Prediction of cognitive scores by joint use of movie-watching fMRI connectivity and eye tracking via Attention-CensNet

Seeing in crowds: Averaging first, then max

Crowding, a fundamental limit in object recognition, is believed to result from excessive integration of nearby items in peripheral vision. To understand its pooling mechanisms, we measured subjects' internal response distributions in an orientation crowding task. Contrary to the prediction of an averaging model, we observed a pattern suggesting that the perceptual judgement is made based on choosing the largest response across the noise-perturbed items. A model featuring first-stage averaging and second-stage signed-max operation predicts the diverse errors made by human observers under various signal strength levels. These findings suggest that different rules operate to resolve the bottleneck at early and high-level stages of visual processing, implementing a combination of linear and nonlinear pooling strategies.

Regularity and variability of functional brain connectivity characteristics between gyri and sulci under naturalistic stimulus

The human cerebral cortex is folded into two fundamentally anatomical units: gyri and sulci. Previous studies have demonstrated the genetical, structural, and functional differences between gyri and sulci, providing a unique perspective for revealing the relationship among brain function, cognition, and behavior. While previous studies mainly focus on the functional differences between gyri and sulci under resting or task-evoked state, such characteristics under naturalistic stimulus (NS) which reflects real-world dynamic environments are largely unknown. To address this question, this study systematically investigates spatio-temporal functional connectivity (FC) characteristics between gyri and sulci under NS using a spatio-temporal graph convolutional network model. Based on the public Human Connectome Project dataset of 174 subjects with four different runs of both movie-watching NS and resting state 7T functional MRI data, we successfully identify unique FC features under NS, which are mainly involved in visual, auditory, emotional and cognitive control, and achieve high discriminative accuracy 93.06 % to resting state. Moreover, gyral regions as well as gyro-gyral connections consistently participate more as functional information exchange hubs than sulcal ones among these networks. This study provides novel insights into the functional brain mechanism under NS and lays a solid foundation for accurately mapping the brain anatomy-function relationship.