Investigating Neurocognitive Mechanism Of Mathematically Gifted Adolescents Based On EEG Analysis

As the cornerstone of natural sciences, mathematics influences and changes our technology-oriented world all the time. Showing innate passion for mathematics and superior problem-solving skills, mathematically gifted children are expected to be creative in mathematics, engineering or technical field in the future. The importance of fostering and developing mathematically gifted children has been acknowledged widely. In the field of cognitive neuroscience, past studies on mathematically gifted brains underlying logical reasoning, mental imagery and creative thinking have concentrated on investigating event-related brain activation regions, cerebral laterality of cognitive functions, functional specialization serving for specific cognitive purposes, and functional integration among discrete brain regions. These studies have witnessed both "general" and "unique" neural characteristics of mathematically gifted brains, from structural and functional perspectives.However, the past empirical studies on mathematically gifted brains have often used fMRI neuroimaging techonology, which has a limitation in that the time information is discounted. On the other hand, although the EEG method has the satisfied temporal resolution, the past studies have not involoved the in-depth data mining of the giftedness-related neural features. In this research, based on the characteristic of gifted adolescents in mathematical thinking process and the previous neuroscience findings on mathematically gifted brains, novel experimental tasks were designed and the data from 11 mathematically gifted and 13 average-ability adolescents were recorded in the experiment. Based on the event-related EEG signals and the relevant data analytical mothods, the following studies have been conducted:1) The study of functional reorganization of low-frequency theta network and global neuronal workspace:Previous studies have established the importance of the fronto-parietal brain network for information processing of reasoning. At the level of cortical source analysis, this EEG study investigated the functional reorganization of theta-band (4-8Hz) neurocognitive network in mathematically gifted adolescents during deductive reasoning. Depending on the dense increase of long-range phase synchronization in the reasoning process, the mathematically gifted adolescents show more significantly adaptive reorganization and enhanced "workspace" configuration in the theta network as compared with the average-ability controls, which are more salient in the anterior cortical vertices of the fronto-parietal network. Further correlation analyses find that the enhanced workspace configuration in the global topological metrics of theta network of the mathematically gifted subjects is correlated with the intensive frontal midline theta (fm theta) response that is related to strong neural effort for a cognitive event. These results suggest that by investing more cognitive resources the mathematically gifted adolescents temporally mobilize an enhanced task-related global neuronal workspace expressed as highly integrated fronto-parietal information processing network during the reasoning process.2) The study of functional binding in high-frequency gamma fronto-parietal network:As enhanced fronto-parietal network has been suggested to support reasoning ability of mathematically gifted adolescents, the main goal of this EEG source analysis is to investigate the temporal binding of the gamma-band (30-60Hz) synchronization between frontal and parietal cortices in adolescents with exceptional mathematical ability, including the functional connectivity of gamma neurocognitive network, the temporal dynamics of fronto-parietal network (phase-locking durations and network lability in time domain), and the self-organized criticality of synchronizing oscillation. Compared with the average-ability subjects, the mathematically gifted adolescents show a highly integrated fronto-parietal network due to distant gamma phase-locking oscillations, which is indicated by lower modularity of the global network topology, more "connector bridges" between the frontal and parietal cortices and less "connector hubs" in the sensorimotor cortex. The time-domain analysis finds that, while maintaining more stable phase dynamics of the fronto-parietal coupling, the mathematically gifted adolescents are characterized by more extensive fronto-parietal connection reconfiguration. The results from sample fitting in the power-law model further show that the phase-locking durations in the mathematically gifted brain abides by a wider interval of the power-law distribution. This phase-lock distribution mechanism could represent a relatively optimized pattern for the functional binding of frontal-parietal network, which underlies stable fronto-parietal connectivity and increases flexibility of timely network reconfiguration.3) The study of localization of neural efficiency related to mathematical giftedness:Based on the neural efficiency hypothesis and task-induced EEG gamma-band response (GBR), this study investigated the brain regions where neural resource can be most efficiently recruited by the mathematically gifted adolescents in response to varying cognitive demands. In this experiment, various GBR-based mental states were generated with three factors (level of mathematical cognition, task complexity and adaptation in cognitive process) modulating the strength of neural activation. A feature subset selection method based on the sequential forward floating search (SFFS) algorithm was used to identify an "optimal" combination of EEG channel locations, where the corresponding GBR feature subset could obtain the highest discrimination accuracy in distinguishing pairwise mental states influenced by each experiment factor. The integrative results from multi-factor selections suggest that the right-lateral fronto-parietal system is highly involved in neural efficiency of the mathematically gifted brain, primarily including the bilateral superior frontal, right inferior frontal, right-lateral sensorimotor and right temporal regions.The analytical results of EEG dynamical network in time domain further develop the neuroscience research on fronto-parietal network of mathematically gifted brain. By means of the feature subset selection method based on single-trial classification of mental states, new GBR features and EEG channel-based brain locations could be useful for the functional improvement of children/adolescents in mathematical learning through brain-computer interface (BCI) systems.