Electrophysiological Prints of Grit

Abstract

While scientific interest in understanding the grit trait has grown exponentially in recent years, one important gap in the grit literature relates to its biological and neural substrate. In the present study, we adopted a hypotheses-driven approach in a large sample of young adults (N = 120) with diverse educational backgrounds and work experiences in order to investigate the electrophysiological correlates of grit both during rest and while performing a learning task. Additionally, we selected a measure of impulsiveness to better understand the neural similarities and differences between grit and related self-control constructs. Based on previous work that implicated the prefrontal cortex in grit, we hypothesized that high grit participants would have lower frontal theta/beta ratio (a broadly used index that reflects prefrontally-mediated top–down processes, which might indicate better control over subcortical information). Furthermore, we expected the perseverance of effort facet of grit to be linked to higher complexity during task engagement because previous research has shown complexity indexes (entropy and fractal dimension) to be linked to effort while performing cognitive tasks. Our results revealed that although there were no differences at rest as a function of grit, the participants with high grit and high consistency of interest scores exhibited lower frontal theta/beta ratios during the learning task. This pattern suggests that individual differences in grit might be more evident when top-down control processes are at work. Furthermore, there was a positive association between perseverance of effort and entropy at task, which might indicate more effort and engagement in the task. Finally, no association was found between the neural indexes (frontal theta/beta ratio, entropy, or fractal dimension) and impulsiveness, neither impulsiveness mediated between grit and brain measures. Finally, when controlling for impulsiveness and demographic variables (gender, age, education, and work experience) the effects at the facet level remained statistically significant. While there is still a long way to fully understand the neural mechanisms of grit, the present work constitutes a step toward unveiling the electrophysiological prints of grit.

The relative role of executive control and personality traits in grit

“…We first performed Spearman correlations between the main variables of interest to identify potential predictors of grit. As can be seen in Table 2 , the two personality traits highly correlated with grit and its facets (please, note that the correlation between BISS and Grit has been previously informed in [ 52 ], where BISS was used as a control variable to partial out the variance explained by this variable in the relationship between grit and the reported brain measures). Correlations between grit and the facets of the FFMQ are available in Supplementary Material 3 in S1 File .…”

“…One possible explanation of this discrepancy is the lack of correspondence between the self-reported measures of self-control and the executive-control indexes derived from experimental tasks [i.e., see, 68 , 69 ], as well as between brain activity and performance. Thus, for example, previous results have showed grit to be linked to electrophysiological activity thought to reflect better effortful control in a learning task, but not to better learning performance [ 52 ].…”

“…A hundred thirty-four people ( M age = 22.92, SD age = 4.1, Range Age = 18–33, 72% female) participated in the study in exchange for course credits (1/40min) or monetary reward (7€/1h). This sample has been previously reported in two related studies: One aimed to examine the relationship between mindfulness and cognitive control modes [ 51 ], and another one focusing on the electrophysiological correlates of grit [ 52 ]. All studies are part of a larger research project on individual differences so that participants were administrated several different experimental tasks and questionnaires along with two assessment sessions.…”

Electrophysiological correlates of dispositional mindfulness: A quantitative and complexity EEG study

“…One hundred twenty people (Mage = 23.11, SDage = 4.19, Range = 18-33, 69% female) completed the study in exchange for course credits (0.1credit/40 min) or monetary reward (7€/1 h). This sample took part in a larger individual differences study from which other non-overlapping findings have been already reported (Aguerre et al, 2020(Aguerre et al, , 2021(Aguerre et al, , 2022. To confirm that the sample size of the bigger project was enough to capture the desired effects, we calculated a priori power analysis (G*Power 3.1.9.2; Erdfelder et al, 1996) based on the effect of the linear regression reported by Kong et al (2016), with an R 2 = .14, as we also adopted an regression approach.…”

Feasibility of a novel neurofeedback system: a parallel randomized single-blinded pilot study

“…We wanted to know whether it is possible to implement such a system based on brain signals recorded above the frontal and occipital cortices. The role of theta-beta ratio (TBR) (i.e., the ratio of power within the 4–7 Hz and 13–30 Hz ranges) of signals measured above the frontal areas have been reported in relation to attentional control 31 – 33 , emotion regulation 34 , 35 , grit (perseverance) 36 and correct time perception 37 negatively and to mind wandering positively 38 – 40 . Despite of not being primary sites of motor planning or execution, occipital areas have also been mentioned in the literature in the context of motor control and SMR NF.…”