extraction during acute, moderately intense, normobaric hypoxia and reoxygenation in elderly adults (71 ± 6 years old). Methods: Thirty-two aMCI and thirty-five control subjects participated. Inspired and expired fractions of O2 and CO2 (mass spectrometry), arterial O2 saturation (SaO2) and prefrontal ScO2 (near-infrared spectroscopy), heart rate, tidal volume and breathing frequency were monitored while subjects breathed hypoxic air (fractional inspired O2 0.10) for 3-5 min (aMCI: 4.5 ± 0.7 min; control: 4.5 ± 0.6 min) and recovered on room air. Values at the pre-hypoxia baseline, the first and last min of hypoxia and the first min of recovery were compared within and between groups using two-factor ANOVA. Results: Despite a similar baseline SaO2 in aMCI (97.2 ± 1.6%) and control (97.3 ± 1.3%) subjects, prefrontal ScO2 was lower (p < 0.05) in the aMCI subjects in both the left (67.0 ± 1.7% vs. 69.6 ± 4.5%) and right (66.8 ± 4.6% vs. 69.4 ± 4.1%) hemispheres. Hypoxia similarly decreased SaO2 and ScO2 in both groups (last min hypoxia, aMCI vs. control subjects: SaO2 76.6 ± 5.3% vs. 77.4 ± 6.1%, left prefrontal ScO2 54.0 ± 4.9% vs. 55.2 ± 6.4%, right prefrontal ScO2 56.0 ± 4.3% vs. 58.2 ± 4.4%). Upon the resumption of room-air breathing, ScO2 recovered at similar rates in aMCI and control subjects. Conclusions: Although it produced a greater deoxygenation in the left vs. the right prefrontal cortex, acute, normobaric, moderate hypoxia was well tolerated by elderly adults, even those with aMCI. Dynamic changes in cerebral oxygenation during hypoxia and recovery were unaltered by aMCI. Brief, moderate hypoxia does not impose more intense cerebrocortical oxygen depletion in elderly adults with aMCI, despite pre-hypoxic cerebrocortical oxygenation below that of their non-MCI counterparts.

Traditional clinical subtype classifications (such as amnestic and non-amnestic mild cognitive impairment) rely on subjective interpretations of overlapping patterns of performance on cognitive tests, which may lead to unreliable categorization. A more precise and objective classification of mild cognitive impairment subtypes can be achieved through data-driven clustering techniques. However, because previous studies have not restricted their cohorts to patients who have mild cognitive impairment with the pathology of Alzheimer's disease, the nature of cognitive variability and its impact on disease progression in a strictly defined biomarker-positive preclinical Alzheimer's disease cohort remains unknown. We examined cognitive heterogeneity among participants with mild cognitive impairment due to Alzheimer's disease and evaluated its prognostic utility. Neuropsychological test data from 389 patients with mild cognitive impairment in whom the cerebrospinal fluid biomarker confirmed Alzheimer's disease were obtained from the Alzheimer's Disease Neuroimaging Initiative cohorts. Principal component analysis and model-based clustering were used to identify cognitive profiles, which were then validated through a 100-time bootstrap analysis. Pairwise comparisons tested for differences between the identified subgroups in participant characteristics, scores on cognitive and clinical outcomes, levels of cerebrospinal fluid biomarkers, and magnetic resonance imaging-derived brain volumes. Longitudinal analyses evaluated differences in rate of change of magnetic resonance imaging volumetric measurements and clinical outcomes over 48 months. Survival analysis assessed risk for conversion to dementia. Alpha-synuclein levels and white matter hyperintensity volumes were considered for sensitivity analysis. Two distinct cognitive profiles were identified: a "typical" group (56.04% of the sample) that demonstrated relatively poorer scores on memory testing than non-memory tests, and an "atypical" group (43.96% of the sample) with smaller differences between memory and non-memory measures, indicating a more uniform pattern of impairment across cognitive domains. While the groups had comparable levels of overall cognitive impairment and cerebrospinal fluid biomarkers of Alzheimer's disease, the typical group displayed accelerated atrophy rates every 6 months across multiple brain regions (hippocampus: 29.02 mm3, standard error [SE] = 10.13, P = 0.005; whole brain: 1799.85 mm3, SE = 781.57, P = 0.023; entorhinal cortex: 22.26 mm3, SE = 11.15, P = 0.048; fusiform gyrus: 66.24 mm3, SE = 28.53, P = 0.021). Survival analysis revealed markedly higher dementia conversion risk (hazard ratio: 1.70, 95% confidence interval: 1.27, 2.27, P < 0.001) and shorter progression time in the typical group. These findings persisted after controlling for comorbid pathologies. In conclusion, this data-driven approach identified two distinct cognitive subtypes of mild cognitive impairment due to Alzheimer's disease that differed in their rates of clinical decline and neurodegeneration. These findings could be used to improve prognostic models and inform clinical trial stratification.

KLOTHO-VS (KL-VS) heterozygosity, a variant of the KLOTHO gene, and its encoded protein, α-Klotho, are associated with brain health and show neuroprotective potential against Alzheimer's disease (AD). We aimed to assess whether KL-VS heterozygosity, cerebrospinal fluid (CSF) and serum soluble α-Klotho (sαKl) levels, would be associated with a lower likelihood of AD and better performance on memory and other cognitive domains in individuals with AD dementia, amnestic mild cognitive impairment (aMCI) due to AD, and cognitively unimpaired controls. In this cross-sectional study, we analyzed two partially overlapping subsamples derived from 296 participants from the Czech Brain Aging Study. The first subsample included 196 participants with KL-VS haplotype data: 71 with AD dementia, 84 with aMCI due to AD, and 41 cognitively unimpaired controls. The second subsample included 147 participants with CSF and/or serum sαKl measurements, including 58 with AD dementia, 59 with aMCI due to AD, and 30 cognitively unimpaired controls. Diagnoses of aMCI and AD dementia were confirmed by positive CSF biomarkers and/or amyloid PET imaging. Logistic regression assessed how KL-VS heterozygosity influenced the odds of aMCI or dementia due to AD. Linear regression investigated associations between cognitive performance and either KL-VS heterozygosity or CSF/serum sαKl levels. Analysis of variance and analysis of covariance with post-hoc tests were used to compare sαKl levels across study groups. KL-VS heterozygosity carriers showed a consistent trend towards lower odds of being classified with aMCI and dementia due to AD, with similar patterns in both Apolipoprotein E ε4 (APOE ε4) allele carriers and non-carriers, although none of the associations reached statistical significance despite moderate (rather than small) effect sizes. Among individuals with aMCI due to AD, KL-VS heterozygotes displayed better memory performance (β = 0.61, p = .008), particularly those who also carried the APOE ε4 allele (β = 0.64, p = .042). Results with other cognitive domains were non-significant. No significant differences in sαKl levels were found between study groups, and soluble α-Klotho levels did not associate with memory performance. KL-VS heterozygosity may be linked to lower likelihood of classification as aMCI or dementia due to AD, and its association with memory might be specific to the aMCI stage of AD and modulated by APOE ε4 status.

ABSTRACT Introduction Many studies have established the relationship between greater burden of beta-amyloid (aβ), a marker of Alzheimer’s disease (AD), and poorer neuropsychological performance. However, it is poorly understood whether neuropsychological test scores predict aβ deposition. This study aimed to evaluate the predictive utility of neuropsychological test scores on aβ deposition in a sample of older adults across the late-life cognitive spectrum. Method One hundred and sixty-five older adults classified as cognitively intact (n = 68), single- or multi-domain amnestic mild cognitive impairment (MCI; n = 52) or mild dementia (n = 45) completed amyloid positron emission topography (PET), and neuropsychological measures including Hopkins Verbal Learning Test – Revised (HVLT-R), Brief Visual Memory Test – Revised (BVMT-R), Trail Making Test (TMT) Parts A and B, and Symbol Digit Modalities Test (SDMT). A series of hierarchical regression were evaluated to assess the predictive association of cognitive test scores to aβ deposition. Results In a predominantly non-Hispanic White, college-educated sample, HVLT-R Total and Delayed Recall were negatively associated with aβ deposition above and beyond demographic covariates (i.e. age, sex, years of education, estimated premorbid functioning), accounting for 31% and 39% of variance in aβ, respectively (p < .001). Similarly, BVMT-R Total and Delayed Recall scores each accounted for 31% of variance (p < .001). Effect sizes for processing speed and executive functioning scores were smaller, with SDMT explaining 12% of the variance and TMT-A and TMT-B explaining 7% and 9% of the variance, respectively (p < .001). Conclusion Cognitive test scores significantly predicted aβ deposition, with memory measures in particular accounting for approximately a third of the variance. These results provide a proof of concept for use of neuropsychological test scores as tools for estimating biomarkers in neurodegenerative disease.

BackgroundCurrent methods for the early detection of Alzheimer’s disease (AD) are constrained by high costs, invasiveness, and limited accessibility, underscoring the urgent need for alternative approaches that are accessible, affordable, and patient-friendly. Previous research has identified speech analysis as a promising tool for the early diagnosis of cognitive impairment (CI). However, the correlation between speech tests and underlying pathology remains undetermined or even obscure. Its clinical utility still lacks pathological validation. We need to further explore the relationship through large-sample analysis and further construct models that can diagnose CIf.Methods1223 participants including probable AD or AD (n = 238), amnestic mild cognitive impairment (aMCI) (n = 461) and cognitively unimpaired (CU) (n = 524) were recruited. The participants underwent neuropsychological tests, speech recordings of the “cookie-theft” task, serum biomarker quantification, APOE genotyping, and part of them underwent Aβ PET imaging. Partial Correlation Analysis and LOWESS were used to explore the correlation between speech digital biomarkers and other core AD biomarkers. Finally, machine learning such as XGBoost and Logistic regression were used for constructing the most cost-effective models for CI and Aβ status, leveraging SHAP values for screening.ResultsSignificant differences in AD biomarkers were observed among different groups. Notably, the speech digital biomarker percentage of silence duration (PSD) was correlated with cognitive level, serum glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), phosphorylated tau protein 217 (p-Tau217) and amyloid deposition in specific brain regions. Additionally, we discovered that as the different stages of Aβ deposition progress, PSD, p-Tau217, and GFAP exhibit a two-stage change pattern. Based on the findings, a machine learning CI diagnostic model (AUC = 0.928, 95% CI 0.897 to 0.960) incorporating PSD, APOE, GFAP, and demographic information was developed. Furthermore, an Aβ status classification model (AUC = 0.845, 95% CI 0.783 to 0.907) with PSD, APOE, p-Tau217, and demographic data was also constructed.ConclusionCombining speech digital markers with serum and other biomarkers helps identify CI, representing a promising advance in AD detection. This study serves as a preliminary yet encouraging step toward applying speech digital biomarkers in AD diagnostics.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13195-025-01877-6.

Apathy, or loss of motivation, is a prominent syndrome accompanying both Alzheimer's and Parkinson's disease, in addition to other disorders. One approach to understanding motivational loss is to examine the processes underlying goal-directed behaviour. Weighing up rewarding outcomes against the effort costs required to obtain them - effort-based decision-making - is a core computation when deciding to act for outcomes. Whilst a growing body of evidence points to disruption of this computation in people with apathy, which underlying decision parameters drive this disruption, their neural associations, and whether these would generalise or differ across brain disorders has not been examined. People with amnestic mild cognitive impairment and probable Alzheimer's disease (aMCI/pAD) (n=37), Parkinson's disease (PD) undergoing workup for deep brain stimulation (n=51), and healthy controls (n=21) performed a physical effort-based decision-making task (Apple gathering task), and caregiver-rated apathy scores were recorded. Following a model-free analysis of choice data, we utilised a stepwise model-based approach to explore the relationship between latent cognitive processes underlying effort-based decision-making, motivation and brain metrics. First, choices made and reaction times were analysed using drift diffusion modeling to uncover latent cognitive processes. Next, associations between apathy, diagnosis and these latent cognitive processes were examined using linear regression models. Finally, associations between latent cognitive processes altered in apathy and brain structure and connectivity in a priori regions were examined using linear mixed models. Model free analysis of choice data showed that apathy in both groups was associated with reduced incentivisation by lower rewards, whereas apathy was associated with increased sensitivity to high effort costs in PD, but reduced sensitivity to effort in aMCI/pAD. Drift diffusion modeling revealed that increased drift rate to reject offers as a function of changing effort levels was significantly associated with lower motivation in PD, but not aMCI/pAD, which was associated with lower fractional anisotropy in the pathways linking the dorsal anterior cingulate cortex and the striatum in PD. Additionally, apathy across participants was associated with bias towards rejecting offers, captured by the decision bias parameter. Furthermore, this bias was associated with increased functional connectivity in the dorsal attention network. In sum, apathy in both aMCI/pAD and PD is associated with alterations in effort-based decision making, but there are differences in these changes with disease type. Disease-specific processes and pathology remain relevant in determining the underlying causes of disrupted motivation, whilst a cross-cutting approach to apathy is still informative from a framework perspective.

BackgroundAlzheimer's disease is a neurodegenerative condition characterized by the accumulation of misfolded proteins disrupting connectivity between brain regions. Electroencephalography provides optimal temporal resolution for assessing neuronal communication.ObjectiveTo detect and compare the localization of brain rhythms and the directional flow of oscillatory activity among default mode network nodes during the resting state in patients with amnestic mild cognitive impairment (aMCI) and healthy older adults (HOA).MethodsWe recruited 94 aMCI patients and 66 HOA. We conducted functional localization and connectivity analyses using scalp recordings of neuronal activity, estimated by eLORETA approach. We calculated the effective connectivity by applying the isolated effective coherence method, allowing the frequency decomposition of the directional flow of oscillatory activity between pairs of brain regions. Eight brain regions from the default mode network were selected.ResultsAlthough trends in spectral power were noted, no statistically significant differences were found between groups. Concerning iCOH analysis, both groups showed increased information flow from the posterior to the anterior nodes. Specifically, the precuneus was dominant in transmitting information to the anterior nodes of the DMN. Furthermore, aMCI patients had lower effective connectivity values than HOA.ConclusionsiCOH analysis effectively profiles default mode nodes during the resting state, adding information on both localization and directionality of information flow, as well as the involved EEG oscillations. Furthermore, it is well-suited to detect between-group connectivity differences, suggesting its usefulness as a biomarker in the prodromal clinical stage of AD.

Aberrant hippocampal subregional network associated with episodic memory decline in amnestic mild cognitive impairment.