Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities
Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain thei...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-07-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811923002628 |
| _version_ | 1797812082122424320 |
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| author | K.L. Lopez A.D. Monachino K.M. Vincent F.C. Peck L.J. Gabard-Durnam |
| author_facet | K.L. Lopez A.D. Monachino K.M. Vincent F.C. Peck L.J. Gabard-Durnam |
| author_sort | K.L. Lopez |
| collection | DOAJ |
| description | Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan. |
| first_indexed | 2024-03-13T07:33:16Z |
| format | Article |
| id | doaj.art-3e075e0fae494bd1b5d0d21a218b3054 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-03-13T07:33:16Z |
| publishDate | 2023-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-3e075e0fae494bd1b5d0d21a218b30542023-06-04T04:23:10ZengElsevierNeuroImage1095-95722023-07-01275120116Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunitiesK.L. Lopez0A.D. Monachino1K.M. Vincent2F.C. Peck3L.J. Gabard-Durnam4Northeastern University, 360 Huntington Ave, Boston, MA, United StatesNortheastern University, 360 Huntington Ave, Boston, MA, United StatesNortheastern University, 360 Huntington Ave, Boston, MA, United StatesUniversity of California, Los Angeles, Los Angeles, CA, United StatesNortheastern University, 360 Huntington Ave, Boston, MA, United States; Corresponding author at: 628 ISEC, Northeastern University, Boston, MA 02115, United States.Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan.http://www.sciencedirect.com/science/article/pii/S1053811923002628EEGIndividual differencesPsychometric reliabilityInternal consistencyTest-retest reliabilityLifespan |
| spellingShingle | K.L. Lopez A.D. Monachino K.M. Vincent F.C. Peck L.J. Gabard-Durnam Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities NeuroImage EEG Individual differences Psychometric reliability Internal consistency Test-retest reliability Lifespan |
| title | Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities |
| title_full | Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities |
| title_fullStr | Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities |
| title_full_unstemmed | Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities |
| title_short | Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities |
| title_sort | stability change and reliable individual differences in electroencephalography measures a lifespan perspective on progress and opportunities |
| topic | EEG Individual differences Psychometric reliability Internal consistency Test-retest reliability Lifespan |
| url | http://www.sciencedirect.com/science/article/pii/S1053811923002628 |
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