4.7 Article

EEG/ERP: Within Episodic Assessment Framework for Cognition

Journal

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 66, Issue 10, Pages 2525-2534

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2017.2668618

Keywords

Electroencephalogram (EEG); event-related potentials (ERPs); mild cognitive impairment (MCI)

Funding

  1. Bruyere Research Institute Growth Fund
  2. Mitacs Accelerate Program
  3. DynamicBrain Inc.
  4. Chartwell Retirement Residences Inc.

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This work explores the potential for electroencephalography (EEG)-based event-related potential (ERP) measurements to be included in the framework for episodic assessment. In current discrete clinical cognitive assessment methods used to diagnose mild cognitive impairment (MCI)/ dementia, physicians see patients annually or biannually. Theyrely on patient's history and clinical cognitive assessments to identify changes in memory or functional ability as indications of MCI/dementia in conjunction with exclusionary tests. They are limited in these discrete assessments by their accuracy and infrequent occurrence. The episodic assessment framework proposed will allow better ongoing information about the true wellbeing of the patient through assessment of memory and functional cognitive ability on a weekly or even daily basis between appointments. This paper identifies features of EEG/ERP measurements during Neuropsychological Behavioral Testing that could allow the future inclusion in the framework using now available consumer EEG devices. A pilot group of 32 participants (17 healthy, 15 MCI) was studied using a 1-back test, while their brain activity was measured using EEG. Features of the ERP thus generated were identified and measured. These ERP features and associated behavioral measurements from the 1-back test were analyzed to identify features both alone and in combination that allowed the correct classification of the participants using a repeated leave-one-out train and test method. A feature pair (1back response time and CPz correlation) was identified that provides the best two-feature performance (1 false positive/1 false negative error) with a third feature (response required -Pz P1 to N1 latency) providing additional improvement. Given these results, it is possible that episodic ERP measurements may help with cognitive impairment diagnosis in the future.

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