Research On The Brain Mechanism Of Personality Traits: Based On Resting-state FMRI Data-driven Classification

Objective: Following the "brain-centered" research strategy, using data-driven method(generalized ranking and averaging independent component analysis by reproducibility,g RAICAR) to dig deeper into the individual brain resting-state functional magnetic resonance imaging(f MRI) data, classification of people based on the individual brain imaging features, with the different theory of "personality genre" to verify and explain the different groups reflect the characteristics of resting state brain activity of inter individual variation, finally finding out those personality traits based on brain neural activity, being independent of the Personality Q uestionnaire makers’ experiences,and have stronger explanatory power of the brain imaging features.Methods: Collecting subjects by posting volunteer recruitment book in the community. Collecting brain imaging data: tried to collect high resolution 3D whole brain T1 weighted and resting-state functional magnetic resonance imaging(f MRI) data by using Germany’s Siemens company Siemens Magnetom Trio 3T MR whole body imaging(MRI) system. Collecting behavioral indicators: using Eysenck Personality Questionnaire(EPQ), Sixteen Personality Factor Questionnaire(16pf) and N EO-FFI to collect different dimensions of personality traits. A data quality control procedure was conducted to ensure the data were usable for subsequent analyses. Finally, we collected a total of 123 participants into the group standard. The images were preprocessed using the Connectome Computation System(Connectome Computation System,CCS). The preprocessed functional images were processed using g RAICAR to characterize the consistency of the ICNs across all of the subjects, investigating whether the subjects can be grouped into communities according to the variations of their resting-state brain functional networks. Using collected psychological variables(multidimensional personality traits from the Three Personality Trait Theory) to verify and explain all groups. Finally, associating resting-state brain activity with psychological characteristics variables reflecting inter-individual variability of different groups.Results: Comprehensive preliminary results and found that after the preliminary results of verification, 18 kinds of personality traits(EPQ : neurotic; NEO : extraversion, neuroticism, agreeableness and responsibility; 16pf: gregarious, stability, dare, experimental, self-discipline, intelligence, aggressiveness, persistence sensitivity, fantasy, anxiety, independence and tension) found no significant correlation to its resting-state brain function network; 6 kinds of personality traits(EPQ : extraversion, psychoticism; NEO: openness; 16pf: sophistication, excitement, suspicion) corresponding to the five resting-state functional connectivity of brain networks have significant correlation to personality score(packet) circumstances : different personality trait score(packet) corresponding to the resting-state functional connectivity of brain networks strength were significantly different.(1) Openness of the subjects group scored higher whose resting-state functional connectivity strength of precuneus- inferior parietal lobule network is significantly higher than the rest of the participants(t=-3.41,p< 0.001).(2) Typical extroversion group of participants whose resting-state functional connectivity strength of salience network is significantly higher than the rest of the participants(t=-2.02,p<0.05).(3) Excitatory scored higher group of participants and skeptical low score group of subjects whose resting-state functional connectivity strength of sensorimotor network is significantly higher than the rest of the participants(t=-3.12,p<0.01;t=2.74,p<0.01).(4) Three groups: sophisticated score low, middle, high sophistication score whose resting-state functional connectivity strength of Left-lateralized parietal- frontal network is significantly different,and sophisticated score low group of participants has top most strong resting-state functional connectivity strength of Left- lateralized parietal- frontal network, high sophistication score group of participants has minimal resting-state functional connectivity strength of Left- lateralized parietal- frontal network(F=3.48,p<0.05).(5) Three groups: the normal range and the tendency of psychoticism and psychoticism whose resting-state functional connectivity strength of default network is significantly different,and psychoticism has top most strong resting-state functional connectivity strength of default network, the normal range of subjects has minimal resting-state functional connectivity strength of default network.Conclusions: The present study follows the research strategies of "brain-centered", based on brain imaging characteristics of individual differences, research on the brain mechanism of 24 kinds of perso nality traits. Eventually found, according to the resting state cerebral network(precuneus- top lobule, highlight the network, the left- lateralized parietal- frontal network, sensorimotor network and network by default) the size of the degree of activity, we can be certain personality traits(openness, typical extroversion, sophistication, excitability, doubting and psychoticism) distinguished individuals from the crowd. We can conclude that the 6 kinds of personality traits relative to the remaining 18 kinds of personality traits, not only on the basis of the brain neural activity, and independent of the personality traits scale makers subjective experience, and have stronger brain imaging characteristics of explanatory power. The 6 kinds of personality traits are: 1. The openness of the big five personality theory. According to the high levels of resting-state functional connectivity strength of the precuneus-inferior parietal lobule network, we can distinguish the individuals with high scores from the crowd. 2. The extroversion of the Eysenck’s personality theory. According to the high levels of resting-state functional connectivity strength of the salience network,we can distinguish the typical extroversion individuals from the crowd. 3. The excitability and doubting of the Cartel personality theory. According to the high or low levels of resting-state functional connectivity strength of the sensorimotor network, we can distinguish the individuals with high excitability scores and individuals with low doubting scores from the crowd. 4. The sophistication of the Cartel personality theory. In the sophisticated score low, intermediate, sophisticated scores of three groups, individuals on the left- lateralized parietal- frontal network connection strength exhibits a high, medium and low distribution. 5. The psychoticism of the Eysenck’s personality theory. In the normal range, the tendency of psychoticism and psychoticism of three groups, individuals on the default network connection strength exhibits a low, medium and high distribution.