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Article ; Online: Lightening the mood: evidence for blue light exposure in the treatment of post-concussion depression.

Killgore, William D S

2020 Volume 20, Issue 11, Page(s) 1081–1083

Language	English
Publishing date	2020-08-30
Publishing country	England
Document type	Editorial ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2112534-X
ISSN	1744-8360 ; 1473-7175
ISSN (online)	1744-8360
ISSN	1473-7175
DOI	10.1080/14737175.2020.1814147
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Zs.A 6155: Show issues

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Article ; Online: Individualised prediction of resilience and vulnerability to sleep loss using EEG features.

Subramaniyan, Manivannan / Hughes, John D / Doty, Tracy J / Killgore, William D S / Reifman, Jaques

Journal of sleep research

2024 , Page(s) e14220

Abstract: It is well established that individuals differ in their response to sleep loss. However, existing methods to predict an individual's sleep-loss phenotype are not scalable or involve effort-dependent neurobehavioural tests. To overcome these limitations, ... ...

Abstract	It is well established that individuals differ in their response to sleep loss. However, existing methods to predict an individual's sleep-loss phenotype are not scalable or involve effort-dependent neurobehavioural tests. To overcome these limitations, we sought to predict an individual's level of resilience or vulnerability to sleep loss using electroencephalographic (EEG) features obtained from routine night sleep. To this end, we retrospectively analysed five studies in which 96 healthy young adults (41 women) completed a laboratory baseline-sleep phase followed by a sleep-loss challenge. After classifying subjects into sleep-loss phenotypic groups, we extracted two EEG features from the first sleep cycle (median duration: 1.6 h), slow-wave activity (SWA) power and SWA rise rate, from four channels during the baseline nights. Using these data, we developed two sets of logistic regression classifiers (resilient versus not-resilient and vulnerable versus not-vulnerable) to predict the probability of sleep-loss resilience or vulnerability, respectively, and evaluated model performance using test datasets not used in model development. Consistently, the most predictive features came from the left cerebral hemisphere. For the resilient versus not-resilient classifiers, we obtained an average testing performance of 0.68 for the area under the receiver operating characteristic curve, 0.72 for accuracy, 0.50 for sensitivity, 0.84 for specificity, 0.61 for positive predictive value, and 3.59 for likelihood ratio. We obtained similar performance for the vulnerable versus not-vulnerable classifiers. These results indicate that logistic regression classifiers based on SWA power and SWA rise rate from routine night sleep can largely predict an individual's sleep-loss phenotype.
Language	English
Publishing date	2024-04-18
Publishing country	England
Document type	Journal Article
ZDB-ID	1122722-9
ISSN	1365-2869 ; 0962-1105
ISSN (online)	1365-2869
ISSN	0962-1105
DOI	10.1111/jsr.14220
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Zs.A 3464: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 343: Show issues

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Article ; Online: Association between emotional intelligence and effective brain connectome: A large-scale spectral DCM study.

Bajaj, Sahil / Killgore, William D S

NeuroImage

2021 Volume 229, Page(s) 117750

Abstract: Introduction: Emotional Intelligence (EI) is a well-documented aspect of social and interpersonal functioning, but the underlying neural mechanisms for this capacity remain poorly understood. Here we used advanced brain connectivity techniques to ... ...

Abstract	Introduction: Emotional Intelligence (EI) is a well-documented aspect of social and interpersonal functioning, but the underlying neural mechanisms for this capacity remain poorly understood. Here we used advanced brain connectivity techniques to explore the associations between EI and effective connectivity (EC) within four functional brain networks. Methods: The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) was used to collect EI data from 55 healthy individuals (mean age = 30.56±8.3 years, 26 males). The MSCEIT comprises two area cores - experiential EI (T1) and strategic EI (T2). The T1 core included two sub-scales - perception of emotions (S1) and using emotions to facilitate thinking (S2), and the T2 core included two sub-scales - understanding of emotions (S3) and management of emotions (S4). All participants underwent structural and resting-state functional magnetic resonance imaging (rsfMRI) scans. The spectral dynamic causal modeling approach was implemented to estimate EC within four networks of interest - the default-mode network (DMN), dorsal attention network (DAN), control-execution network (CEN) and salience network (SN). The strength of EC within each network was correlated with the measures of EI, with correlations at p Results: There was no significant association between any of the measures of EI and EC strength within the DMN and DAN. For CEN, however, we found that there were significant negative associations between EC strength from the right anterior prefrontal cortex (RAPFC) to the left anterior prefrontal cortex (LAPFC) and both S2 and T1, and significant positive associations between EC strength from LAPFC to RAPFC and S2. EC strength from the right superior parietal cortex (SPC) to RAPFC also showed significant negative association with S4 and T2. For the SN, S3 showed significant negative association with EC strength from the right insula to RAPFC and significant positive association with EC strength from the left insula to dorsal anterior cingulate cortex (DACC). Conclusions: We provide evidence that the negative ECs within the right hemisphere, and from the right to left hemisphere, and positive ECs within the left hemisphere and from the left to right hemisphere of CEN (involving bilateral frontal and right parietal region) and SN (involving right frontal, anterior cingulate and bilateral insula) play a significant role in regulating and processing emotions. These findings also suggest that measures of EC can be utilized as important biomarkers to better understand the underlying neural mechanisms of EI.
MeSH term(s)	Adult ; Brain/diagnostic imaging ; Brain/physiology ; Connectome/methods ; Default Mode Network/diagnostic imaging ; Default Mode Network/physiology ; Emotional Intelligence/physiology ; Female ; Humans ; Magnetic Resonance Imaging/methods ; Male ; Young Adult
Language	English
Publishing date	2021-01-14
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1147767-2
ISSN	1095-9572 ; 1053-8119
ISSN (online)	1095-9572
ISSN	1053-8119
DOI	10.1016/j.neuroimage.2021.117750
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Zs.A 3664: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 7: Show issues

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Article: Treatment with morning blue light increases left amygdala volume and sleep duration among individuals with posttraumatic stress disorder.

Killgore, William D S / Vanuk, John R / Dailey, Natalie S

Frontiers in behavioral neuroscience

2022 Volume 16, Page(s) 910239

Abstract: Background: Posttraumatic stress disorder (PTSD) is associated with numerous cognitive, affective, and psychophysiological outcomes, including problems with sleep and circadian rhythms. We tested the effectiveness of a daily morning blue-light exposure ... ...

Abstract	Background: Posttraumatic stress disorder (PTSD) is associated with numerous cognitive, affective, and psychophysiological outcomes, including problems with sleep and circadian rhythms. We tested the effectiveness of a daily morning blue-light exposure treatment (BLT) versus a matched amber light treatment (ALT) to regulate sleep in individuals diagnosed with PTSD. Moreover, PTSD is also associated with reliable findings on structural neuroimaging scans, including reduced amygdala volumes and other differences in cortical gray matter volume (GMV) that may be indicative of underlying neurobehavioral dysfunctions. We examined the effect of BLT versus ALT on GMV and its association with sleep outcomes. Methods: Seventy-six individuals (25 male; 51 female) meeting DSM-V criteria for PTSD ( Results: The BLT condition produced significant increases in total time in bed and total sleep time from actigraphy compared to the ALT condition, while ALT improved wake after sleep onset and sleep efficiency compared to BLT. Additionally, BLT led to an increase in left amygdala volume compared to ALT but did not affect hypothesized medial prefrontal regions. Finally, within group correlations showed that improvements in sleep quality and nightmare severity were correlated with increases in left amygdala volume over the course of treatment for the BLT group but not the ALT group. Conclusion: In individuals with PTSD, daily exposure to morning blue light treatment was associated with improvements in objective sleep duration and increased volume of the left amygdala compared to amber placebo light treatment, and changes in amygdala volume correlated with subjective improvement in sleep. These findings suggest that daily morning BLT may provide an important non-pharmacologic adjunctive approach for facilitating sleep and neurobehavioral recovery from PTSD.
Language	English
Publishing date	2022-09-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2452960-6
ISSN	1662-5153
ISSN	1662-5153
DOI	10.3389/fnbeh.2022.910239
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Article ; Online: Neighborhood-level sleep health and childhood opportunities.

Gorovoy, Suzanne / Phan, Sydney / Begay, Tommy K / Valencia, Dora / Hale, Lauren / Robbins, Rebecca / Killgore, William D S / Williamson, Ariel A / Grandner, Michael

Frontiers in public health

2024 Volume 11, Page(s) 1307630

Abstract: Objectives: Regional sleep differences may reflect other important indicators of health and well-being. Examining sleep health at the regional level can help inform policies to improve population health. We examined the relationship between neighborhood- ...

Abstract	Objectives: Regional sleep differences may reflect other important indicators of health and well-being. Examining sleep health at the regional level can help inform policies to improve population health. We examined the relationship between neighborhood-level adult sleep health (modeled in this study via adult sleep duration) and other health metrics and multiple indicators of child-relevant opportunity. Methods: Data were obtained from the "500 Cities" data collected by the CDC, including the proportion of the adult population in each tract that report obtaining at least 7 h of sleep. The Child Opportunity Index (COI) provides indices for "education," "health and environment," and "social and economic" domains, as well as a global score. When data were merged, 27,130 census tracts were included. Linear regression analyses examined COI associated with the proportion of the adult population obtaining 7 h of sleep. Results: Adult sleep duration was associated with global COI, such that for each additional percent of the population that obtains ≥ 7 h of sleep, COI increases by 3.6 points (95%CI[3.57, 3.64]). Each component of COI was separately related to adult sleep duration. All associations were attenuated but significant in adjusted analyses. In stepwise analyses, sleep health via adult sleep duration emerged as the strongest correlate of global COI, accounting for 57.2% of the variance ( Conclusion: Community levels of sufficient sleep are associated with greater childhood opportunities, which itself is robustly associated with a wide range of health and economic outcomes. Future work can examine whether this association can develop into scalable interventions.
MeSH term(s)	Child ; Adult ; Humans ; Sleep ; Residence Characteristics ; Health Status
Language	English
Publishing date	2024-02-05
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2023.1307630
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Article ; Online: Higher emotional awareness is associated with greater domain-general reflective tendencies.

Smith, Ryan / Persich, Michelle / Lane, Richard D / Killgore, William D S

Scientific reports

2022 Volume 12, Issue 1, Page(s) 3123

Abstract: The tendency to reflect on the emotions of self and others is a key aspect of emotional awareness (EA)-a trait widely recognized as relevant to mental health. However, the degree to which EA draws on general reflective cognition vs. specialized socio- ... ...

Abstract	The tendency to reflect on the emotions of self and others is a key aspect of emotional awareness (EA)-a trait widely recognized as relevant to mental health. However, the degree to which EA draws on general reflective cognition vs. specialized socio-emotional mechanisms remains unclear. Based on a synthesis of work in neuroscience and psychology, we recently proposed that EA is best understood as a learned application of domain-general cognitive processes to socio-emotional information. In this paper, we report a study in which we tested this hypothesis in 448 (125 male) individuals who completed measures of EA and both general reflective cognition and socio-emotional performance. As predicted, we observed a significant relationship between EA measures and both general reflectiveness and socio-emotional measures, with the strongest contribution from measures of the general tendency to engage in effortful, reflective cognition. This is consistent with the hypothesis that EA corresponds to the application of general reflective cognitive processes to socio-emotional signals.
MeSH term(s)	Adult ; Awareness ; Cognition/physiology ; Emotional Intelligence/physiology ; Emotions/physiology ; Female ; Humans ; Male ; Self Concept
Language	English
Publishing date	2022-02-24
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-022-07141-3
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Article ; Online: 2B-Alert App 2.0: personalized caffeine recommendations for optimal alertness.

Vital-Lopez, Francisco G / Doty, Tracy J / Anlap, Ian / Killgore, William D S / Reifman, Jaques

Sleep

2023 Volume 46, Issue 7

Abstract: Study objectives: If properly consumed, caffeine can safely and effectively mitigate the effects of sleep loss on alertness. However, there are no tools to determine the amount and time to consume caffeine to maximize its effectiveness. Here, we ... ...

Abstract	Study objectives: If properly consumed, caffeine can safely and effectively mitigate the effects of sleep loss on alertness. However, there are no tools to determine the amount and time to consume caffeine to maximize its effectiveness. Here, we extended the capabilities of the 2B-Alert app, a unique smartphone application that learns an individual's trait-like response to sleep loss, to provide personalized caffeine recommendations to optimize alertness. Methods: We prospectively validated 2B-Alert's capabilities in a 62-hour total sleep deprivation study in which 21 participants used the app to measure their alertness throughout the study via the psychomotor vigilance test (PVT). Using PVT data collected during the first 36 hours of the sleep challenge, the app learned the participant's sleep-loss response and provided personalized caffeine recommendations so that each participant would sustain alertness at a pre-specified target level (mean response time of 270 milliseconds) during a 6-hour period starting at 44 hours of wakefulness, using the least amount of caffeine possible. Starting at 42 hours, participants consumed 0 to 800 mg of caffeine, per the app recommendation. Results: 2B-Alert recommended no caffeine to five participants, 100-400 mg to 11 participants, and 500-800 mg to five participants. Regardless of the consumed amount, participants sustained the target alertness level ~80% of the time. Conclusions: 2B-Alert automatically learns an individual's phenotype and provides personalized caffeine recommendations in real time so that individuals achieve a desired alertness level regardless of their sleep-loss susceptibility.
MeSH term(s)	Humans ; Caffeine/pharmacology ; Mobile Applications ; Psychomotor Performance/physiology ; Attention/physiology ; Wakefulness/physiology ; Reaction Time/physiology ; Sleep Deprivation
Chemical Substances	Caffeine (3G6A5W338E)
Language	English
Publishing date	2023-03-29
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	424441-2
ISSN	1550-9109 ; 0161-8105
ISSN (online)	1550-9109
ISSN	0161-8105
DOI	10.1093/sleep/zsad080
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Article ; Online: Sex differences in limbic network and risk-taking propensity in healthy individuals.

Bajaj, Sahil / Killgore, William D S

Journal of neuroscience research

2019 Volume 98, Issue 2, Page(s) 371–383

Abstract: Little is known about the structural neural substrates that may contribute to sex differences in risk-taking propensity (RTP). A close association between risk-seeking behavior and the emotional-regulation network led us to hypothesize that the sex ... ...

Abstract	Little is known about the structural neural substrates that may contribute to sex differences in risk-taking propensity (RTP). A close association between risk-seeking behavior and the emotional-regulation network led us to hypothesize that the sex differences in RTP would be associated with sex differences in brain morphometry of the limbic network (LN). We collected RTP scores using the bubble sheet version of the evaluation of risk (EVAR) scale and neuroanatomical data from 57 healthy individuals (29 males). The EVAR scale included sub-scales measuring recklessness/impulsivity, self-confidence, and need for control (NFC). We observed significant sex differences in NFC showing greater desire for control and dominance in males than females (multivariate analysis of covariance, MANCOVAN: p = .01). Morphometry analysis showed that it was only the right LN, which showed significant sex differences in normalized surface area, normalized cortical volume, and adjusted mean curvature index (females > males) at p < .01 (MANCOVAN, corrected for multiple comparisons). Correlation analysis showed that greater curvature of the right LN was significantly associated with lower desire for control in high-risk events (r = -.31, p = .02 at 95% CI of [-0.53, -0.05]). Our findings suggest that the normalized cortical measures could indicate specific sex differences in brain morphometry, particularly within the LN. The curvature index was the only differentiating factor for greater/lower propensity for risk-taking behavior in overall sample. Therefore, the LN and the curvature measures could be key biomarkers, which play an important role in predicting risk-taking behavior.
MeSH term(s)	Adolescent ; Adult ; Female ; Humans ; Impulsive Behavior/physiology ; Limbic System/diagnostic imaging ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Risk-Taking ; Sex Characteristics ; Young Adult
Language	English
Publishing date	2019-08-01
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	195324-2
ISSN	1097-4547 ; 0360-4012
ISSN (online)	1097-4547
ISSN	0360-4012
DOI	10.1002/jnr.24504
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Zs.A 1232: Show issues

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Article ; Online: Vulnerability to mood degradation during sleep deprivation is influenced by white-matter compactness of the triple-network model.

Bajaj, Sahil / Killgore, William D S

NeuroImage

2019 Volume 202, Page(s) 116123

Abstract: Sleep deprivation (SD) is often associated with significant shifts in mood state relative to baseline functioning. Prior work suggests that there are consistent trait-like differences among individuals in the degree to which their mood and performances ... ...

Abstract	Sleep deprivation (SD) is often associated with significant shifts in mood state relative to baseline functioning. Prior work suggests that there are consistent trait-like differences among individuals in the degree to which their mood and performances are affected by sleep loss. The goal of this study was to determine the extent to which trait-like individual differences in vulnerability/resistance to mood degradation during a night of SD are dependent upon region-specific white and grey matter (WM/GM) characteristics of a triple-network model, including the default-mode network (DMN), control-execution network (CEN) and salience network (SN). Diffusion-weighted and anatomical brain data were collected from 45 healthy individuals several days prior to a 28-h overnight SD protocol. During SD, a visual analog mood scale was administered every hour from 19:15 (time point1; TP1) to 11:15 (TP17) the following morning to measure two positive and six negative mood states. Four core regions within the DMN, five within the CEN, and seven within the SN were used as regions of interest (ROIs). An index of mood resistance (IMR) was defined as the averaged differences between positive and negative mood states over 12 TPs (TP5 to TP16) relative to baseline (TP1 to TP4). For each ROI, characteristics of WM - quantitative anisotropy (QA) and mean curvature index (WM-MCI), and GM - cortical volume (CV) and GM-MCI were estimated, and used to predict IMR. WM characteristics, particularly QA, of all of regions within the DMN, and most of the regions within the CEN and SN predicted IMR during SD. In contrast, most ROIs did not show significant association between IMR and any of the GM characteristics (CV and MCI) or WM MCI. Our findings suggest that greater resilience to mood degradation induced by total SD appears to be associated with more compact axonal pathways within the DMN, CEN and SN.
MeSH term(s)	Adult ; Affect/physiology ; Cerebral Cortex/anatomy & histology ; Cerebral Cortex/diagnostic imaging ; Diffusion Tensor Imaging/methods ; Female ; Gray Matter/anatomy & histology ; Gray Matter/diagnostic imaging ; Humans ; Individuality ; Magnetic Resonance Imaging/methods ; Male ; Models, Biological ; Nerve Net/anatomy & histology ; Nerve Net/diagnostic imaging ; Resilience, Psychological ; Sleep Deprivation/complications ; Sleep Deprivation/physiopathology ; White Matter/anatomy & histology ; White Matter/diagnostic imaging ; Young Adult
Language	English
Publishing date	2019-08-25
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1147767-2
ISSN	1095-9572 ; 1053-8119
ISSN (online)	1095-9572
ISSN	1053-8119
DOI	10.1016/j.neuroimage.2019.116123
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Article ; Online: Multiple caffeine doses maintain vigilance, attention, complex motor sequence expression, and manual dexterity during 77 hours of total sleep deprivation.

Killgore, William D S / Kamimori, Gary H

Neurobiology of sleep and circadian rhythms

2020 Volume 9, Page(s) 100051

Abstract: ... group. Caffeine maintained attentiveness (1-5 s lapses) on night 1, but this advantage was lost ... on nights 2 and 3. Caffeine outperformed placebo for responsive lapses (5-9 s lapses) across all three ... lapses (beyond 10 s) were only reduced by caffeine on night 2. Caffeine was more effective than placebo ...

Abstract	Sleep deprivation (SD) and fatigue have detrimental effects on performance in operational settings. Few studies have investigated the cumulative effects of SD and fatigue on performance under heavy workload demands. Therefore, we investigated the efficacy of multiple repeated doses of caffeine as a countermeasure to SD and fatigue during 77 h total SD (TSD) during the early morning hours. Twenty-three males and females, 18 - 35 years of age, who identified as moderate caffeine consumers completed the Psychomotor Vigilance Task (PVT) 141 times during the experimental test period. Caffeine was administered in a multi-dose paradigm over three nights without sleep. Participants received either caffeine (200 mg) or placebo at the beginning of each 2-h test block from 0100 - 0900 (800 mg total per night). While PVT speed declined for both groups across all 3 nights, the caffeine group consistently out-performed the placebo group. Caffeine maintained attentiveness (1-5 s lapses) on night 1, but this advantage was lost on nights 2 and 3. Caffeine outperformed placebo for responsive lapses (5-9 s lapses) across all three nights, but caffeine performance was still notably worse than at baseline. Prolonged non-responsive lapses (beyond 10 s) were only reduced by caffeine on night 2. Caffeine was more effective than placebo across all nights at sustaining completion speed of a complex motor sequence task and a manual coordination task. Essentially, caffeine is an effective countermeasure for SD, as it mitigates declines in speed and failures to respond, and sustains motor planning and coordination. However, caffeine does not restore normal functioning during SD and cannot be considered as a replacement for sleep.
Language	English
Publishing date	2020-05-31
Publishing country	United States
Document type	Journal Article
ISSN	2451-9944
ISSN (online)	2451-9944
DOI	10.1016/j.nbscr.2020.100051
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