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Published in final edited form as: Psychiatry Res Neuroimaging. 2023 Aug 29;335:111712. doi: 10.1016/j.pscychresns.2023.111712

Cognitive control as a potential neural mechanism of protective role of spirituality in anxiety disorders among American Indian people: An ERP study

Nicole R Baughman 1, Ricardo A Wilhelm 1, Philip A Spechler 1, Breanna A McNaughton 1, Mara J Demuth 1, Gary L Lawrence 2, Glenna Stumblingbear Riddle 3, Joanna O Shadlow 4, Terrence Kominsky 5, Jennifer L Stewart 1,6, Robin L Aupperle 1,6, Martin P Paulus 1,6, Evan J White 1,6,±,*
PMCID: PMC10840908  NIHMSID: NIHMS1928824  PMID: 37660442

Abstract

Research suggests that traditional cultural factors are protective against mental health conditions in American Indian (AI) populations. This study aims to determine if cognitive control is a neurocognitive mechanism of the protective role of spirituality in AI people with generalized anxiety disorder (GAD). Participants self-identified as AI (n=52) and included individuals with GAD (n=16) and without GAD (n=36). Electroencephalography was collected during a stop-signal task to probe cognitive control using the P3 event-related potential. Higher levels of spirituality attenuated the processing efficiency disruption among individuals with GAD as indicated by P3 amplitudes closer to that of individuals without GAD.

1. Introduction

American Indian (AI)1 communities face disproportionately high risk for psychopathology (e.g., Generalized Anxiety Disorder; GAD) resultant from colonization and its lasting effects such as historical loss, trauma, and discrimination (e.g., Walls et al., 2021). Prior literature suggests once these prevalence rates are contextualized with respect to increased risk burden, AIs demonstrate high levels of resilience and positive mental health (Kading et al, 2015). There is a growing body of literature on culturally specific protective factors among AI communities such as spirituality (e.g., Fleming & Ledogar, 2008; Running Bear et al., 2018). However, little is known about the underlying neurocognitive functions of these protective factors. Delineating such mechanisms will serve as a foundation for culturally grounded treatment targets informed by clinical neuroscience, a large gap in our current knowledge and mental health equity.

Anxiety is associated with cognitive control disruptions relative to healthy individuals (Sehlmeyer et al., 2010) and adversely affects processing efficiency even though quality of performance may not be impacted due to the use of compensatory strategies like employing increased effort (Derakshan & Eysenck, 2011). Event-related potentials (ERP) offer an objective neural marker of these processes (e.g., Luck, 2014). Consistent with evidence of decreased processing efficiency in anxiety, subjects with high trait anxiety display increased P3 wave amplitudes during an inhibitory control task (Sehlmeyer et al., 2010).

Spirituality has been associated with lower rates of psychopathology including, anxiety disorders (Oman, 2018) and has been identified as a potential component for adapting evidence based anxiety treatment in AI, although the evidence base underlying adaptation is underdeveloped (De Coteau et al., 2006). Notably, neurocognitive research has shown individuals who are more spiritually engaged demonstrate better performance on an EEG based neurofeedback task (Kober et al., 2017). Despite conceptual connections to mechanisms that may facilitate resilience and or recovery in AI individuals with anxiety disorders, no research to date has delineated potential neural mechanisms associated with spirituality as a protective factor among AI populations in anxiety disorders.

This study aims to examine the relationship between spirituality and response inhibition in AIs with and without GAD. Our hypotheses were as follows: (H1) Individuals with GAD would demonstrate elevated P3 amplitudes during a stop-signal task indicating higher cognitive effort; and (H2) this effect would be attenuated with greater levels of spirituality. There were no a priori hypotheses about overall task performance.

2. Methods

2.1. Participants

Participants (n=52; GAD=16, non-GAD=36) were recruited from the Tulsa-1000 study (see: Victor et al., 2018) participant pool. Participants were eligible if they were included in the Tulsa-1000 study and identified as AI. Participants were groups based on GAD diagnosis into a GAD and non-GAD group. Demographic data are presented in supplemental material Table S1.

2.3. Measures and Analysis

The MINI International Neuropsychiatric Interview (MINI) was used to assess psychopathology according to the Diagnostic and Statistical Manual of Mental Disorders (Sheehan et al., 2015; American Psychiatric Association, 2015). Participants also completed the Native American Spirituality Scale (NASS; Greenfield et al., 2015). The stop-signal task was used to probe response inhibition. P3 was quantified as the mean amplitude at Cz 250-430ms post stop-signal onset and baseline corrected from −200-0 ms. Details of task design and EEG processing are in supplementary material. Linear mixed-effects modeling was used to analyze the interaction of GAD diagnosis, trial performance (correct vs. incorrect), and spirituality on P3 amplitude. The model was fit with a random effect for each subject as P3 amplitude is a repeated measure and trials are nested within participants. Model specification and full results (Table S2.) can be found in the supplemental material.

3. Results

The interaction between diagnosis and trial performance was marginal (β = −2.34, p = 0.065). Exploratory post-hoc analyses indicated significant differences between P3 amplitudes during correct and incorrect trials in the GAD group (β = 4.069, p <0.001), and the control group (β = 1.696, p =0.015), indicating that P3 amplitudes were higher on average during correct trials than incorrect trials in both groups. Additionally, the difference between P3 amplitude in correct versus incorrect trials in the GAD group was significantly larger than the difference in the control group (d=.472, p=0.004). There was no significant, difference in trial performance between groups. In correct trials, there was a significant spirituality by diagnosis interaction (β = −0.31, p = 0.02) such that higher NASS scores predicted lower P3 amplitudes for individuals with GAD, suggesting higher levels of spiritual engagement in individuals with GAD were associated with increased processing efficiency during correct trials of the task.

4. Discussion

Current results were consistent with prior basic task effects (Sehlmeyer et al., 2010). Additionally, there was a greater difference in P3 amplitude during correct versus incorrect trials in the GAD group than the control group. These elevated P3 amplitudes suggest that relative to incorrect trials, individuals with GAD had to utilize more cognitive effort on correct vs. incorrect trials. Our findings indicate higher levels of spiritual engagement related to reduced P3 amplitudes in GAD, suggesting spirituality may serve as a protective factor that promotes cognitive efficiency among AIs with GAD (Kirmayer et al., 2011; LaFromboise et al., 2006). There are numerous factors within AI spiritual practices that may promote cognitive control. AI spiritual engagement often involves the formation and maintenance of social relationships (Irwin, 1996), which may be vital to cognitive health (Dunbar, 2003). Additionally, spiritual practice often involves singing, praying, etc., which can maintain dense neocortical synapses and preserve cognitive function (Hosseini et al., 2019). This study was limited by the small sample size and results should therefore be considered preliminary until replicated in larger samples to increase power to test multi-faceted predictor sets.

In sum, despite the reported high prevalence rates of mental health conditions within AI communities, there has been little research contextualizing these findings relative to higher risk burdens and using a strengths-based approach to understand mechanisms of resilience factors in AI communities. This study extends our novel effort to leverage neural indicators of cognitive function to inform culturally grounded mental health research in AI populations. Future research is needed to (1) identify potential culturally specific protective factors in AI individuals, and (2) explain the mechanisms of these constructs to inform prevention and treatment efforts.

Supplementary Material

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Fig. 1.

Fig. 1.

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A. Illustrates grand average waves at Cz separated by diagnosis and trial performance. Figure 1.B. Represents difference waves (correct-incorrect) for trials by diagnosis. Figure 1.C. Demonstrates the relationship between Native American Spirituality Levels and P300 amplitude during correct, incorrect, easy, and hard trials is moderated by GAD diagnosis. Figure 1.D. Shows the topography difference maps (correct-incorrect) for trials by diagnosis.

Highlights.

  • AI individuals with GAD demonstrated increased attention allocation during a stop-signal task relative to individuals without GAD with similar performance.

  • Higher levels of self-reported spirituality attenuated this effect in individuals with GAD.

  • Spirituality may beneficially impact neurocognitive processes associated with anxiety related disruptions.

Acknowledgements

We would like to thank Chief Benjamin Barnes, Jake Roberts, M.S., and Drs. Jason Menting, Ashleigh Coser, Gloria Sly, as well as co-authors: GLL, GSR, JOS, and TKK for their roles on the community and scientific advisory council for this project. EJW receives funding for the project through NIMHD R00MD015736.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

1

Terms such as American Indian/Alaska Native (AIAN), Native, Indigenous, First Peoples, are often used interchangeably. It is most respectful to use terminology individuals and communities prefer. We use the term AI to refer to individuals from heterogenous Native tribes of northeastern Oklahoma.

Competing interest statement

MPP is an advisor to Spring Care, Inc., a behavioral health startup, he has received royalties for an article about methamphetamine in UpToDate. We have no other competing interests to report.

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Supplementary Materials

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NIHMS1928824-supplement-1.docx (51.2KB, docx)

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