Resting-state EEG signatures of Alzheimer's disease are driven by periodic but not aperiodic changes.

Electroencephalography (EEG) has shown potential for identifying early-stage biomarkers of neurocognitive dysfunction associated with dementia due to Alzheimer's disease (AD). A large body of evidence shows that, compared to healthy controls (HC), AD is associated with power increases in lower EEG frequencies (delta and theta) and decreases in higher frequencies (alpha and beta), together with slowing of the peak alpha frequency. However, the pathophysiological processes underlying these changes remain unclear. For instance, recent studies have shown that apparent shifts in EEG power from high to low frequencies can be driven either by frequency specific periodic power changes or rather by non-oscillatory (aperiodic) changes in the underlying 1/f slope of the power spectrum. Hence, to clarify the mechanism(s) underlying the EEG alterations associated with AD, it is necessary to account for both periodic and aperiodic characteristics of the EEG signal. Across two independent datasets, we examined whether resting-state EEG changes linked to AD reflect true oscillatory (periodic) changes, changes in the aperiodic (non-oscillatory) signal, or a combination of both. We found strong evidence that the alterations are purely periodic in nature, with decreases in oscillatory power at alpha and beta frequencies (AD < HC) leading to lower (alpha + beta) / (delta + theta) power ratios in AD. Aperiodic EEG features did not differ between AD and HC. By replicating the findings in two cohorts, we provide robust evidence for purely oscillatory pathophysiology in AD and against aperiodic EEG changes. We therefore clarify the alterations underlying the neural dynamics in AD and emphasize the robustness of oscillatory AD signatures, which may further be used as potential prognostic or interventional targets in future clinical investigations.

Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition.

Large-scale brain networks are often described using resting-state functional magnetic resonance imaging (fMRI). However, the blood oxygenation level-dependent (BOLD) signal provides an indirect measure of neuronal firing and reflects slow-evolving hemodynamic activity that fails to capture the faster timescale of normal physiological function. Here we used fMRI-guided transcranial magnetic stimulation (TMS) and simultaneous electroencephalography (EEG) to characterize individual brain dynamics within discrete brain networks at high temporal resolution. TMS was used to induce controlled perturbations to individually defined nodes of the default mode network (DMN) and the dorsal attention network (DAN). Source-level EEG propagation patterns were network-specific and highly reproducible across sessions 1 month apart. Additionally, individual differences in high-order cognitive abilities were significantly correlated with the specificity of TMS propagation patterns across DAN and DMN, but not with resting-state EEG dynamics. Findings illustrate the potential of TMS-EEG perturbation-based biomarkers to characterize network-level individual brain dynamics at high temporal resolution, and potentially provide further insight on their behavioral significance.

Phase-dependent local brain states determine the impact of image-guided transcranial magnetic stimulation on motor network electroencephalographic synchronization.

Recent studies have synchronized transcranial magnetic stimulation (TMS) application with pre-defined brain oscillatory phases showing how brain response to perturbation depends on the brain state. However, none have investigated whether phase-dependent TMS can possibly modulate connectivity with homologous distant brain regions belonging to the same network. In the framework of network-targeted TMS, we investigated whether stimulation delivered at a specific phase of ongoing brain oscillations might favour stronger cortico-cortical (c-c) synchronization of distant network nodes connected to the stimulation target. Neuronavigated TMS pulses were delivered over the primary motor cortex (M1) during ongoing electroencephalography recording in 24 healthy individuals over two repeated sessions 1 month apart. Stimulation effects were analysed considering whether the TMS pulse was delivered at the time of a positive (peak) or negative (trough) phase of µ-frequency oscillation, which determines c-c synchrony within homologous areas of the sensorimotor network. Diffusion weighted imaging was used to study c-c connectivity within the sensorimotor network and identify contralateral regions connected with the stimulation spot. Depending on when during the µ-activity the TMS-pulse was applied (peak or trough), its impact on inter-hemispheric network synchrony varied significantly. Higher M1-M1 phase-lock synchronization after the TMS-pulse (0-200 ms) in the µ-frequency band was found for trough compared to peak stimulation trials in both study visits. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of the response to the external perturbation, with implications for interventions aimed at engaging more distributed functional brain networks. KEY POINTS: Synchronized transcranial magnetic stimulation (TMS) pulses with pre-defined brain oscillatory phases allow evaluation of the impact of brain states on TMS effects. TMS pulses over M1 at the negative peak of the µ-frequency band induce higher phase-lock synchronization with interconnected contralateral homologous regions. Cortico-cortical synchronization changes are linearly predicted by the fibre density and cross-section of the white matter tract that connects the two brain regions. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of within-network synchronization.

Effect of group-based vs individualized stimulation site selection on reliability of network-targeted TMS.

BACKGROUND: Transcranial magnetic stimulation (TMS) is a widely used technique for the noninvasive assessment and manipulation of brain activity and behavior. Although extensively used for research and clinical purposes, recent studies have questioned the reliability of TMS findings because of the high inter-individual variability that has been observed. OBJECTIVE: In this study, we compared the efficacy and reliability of different targeting scenarios on the TMS-evoked response. METHODS: 24 subjects underwent a single pulse stimulation protocol over two parietal nodes belonging to the Dorsal Attention (DAN) and Default Mode (DMN) Networks respectively. Across visits, the stimulated target for both networks was chosen either based on group-derived networks' maps or personalized network topography based on individual anatomy and functional profile. All stimulation visits were conducted twice, one month apart, during concomitant electroencephalography recording. RESULTS: At the network level, we did not observe significant differences in the TMS-evoked response between targeting conditions. However, reliable patterns of activity were observed- for both networks tested- following the individualized targeting approach. When the same analyses were carried out at the electrode space level, evidence of reliable patterns was observed following the individualized stimulation of the DAN, but not of the DMN. CONCLUSIONS: Our findings suggest that individualization of stimulation sites might ensure reliability of the evoked TMS-response across visits. Furthermore, individualized stimulation sites appear to be of foremost importance in highly variable, high order task-positive networks, such as the DAN.

Electroencephalographic Abnormalities are Common in COVID-19 and are Associated with Outcomes.

OBJECTIVE: The aim was to determine the prevalence and risk factors for electrographic seizures and other electroencephalographic (EEG) patterns in patients with Coronavirus disease 2019 (COVID-19) undergoing clinically indicated continuous electroencephalogram (cEEG) monitoring and to assess whether EEG findings are associated with outcomes. METHODS: We identified 197 patients with COVID-19 referred for cEEG at 9 participating centers. Medical records and EEG reports were reviewed retrospectively to determine the incidence of and clinical risk factors for seizures and other epileptiform patterns. Multivariate Cox proportional hazards analysis assessed the relationship between EEG patterns and clinical outcomes. RESULTS: Electrographic seizures were detected in 19 (9.6%) patients, including nonconvulsive status epilepticus (NCSE) in 11 (5.6%). Epileptiform abnormalities (either ictal or interictal) were present in 96 (48.7%). Preceding clinical seizures during hospitalization were associated with both electrographic seizures (36.4% in those with vs 8.1% in those without prior clinical seizures, odds ratio [OR] 6.51, p = 0.01) and NCSE (27.3% vs 4.3%, OR 8.34, p = 0.01). A pre-existing intracranial lesion on neuroimaging was associated with NCSE (14.3% vs 3.7%; OR 4.33, p = 0.02). In multivariate analysis of outcomes, electrographic seizures were an independent predictor of in-hospital mortality (hazard ratio [HR] 4.07 [1.44-11.51], p < 0.01). In competing risks analysis, hospital length of stay increased in the presence of NCSE (30 day proportion discharged with vs without NCSE: HR 0.21 [0.03-0.33] vs 0.43 [0.36-0.49]). INTERPRETATION: This multicenter retrospective cohort study demonstrates that seizures and other epileptiform abnormalities are common in patients with COVID-19 undergoing clinically indicated cEEG and are associated with adverse clinical outcomes. ANN NEUROL 2021;89:872-883.

Network-level macroscale structural connectivity predicts propagation of transcranial magnetic stimulation.

Information processing in the brain is mediated by structural white matter pathways and is highly dependent on topological brain properties. Here we combined transcranial magnetic stimulation (TMS) with high-density electroencephalography (EEG) and Diffusion Weighted Imaging (DWI), specifically looking at macroscale connectivity to understand whether regional, network-level or whole-brain structural properties are more responsible for stimulus propagation. Neuronavigated TMS pulses were delivered over two individually defined nodes of the default mode (DMN) and dorsal attention (DAN) networks in a group of healthy subjects, with test-retest reliability assessed 1-month apart. TMS-evoked activity was predicted by the modularity and structural integrity of the stimulated network rather than the targeted region(s) or the whole-brain connectivity, suggesting network-level structural connectivity as more relevant than local and global brain properties in shaping TMS signal propagation. The importance of network structural connectome was unveiled only by evoked activity, but not resting-state data. Future clinicals interventions might enhance target engagement by adopting DWI-guided, network-focused TMS.

EEG Functional Connectivity is a Weak Predictor of Causal Brain Interactions.

In recent years there has been an explosion of research evaluating resting-state brain functional connectivity (FC) using different modalities. However, the relationship between such measures of FC and the underlying causal brain interactions has not been well characterized. To further characterize this relationship, we assessed the relationship between electroencephalography (EEG) resting state FC and propagation of transcranial magnetic stimulation (TMS) evoked potentials (TEPs) at the sensor and source level in healthy participants. TMS was applied to six different cortical regions in ten healthy individuals (9 male; 1 female), and effects on brain activity were measured using simultaneous EEG. Pre-stimulus FC was assessed using five different FC measures (Pearson's correlation, mutual information, weighted phase lag index, coherence and phase locking value). Propagation of the TEPs was quantified as the root mean square (RMS) of the TEP voltage and current source density (CSD) at the sensor and source level, respectively. The relationship between pre-stimulus FC and the spatial distribution of TEP activity was determined using a generalized linear model (GLM) analysis. On the group level, all FC measures correlated significantly with TEP activity over the early (15-75 ms) and full range (15-400 ms) of the TEP at the sensor and source level. However, the predictive value of all FC measures is quite limited, accounting for less than 10% of the variance of TEP activity, and varies substantially across participants and stimulation sites. Taken together, these results suggest that EEG functional connectivity studies in sensor and source space should be interpreted with caution.

Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: A prospective study of diagnostic accuracy.

OBJECTIVE: Delayed cerebral ischemia (DCI) is a common, disabling complication of subarachnoid hemorrhage (SAH). Preventing DCI is a key focus of neurocritical care, but interventions carry risk and cannot be applied indiscriminately. Although retrospective studies have identified continuous electroencephalographic (cEEG) measures associated with DCI, no study has characterized the accuracy of cEEG with sufficient rigor to justify using it to triage patients to interventions or clinical trials. We therefore prospectively assessed the accuracy of cEEG for predicting DCI, following the Standards for Reporting Diagnostic Accuracy Studies. METHODS: We prospectively performed cEEG in nontraumatic, high-grade SAH patients at a single institution. The index test consisted of clinical neurophysiologists prospectively reporting prespecified EEG alarms: (1) decreasing relative alpha variability, (2) decreasing alpha-delta ratio, (3) worsening focal slowing, or (4) late appearing epileptiform abnormalities. The diagnostic reference standard was DCI determined by blinded, adjudicated review. Primary outcome measures were sensitivity and specificity of cEEG for subsequent DCI, determined by multistate survival analysis, adjusted for baseline risk. RESULTS: One hundred three of 227 consecutive patients were eligible and underwent cEEG monitoring (7.7-day mean duration). EEG alarms occurred in 96.2% of patients with and 19.6% without subsequent DCI (1.9-day median latency, interquartile range = 0.9-4.1). Among alarm subtypes, late onset epileptiform abnormalities had the highest predictive value. Prespecified EEG findings predicted DCI among patients with low (91% sensitivity, 83% specificity) and high (95% sensitivity, 77% specificity) baseline risk. INTERPRETATION: cEEG accurately predicts DCI following SAH and may help target therapies to patients at highest risk of secondary brain injury. Ann Neurol 2018;83:958-969.

EEG Microstate Correlates of Fluid Intelligence and Response to Cognitive Training.

The neurobiological correlates of human fluid intelligence (Gf) remain elusive. Here, we demonstrate that spatiotemporal dynamics of EEG activity correlate with baseline measures of Gf and with its modulation by cognitive training. EEG dynamics were assessed in 74 healthy participants by examination of fast-changing, recurring, topographically-defined electric patterns termed "microstates", which characterize the electrophysiological activity of distributed cortical networks. We find that the frequency of appearance of specific brain topographies, spatially associated with visual (microstate B) and executive control (microstate C) networks, respectively, is inversely related to Gf scores. Moreover, changes in Gf scores with cognitive training are inversely correlated with changes in microstate properties, indicating that the changes in brain network dynamics are behaviorally relevant. Finally, we find that cognitive training that increases Gf scores results in a posterior shift in the topography of microstate C. These results highlight the role of fast-changing brain electrical states in individual variability in Gf and in the response to cognitive training.

Physiological consequences of abnormal connectivity in a developmental epilepsy.

OBJECTIVE: Many forms of epilepsy are associated with aberrant neuronal connections, but the relationship between such pathological connectivity and the underlying physiological predisposition to seizures is unclear. We sought to characterize the cortical excitability profile of a developmental form of epilepsy known to have structural and functional connectivity abnormalities. METHODS: We employed transcranial magnetic stimulation (TMS) with simultaneous electroencephalographic (EEG) recording in 8 patients with epilepsy from periventricular nodular heterotopia and matched healthy controls. We used connectivity imaging findings to guide TMS targeting and compared the evoked responses to single-pulse stimulation from different cortical regions. RESULTS: Heterotopia patients with active epilepsy demonstrated a relatively augmented late cortical response that was greater than that of matched controls. This abnormality was specific to cortical regions with connectivity to subcortical heterotopic gray matter. Topographic mapping of the late response differences showed distributed cortical networks that were not limited to the stimulation site, and source analysis in 1 subject revealed that the generator of abnormal TMS-evoked activity overlapped with the spike and seizure onset zone. INTERPRETATION: Our findings indicate that patients with epilepsy from gray matter heterotopia have altered cortical physiology consistent with hyperexcitability, and that this abnormality is specifically linked to the presence of aberrant connectivity. These results support the idea that TMS-EEG could be a useful biomarker in epilepsy in gray matter heterotopia, expand our understanding of circuit mechanisms of epileptogenesis, and have potential implications for therapeutic neuromodulation in similar epileptic conditions associated with deep lesions.

Preoperative Cognitive Performance Dominates Risk for Delirium Among Older Adults.

BACKGROUND: Cognitive impairment is a well-recognized risk factor for delirium. Our goal was to determine whether the level of cognitive performance across the nondemented cognitive ability spectrum is correlated with delirium risk and to gauge the importance of cognition relative to other known risk factors for delirium. METHODS: The Successful Aging after Elective Surgery study enrolled 566 adults aged ≥70 years scheduled for major surgery. Patients were assessed preoperatively and daily during hospitalization for the occurrence of delirium using the Confusion Assessment Method. Cognitive function was assessed preoperatively with an 11-test neuropsychological battery combined into a composite score for general cognitive performance (GCP). We examined the risk for delirium attributable to GCP, as well as demographic factors, vocabulary ability, and informant-rated cognitive decline, and compared the strength of association with risk factors identified in a previously published delirium prediction rule for delirium. RESULTS: Delirium occurred in 135 (24%) patients. Lower GCP score was strongly and linearly predictive of delirium risk (relative risk = 2.0 per each half standard deviation difference in GCP score, 95% confidence interval, 1.5-2.5). This effect was not attenuated by statistical adjustment for demographics, vocabulary ability, and informant-rated cognitive decline. The effect was stronger than, and largely independent from, both standard delirium risk factors and comorbidity. CONCLUSION: Risk of delirium is linearly and strongly related to presurgical cognitive performance level even at levels above the population median, which would be considered unimpaired.

Utility of foramen ovale electrodes in mesial temporal lobe epilepsy.

OBJECTIVES: To determine the ability of foramen ovale electrodes (FOEs) to localize epileptogenic foci after inconclusive noninvasive investigations in patients with suspected mesial temporal lobe epilepsy (MTLE). METHODS: We identified patients with medically intractable epilepsy who had undergone FOE investigation for initial invasive monitoring at our institution between 2005 and 2012. Indications for initiating FOE investigation were grouped into four categories: (1) bilateral anterior temporal ictal activity on scalp electroencephalography (EEG), (2) unclear laterality of scalp EEG onset due to muscle artifact or significant delay following clinical manifestation, (3) discordance between ictal and interictal discharges, and (4) investigation of a specific anatomic abnormality or competing putative focus. The FOE investigation was classified as informative if it provided sufficient evidence to make a treatment decision. RESULTS: Forty-two consecutive patients underwent FOE investigation, which was informative in 38 patients (90.5%). Of these 38 patients, 24 were determined to be appropriate candidates for resective surgery. Five were localized sufficiently for surgery, but were considered high risk for verbal memory deficit, and nine were deemed poor surgical candidates because of bilateral ictal origins. The remaining 4 of 42 patients had inconclusive FOE studies and were referred for further invasive investigation. Of the 18 patients who underwent resective surgery, 13 (72%) were seizure-free (Engel class I) at last follow-up (mean 22.5 months). SIGNIFICANCE: More than 90% of our 42 FOE studies provided sufficient evidence to render treatment decisions. When undertaken with an appropriate hypothesis, FOE investigations are a minimally invasive and efficacious means for evaluating patients with suspected MTLE after an inconclusive noninvasive investigation.

Modulation of EEG functional connectivity networks in subjects undergoing repetitive transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique that utilizes magnetic fluxes to alter cortical activity. Continuous theta-burst repetitive TMS (cTBS) results in long-lasting decreases in indices of cortical excitability, and alterations in performance of behavioral tasks. We investigated the effects of cTBS on cortical function via functional connectivity and graph theoretical analysis of EEG data. Thirty-one channel resting-state EEG recordings were obtained before and after 40 s of cTBS stimulation to the left primary motor cortex. Functional connectivity between nodes was assessed in multiple frequency bands using lagged max-covariance, and subsequently thresholded to construct undirected graphs. After cTBS, we find widespread decreases in functional connectivity in the alpha band. There are also simultaneous increases in functional connectivity in the high-beta bands, especially amongst anterior and interhemispheric connections. The analysis of the undirected graphs reveals that interhemispheric and interregional connections are more likely to be modulated after cTBS than local connections. There is also a shift in the topology of network connectivity, with an increase in the clustering coefficient after cTBS in the beta bands, and a decrease in clustering and increase in path length in the alpha band, with the alpha-band connectivity primarily decreased near the site of stimulation. cTBS produces widespread alterations in cortical functional connectivity, with resulting shifts in cortical network topology.

Sensitivity of compressed spectral arrays for detecting seizures in acutely ill adults.

BACKGROUND: Continuous EEG recordings (cEEGs) are increasingly used in evaluation of acutely ill adults. Pre-screening using compressed data formats, such as compressed spectral array (CSA), may accelerate EEG review. We tested whether screening with CSA can enable detection of seizures and other relevant patterns. METHODS: Two individuals reviewed the CSA displays of 113 cEEGs. While blinded to the raw EEG data, they marked each visually homogeneous CSA segment. An independent experienced electroencephalographer reviewed the raw EEG within 60 s on either side of each mark and recorded any seizures (and isolated epileptiform discharges, periodic epileptiform discharges (PEDs), rhythmic delta activity (RDA), and focal or generalized slowing). Seizures were considered to have been detected if the CSA mark was within 60 s of the seizure. The electroencephalographer then determined the total number of seizures (and other critical findings) for each record by exhaustive, page-by-page review of the entire raw EEG. RESULTS: Within each of the 39 cEEG recordings containing seizures, one CSA reviewer identified at least one seizure, while the second CSA reviewer identified 38/39 patients with seizures. The overall detection rate was 89.0 % of 1,190 total seizures. When present, an average of 87.9 % of seizures were detected per individual patient. Detection rates for other critical findings were as follows: epileptiform discharges, 94.0 %; PEDs, 100 %; RDA, 97.9 %; focal slowing, 100 %; and generalized slowing, 100 %. CONCLUSIONS: CSA-guided review can support sensitive screening of critical pathological information in cEEG recordings. However, some patients with seizures may not be identified.

High risk for seizures following subarachnoid hemorrhage regardless of referral bias.

BACKGROUND: To investigate the frequency, predictors, and clinical impact of electrographic seizures in patients with high clinical or radiologic grade non-traumatic subarachnoid hemorrhage (SAH), independent of referral bias. METHODS: We compared rates of electrographic seizures and associated clinical variables and outcomes in patients with high clinical or radiologic grade non-traumatic SAH. Rates of electrographic seizure detection before and after institution of a guideline which made continuous EEG monitoring routine in this population were compared. RESULTS: Electrographic seizures occurred in 17.6 % of patients monitored expressly because of clinically suspected subclinical seizures. In unselected patients, seizures still occurred in 9.6 % of all cases, and in 8.6 % of cases in which there was no a priori suspicion of seizures. The first seizure detected occurred 5.4 (IQR 2.9-7.3) days after onset of subarachnoid hemorrhage with three of eight patients (37.5 %) having the first recorded seizure more than 48 h following EEG initiation, and 2/8 (25 %) at more than 72 h following EEG initiation. High clinical grade was associated with poor outcome at time of hospital discharge; electrographic seizures were not associated with poor outcome. CONCLUSIONS: Electrographic seizures occur at a relatively high rate in patients with non-traumatic SAH even after accounting for referral bias. The prolonged time to the first detected seizure in this cohort may reflect dynamic clinical features unique to the SAH population.

Relationship between cortical brain atrophy, delirium, and long-term cognitive decline in older surgical patients.

In older patients, delirium after surgery is associated with long-term cognitive decline (LTCD). The neural substrates of this association are unclear. Neurodegenerative changes associated with dementia are possible contributors. We investigated the relationship between brain atrophy rates in Alzheimer's disease (AD) and cognitive aging signature regions from magnetic resonance imaging before and one year after surgery, LTCD assessed by the general cognitive performance (GCP) score over 6 years post-operatively, and delirium in 117 elective surgery patients without dementia (mean age = 76). The annual change in cortical thickness was 0.2(1.7) % (AD-signature p = 0.09) and 0.4(1.7) % (aging-signature p = 0.01). Greater atrophy was associated with LTCD (AD-signature: beta(CI) = 0.24(0.06-0.42) points of GCP/mm of cortical thickness; p < 0.01, aging-signature: beta(CI) = 0.55(0.07-1.03); p = 0.03). Atrophy rates were not significantly different between participants with and without delirium. We found an interaction with delirium severity in the association between atrophy and LTCD (AD-signature: beta(CI) = 0.04(0.00-0.08), p = 0.04; aging-signature: beta(CI) = 0.08(0.03-0.12), p < 0.01). The rate of cortical atrophy and severity of delirium are independent, synergistic factors determining postoperative cognitive decline in the elderly.

Successful aging after elective surgery II: Study cohort description.

BACKGROUND: The Successful Aging after Elective Surgery (SAGES) II Study was designed to examine the relationship between delirium and Alzheimer's disease and related dementias (AD/ADRD), by capturing novel fluid biomarkers, neuroimaging markers, and neurophysiological measurements. The goal of this paper is to provide the first complete description of the enrolled cohort, which details the baseline characteristics and data completion. We also describe the study modifications necessitated by the COVID-19 pandemic, and lay the foundation for future work using this cohort. METHODS: SAGES II is a prospective observational cohort study of community-dwelling adults age 65 and older undergoing major non-cardiac surgery. Participants were assessed preoperatively, throughout hospitalization, and at 1, 2, 6, 12, and 18 months following discharge to assess cognitive and physical functioning. Since participants were enrolled throughout the COVID-19 pandemic, procedural modifications were designed to reduce missing data and allow for high data quality. RESULTS: About 420 participants were enrolled with a mean (standard deviation) age of 73.4 (5.6) years, including 14% minority participants. Eighty-eight percent of participants had either total knee or hip replacements; the most common surgery was total knee replacement with 210 participants (50%). Despite the challenges posed by the COVID-19 pandemic, which required the use of novel procedures such as video assessments, there were minimal missing interviews during hospitalization and up to 1-month follow-up; nearly 90% of enrolled participants completed interviews through 6-month follow-up. CONCLUSION: While there are many longitudinal studies of older adults, this study is unique in measuring health outcomes following surgery, along with risk factors for delirium through the application of novel biomarkers-including fluid (plasma and cerebrospinal fluid), imaging, and electrophysiological markers. This paper is the first to describe the characteristics of this unique cohort and the data collected, enabling future work using this novel and important resource.

Prediction of Postoperative Delirium in Older Adults from Preoperative Cognition and Occipital Alpha Power from Resting-State Electroencephalogram.

BACKGROUND: Postoperative delirium is the most common complication following surgery among older adults, and has been consistently associated with increased mortality and morbidity, cognitive decline, and loss of independence, as well as markedly increased health-care costs. Electroencephalography (EEG) spectral slowing has frequently been observed during episodes of delirium, whereas intraoperative frontal alpha power is associated with postoperative delirium. We sought to identify preoperative predictors that could identify individuals at high risk for postoperative delirium, which could guide clinical decision-making and enable targeted interventions to potentially decrease delirium incidence and postoperative delirium-related complications. METHODS: In this prospective observational study, we used machine learning to evaluate whether baseline (preoperative) cognitive function and resting-state EEG could be used to identify patients at risk for postoperative delirium. Preoperative resting-state EEGs and the Montreal Cognitive Assessment were collected from 85 patients (age = 73 +- 6.4 years, 12 cases of delirium) undergoing elective surgery. The model with the highest f1-score was subsequently validated in an independent, prospective cohort of 51 older adults (age = 68 +- 5.2 years, 6 cases of delirium) undergoing elective surgery. RESULTS: Occipital alpha powers have higher f1-score than frontal alpha powers and EEG spectral slowing in the training cohort. Occipital alpha powers were able to predict postoperative delirium with AUC, specificity and accuracy all >90%, and sensitivity >80%, in the validation cohort. Notably, models incorporating transformed alpha powers and cognitive scores outperformed models incorporating occipital alpha powers alone or cognitive scores alone. CONCLUSIONS: While requiring prospective validation in larger cohorts, these results suggest that strong prediction of postoperative delirium may be feasible in clinical settings using simple and widely available clinical tools. Additionally, our results suggested that the thalamocortical circuit exhibits different EEG patterns under different stressors, with occipital alpha powers potentially reflecting baseline vulnerabilities.

Levetiracetam Increases Hippocampal Blood Flow in Alzheimer's Disease as Measured by Arterial Spin Labelling MRI.

BACKGROUND: Patients with Alzheimer's disease (AD) have an increased risk of developing epileptiform discharges, which is associated with a more rapid rate of progression. This suggests that suppression of epileptiform activity could have clinical benefit in patients with AD. OBJECTIVE: In the current study, we tested whether acute, intravenous administration of levetiracetam led to changes in brain perfusion as measured with arterial spin labeling MRI (ASL-MRI) in AD. METHODS: We conducted a double-blind, within-subject crossover design study in which participants with mild AD (n = 9) received placebo, 2.5 mg/kg, and 7.5 mg/kg of LEV intravenously in a random order in three sessions. Afterwards, the participants underwent ASL-MRI. RESULTS: Analysis of relative cerebral blood flow (rCBF) between 2.5 mg of levetiracetam and placebo showed significant decreases in a cluster that included the posterior cingulate cortex, the precuneus, and the posterior part of the cingulate gyrus, while increased cerebral blood flow was found in both temporal lobes involving the hippocampus. CONCLUSION: Administration of 2.5 mg/kg of LEV in patients without any history of epilepsy leads to changes in rCBF in areas known to be affected in the early stages of AD. These areas may be the focus of the epileptiform activity. Larger studies are needed to confirm the current findings.