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15 Exploratory Factor Analysis of Cognitive and Positive Valence Measures for the RDoC
- Emily T Sturm, John R Duffy, Anastasia G Sares, Andrea Mendez-Colmenares, Lauren Sarabia, Eve Delao, Max Henneke, Raana Manavi, Donald C Rojas, Jason R Tregellas, Jared W Young, Michael L Thomas
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 698-699
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Objective:
As part of the Research Domain Criteria (RDoC) initiative, the NIMH seeks to improve experimental measures of cognitive and positive valence systems for use in intervention research. However, many RDoC tasks have not been psychometrically evaluated as a battery of measures. Our aim was to examine the factor structure of 7 such tasks chosen for their relevance to schizophrenia and other forms of serious mental illness. These include the n-back, Sternberg, and self-ordered pointing tasks (measures of the RDoC cognitive systems working memory construct); flanker and continuous performance tasks (measures of the RDoC cognitive systems cognitive control construct); and probabilistic learning and effort expenditure for reward tasks (measures of reward learning and reward valuation constructs).
Participants and Methods:The sample comprised 286 cognitively healthy participants who completed novel versions of all 7 tasks via an online recruitment platform, Prolific, in the summer of 2022. The mean age of participants was 38.6 years (SD = 14.5, range 18-74), 52% identified as female, and stratified recruitment ensured an ethnoracially diverse sample. Excluding time for instructions and practice, each task lasted approximately 6 minutes. Task order was randomized. We estimated optimal scores from each task including signal detection d-prime measures for the n-back, Sternberg, and continuous performance task, mean accuracy for the flanker task, win-stay to win-shift ratio for the probabilistic learning task, and trials completed for the effort expenditure for reward task. We used parallel analysis and a scree plot to determine the number of latent factors measured by the 7 task scores. Exploratory factor analysis with oblimin (oblique) rotation was used to examine the factor loading matrix.
Results:The scree plot and parallel analyses of the 7 task scores suggested three primary factors. The flanker and continuous performance task both strongly loaded onto the first factor, suggesting that these measures are strong indicators of cognitive control. The n-back, Sternberg, and self-ordered pointing tasks strongly loaded onto the second factor, suggesting that these measures are strong indicators of working memory. The probabilistic learning task solely loaded onto the third factor, suggesting that it is an independent indicator of reinforcement learning. Finally, the effort expenditure for reward task modestly loaded onto the second but not the first and third factors, suggesting that effort is most strongly related to working memory.
Conclusions:Our aim was to examine the factor structure of 7 RDoC tasks. Results support the RDoC suggestion of independent cognitive control, working memory, and reinforcement learning. However, effort is a factorially complex construct that is not uniquely or even most strongly related to positive valance. Thus, there is reason to believe that the use of at least 6 of these tasks are appropriate measures of constructs such as working memory, reinforcement learning and cognitive control.
27 Clinical Symptoms, Cognitive Functioning, and Brain Health in Agricultural Workers
- Jazmin M. Diaz, Stephen R. Kellam, Emily T. Sturm, Max Henneke, Emily Pehlke, John R. Duffy, Andrea Mendez-Colmenares, Agnieszka Z. Burzynska, Lorann Stallones, Michael L. Thomas
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 903
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Objective:
Agricultural workers are immersed in environments associated with increased risk for adverse psychiatric and neurological outcomes. Agricultural work-related risks to brain health include exposure to pesticides, heavy metals, and organic dust. Despite this, there is a gap in our understanding of the underlying brain systems impacted by these risks. This study explores clinical and cognitive domains, and functional brain activity in agricultural workers. We hypothesized that a history of agricultural work-related risks would be associated with poorer clinical and cognitive outcomes as well as changes in functional brain activity within cortico-striatal regions.
Participants and Methods:The sample comprised 17 agricultural workers and a comparison group of 45 non-agricultural workers recruited in the Northern Colorado area. All participants identified as White and non-Hispanic. The mean age of participants was 51.7 years (SD = 21.4, range 18-77), 60% identified as female, and 37% identified as male. Participants completed the National Institute of Health Toolbox (NIH Toolbox) and Montreal Cognitive Assessment (MoCA) on their first visit. During the second visit, they completed NIH Patient-Reported Outcomes Measurement Information System (PROMIS) measures and underwent functional magnetic resonance imaging (fMRI; N = 15 agriculture and N = 35 non-agriculture) while completing a working memory task (Sternberg). Blood oxygen-level dependent (BOLD) response was compared between participants. Given the small sample size, the whole brain voxel-wise group comparison threshold was set at alpha = .05, but not otherwise corrected for multiple comparisons. Cohen’s d effect sizes were estimated for all voxels.
Results:Analyses of cognitive scores showed significant deficits in episodic memory for the agricultural work group. Additionally, the agricultural work group scored higher on measures of self-reported anger, cognitive concerns, and social participation. Analyses of fMRI data showed increased BOLD activity around the orbitofrontal cortex (medium to large effects) and bilaterally in the entorhinal cortex (large effects) for the agricultural work group. The agricultural work group also showed decreased BOLD activity in the cerebellum and basal ganglia (medium to large effects).
Conclusions:To our knowledge, this study provides the first-ever evidence showing differences in brain activity associated with a history of working in agriculture. These findings of poorer memory, concerns about cognitive functioning, and increased anger suggest clinical relevance. Social participation associated with agricultural work should be explored as a potential protective factor for cognition and brain health. Brain imaging data analyses showed increased activation in areas associated with motor functioning, cognitive control, and emotion. These findings are limited by small sample size, lack of diversity in our sample, and coarsely defined risk. Despite these limitations, the results are consistent with an overall concern that risks associated with agricultural work can lead to cognitive and psychiatric harm via changes in brain health. Replications and future studies with larger sample sizes, more diverse participants, and more accurately defined risks (e.g., pesticide exposure) are needed.
70 Comparison of MCCB Autocorrelations Between Schizophrenia and Healthy Comparison Populations
- Max Henneke, Emily T. Sturm, John R. Duffy, Anastasia Sares, Andrea Mendez-Colmenares, Lauren Sarabia, Eve Delao, Tessa Mitchell, Raana Manavi, Michael L. Thomas
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 854-855
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Objective:
Deficits in cognitive ability are common among patients with schizophrenia. The MATRICS Consensus Cognitive Battery (MCCB) was designed to assess cognitive ability in studies of patients diagnosed with schizophrenia and has demonstrated high test-retest reliability with minimal practice effects, even in multi-site trials. However, given the motivational challenges associated with schizophrenia, it is unknown whether performance on MCCB tasks affects performance at later stages of testing. The goal of this study was to determine whether there are differences between people with and without schizophrenia in how their performance on individual MCCB tasks influences their performance throughout the battery.
Participants and Methods:The sample comprised 92 total participants including 49 cognitively healthy comparison participants and 43 outpatients diagnosed with schizophrenia. The mean age of participants was 44.2 years (SD = 12.0, range 21–69) and 61% identified as male. The Trail Making Test, Brief Assessment of Cognition in Schizophrenia, Hopkins Verbal Learning Test – Revised, Letter-Number Span, and Category Fluency from the MCCB were administered in the same order at 2 different sites and studies from 2016–2022. The autocorrelation between t-scores for task scores within each participant was computed and then compared between control and outpatient participants to determine if there are differences between groups. Group mean t-scores for each task were also compared between groups.
Results:We found no significant difference in autocorrelations across MCCB tasks between healthy comparison participants and outpatients. However, mean performance in all tasks was lower for the outpatient group than for the healthy comparison group. None of the tasks used stood out as having significantly lower mean scores than other tasks for either group.
Conclusions:Our findings suggest that performance on individual MCCB tasks do not affect performance throughout the battery differently between the healthy comparison group and outpatients. This suggests that participants with schizophrenia are not particularly reactive to past performance on MCCB tasks. Additionally, this finding further supports use of the MCCB in this population. Further research is needed to determine whether subgroups of patients and/or different batteries of measures show different patterns of reactivity.