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Institut
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ~ .20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the defaultmode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Significance Statement Spontaneous brain activity builds the foundation for intelligent processing - the ability of humans to adapt to various cognitive demands. Using resting-state EEG, we extracted multiple aspects of temporally highly resolved intrinsic brain dynamics to investigate their relationship with individual differences in intelligence. Single associations were of small effect sizes and varied critically across spatial and temporal scales. However, combining multiple measures in a multimodal cross-validated prediction model, allows to significantly predict individual intelligence scores in unseen participants. Our study adds to a growing body of research suggesting that observable associations between complex human traits and neural parameters might be rather small and proposes multimodal prediction approaches as promising tool to derive robust brain-behavior relations despite limited sample sizes.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. A huge number of neuroimaging studies identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, respective research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) in regard to their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ~ .20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Significance Statement Spontaneous brain activity builds the foundation for intelligent processing - the ability of humans to adapt to various cognitive demands. Using resting-state EEG, we extracted multiple aspects of temporally highly resolved intrinsic brain dynamics to investigate their relationship with individual differences in intelligence. Single associations were of small effect sizes and varied critically across spatial and temporal scales. However, combining multiple measures in a multimodal cross-validated prediction model, allows to significantly predict individual intelligence scores in unseen participants. Our study adds to a growing body of research suggesting that observable associations between complex human traits and neural parameters might be rather small and proposes multimodal prediction approaches as promising tool to derive robust brain-behavior relations despite limited sample sizes.
The implications of telework are discussed controversially and research on its positive and negative effects has produced contradictory results. We explore voluntariness of employee telework as a boundary condition which may underpin these contradictory findings. Under normal circumstances, individuals who do more telework should perceive fewer disadvantages. However, during the COVID-19 pandemic, employees could no longer voluntarily choose to telecommute, as many organizations were forced to introduce telework by governmental regulations. In two studies, we examine whether the voluntary nature of telework moderates the association between the amount of telework and perceptions of disadvantage. In Study 1, we collected data before and during the COVID-19 pandemic (N = 327). Results show that pre-pandemic participants (who were more likely to voluntarily choose this form of work) reported fewer disadvantages the more telework they did, but this was not the case for employees during the COVID-19 pandemic. To validate these findings, we measured employees’ voluntariness of telework in Study 2 (N = 220). Results support the importance of voluntariness: Individuals who experience a high degree of voluntariness in choosing telework perceive fewer disadvantages the more they telework. However, the amount of telework was not related to reduced perceptions of disadvantages for those who experienced low voluntariness regarding the telecommuting arrangement. Our findings help to understand when telework is related to the perception of disadvantages and they can provide organizations with starting points for practical interventions to reduce the negative effects of telework.
The implications of telework are discussed controversially and research on its positive and negative effects has produced contradictory results. We explore voluntariness of employee telework as a boundary condition which may underpin these contradictory findings. Under normal circumstances, individuals who do more telework should perceive fewer disadvantages. However, during the COVID-19 pandemic, employees could no longer voluntarily choose to telecommute, as many organizations were forced to introduce telework by governmental regulations. In two studies, we examine whether the voluntary nature of telework moderates the association between the amount of telework and perceptions of disadvantage. In Study 1, we collected data before and during the COVID-19 pandemic (N = 327). Results show that pre-pandemic participants (who were more likely to voluntarily choose this form of work) reported fewer disadvantages the more telework they did, but this was not the case for employees during the COVID-19 pandemic. To validate these findings, we measured employees’ voluntariness of telework in Study 2 (N = 220). Results support the importance of voluntariness: Individuals who experience a high degree of voluntariness in choosing telework perceive fewer disadvantages the more they telework. However, the amount of telework was not related to reduced perceptions of disadvantages for those who experienced low voluntariness regarding the telecommuting arrangement. Our findings help to understand when telework is related to the perception of disadvantages and they can provide organizations with starting points for practical interventions to reduce the negative effects of telework.
Free gaze and moving images are typically avoided in EEG experiments due to the expected generation of artifacts and noise. Yet for a growing number of research questions, loosening these rigorous restrictions would be beneficial. Among these is research on visual aesthetic experiences, which often involve open-ended exploration of highly variable stimuli. Here we systematically compare the effect of conservative vs. more liberal experimental settings on various measures of behavior, brain activity and physiology in an aesthetic rating task. Our primary aim was to assess EEG signal quality. 43 participants either maintained fixation or were allowed to gaze freely, and viewed either static images or dynamic (video) stimuli consisting of dance performances or nature scenes. A passive auditory background task (auditory steady-state response; ASSR) was added as a proxy measure for overall EEG recording quality. We recorded EEG, ECG and eye tracking data, and participants rated their aesthetic preference and state of boredom on each trial. Whereas both behavioral ratings and gaze behavior were affected by task and stimulus manipulations, EEG SNR was barely affected and generally robust across all conditions, despite only minimal preprocessing and no trial rejection. In particular, we show that using video stimuli does not necessarily result in lower EEG quality and can, on the contrary, significantly reduce eye movements while increasing both the participants’ aesthetic response and general task engagement. We see these as encouraging results indicating that — at least in the lab — more liberal experimental conditions can be adopted without significant loss of signal quality.
This cross-sectional study examined gender differences between male- and female-typed housework during the early COVID-19 lockdowns in 2020. Participants in Germany, India, Nigeria, and South Africa (N = 823) rated their housework share before and during the lockdown, then speculated about the division of housework performed by men and women in general, before and post-lockdown. Women spent more time on female-typed tasks and men (in Nigeria and South Africa) on male-typed tasks before and during the lockdown. Irrespective of participants’ gender, they speculated that men's and women's housework was more pronounced post-lockdown than before, but we only found gender differences in South Africa and India. Gender role ideology (GRI) moderated the gender‒housework relationship in Germany, but gender did not moderate the paid work hours and housework relationship in any country. Our findings suggest that gendered housework persisted in these countries and raises concerns that this pattern is likely to continue post-lockdown.
Based on the stressor-detachment model, previous research has assumed that work-related ICT use in the evening impairs psychological detachment. However, since most of the studies to date have assessed cross-sectional relationships, little is known about the actual direction of effects. In this 5-day diary study, we implemented a day-level longitudinal model to shed light on the causal relationships between work-related ICT use, detachment, and task progress (N = 340 employees, N = 1289 day-level cases). We also investigated the role of unfinished work tasks because we assumed, based on boundary theory, that they are a driving force leading to impaired detachment and work-related ICT use in the evening. Contrary to current research consensus but in line with our expectations, we found that low psychological detachment increased work-related ICT use and task progress. We found no evidence for reversed lagged effects. These results applied both to planned and unplanned ICT use. Furthermore, our results support the notion that unfinished work tasks precede ICT use and detachment. Thus, our findings suggest that work-related ICT use should not be treated as a stressor in its own right in the stressor-detachment model. Instead, it needs to be investigated as a behavioral outcome that employees engage in when they cannot detach from work.
Rezension zu: Social preferences: an introduction to behavioural economics and experimental research, by Michalis Drouvelis, Newcastle upon Tyne: Agenda Publishing, 2021, 205 pages, £22.99, ISBN 978-1-78821-417-9 (paperback).
Innovation is considered essential for today's organizations to survive and thrive. Researchers have also stressed the importance of leadership as a driver of followers' innovative work behavior (FIB). Yet, despite a large amount of research, three areas remain understudied: (a) The relative importance of different forms of leadership for FIB; (b) the mechanisms through which leadership impacts FIB; and (c) the degree to which relationships between leadership and FIB are generalizable across cultures. To address these lacunae, we propose an integrated model connecting four types of positive leadership behaviors, two types of identification (as mediating variables), and FIB. We tested our model in a global data set comprising responses of N = 7,225 participants from 23 countries, grouped into nine cultural clusters. Our results indicate that perceived LMX quality was the strongest relative predictor of FIB. Furthermore, the relationships between both perceived LMX quality and identity leadership with FIB were mediated by social identification. The indirect effect of LMX on FIB via social identification was stable across clusters, whereas the indirect effects of the other forms of leadership on FIB via social identification were stronger in countries high versus low on collectivism. Power distance did not influence the relations.
Objectives: Interpersonal factors, such as impairments in social interaction or lack of social support, have an important share when it comes to the development, maintenance, and progression of various mental disorders.
Methods: Individuals suffering from prolonged grief disorder (PGD) and matched bereaved healthy controls (n = 54) underwent a thorough diagnostic procedure, further completed the Inventory of Interpersonal Problems (IIP-D-32), and participated in a finitely iterated prisoner's dilemma (FIPD).
Results: Individuals suffering from PGD reported significantly more interpersonal problems. Both groups behaved differently in the FIPD with healthy controls being more carefully, adapting their behavior more flexible, whereas PGD patients displayed a lower responsiveness, which may indicate an inability to adapt to changes in relationships.
Conclusion: We conclude that interpersonal problems appear to be a relevant feature of PGD. Future studies need to clarify the causal relation behind this link, and should also include measures of attachment, social support, and disconnectedness.