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79 Continuous Theta Burst Stimulation (cTBS) over the Inferior Parietal Cortex Decreases Default Mode Connectivity and Improves Overnight Sleep in People with Insomnia
- William D. S. Killgore, Samantha Jankowski, Kymberly Henderson-Arredondo, Christopher Trapani, Heidi Elledge, Daniel Lucas, Andrew Le, Emmett Suckow, Lindsey Hildebrand, Michelle Persich, Brianna Zahorecz, Cohelly Salazar, Tyler Watson, Camryn Wellman, Deva Reign, Yu-Chin Chen, Ying-Hui Chou, Natalie S. Dailey
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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. 587-588
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Objective:
Chronic insomnia is a highly prevalent disorder affecting approximately one-in-three Americans. Insomnia is associated with increased cognitive and brain arousal. Compared to healthy individuals, those with insomnia tend to show greater activation/connectivity within the default mode network (DMN) of the brain, consistent with the hyperarousal theory. We investigated whether it would be possible to suppress activation of the DMN to improve sleep using a type of repetitive transcranial magnetic stimulation (rTMS) known as continuous theta burst stimulation (cTBS).
Participants and Methods:Participants (n=9, 6 female; age=25.4, SD=5.9 years) meeting criteria for insomnia/sleep disorder on standardized scales completed a counterbalanced sham-controlled crossover design in which they served as their own controls on two separate nights of laboratory monitored sleep on separate weeks. Each session included two resting state functional magnetic resonance imaging (fMRI) sessions separated by a brief rTMS session. Stimulation involved a 40 second cTBS stimulation train applied over an easily accessible cortical surface node of the DMN located at the left inferior parietal lobe. After scanning/stimulation, the participant was escorted to an isolated sleep laboratory bedroom, fitted with polysomnography (PSG) electrodes, and allowed an 8-hour sleep opportunity from 2300 to 0700. PSG was monitored continuously and scored for standard outcomes, including total sleep time (TST), percentage of time various sleep stages, and number of arousals.
Results:Consistent with our hypothesis, a single session of active cTBS produced a significant reduction of functional connectivity (p < .05, FDR corrected) within the DMN. In contrast, the sham condition produced no changes in functional connectivity from pre- to post-treatment. Furthermore, after controlling for age, we also found that the active treatment was associated with meaningful trends toward greater overnight improvements in sleep compared to the sham condition. First, the active cTBS condition was associated with significantly greater TST compared to sham (F(1,7)=14.19, p=.007, partial eta-squared=.67). Overall, individuals obtained 26.5 minutes more sleep on the nights that they received the active cTBS compared to the sham condition. Moreover, the active cTBS condition was associated with a significant increase in the percentage of time in rapid eye movement (REM%) sleep compared to the sham condition (F(1,7)=7.05, p=.033, partial eta-squared=.50), which was significant after controlling for age. Overall, active treatment was associated with an increase of 6.76% more of total sleep time in REM compared to sham treatment. Finally, active cTBS was associated with fewer arousals from sleep (t(8) = -1.84, p = .051, d = .61), with an average of 15.1 fewer arousals throughout the night than sham.
Conclusions:Overall, these findings suggest that this simple and brief cTBS approach can alter DMN brain functioning in the expected direction and was associated with trends toward improved objectively measured sleep, including increased TST and REM% and fewer arousals during the night following stimulation. These findings emerged after only a single 40-second treatment, and it remains to be seen whether multiple treatments over several days or weeks can sustain or even improve upon these outcomes.
58 Preliminary Development of a Virtual Reality Neuropsychological Assessment System
- William D. Killgore, Kymberly Henderson-Arredondo, Natalie S. Dailey, Jason Zhang, Samantha Jankowski, Ao Li, Huayu Li, Deva Reign, Emmett Suckow, Lindsey Hildebrand, Camryn Wellman, Jerzy Rozenblit, Janet Roveda
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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. 735-736
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Objective:
While there exist numerous validated neuropsychological tests and batteries to measure cognitive and behavioral capacities, the vast majority of these are time intensive and difficult to administer and score outside of the clinic. Moreover, many existing assessments may have limited ecological validity in some contexts (e.g., military operations). Therefore, we have been developing a novel approach to administering neuropsychological assessment using a virtual reality (VR) “game” that will collect simultaneously acquired multidimensional data that is synthesized by machine learning algorithms to identify neurocognitive strengths and weaknesses in a fraction of the time of typical assessment approaches. For our initial pilot project, we developed a preliminary VR task that involved a brief game-like military “shoot/no-shoot” task that collected data on hits, false alarms, discriminability, and response times under a context-dependent rule set. This prototype task will eventually be expanded to include a significantly more complex set of tasks with greater cognitive demands, sensor feeds, and response variables that could be modified to fit many other contexts. The objective of this project was to construct a rudimentary pilot version and demonstrate whether it could predict outcomes on standard neuropsychological assessments.
Participants and Methods:To demonstrate proof-of-concept, we collected data from 20 healthy participants from the general population (11 male; age=24.8, SD=7.8) with high average intelligence (IQ = 112, SD=10.7). All participants completed the Wechsler Abbreviated Scale of Intelligence-II (WASI-II), and several neuropsychological tests including the ImPACT, the Attention and Executive Function modules of the Neuropsychological Assessment Battery (NAB), and the VR task. Initially, we used a prior dataset from 359 participants (n=191 mild traumatic brain injury; n=120healthy control; n=48 sleep deprived) to serve as a training sample for machine learning models. Based on these outcomes, we applied machine learning, as well as standard multiple regression approaches to predict neuropsychological outcomes in the 20 test participants.
Results:In this limited study, the machine learning approach did not converge on a meaningful prediction due to the instability of the small sample. However, standard multiple linear regression using stepwise entry/deletion of the VR task variables significantly predicted neuropsychological performance. The VR task predicted WASI-II vocabulary (R=.457, p=.043), NAB Attention Index (R=.787, p=.001), and NAB Executive Function Index (R=.715, p=.002). Interestingly, these performances were generally as good or better than the predictions resulting from the ImPACT, a commercially available neuropsychological test battery, which correlated with WASI-II vocabulary (R=.557, p=.011), NAB Attention Index (R=.574, p=.008), and NAB Executive Function Index (R=.619, p=.004).
Conclusions:Our pilot VR task was able to predict performances on standard neuropsychological assessment measures at a level comparable to that of a commercially available computerized assessment battery, providing preliminary evidence of concurrent validity. Ongoing work is expanding this rudimentary task into one involving greater complexity and nuance. As multivariate data integration models are incorporated into the tasks and extraction features, future work will collect data on much larger samples of individuals to develop and refine the machine learning models. With additional work this approach may provide an important advance in neuropsychological assessment methods.
40 Sex Differences in Emotional Intelligence Ability and Risk-Taking Behavior
- Lindsey Hildebrand, William D. S. Killgore
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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. 828-829
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Objective:
People differ in their propensity to engage in risky behaviors. Numerous factors such as cognition and personality have been utilized in predicting risk-taking, but little is known about the influence of stable emotional competencies, such as Emotional Intelligence (EI), in risk-taking. EI is defined as the ability and capacity to understand, perceive, and manage one's own, as well as others', emotions. However there has been little published research on the effect of ability emotional intelligence in engaging in risk- taking behavior. We hypothesized that those with higher emotional intelligence ability scores would demonstrate higher and more optimal risk-taking propensity. Furthermore, as prior research has demonstrated that males engage in more risk-taking behaviors, we accounted for sex differences within our analysis.
Participants and Methods:One-hundred and twelve healthy adults completed this study, including 56 females (Mage=21.7, SD=5.8) and 56 males (Mage=21.5, SD=3.2). The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) was used to assess total EI ability while the Balloon Analog Risk Task (BART) was used to assess risk-taking propensity. We specifically analyzed adjusted number of pumps on unexploded balloons throughout the BART to account for the increased risk. We conducted Pearson correlations and a multiple regression to assess the if ability emotional intelligence and gender significantly predicted risk-taking propensity.
Results:There was a significant correlation between total emotional intelligence ability score and adjusted number of pumps on the BART for females, r(55)=.362, p = .006, but not for males r(55)=.053, p=.701, suggesting that females who score higher in emotional intelligence ability also had a higher risk-taking propensity. Due to these findings, we conducted a multiple regression to assess if ability emotional intelligence and gender significantly predict risk-taking propensity on the BART. The results of the regression indicated the two predictors explained 9.0% of the variance (R2 =.09, F(2,108)=5.32, p<.01). However, it was found that ability emotional intelligence significantly predicted risk-taking propensity (β = .23, p<.05), but not sex (β = -.17, p=.06). There was no sex x EI interaction.
Conclusions:Higher ability emotional intelligence was significantly related to greater risk-taking propensity, but this was only observed for females. However, the lack of significance of sex in significantly predicting risk-taking may just be due to lower statistical power in the study. Importantly, the adjusted number of pumps for the participants in this sample was generally far below the mid-point for popping balloons, suggesting that the higher scores observed here represent more optimal decision performance rather than just greater risk. Thus, greater EI may reflect greater capacity to learn from reward and punishment feedback and apply that learning to optimize performance. Future research should look at the effect of emotional intelligence training in improving optimal risk-taking, particularly for populations known for engaging in risky behaviors such as those with mTBI.
Reduced anhedonia following internet-based cognitive-behavioral therapy for depression is mediated by enhanced reward circuit activation
- Shir Hanuka, Elizabeth A. Olson, Roee Admon, Christian A. Webb, William D. S. Killgore, Scott L. Rauch, Isabelle M. Rosso, Diego A. Pizzagalli
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- Journal:
- Psychological Medicine / Volume 53 / Issue 10 / July 2023
- Published online by Cambridge University Press:
- 17 June 2022, pp. 4345-4354
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Background
Major depressive disorder (MDD) is a highly prevalent psychiatric condition, yet many patients do not receive adequate treatment. Novel and highly scalable interventions such as internet-based cognitive-behavioral-therapy (iCBT) may help to address this treatment gap. Anhedonia, a hallmark symptom of MDD that refers to diminished interest and ability to experience pleasure, has been associated with reduced reactivity in a neural reward circuit that includes medial prefrontal and striatal brain regions. Whether iCBT can reduce anhedonia severity in MDD patients, and whether these therapeutic effects are accompanied by enhanced reward circuit reactivity has yet to be examined.
MethodsFifty-two MDD patients were randomly assigned to either 10-week iCBT (n = 26) or monitored attention control (MAC, n = 26) programs. All patients completed pre- and post-treatment assessments of anhedonia (Snaith–Hamilton Pleasure Scale; SHAPS) and reward circuit reactivity [monetary incentive delay (MID) task during functional magnetic resonance imaging (fMRI)]. Healthy control participants (n = 42) also underwent two fMRI scans while completing the MID task 10 weeks apart.
ResultsBoth iCBT and MAC groups exhibited a reduction in anhedonia severity post-treatment. Nevertheless, only the iCBT group exhibited enhanced nucleus accumbens (Nacc) and subgenual anterior cingulate cortex (sgACC) activation and functional connectivity from pre- to post-treatment in response to reward feedback. Enhanced Nacc and sgACC activations were associated with reduced anhedonia severity following iCBT treatment, with enhanced Nacc activation also mediating the reduction in anhedonia severity post-treatment.
ConclusionsThese findings suggest that increased reward circuit reactivity may contribute to a reduction in anhedonia severity following iCBT treatment for depression.
Contributors
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- By Brian Abaluck, Imran M. Ahmed, Torbjörn Åkerstedt, Sonia Ancoli-Israel, Anna Anund, Donna L. Arand, Isabelle Arnulf, Fiona C. Baker, Thomas J. Balkin, Christian R. Baumann, Michel Billiard, Michael H. Bonnet, Meredith Broderick, Christian Cajochen, Scott S. Campbell, Sarah Laxhmi Chellappa, Fabio Cirignotta, Yves Dauvilliers, David F. Dinges, Christopher L. Drake, Neil T. Feldman, Catherine S. Fichten, Charles F. P. George, Namni Goel, Christian Guilleminault, Shelby F. Harris, Melinda L. Jackson, Joseph Kaleyias, Göran Kecklund, William D. S. Killgore, Sanjeev V. Kothare, Andrew D. Krystal, Clete A. Kushida, Luc Laberge, Gert Jan Lammers, Christopher P. Landrigan, Sandrine H. Launois, Patrick Levy, Eva Libman, Yinghui Low, Jennifer L. Martin, Una D. McCann, Renee Monderer, Patricia J. Murphy, Sona Nevsimalova, Seiji Nishino, Eric A. Nofzinger, Maurice M. Ohayon, Masashi Okuro, Jean-Louis Pepin, Fabio Pizza, Anil N. Rama, David B. Rye, Paula K. Schweitzer, Hideto Shinno, Renaud Tamsier, Michael J. Thorpy, Astrid van der Heide, Hans P. A. Van Dongen, Mari Viola-Saltzman, Jim Waterhouse, Nathaniel F. Watson, Rajive Zachariah
- Edited by Michael J. Thorpy, Michel Billiard
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- Book:
- Sleepiness
- Published online:
- 04 February 2011
- Print publication:
- 27 January 2011, pp vii-x
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Chapter 38 - Caffeine and other alerting agents
- from Section 4 - Therapy of Excessive Sleepiness
- Edited by Michael J. Thorpy, Michel Billiard
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- Book:
- Sleepiness
- Published online:
- 04 February 2011
- Print publication:
- 27 January 2011, pp 430-443
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Summary
Myotonic dystrophy type I (DM1) is one of the most variable of all human disorders, with virtually all body systems affected in some way, and age at disease onset varies from fetal life to old age. The character of DM1-related excessive daytime sleepiness (EDS) is that of a persistent sleepiness unaffected by naps, the latter being long, unrefreshing and without any associated dream. This chapter presents the scores of DM1 patients with and without EDS on the eight Short-Form 36-item Health Survey subscales, a frequently used generic health-related quality of life (HRQoL) questionnaire. It describes the personality and cognitive characteristics of 200 DM1 patients with and without EDS. The chapter discusses the habitual sleep-wake schedule and sleep-related complaints of 200 DM1 patients with and without EDS. Sleep-disordered breathing (SDB), hypercapnia, and nocturnal desaturation are all frequent in DM1. Psychostimulant drugs are increasingly used to treat EDS in DM1.