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van der Wijk G, Enkhbold Y, Cnudde K, Szostakiwskyj MW, Blier P, Knott V, Jaworska N, Protzner AB. One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response. Front Psychiatry 2024; 15:1358018. [PMID: 38628260 PMCID: PMC11018891 DOI: 10.3389/fpsyt.2024.1358018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 03/18/2024] [Indexed: 04/19/2024] Open
Abstract
Introduction To date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response. Methods Resting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients. Results Responders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization. Discussion Our single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability. Clinical trial registration https://clinicaltrials.gov, identifier NCT00519428.
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Affiliation(s)
- Gwen van der Wijk
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Yaruuna Enkhbold
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Kelsey Cnudde
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | | | - Pierre Blier
- Institute of Mental Health Research, Affiliated with the University of Ottawa, Ottawa, ON, Canada
- Department of Cellular & Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Verner Knott
- Institute of Mental Health Research, Affiliated with the University of Ottawa, Ottawa, ON, Canada
- Department of Cellular & Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Natalia Jaworska
- Institute of Mental Health Research, Affiliated with the University of Ottawa, Ottawa, ON, Canada
- Department of Cellular & Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Andrea B. Protzner
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Mathison Centre, University of Calgary, Calgary, AB, Canada
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Cnudde K, Kim G, Murch WS, Handy TC, Protzner AB, Kam JWY. EEG complexity during mind wandering: A multiscale entropy investigation. Neuropsychologia 2023; 180:108480. [PMID: 36621593 DOI: 10.1016/j.neuropsychologia.2023.108480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 10/16/2022] [Accepted: 01/05/2023] [Indexed: 01/07/2023]
Abstract
Our attention often drifts away from the ongoing task to task-unrelated thoughts, a phenomenon commonly referred to as mind wandering. Ample studies dedicated to delineating its electrophysiological correlates have revealed distinct event-related potentials (ERP) and spectral patterns associated with mind wandering. It remains less clear whether the complexity of the electroencephalography (EEG) changes when our minds wander, a metric that captures the predictability of the time series at varying timescales. Accordingly, this study investigated whether mind wandering impacts EEG signal complexity. We further explored whether such effects differ across timescales, and change in a context-dependent manner as indexed by global and local levels of processing. To address this, we recorded participants' EEG while they completed Navon's global and local processing task and occasionally reported whether they were on-task or mind wandering throughout the task. We found that brain signal complexity as indexed by multiscale entropy decreased at medium timescales in centro-parietal regions and increased at coarse timescales in anterior and posterior regions during mind wandering, as compared to the on-task state, for global processing. Moreover, global processing showed increased complexity at fine to medium timescales compared to local processing. Finally, behavioral performance revealed a context-dependent effect in accuracy measures, with mind wandering showing lower accuracy compared to the on-task state only during the local condition. Taken together, these results indicate that changes in brain signal complexity across timescales may be an important feature of mind wandering.
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Affiliation(s)
- Kelsey Cnudde
- Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada, T2N 1N4.
| | - Gahyun Kim
- Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada, T2N 1N4
| | - W Spencer Murch
- Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, British Columbia, Canada, V6T 1Z4; Department of Sociology & Anthropology, Concordia University, 1455 de Maisonneuve Blvd W, Montreal, Quebec, Canada, H3G 1M8
| | - Todd C Handy
- Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, British Columbia, Canada, V6T 1Z4
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada, T2N 1N4; Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Canada, T2N 1N4; Mathison Centre for Mental Health, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, Canada, T2N 4Z6
| | - Julia W Y Kam
- Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada, T2N 1N4; Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, British Columbia, Canada, V6T 1Z4; Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Canada, T2N 1N4
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The modulatory effect of adaptive task-switching training on resting-state neural network dynamics in younger and older adults. Sci Rep 2022; 12:9541. [PMID: 35680953 PMCID: PMC9184743 DOI: 10.1038/s41598-022-13708-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/26/2022] [Indexed: 11/08/2022] Open
Abstract
With increasing life expectancy and active aging, it becomes crucial to investigate methods which could compensate for generally detected cognitive aging processes. A promising candidate is adaptive cognitive training, during which task difficulty is adjusted to the participants' performance level to enhance the training and potential transfer effects. Measuring intrinsic brain activity is suitable for detecting possible distributed training-effects since resting-state dynamics are linked to the brain's functional flexibility and the effectiveness of different cognitive processes. Therefore, we investigated if adaptive task-switching training could modulate resting-state neural dynamics in younger (18-25 years) and older (60-75 years) adults (79 people altogether). We examined spectral power density on resting-state EEG data for measuring oscillatory activity, and multiscale entropy for detecting intrinsic neural complexity. Decreased coarse timescale entropy and lower frequency band power as well as increased fine timescale entropy and higher frequency band power revealed a shift from more global to local information processing with aging before training. However, cognitive training modulated these age-group differences, as coarse timescale entropy and lower frequency band power increased from pre- to post-training in the old-training group. Overall, our results suggest that cognitive training can modulate neural dynamics even when measured outside of the trained task.
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