Fluid Intelligence Based On FNIRS And EEG Characterization Of Brain Functional Networks And EEG Spectrum

Intelligence is a general ability involving multiple cognitive processes and many cortical areas throughout the brain,of which fluid intelligence and crystal intelligence have been considered by many theories of intelligence as the two main categories of cognitive ability,crystal intelligence being the cognitive ability based on learned experience and fluid intelligence being the ability to solve novel problems in the absence of experience.For fluid intelligence,both traditional paper-and-pencil tests and studies of brain mechanisms can reflect intelligence levels,where studies of brain mechanisms are more objective and direct,and new brain imaging techniques such as functional near-infrared imaging(fNIRS)and electroencephalography(EEG)can also help us to obtain more information about brain activity.Therefore,we need to further investigate the mechanisms based on the functional brain network and the state of consciousness influencing the level of individual fluid intelligence by fNIRS and EEG to uncover the characteristics of fNIRS and EEG on the functional brain network and EEG spectrum.Through this study,we were able to clarify the exploration and application of brain function for intelligence,identify the brain function characteristics of fluid intelligence,and provide a basis for the development of portable intelligence testing tools.In Experiment 1,154 university students were recruited,and near-infrared imaging was used in combination with the Behavioral Test of Fluid Intelligence(Raven’s Advanced Reasoning Test)to perform 30-minute resting-state near-infrared measurements of the subjects’ DLPFC brain regions,and the raw data were preprocessed,and the processed light intensities were subsequently calculated according to a modified Beer-Lambert law,yielding changes in the relative concentrations of the overall hemoglobin(HbT)The signal of HbT was calculated based on the HbT values,paired Pearson correlation was calculated to form a functional connectivity matrix,and the correlation matrix values calculated based on HbT were used to represent the functional connectivity values of the brain,and a partial correlation analysis was done between the mean prefrontal functional connectivity values and the Raven’s Advanced Reasoning Test scores to detect the association between the fluid intelligence level and the functional brain network of individuals in the resting state.It was found that the mean values of prefrontal functional connectivity at rest were significantly and negatively correlated with the level of fluid intelligence(r =-0.227,p= 0.019).This suggests that individuals with high levels of fluid intelligence have lower levels of functional prefrontal brain information exchange at rest,and that low connectivity between prefrontal brain functions at rest is more conducive to the performance of fluid intelligence,meaning that individuals with high levels of fluid intelligence tend to have weaker prefrontal brain functional connectivity and lower levels of information exchange in the corresponding brain regions at rest.In Experiment 2,93 university students were recruited,and the EEG technique was combined with the Fluid Intelligence Behavior Test(Raven’s Advanced Reasoning Test)to perform 10-minute resting EEG measurements on the subjects,and the EEG power spectral density(uV2/Hz)of the electrodes was calculated using Fast Fourier Transform(FFT)after pre-processing the raw data.The absolute power in the delta band(1-4Hz),theta band(4-8Hz),alpha low band(8-10Hz),alpha high band(10-13Hz),alpha band(8-13Hz),and beta band(13-30Hz)was calculated,and the ratio of theta power to alpha power(TAR)was calculated,and the correlation between the power of each EEG frequency band and the level of fluid intelligence was analyzed as a partial correlation to detect the association between the level of fluid intelligence and the state of consciousness in the resting state.Specifically,the absolute power of theta and TAR were significantly negatively correlated with the level of fluid intelligence(r =-0.343,p = 0.008;r =-0.261,p =0.048).This indicates that the level of relaxation of the individual in the resting state is associated with fluid intelligence,and the lower the activity level of the individual’s brain,the higher the level of fluid intelligence.Overall,the present study used fNIRS and EEG to explore the characteristics of the individual’s functional brain network mechanisms and states of consciousness as reflected in the level of fluid intelligence.Using fNIRS results we found that individuals with higher levels of intelligence had lower levels of information exchange in their brains.Using the EEG results we found that individuals with higher levels of intelligence had lower levels of brain activity and higher levels of intelligence.This suggests that individuals with high fluid intelligence have lower levels of overall brain activity,which may be related to the fact that they are better at allocating cognitive resources rationally.In the task state,task-related brain areas are aroused,while unrelated brain areas are under-connected to maximize efficiency,whereas individuals in the resting state,where the brain is in a "resting" state,are able to reduce "meaningless" In the resting state,individuals whose brains are in a "resting" state can reduce the waste of "meaningless" cognitive resources and tend to exhibit higher fluid intelligence.