Electrode Surface Area Impacts Measurement of High Frequency Oscillations in Human Intracranial EEG.

OBJECTIVE: High-frequency oscillations (HFOs) are a promising prognostic biomarker of surgical outcome in patients with epilepsy. Their rates of occurrence and morphology have been studied extensively using recordings from electrodes of various geometries. While electrode size is a potential confounding factor in HFO studies, it has largely been disregarded due to a lack of consistent evidence. Therefore, we designed an experiment to directly test the impact of electrode size on HFO measurement. METHODS: We first simulated HFO measurement using a lumped model of the electrode-tissue interaction. Then eight human subjects were each implanted with a high-density 8x8 grid of subdural electrodes. After implantation, the electrode sizes were altered using a technique recently developed by our group, enabling intracranial EEG recordings for three different electrode surface areas from a static brain location. HFOs were automatically detected in the data and their characteristics were calculated. RESULTS: The human subject measurements were consistent with the model. Specifically, HFO rate measured per area of tissue decreased significantly as electrode surface area increased. The smallest electrodes recorded more fast ripples than ripples. Amplitude of detected HFOs also decreased as electrode surface area increased, while duration and peak frequency were unaffected. CONCLUSION: These results suggest that HFO rates measured using electrodes of different surface areas cannot be compared directly. SIGNIFICANCE: This has significant implications for HFOs as a tool for surgical planning, particularly for individual patients implanted with electrodes of multiple sizes and comparisons of HFO rate made across patients and studies.

Automated detection of ripple oscillations in long-term scalp EEG from patients with infantile spasms.

Objective.Scalp high-frequency oscillations (HFOs) are a promising biomarker of epileptogenicity in infantile spasms (IS) and many other epilepsy syndromes, but prior studies have relied on visual analysis of short segments of data due to the prevalence of artifacts in EEG. Here we set out to robustly characterize the rate and spatial distribution of HFOs in large datasets from IS subjects using fully automated HFO detection techniques.Approach.We prospectively collected long-term scalp EEG data from 12 subjects with IS and 18 healthy controls. For patients with IS, recording began prior to diagnosis and continued through initiation of treatment with adrenocorticotropic hormone (ACTH). The median analyzable EEG duration was 18.2 h for controls and 84.5 h for IS subjects (∼1300 h total). Ripples (80-250 Hz) were detected in all EEG data using an automated algorithm.Main results.HFO rates were substantially higher in patients with IS compared to controls. In IS patients, HFO rates were higher during sleep compared to wakefulness (median 5.5 min-1and 2.9 min-1, respectively;p = 0.002); controls did not exhibit a difference in HFO rate between sleep and wakefulness (median 0.98 min-1and 0.82 min-1, respectively). Spatially, IS patients exhibited significantly higher rates of HFOs in the posterior parasaggital region and significantly lower HFO rates in frontal channels, and this difference was more pronounced during sleep. In IS subjects, ACTH therapy significantly decreased the rate of HFOs.Significance.Here we provide a detailed characterization of the spatial distribution and rates of HFOs associated with IS, which may have relevance for diagnosis and assessment of treatment response. We also demonstrate that our fully automated algorithm can be used to detect HFOs in long-term scalp EEG with sufficient accuracy to clearly discriminate healthy subjects from those with IS.

Relation of quantitative indexes of concurrent alpha-synuclein abnormalities to clinical outcome in autopsy-proven Alzheimer disease.

BACKGROUND: Lewy bodies (LBs) and Lewy neurites are frequent concomitant neuropathologic observations in clinical and neuropathologically defined Alzheimer disease (AD), but their relation to clinical features in AD is uncertain. Most studies used semiquantitative measures to determine the presence or absence of LB abnormalities. OBJECTIVE: To determine the clinical consequences of LB abnormalities in the setting of AD. DESIGN: Prospective study. SETTING: Three outpatient research and treatment centers. PARTICIPANTS: Fourteen autopsy cases with a pathologic diagnosis of AD abnormalities and concomitant LBs followed semiannually for up to 8 years (mean age at intake, 72 years; mean age at death, 77 years; mean education, 15 years; 12 women). MAIN OUTCOME MEASURES: The modified Mini-Mental State Examination was used to assess cognitive function. The Unified Parkinson Disease Rating Scale was used to rate extrapyramidal motor signs. Hallucinations were evaluated using the Columbia University Scale for Psychopathology in Alzheimer's Disease. Time from the first evaluation in which diagnostic criteria for probable AD were met to death was used to determine illness duration. Quantitative measures of LB abnormalities were obtained for the frontal cortex, entorhinal cortex, substantia nigra, and hippocampus. RESULTS: Independent-samples t tests were used to assess whether the degree of LB abnormality varied as a function of the presence or absence of hallucinations and extrapyramidal signs. Pearson r correlations were run to examine whether there was a relation among LB abnormalities, cognitive function, and illness duration. There was no relation between quantitative neuropathologic indexes of LB abnormalities and clinical outcome. CONCLUSION: The variability of clinical features in AD was not related to the presence or degree of LB abnormalities.

Longitudinal assessment of patient dependence in Alzheimer disease.

BACKGROUND: The Dependence Scale measures the amount of assistance patients with dementia require in performing daily activities. Validity and reliability of this scale have been demonstrated, but the progression throughout long periods in patients with Alzheimer disease (AD) has not previously been examined. OBJECTIVE: To determine the longitudinal course of patient dependence in a cohort of prospectively followed AD patients. METHODS: Two hundred thirty AD patients enrolled in the Predictors Study were followed up prospectively at 6-month intervals for an average of 6.5 visits. The Dependence Scale was administered to a caregiver, and patients were assessed with the modified Mini-Mental State Examination (mMMSE) and the Blessed Dementia Rating Scale. Dependence level and the additive sum of the Dependence Scale items were considered for analysis. RESULTS: Generalized estimating equations to regression analyses were used to determine that both Dependence Scale scores and dependence level significantly decline with time. By covarying mMMSE scores and self-care deficits factor scores of the Blessed Dementia Rating Scale, generalized estimating equations analysis also demonstrated that change in patient dependence was independent of global cognitive decline and other measures of activities of daily living, respectively. CONCLUSIONS: This study shows the validity of the Dependence Scale and demonstrated that dependency in AD significantly declines with time independent of global cognition and other self-care deficits. The scale is a valuable instrument for outcomes research, efficacy trials, and behavioral research in AD.