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46 Depression and Reward Responsiveness in Multiple Sclerosis
- Valerie Humphreys, Fareshte Irani, Darshan Patel, Maria Schultheis, John Medaglia, Kathryn N. Devlin
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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. 559-560
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Objective:
Depression is common in persons with MS (PwMS), substantially contributing to morbidity and mortality. Depression can dually impact PwMS as both a psychosocial reaction to living with the disease and a neurological effect of it. Cardinal features of depression include reduced ability to seek and experience pleasure, often attributed to dysregulation of the brain's reward system. People with depression exhibit atypical reward processing, as do fatigued PwMS. However, it is unclear whether MS itself affects reward processing, and whether it interacts with depression. The current study explored the associations of depression, MS, and their interaction on reward responsiveness. We hypothesized that depression and MS would independently be associated with poorer reward responsiveness and that they would interact synergistically to impair reward responsiveness.
Participants and Methods:Forty PwMS and 40 healthy age- and education-matched healthy controls (HC) participated in a computerized switching task with high- and low-reward manipulations. The Chicago Multiscale Depression Inventory (CMDI) Mood subscale measured depressive symptoms. The Behavioral Inhibition/Activation Scales (BIS/BAS) measured self-reported reward responsiveness and behavioral inhibition. Switching task performance was measured as response time (RT) and accuracy. Performance differences between the high- and low-reward conditions represented performance-based reward responsiveness. Linear mixed effects models were used to estimate the associations of MS and depression with reward responsiveness, behavioral inhibition, and task performance.
Results:Depression, but not MS, was associated with higher BIS scores (p=.007). Neither depression nor MS was associated with BAS subscales. On the switching task, participants who reported lower depression responded to reward such that they were slightly faster in the high-reward condition compared to the low-reward condition (p=.07). By contrast, in participants who reported higher depression, there was no effect of reward on response time. Additionally, MS (p=.009) and depression (p=.018) were each associated with slower response times. Regarding accuracy, no effects of reward were observed; however, there was an interaction between MS and depression. Among HC participants, depression was not related to accuracy. In comparison, PwMS who reported higher depression were more accurate than PwMS who reported less depression (p=.043).
Conclusions:Consistent with hypotheses, higher depressive symptoms were associated with increased behavioral inhibition. Depression was not associated with self-reported reward responsiveness, but it was associated with reduced reward responsiveness on a cognitive task. Contrary to hypotheses, MS was not associated with reduced reward responsiveness. Additionally, higher depression and an MS diagnosis were related to slower response time, consistent with prior findings that psychomotor slowing is a hallmark feature of both disorders. Interestingly, we observed a unique behavioral trend in PwMS, such that PwMS with higher depressive symptoms were more accurate than PwMS with lower depressive symptoms, whereas this relationship was not present among HCs. Altogether, depression in both PwMS and cognitively healthy individuals may be associated with blunted reward responsiveness, but MS does not exacerbate this relationship. In fact, PwMS with depression may be more conscientious in their functioning and therefore perform better on cognitive task accuracy. Continued work should examine how reward processing and its underlying mechanisms may differ in depressed PwMS.
13 Money versus Feedback: Comparing Reward Types and Frequency on Cognitive Fatigue
- Fareshte Erani, Harrison Stoll, Darshan Patel, Maria T Schultheis, John D Medaglia
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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. 805
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Objective:
Cognitive fatigue (CF) is a common, yet poorly understood symptom in neurological disorders (e.g., multiple sclerosis, Parkinson’s disease, stroke). Studies show that reward plays a central role in CF. For instance, introducing or increasing reward often improves task performance. It is less clear, however, how reward affects subjective (self-reported) CF (SCF). This study examined the effect of reward type (monetary or performance feedback) and frequency (infrequent or frequent) on SF.
Participants and Methods:In an online between-subjects study, 400 participants completed a computerized cognitive switching task and were randomly grouped into one of the five possible groups based on reward condition: [1] infrequent monetary reward, [2] frequent monetary reward, [3] infrequent performancefeedback reward, [4] frequent performance feedback reward, and [5] a no-reward group. SCF was assessed using the Visual Analog Scale of Fatigue (VAS-F) during the task. Mixed effects models were used to estimate the influence of reward type and frequency on task performance and SCF.
Results:We found that the monetary groups were significantly faster (p<.001) compared to the feedback and no-reward groups, and that the frequent group was faster (p=.05) compared to the infrequent group. Reward type and frequency did not have a significant effect on VAS-F scores. However, when we looked at each reward group, we found that the monetary-infrequent reward group was associated with a decrease in VAS-F scores on average compared to the no-reward group (p=.04).
Conclusions:The type and frequency of reward influence aspects of task performance (response time but not accuracy). Findings suggest that money had a greater effect on response time and may decrease SCF in cognitively healthy individuals when provided infrequently. Future studies should examine how these findings translate to clinical populations. Continued work is needed to understand how and which specific behavioral reward manipulations reduce fatigue, which could eventually lead to improved assessment and our ability to target fatigue across clinical populations.
The “‘Crisis’ Crisis” in psychology
- John D. Medaglia, Kiante A. Fernandez
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- Journal:
- Behavioral and Brain Sciences / Volume 45 / 2022
- Published online by Cambridge University Press:
- 10 February 2022, e28
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The recent trend to label dilemmas in psychology as “crises” is insidious. The “‘Crisis’ Crisis” in psychology can distract us from actionable practices. As a case in point, “The Generalizability Crisis” offers the valuable central thesis that verbal-quantitative gaps imperil psychological science. Focusing on the key issues rather than crisis narratives can lead to progress in our discourse and research.
A Computational Network Control Theory Analysis of Depression Symptoms
- Yoed N. Kenett, Roger E. Beaty, John D. Medaglia
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- Journal:
- Personality Neuroscience / Volume 1 / 2018
- Published online by Cambridge University Press:
- 15 October 2018, e16
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Rumination and impaired inhibition are considered core characteristics of depression. However, the neurocognitive mechanisms that contribute to these atypical cognitive processes remain unclear. To address this question, we apply a computational network control theory approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how network control theory relates to individual differences in subclinical depression. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that subclinical depression is negatively related to higher integration abilities in the right anterior insula, replicating and extending previous studies implicating atypical switching between the default mode and Executive Control Networks in depression. We also find that subclinical depression is related to the ability to “drive” the brain system into easy to reach neural states in several brain regions, including the bilateral lingual gyrus and lateral occipital gyrus. These findings highlight brain regions less known in their role in depression, and clarify their roles in driving the brain into different neural states related to depression symptoms.