Lifetime Stressful Events Associated with Alzheimer's Pathologies, Neuroinflammation and Brain Structure in a Risk Enriched Cohort.

OBJECTIVE: Along with the known effects of stress on brain structure and inflammatory processes, increasing evidence suggest a role of chronic stress in the pathogenesis of Alzheimer's disease (AD). We investigated the association of accumulated stressful life events (SLEs) with AD pathologies, neuroinflammation, and gray matter (GM) volume among cognitively unimpaired (CU) individuals at heightened risk of AD. METHODS: This cross-sectional cohort study included 1,290 CU participants (aged 48-77) from the ALFA cohort with SLE, lumbar puncture (n = 393), and/or structural magnetic resonance imaging (n = 1,234) assessments. Using multiple regression analyses, we examined the associations of total SLEs with cerebrospinal fluid (1) phosphorylated (p)-tau181 and Aß1-42/1-40 ratio, (2) interleukin 6 (IL-6), and (3) GM volumes voxel-wise. Further, we performed stratified and interaction analyses with sex, history of psychiatric disease, and evaluated SLEs during specific life periods. RESULTS: Within the whole sample, only childhood and midlife SLEs, but not total SLEs, were associated with AD pathophysiology and neuroinflammation. Among those with a history of psychiatric disease SLEs were associated with higher p-tau181 and IL-6. Participants with history of psychiatric disease and men, showed lower Aß1-42/1-40 with higher SLEs. Participants with history of psychiatric disease and women showed reduced GM volumes in somatic regions and prefrontal and limbic regions, respectively. INTERPRETATION: We did not find evidence supporting the association of total SLEs with AD, neuroinflammation, and atrophy pathways. Instead, the associations appear to be contingent on events occurring during early and midlife, sex and history of psychiatric disease. ANN NEUROL 2024;95:1058-1068.

Astrocyte biomarkers GFAP and YKL-40 mediate early Alzheimer's disease progression.

INTRODUCTION: We studied how biomarkers of reactive astrogliosis mediate the pathogenic cascade in the earliest Alzheimer's disease (AD) stages. METHODS: We performed path analysis on data from 384 cognitively unimpaired individuals from the ALzheimer and FAmilies (ALFA)+ study using structural equation modeling to quantify the relationships between biomarkers of reactive astrogliosis and the AD pathological cascade. RESULTS: Cerebrospinal fluid (CSF) amyloid beta (Aß)42/40 was associated with Aß aggregation on positron emission tomography (PET) and with CSF p-tau181 , which was in turn directly associated with CSF neurofilament light (NfL). Plasma glial fibrillary acidic protein (GFAP) mediated the relationship between CSF Aß42/40 and Aß-PET, and CSF YKL-40 partly explained the association between Aß-PET, p-tau181 , and NfL. DISCUSSION: Our results suggest that reactive astrogliosis, as indicated by different fluid biomarkers, influences the pathogenic cascade during the preclinical stage of AD. While plasma GFAP mediates the early association between soluble and insoluble Aß, CSF YKL-40 mediates the latter association between Aß and downstream Aß-induced tau pathology and tau-induced neuronal injury. HIGHLIGHTS: Lower CSF Aß42/40 was directly linked to higher plasma GFAP concentrations. Plasma GFAP partially explained the relationship between soluble Aß and insoluble Aß. CSF YKL-40 mediated Aß-induced tau phosphorylation and tau-induced neuronal injury.

Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3.

INTRODUCTION: Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear. METHODS: We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269). RESULTS: CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 × 10-5) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 × 10-7). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 × 10-6) and CSF p-tau levels (P = 4.38 × 10-9). DISCUSSION: These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels. HIGHLIGHTS: Cerebrospinal fluid (CSF) glutathione peroxidase 3 (GPX3) levels decreased with amyloid and tau positivity and higher CSF phosphorylated tau. The minor allele of rs34294852 was associated with lower CSF GPX3. levels when also controlling for amyloid and tau category. GPX3 transcript levels in the prefrontal cortex were lower in Alzheimer's disease than controls. rs34294852 is an expression quantitative trait locus for GPX3 in blood, neutrophils, and microglia.

The potential clinical value of plasma biomarkers in Alzheimer's disease.

INTRODUCTION: Many people with cognitive complaints or impairment never receive an accurate diagnosis of the underlying condition, potentially impacting their access to appropriate treatment. To address this unmet need, plasma biomarker tests are being developed for use in Alzheimer's disease (AD). Plasma biomarker tests span various stages of development, including in vitro diagnostic devices (or tests) (IVDs), laboratory-developed tests (LDTs) and research use only devices (or tests) (RUOs). Understanding the differences between each test type is important for appropriate implementation into the AD diagnostic pathway and care continuum. METHODS: Authors reviewed scientific literature (PubMed, meeting abstracts and presentations, company press releases and websites) on AD plasma biomarkers. RESULTS: This article defines IVDs, LDTs, and RUOs, discusses potential clinical applications and highlights the steps necessary for their clinical implementation. DISCUSSION: Plasma biomarkers could revolutionize many areas of the AD diagnostic pathway and care continuum, but further research is needed. HIGHLIGHTS: There is a need for a minimally invasive Alzheimer's disease (AD) diagnostic tool. AD plasma biomarker tests exist at various stages of commercial development. Understanding the development stage of a test is important for its appropriate use. Plasma biomarker tests could function as a triage tool to streamline AD diagnosis. Further steps remain before AD plasma biomarkers can be used routinely.

Increased delta power as a scalp marker of epileptic activity: a simultaneous scalp and intracranial electroencephalography study.

BACKGROUND AND PURPOSE: The purpose was to evaluate whether intracranial interictal epileptiform discharges (IEDs) that are not visible on the scalp are associated with changes in the frequency spectrum on scalp electroencephalograms (EEGs). METHODS: Simultaneous scalp high-density EEG and intracranial EEG recordings were recorded in nine patients undergoing pre-surgical invasive recordings for pharmaco-resistant temporal lobe epilepsy. Epochs with hippocampal IED visible on intracranial EEG (ic-IED) but not on scalp EEG were selected, as well as control epochs without ic-IED. Welch's power spectral density was computed for each scalp electrode and for each subject; the power spectral density was further averaged across the canonical frequency bands and compared between the two conditions with and without ic-IED. For each patient the peak frequency in the delta band (the significantly strongest frequency band in all patients) was determined during periods of ic-IED. The five electrodes showing strongest power at the peak frequency were also determined. RESULTS: It was found that intracranial IEDs are associated with an increase in delta power on scalp EEGs, in particular at a frequency ≥1.4 Hz. Electrodes showing slow frequency power changes associated with IEDs were consistent with the hemispheric lateralization of IEDs. Electrodes with maximum power of slow activity were not limited to temporal regions but also involved frontal (bilateral or unilateral) regions. CONCLUSIONS: In patients with a clinical picture suggestive of temporal lobe epilepsy, the presence of delta slowing ≥1.4 Hz in anterior temporal regions can represent a scalp marker of hippocampal IEDs. To our best knowledge this is the first study that demonstrates the co-occurrence of ic-IED and increased delta power.

The connectome spectrum as a canonical basis for a sparse representation of fast brain activity.

The functional organization of neural processes is constrained by the brain's intrinsic structural connectivity, i.e., the connectome. Here, we explore how structural connectivity can improve the representation of brain activity signals and their dynamics. Using a multi-modal imaging dataset (electroencephalography, structural MRI, and diffusion MRI), we represent electrical brain activity at the cortical surface as a time-varying composition of harmonic modes of structural connectivity. These harmonic modes are known as connectome harmonics. Here we describe brain activity signal as a time-varying combination of connectome harmonics. We term this description as the connectome spectrum of the signal. We found that: first, the brain activity signal is represented more compactly by the connectome spectrum than by the traditional area-based representation; second, the connectome spectrum characterizes fast brain dynamics in terms of signal broadcasting profile, revealing different temporal regimes of integration and segregation that are consistent across participants. And last, the connectome spectrum characterizes fast brain dynamics with fewer degrees of freedom than area-based signal representations. Specifically, we show that a smaller number of dimensions capture the differences between low-level and high-level visual processing in the connectome spectrum. Also, we demonstrate that connectome harmonics capture more sensitively the topological properties of brain activity. In summary, this work provides statistical, functional, and topological evidence indicating that the description of brain activity in terms of structural connectivity fosters a more comprehensive understanding of large-scale dynamic neural functioning.

Connectome spectral analysis to track EEG task dynamics on a subsecond scale.

We present an approach for tracking fast spatiotemporal cortical dynamics in which we combine white matter connectivity data with source-projected electroencephalographic (EEG) data. We employ the mathematical framework of graph signal processing in order to derive the Fourier modes of the brain structural connectivity graph, or "network harmonics". These network harmonics are naturally ordered by smoothness. Smoothness in this context can be understood as the amount of variation along the cortex, leading to a multi-scale representation of brain connectivity. We demonstrate that network harmonics provide a sparse representation of the EEG signal, where, at certain times, the smoothest 15 network harmonics capture 90% of the signal power. This suggests that network harmonics are functionally meaningful, which we demonstrate by using them as a basis for the functional EEG data recorded from a face detection task. There, only 13 network harmonics are sufficient to track the large-scale cortical activity during the processing of the stimuli with a 50 â€‹ms resolution, reproducing well-known activity in the fusiform face area as well as revealing co-activation patterns in somatosensory/motor and frontal cortices that an unconstrained ROI-by-ROI analysis fails to capture. The proposed approach is simple and fast, provides a means of integration of multimodal datasets, and is tied to a theoretical framework in mathematics and physics. Thus, network harmonics point towards promising research directions both theoretically - for example in exploring the relationship between structure and function in the brain - and practically - for example for network tracking in different tasks and groups of individuals, such as patients.

Modifiable dementia risk factors and AT(N) biomarkers: findings from the EPAD cohort.

Introduction: Modifiable risk factors account for a substantial proportion of Alzheimer's disease (AD) cases and we currently have a discrete AT(N) biomarker profile for AD biomarkers: amyloid (A), p-tau (T), and neurodegeneration (N). Here, we investigated how modifiable risk factors relate to the three hallmark AT(N) biomarkers of AD. Methods: Participants from the European Prevention of Alzheimer's Dementia (EPAD) study underwent clinical assessments, brain magnetic resonance imaging, and cerebrospinal fluid collection and analysis. Generalized additive models (GAMs) with penalized regression splines were modeled in the AD Workbench on the NTKApp. Results: A total of 1,434 participants were included (56% women, 39% APOE ε4+) with an average age of 65.5 (± 7.2) years. We found that modifiable risk factors of less education (t = 3.9, p < 0.001), less exercise (t = 2.1, p = 0.034), traumatic brain injury (t = -2.1, p = 0.036), and higher body mass index (t = -4.5, p < 0.001) were all significantly associated with higher AD biomarker burden. Discussion: This cross-sectional study provides further support for modifiable risk factors displaying neuroprotective associations with the characteristic AT(N) biomarkers of AD.

Associations between recall of proper names in story recall and CSF amyloid and tau in adults without cognitive impairment.

Neuropsychological measures sensitive to decline in the preclinical phase of Alzheimer's disease are needed. We previously demonstrated that higher amyloid-beta (Aß) assessed by positron emission tomography in adults without cognitive impairment was associated with recall of fewer proper names in Logical Memory story recall. The current study investigated the association between proper names and cerebrospinal fluid biomarkers (Aß42/40, phosphorylated tau181 [pTau181], neurofilament light) in 223 participants from the Wisconsin Registry for Alzheimer's Prevention. We assessed associations between biomarkers and delayed Logical Memory total score and proper names using binary logistic regressions. Sensitivity analyses used multinomial logistic regression and stratified biomarker groups. Lower Logical Memory total score and proper names scores from the most recent visit were associated with biomarker positivity. Relatedly, there was a 27% decreased risk of being classified Aß42/40+/pTau181+ for each additional proper name recalled. A linear mixed effects model found that longitudinal change in proper names recall was predicted by biomarker status. These results demonstrate a novel relationship between proper names and Alzheimer's disease-cerebrospinal fluid pathology.

Current Diagnostic Pathways for Alzheimer's Disease: A Cross-Sectional Real-World Study Across Six Countries.

Background: Diagnostic pathways for patients presenting with cognitive complaints may vary across geographies. Objective: To describe diagnostic pathways of patients presenting with cognitive complaints across 6 countries. Methods: This real-world, cross-sectional study analyzed chart-extracted data from healthcare providers (HCPs) for 6,744 patients across China, France, Germany, Spain, UK, and the US. Results: Most common symptoms at presentation were cognitive (memory/amnestic; 89.86%), followed by physical/behavioral (87.13%). Clinical/cognitive tests were used in > 95%, with Mini-Mental State Examination being the most common cognitive test (79.0%). Blood tests for APOE ɛ4/other mutations, or to rule out treatable causes, were used in half of the patients. Clinical and cognitive tests were used at higher frequency at earlier visits, and amyloid PET/CSF biomarker testing at higher frequency at later visits. The latter were ordered at low rates even by specialists (across countries, 5.7% to 28.7% for amyloid PET and 5.0% to 27.3% for CSF testing). Approximately half the patients received a diagnosis (52.1% of which were Alzheimer's disease [AD]). Factors that influenced risk of not receiving a diagnosis were HCP type (higher for primary care physicians versus specialists) and region (highest in China and Germany). Conclusion: These data highlight variability in AD diagnostic pathways across countries and provider types. About 45% of patients are referred/told to 'watch and wait'. Improvements can be made in the use of amyloid PET and CSF testing. Efforts should focus on further defining biomarkers for those at risk for AD, and on dismantling barriers such low testing capacity and reimbursement challenges.

Identifying clinically useful biomarkers in neurodegenerative disease through a collaborative approach: the NeuroToolKit.

BACKGROUND: Alzheimer's disease (AD) is a complex and heterogeneous disease, which requires reliable biomarkers for diagnosis and monitoring disease activity. Preanalytical protocol and technical variability associated with biomarker immunoassays makes comparability of biomarker data across multiple cohorts difficult. This study aimed to compare cerebrospinal fluid (CSF) biomarker results across independent cohorts, including participants spanning the AD continuum. METHODS: Measured on the NeuroToolKit (NTK) prototype panel of immunoassays, 12 CSF biomarkers were evaluated from three cohorts (ALFA+, Wisconsin, and Abby/Blaze). A correction factor was applied to biomarkers found to be affected by preanalytical procedures (amyloid-ß1-42, amyloid-ß1-40, and alpha-synuclein), and results between cohorts for each disease stage were compared. The relationship between CSF biomarker concentration and cognitive scores was evaluated. RESULTS: Biomarker distributions were comparable across cohorts following correction. Correlations of biomarker values were consistent across cohorts, regardless of disease stage. Disease stage differentiation was highest for neurofilament light (NfL), phosphorylated tau, and total tau, regardless of the cohort. Correlation between biomarker concentration and cognitive scores was comparable across cohorts, and strongest for NfL, chitinase-3-like protein-1 (YKL40), and glial fibrillary acidic protein. DISCUSSION: The precision of the NTK enables merging of biomarker datasets, after correction for preanalytical confounders. Assessment of multiple cohorts is crucial to increase power in future studies into AD pathogenesis.

Blood-based biomarkers in Alzheimer's disease: Future directions for implementation.

INTRODUCTION: Disease-modifying therapies (DMTs) for Alzheimer's disease (AD) will increase diagnostic demand. A non-invasive blood-based biomarker (BBBM) test for detection of amyloid-ß pathology may reduce diagnostic barriers and facilitate DMT initiation. OBJECTIVE: To explore heterogeneity in AD care pathways and potential role of BBBM tests. METHODS: Survey of 213 healthcare professionals/payers in US/China/UK/Germany/Spain/France and two advisory boards (US/Europe). RESULTS: Current diagnostic pathways are heterogeneous, meaning many AD patients are missed while low-risk patients undergo unnecessary procedures. Confirmatory amyloid testing (cerebrospinal fluid biomarkers/positron emission tomography) is utilized in few patients, resulting in diagnostic/treatment delays. A high negative-predictive-value test could streamline the diagnostic pathway by reducing unnecessary procedures in low-risk patients; supporting confirmatory testing where needed. Imminent approval of DMTs will increase need for fast and reliable AD diagnostic tests. DISCUSSION: An easy-to-use, accurate, non-invasive BBBM test for amyloid pathology could guide diagnostic procedures or referral, streamlining early diagnosis and DMT initiation. Highlights: This study explored AD care pathways and how BBBM may meet diagnostic demandsCurrent diagnostic pathways are heterogeneous, with country and setting variationsMany AD patients are missed, while low-risk patients undergo unnecessary proceduresAn easy-to-use, accurate, non-invasive BBBM test for amyloid pathology is neededThis test could streamline early diagnosis of amyloid pathology and DMT initiation.

Effect of Pathway-specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-related Biomarkers among Asymptomatic Individuals.

Background: Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan. Objective: In this study, we leveraged 10 years of longitudinal data from initially cognitively unimpaired individuals in the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways. Methods: PRS and p-PRSs with and without apolipoprotein E ( APOE ) were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and global/domain-specific cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers for beta-amyloid 42 (Aß42), Aß42/40 ratio, total tau, and phosphorylated tau in a subset. Replication analyses were performed in an independent sample. Results: We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of p-PRSs/PRS on rate of change in cognition, beta-amyloid, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded. Conclusion: In addition to APOE , the p-PRSs can predict age-dependent changes in beta-amyloid, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating beta-amyloid and tau, long before the onset of clinical symptoms.

Effect of Pathway-Specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-Related Biomarkers Among Asymptomatic Individuals.

BACKGROUND: Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan. OBJECTIVE: In this study, we leveraged longitudinal data from the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways. METHODS: PRS and p-PRSs with and without APOE were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers in a subset. Replication analyses were performed in an independent sample. RESULTS: We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of PRS/p-PRSs on rate of change in cognition, amyloid-ß, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded. CONCLUSION: In addition to APOE, the p-PRSs can predict age-dependent changes in amyloid-ß, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating amyloid-ß and tau, long before the onset of clinical symptoms.

A comparison of diagnostic performance of word-list and story recall tests for biomarker-determined Alzheimer's disease.

BACKGROUND: Wordlist and story recall tests are routinely employed in clinical practice for dementia diagnosis. In this study, our aim was to establish how well-standard clinical metrics compared to process scores derived from wordlist and story recall tests in predicting biomarker determined Alzheimer's disease, as defined by CSF ptau/Aß42 ratio. METHODS: Data from 295 participants (mean age = 65 ± 9.) were drawn from the University of Wisconsin - Madison Alzheimer's Disease Research Center (ADRC) and Wisconsin Registry for Alzheimer's Prevention (WRAP). Rey's Auditory Verbal Learning Test (AVLT; wordlist) and Logical Memory Test (LMT; story) data were used. Bayesian linear regression analyses were carried out with CSF ptau/Aß42 ratio as outcome. Sensitivity analyses were carried out with logistic regressions to assess diagnosticity. RESULTS: LMT generally outperformed AVLT. Notably, the best predictors were primacy ratio, a process score indexing loss of information learned early during test administration, and recency ratio, which tracks loss of recently learned information. Sensitivity analyses confirmed this conclusion. CONCLUSIONS: Our study shows that story recall tests may be better than wordlist tests for detection of dementia, especially when employing process scores alongside conventional clinical scores.

Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes.

We describe the multimodal neuroimaging dataset VEPCON (OpenNeuro Dataset ds003505). It includes raw data and derivatives of high-density EEG, structural MRI, diffusion weighted images (DWI) and single-trial behavior (accuracy, reaction time). Visual evoked potentials (VEPs) were recorded while participants (n = 20) discriminated briefly presented faces from scrambled faces, or coherently moving stimuli from incoherent ones. EEG and MRI were recorded separately from the same participants. The dataset contains raw EEG and behavioral data, pre-processed EEG of single trials in each condition, structural MRIs, individual brain parcellations at 5 spatial resolutions (83 to 1015 regions), and the corresponding structural connectomes computed from fiber count, fiber density, average fractional anisotropy and mean diffusivity maps. For source imaging, VEPCON provides EEG inverse solutions based on individual anatomy, with Python and Matlab scripts to derive activity time-series in each brain region, for each parcellation level. The BIDS-compatible dataset can contribute to multimodal methods development, studying structure-function relations, and to unimodal optimization of source imaging and graph analyses, among many other possibilities.

Linear distributed inverse solutions for interictal EEG source localisation.

OBJECTIVE: To compare the spatial accuracy of 6 linear distributed inverse solutions for EEG source localisation of interictal epileptic discharges: Minimum Norm, Weighted Minimum Norm, Low-Resolution Electromagnetic Tomography (LORETA), Local Autoregressive Average (LAURA), Standardised LORETA, and Exact LORETA. METHODS: Spatial accuracy was assessed clinically by retrospectively comparing the maximum source of averaged interictal discharges to the resected brain area in 30 patients with successful epilepsy surgery, based on 204-channel EEG. Additionally, localisation errors of the inverse solutions were assessed in computer simulations, with different levels of noise added to the signal in both sensor space and source space. RESULTS: In the clinical evaluations, the source maximum was located inside the resected brain area in 50-57% of patients when using LORETA or LAURA, while all other inverse solutions performed significantly worse (17-30%; corrected p < 0.01). In the simulation studies, when noise levels exceeded 10%, LORETA and LAURA had substantially smaller localisation errors than the other inverse solutions. CONCLUSIONS: LORETA and LAURA provided the highest spatial accuracy both in clinical and simulated data, alongside with a comparably high robustness towards noise. SIGNIFICANCE: Among the different linear inverse solution algorithms tested, LORETA and LAURA might be preferred for interictal EEG source localisation.

Brain networks involved in generalized periodic discharges (GPD) in post-anoxic-ischemic encephalopathy.

AIM: Generalized periodic discharge (GPD) is an EEG pattern of poor neurological outcome, frequently observed in comatose patients after cardiac arrest. The aim of our study was to identify the neuronal network generating ≤2.5 Hz GPD using EEG source localization and connectivity analysis. METHODS: We analyzed 40 comatose adult patients with anoxic-ischemic encephalopathy, who had 19 channel-EEG recording. We computed electric source analysis based on distributed inverse solution (LAURA) and we estimated cortical activity in 82 atlas-based cortical brain regions. We applied directed connectivity analysis (Partial Directed Coherence) on these sources to estimate the main drivers. RESULTS: Source analysis suggested that the GPD are generated in the cortex of the limbic system in the majority of patients (87.5%). Connectivity analysis revealed main drivers located in thalamus and hippocampus for the large majority of patients (80%), together with important activation also in amygdala (70%). CONCLUSIONS: We hypothesize that the anoxic-ischemic dysfunction, leading to hyperactivity of the thalamo-cortical (limbic presumably) circuit, can result in an oscillatory thalamic activity capable of inducing periodic cortical (limbic, mostly medial-temporal and orbitofrontal) discharges, similarly to the case of generalized rhythmic spike-wave discharge in convulsive or non-convulsive status epilepticus.

Using structural connectivity to augment community structure in EEG functional connectivity.

Recently, EEG recording techniques and source analysis have improved, making it feasible to tap into fast network dynamics. Yet, analyzing whole-cortex EEG signals in source space is not standard, partly because EEG suffers from volume conduction: Functional connectivity (FC) reflecting genuine functional relationships is impossible to disentangle from spurious FC introduced by volume conduction. Here, we investigate the relationship between white matter structural connectivity (SC) and large-scale network structure encoded in EEG-FC. We start by confirming that FC (power envelope correlations) is predicted by SC beyond the impact of Euclidean distance, in line with the assumption that SC mediates genuine FC. We then use information from white matter structural connectivity in order to smooth the EEG signal in the space spanned by graphs derived from SC. Thereby, FC between nearby, structurally connected brain regions increases while FC between nonconnected regions remains unchanged, resulting in an increase in genuine, SC-mediated FC. We analyze the induced changes in FC, assessing the resemblance between EEG-FC and volume-conduction- free fMRI-FC, and find that smoothing increases resemblance in terms of overall correlation and community structure. This result suggests that our method boosts genuine FC, an outcome that is of interest for many EEG network neuroscience questions.

High-density Electric Source Imaging of interictal epileptic discharges: How many electrodes and which time point?

OBJECTIVE: To assess the value of caudal EEG electrodes over cheeks and neck for high-density electric source imaging (ESI) in presurgical epilepsy evaluation, and to identify the best time point during averaged interictal epileptic discharges (IEDs) for optimal ESI accuracy. METHODS: We retrospectively examined presurgical 257-channel EEG recordings of 45 patients with pharmacoresistant focal epilepsy. By stepwise removal of cheek and neck electrodes, averaged IEDs were downsampled to 219, 204, and 156 EEG channels. Additionally, ESI at the IED's half-rise was compared to other time points. The respective sources of maximum activity were compared to the resected brain area and postsurgical outcome. RESULTS: Caudal channels had disproportionately more artefacts. In 30 patients with favourable outcome, the 204-channel array yielded the most accurate results with ESI maxima < 10 mm from the resection in 67% and inside affected sublobes in 83%. Neither in temporal nor in extratemporal cases did the full 257-channel setup improve ESI accuracy. ESI was most accurate at 50% of the IED's rising phase. CONCLUSION: Information from cheeks and neck electrodes did not improve high-density ESI accuracy, probably due to higher artefact load and suboptimal biophysical modelling. SIGNIFICANCE: Very caudal EEG electrodes should be used for ESI with caution.