This study investigates the relationship between autistic traits, interoceptive awareness, and sensorimotor cognitive flexibility. Building on the Interoceptive Trait Prediction Error (ITPE) theory...Show moreThis study investigates the relationship between autistic traits, interoceptive awareness, and sensorimotor cognitive flexibility. Building on the Interoceptive Trait Prediction Error (ITPE) theory, it is hypothesized that autistic traits are predictive of cognitive flexibility in a negative direction, while interoceptive awareness is predictive of cognitive flexibility in a positive direction. Interoceptive awareness was measured with the eight subscales of the Multidimensional Assessment of Interoceptive Awareness Version 2 (Noticing, Not Distracting, Not Worrying, Attention Regulation, Emotional Awareness, Self-Regulation, Body Listening, and Trust), and autistic traits were measured with the short version of the Autism Quotient (AQ-10). Sensorimotor cognitive flexibility was measured with a virtual reality game task. With the data of 80 participants, a multiple linear regression was performed. Emotional awareness significantly and positively predicted cognitive flexibility, which can be explained through the lens of emotion regulation. Autistic traits significantly predicted cognitive flexibility in a negative direction. However, the regression model in which these predictors existed was insignificant, leading to overall inconclusive results. Future replication based on our limitations is encouraged, and the necessity of similar research is underlined in light of autistic trait networks.Show less
This study aimed to expand on previous research regarding the stability-flexibility dilemma and the adjustment of neural gain. Specifically, it was investigated if people lower their neural gain in...Show moreThis study aimed to expand on previous research regarding the stability-flexibility dilemma and the adjustment of neural gain. Specifically, it was investigated if people lower their neural gain in response to a short CSI. Previous research showed that people can adjust their neural gain based on the demand for flexibility. Specifically, lower neural gain would facilitate flexibility, but at the cost of stability. In addition, the relation between ADHD and neural gain was studied. Participants were asked to take part in a task-switching experiment in which they had to classify digits either based on parity or magnitude. Herein, the CSI duration was manipulated. Afterwards, a computational model estimated the neural gain values per condition. Participants were also asked to fill out an ADHD questionnaire. The final number of participants was 60 aged between 18 and 30. The results showed that the participants had higher switch costs and higher incongruency costs when the time to prepare was short. In addition, it was found that the participants lowered their neural gain in response to a short preparation time. Contradictory to our expectations, no relation was found between ADHD and neural gain adjustment. Together, the behavioral results and the neural gain analysis show that while lowering gain facilitates switching and thus flexibility, it also reduces focus and thus stability. For future research, it is suggested to replicate the study in a controlled environment and specifically regarding ADHD to either use a clinical sample or additional assessment tools, such as eye-tracking.Show less
Numerous studies have been directed to the interaction between intelligence and (mathematical) creativity. However, there is no consistency in the results of these studies they are mostly based on...Show moreNumerous studies have been directed to the interaction between intelligence and (mathematical) creativity. However, there is no consistency in the results of these studies they are mostly based on adolescents and/or adults. This study aims to understand the relationship between intelligence and mathematical creativity by examining these constructs among primary school children in the age of 8 to 12. The sample was collected in The Netherlands among nine primary schools and consists of 334 students. A verbal intelligence subtask was conducted to determine the verbal intelligence level of students in either low, average or high. A mathematical divergent thinking task was conducted to determine the mathematical creativity score of students, the score is based on the creativity components fluency, flexibility and originality. The results indicate a positive relationship between intelligence and mathematical creativity. Students with the highest intelligence scores also have the highest mathematical creativity scores. Accordingly, students with average or low intelligence scores have a significantly lower level of mathematical creativity than students with high intelligence scores. No support was obtained for the hypothesis that the relationship between originality and intelligence would be stronger than the relationship between intelligence and fluency and flexibility. These results are discussed in light of domain-specificity, executive functions, uncontrolled variables and reliability.Numerous studies have been directed to the interaction between intelligence and (mathematical) creativity. However, there is no consistency in the results of these studies they are mostly based on adolescents and/or adults. This study aims to understand the relationship between intelligence and mathematical creativity by examining these constructs among primary school children in the age of 8 to 12. The sample was collected in The Netherlands among nine primary schools and consists of 334 students. A verbal intelligence subtask was conducted to determine the verbal intelligence level of students in either low, average or high. A mathematical divergent thinking task was conducted to determine the mathematical creativity score of students, the score is based on the creativity components fluency, flexibility and originality. The results indicate a positive relationship between intelligence and mathematical creativity. Students with the highest intelligence scores also have the highest mathematical creativity scores. Accordingly, students with average or low intelligence scores have a significantly lower level of mathematical creativity than students with high intelligence scores. No support was obtained for the hypothesis that the relationship between originality and intelligence would be stronger than the relationship between intelligence and fluency and flexibility. These results are discussed in light of domain-specificity, executive functions, uncontrolled variables and reliability.Show less