Abstract
The Eriksen Flanker task has been widely used as a measurement of cognitive control, however till now information is still scarce about how the neuroanatomical properties are related to performance in this task. Using voxel-based morphometry technique (VBM), the current study identified a set of distributed areas where the gray matter volume (GM) correlated positively with participants’ efficiency in interference inhibition. These areas included the bilateral prefrontal gyri, left insula and inferior temporal gyrus, the left inferior parietal lobule. Further analysis using a novel machine learning algorithm with balanced cross-validation procedure confirmed that in these areas the GM-behavioral association was unlikely a byproduct of outlier values, instead, the gray matter volume could predict reliably participants’ interference inhibition efficiency. These results underscore the importance of the fronto-parietal and insula systems to the brain functioning of interference inhibition from the neuroanatomical perspective.
Highlights
Efficient task execution requires fast and accurate target orienting and processing
Since the conventional regression models assess correlation coefficients, which are sensitive to outliers and likely correlational with no predictive value [29, 33, 35], we used a machine learning algorithm with balanced cross-validation [28, 29] to confirm the robustness of the relation between interference inhibition and gray matter volume (GM) volume in—clusters identified above
It was hypothesized that if the regional GM volume was predictive for the efficiency of interference inhibition, randomly reallocating this variable would reduce the predictability of the model
Summary
Efficient task execution requires fast and accurate target orienting and processing. But quite frequently, the target isn’t presented alone but accompanied by some distracting stimuli irrelevant to our goal. They found that the deterioration in interference inhibition was associated with atrophy in the lateral prefrontal cortex bilaterally, DLPFC, extending to the frontal pole and orbitofrontal cortex, right VLPFC and right temporal-parietal junction, as well as left anterior cingulate cortex and cerebellum Since these two studies were conducted on elderly or patients[26, 27], questions remain wide open if their findings could be generalized to healthy young adults, because aging could alter the brain structure and function of cognitive control [26, 27]. We conducted a novel validation analysis using machine learning algorithms with a balanced threefold cross-validation procedure [28, 29] to verify the robustness of the neural-behavioral correlation in the areas identified
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
