Study Results
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Basic Information
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UNKNOWN
2000 participants
OBSERVATIONAL
2018-07-20
2020-11-30
Brief Summary
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Detailed Description
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Quantitative electroencephalograph (qEEG) is a non-invasive assessment which records multi-channel EEG event-related potentials (ERPs) and a comprehensive multi-dimensional analysis of such recordings by advanced algorithms aimed at understanding and visualizing the network complexity of brain function. Our goal is to compare assessments from both symptomatic and asymptomatic individuals to further develop differential diagnoses in the early-most stages of preclinical AD. Expounding upon an investigative technique that has shown promise in identifying region-specific abnormalities in concussed patients not only allows us to take advantage of an existing framework which provides a clear and elegant topographical output but also establishes a repeatable metric for quantifying MCI related dysfunction. Abiding by the measures within the existing framework contributes to a more standardized neurodiagnostic approach for dementia-related pathologies and supports continuity of care.
Ultimately this neurophysiological assessment will shed new light on the progression of cognitive impairment and the response of developing therapeutic interventions for a variety of neurologic, psychiatric and behavioral conditions. The WAVi system uses algorithms and sets of signal processing and pattern recognition techniques to seek and map activated neural pathways in task-related data points with respect to time, location, amplitude, and frequency. By projecting the individual data points into clusters, they reveal three-dimensional images of brain network activation patterns which represent high resolution functional neural pathways. These brain network patterns and scores can aid clinicians with profiling of brain functionality in comparison to the reference brain network model to assess similarity to normal brain functioning. Measuring alterations in functionality and/or dysfunctionality can potentially assist treatment courses following changes in disease progression. When combined with data supplied from information from self-reported and observed cognitive and behavior patterns clarity arises with respect to brain processes and determination of the medical condition.
For this investigation we will evaluate the ability of qEEG P300 and P50 waveform amplitudes and auditory response times to differentiate healthy aging individuals from those developing MCI characteristics. WAVi recording in the awake-responding state is an ideal low-cost and non-invasive methodology with a high temporal resolution (milliseconds) that provides an optimal investigational tool for the emerging features of brain pathophysiology. These procedures are well-tolerated by patients, unaffected by task difficulty and are widely available to all subpopulations, even those traditionally underrepresented in clinical study. Additionally, they can be repeated over time without habituation effects.
Aim 1 determines individual baseline qEEG P300/P50 amplitudes and auditory response times in a population of healthy participants ages 50-65 without a history of dementia that have previously received PET scan imaging. Assess the population mean, median and variability. If possible, a subset will be retested at a standard interval to determine test-retest reliability for this instrument.
Aim 2 evaluates the ability of qEEG P300 amplitudes and auditory response times to discriminate between aged participants with MCI/preclinical AD symptoms and healthy participants of similar age.
Aim 3 evaluates the ability of qEEG P50 amplitudes to discriminate between aged participants with MCI/preclinical AD symptoms and healthy participants of similar age.
Aim 4 confirms the efficacy of qEEG/amyloid plaque loading correlation with previous PET scan imaging data.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Early stage of MCI symptoms
Subjects with cognitive decline representing MCI symptomology and with previous PET amyloid-beta (Aβ) imaging results.
EEG scan
WAVi EEG and evoked potential platform. Participants will be scanned using the ElectroCap (FDA Class II) and/or the WAVi Headset with the WAVi Co EEG P300 system, along with the structured clinical interviews and assessments for the various ailments or baseline screenings
Interventions
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EEG scan
WAVi EEG and evoked potential platform. Participants will be scanned using the ElectroCap (FDA Class II) and/or the WAVi Headset with the WAVi Co EEG P300 system, along with the structured clinical interviews and assessments for the various ailments or baseline screenings
Eligibility Criteria
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Inclusion Criteria
* Medicare beneficiary;
* Diagnosis of MCI or dementia, according to DSM-IV and/or National Institutes of Aging-Alzheimer's Association criteria, verified by a dementia specialist within 24 months (American Psychiatric Association. 2000; McKhann et al. 2011; Albert et al. 2011);
* Cognitive complaint verified by objectively confirmed cognitive impairment;
Exclusion Criteria
* Normal cognition or subjective complaints that are not verified by cognitive testing.
* Knowledge of amyloid status, in the opinion of the referring dementia expert, may cause significant psychological harm or otherwise negatively impact the patient or family.
* Scan being ordered for nonmedical purposes (e.g., legal, insurance coverage, or employment screening).
* Cancer requiring active therapy (excluding non-melanoma skin cancer);
* Life expectancy less than 24 months based on medical co-morbidities;
* Residence in a skilled nursing facility.
60 Years
ALL
No
Sponsors
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Institute of Asian American Adult Development
UNKNOWN
Metabolic Therapy Inc.
OTHER
Responsible Party
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Locations
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Translational Cognitive Research
Houston, Texas, United States
Countries
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Central Contacts
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Facility Contacts
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Dewey Brown II, PhD
Role: primary
References
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Smailovic U, Koenig T, Kareholt I, Andersson T, Kramberger MG, Winblad B, Jelic V. Quantitative EEG power and synchronization correlate with Alzheimer's disease CSF biomarkers. Neurobiol Aging. 2018 Mar;63:88-95. doi: 10.1016/j.neurobiolaging.2017.11.005. Epub 2017 Nov 16.
Kramberger MG, Kareholt I, Andersson T, Winblad B, Eriksdotter M, Jelic V. Association between EEG abnormalities and CSF biomarkers in a memory clinic cohort. Dement Geriatr Cogn Disord. 2013;36(5-6):319-28. doi: 10.1159/000351677. Epub 2013 Sep 10.
Stomrud E, Hansson O, Minthon L, Blennow K, Rosen I, Londos E. Slowing of EEG correlates with CSF biomarkers and reduced cognitive speed in elderly with normal cognition over 4 years. Neurobiol Aging. 2010 Feb;31(2):215-23. doi: 10.1016/j.neurobiolaging.2008.03.025.
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1. Cassani R, Falk TH, Fraga FJ, Cecchi M, Moore DK, Anghinah R. Towards automated electroencephalography-based Alzheimer's disease diagnosis using portable low-density devices. Biomedical Signal Processing and Control. 2017,33:261-71.
Pratap-Chand R, Sinniah M, Salem FA. Cognitive evoked potential (P300): a metric for cerebral concussion. Acta Neurol Scand. 1988 Sep;78(3):185-9. doi: 10.1111/j.1600-0404.1988.tb03643.x.
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van Dinteren R, Arns M, Jongsma ML, Kessels RP. P300 development across the lifespan: a systematic review and meta-analysis. PLoS One. 2014 Feb 13;9(2):e87347. doi: 10.1371/journal.pone.0087347. eCollection 2014.
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Frodl T, Hampel H, Juckel G, Burger K, Padberg F, Engel RR, Moller HJ, Hegerl U. Value of event-related P300 subcomponents in the clinical diagnosis of mild cognitive impairment and Alzheimer's Disease. Psychophysiology. 2002 Mar;39(2):175-81. doi: 10.1017/S0048577202010260.
Bennys K, Portet F, Touchon J, Rondouin G. Diagnostic value of event-related evoked potentials N200 and P300 subcomponents in early diagnosis of Alzheimer's disease and mild cognitive impairment. J Clin Neurophysiol. 2007 Oct;24(5):405-12. doi: 10.1097/WNP.0b013e31815068d5.
Papaliagkas VT, Anogianakis G, Tsolaki MN, Koliakos G, Kimiskidis VK. Combination of P300 and CSF beta-amyloid(1-42) assays may provide a potential tool in the early diagnosis of Alzheimer's disease. Curr Alzheimer Res. 2010 Jun;7(4):295-9. doi: 10.2174/156720510791162421.
Korzyukov O, Pflieger ME, Wagner M, Bowyer SM, Rosburg T, Sundaresan K, Elger CE, Boutros NN. Generators of the intracranial P50 response in auditory sensory gating. Neuroimage. 2007 Apr 1;35(2):814-26. doi: 10.1016/j.neuroimage.2006.12.011. Epub 2006 Dec 19.
Golob EJ, Johnson JK, Starr A. Auditory event-related potentials during target detection are abnormal in mild cognitive impairment. Clin Neurophysiol. 2002 Jan;113(1):151-61. doi: 10.1016/s1388-2457(01)00713-1.
Green DL, Payne L, Polikar R, Moberg PJ, Wolk DA, Kounios J. P50: A candidate ERP biomarker of prodromal Alzheimer's disease. Brain Res. 2015 Oct 22;1624:390-397. doi: 10.1016/j.brainres.2015.07.054. Epub 2015 Aug 6.
Boutros NN, Belger A. Midlatency evoked potentials attenuation and augmentation reflect different aspects of sensory gating. Biol Psychiatry. 1999 Apr 1;45(7):917-22. doi: 10.1016/s0006-3223(98)00253-4.
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Azumi T, Nakashima K, Takahashi K. Aging effects on auditory middle latency responses. Electromyogr Clin Neurophysiol. 1995 Nov;35(7):397-401.
Hubl D, Kleinlogel H, Frolich L, Weinandi T, Maurer K, Holstein W, Czekalla J, Dierks T. Multilead quantitative electroencephalogram profile and cognitive evoked potentials (P300) in healthy subjects after a single dose of olanzapine. Psychopharmacology (Berl). 2001 Nov;158(3):281-8. doi: 10.1007/s002130100861.
Other Identifiers
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1R02TCR0072518
Identifier Type: -
Identifier Source: org_study_id
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