Dataset Information

Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation.

ABSTRACT: Theta oscillations in the EEG have been shown to reflect ongoing cognitive processes related to mental effort. Here, we show that the pattern of theta oscillation in response to varying cognitive demands reflects stable individual differences in the personality trait epistemic motivation: Individuals with high levels of epistemic motivation recruit relatively more cognitive resources in response to situations possessing high, compared to low, cognitive demand; individuals with low levels do not show such a specific response. Our results provide direct evidence for the theory of the construct need for cognition and add to our understanding of the neural processes underlying theta oscillations. More generally, we provide an explanation how individual differences in personality traits might be represented on a neural level.

SUBMITTER: Mussel P

PROVIDER: S-EPMC4933953 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation.

Mussel Patrick P Ulrich Natalie N Allen John J B JJ Osinsky Roman R Hewig Johannes J

Scientific reports 20160706

Theta oscillations in the EEG have been shown to reflect ongoing cognitive processes related to mental effort. Here, we show that the pattern of theta oscillation in response to varying cognitive demands reflects stable individual differences in the personality trait epistemic motivation: Individuals with high levels of epistemic motivation recruit relatively more cognitive resources in response to situations possessing high, compared to low, cognitive demand; individuals with low levels do not ...[more]

PMID: 27380648

Similar Datasets

Project description:Through selective attention, decision-makers can learn to ignore behaviorally irrelevant stimulus dimensions. This can improve learning and increase the perceptual discriminability of relevant stimulus information. Across cognitive models of categorization, this is typically accomplished through the inclusion of attentional parameters, which provide information about the importance assigned to each stimulus dimension by each participant. The effect of these parameters on psychological representation is often described geometrically, such that perceptual differences over relevant psychological dimensions are accentuated (or stretched), and differences over irrelevant dimensions are down-weighted (or compressed). In sensory and association cortex, representations of stimulus features are known to covary with their behavioral relevance. Although this implies that neural representational space might closely resemble that hypothesized by formal categorization theory, to date, attentional effects in the brain have been demonstrated through powerful experimental manipulations (e.g., contrasts between relevant and irrelevant features). This approach sidesteps the role of idiosyncratic conceptual knowledge in guiding attention to useful information sources. To bridge this divide, we used formal categorization models, which were fit to behavioral data, to make inferences about the concepts and strategies used by individual participants during decision-making. We found that when greater attentional weight was devoted to a particular visual feature (e.g., "color"), its value (e.g., "red") was more accurately decoded from occipitotemporal cortex. We also found that this effect was sufficiently sensitive to reflect individual differences in conceptual knowledge, indicating that occipitotemporal stimulus representations are embedded within a space closely resembling that formalized by classic categorization theory. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Project description:Sleep deprivation (SD) has been reported to severely affect executive function, and interindividual differences in these effects may contribute to the SD-associated cognition impairment. However, it is unclear how individual differences in chronotypes (morning-type, MT; evening-type, ET) influence neurobehavioral functions after SD. To address this question, we used functional magnetic resonance imaging (fMRI) to evaluate whether 24 h of SD differentially affect response inhibition, a core component of executive function, in MT and ET individuals. Accordingly, MT and ET participants were instructed to follow their preferred 7-9-h sleep schedule for 2 weeks at home both prior to and throughout the course of the study, and then performed a go/no-go task during fMRI scanning at 08:00 a.m. both at rested wakefulness (RW) and following SD. We also examined whether the neurobehavioral inhibition differences in the chronotypes in each session can be predicted by subjective ratings (sleepiness, mood, and task) or objective attention. Behaviorally, SD led to an increased response time of go trials (hit RT), more attentional lapses, higher subjective sleepiness, and worse mood indices, but it did not impair the accuracy of go trials (hit rate) and no-go trials (stop rate). Regardless of the presence of SD, ET individuals exhibited a lower stop rate, higher subjective ratings of sleepiness, exhausted mood, and task difficulty in comparison with MT individuals. On the neural level, SD resulted in decreased inhibition-related activation of the right lateral inferior frontal gyrus (rIFG) in MT individuals and increased rIFG activation in ET individuals. Moreover, the rIFG activation in ET individuals after SD was positively correlated to the subjective ratings of sleepiness and effort put into the task, which was considered as a compensatory response to the adverse effects of SD. These findings suggest that individual differences in inhibition-related cerebral activation after SD are influenced by chronotypes. In addition, ET individuals may be vulnerable to response inhibition. Thus, it is essential to take into consideration the chronotype in SD research and sleep medicine.

Dataset Information

Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation.

Publications

Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets