| Background: Meta-control ability is a kind of advanced cognitive control ability,which indirectly affects decision making and behavior outcomes by controlling other cognitive control processes.Psychological and cognitive researchers have become interested in various attributes of meta-control,and have therefore developed some interesting new cognitive paradigms and research tools for meta-control.A recent study using a novel two-step decision-making task found that meta-control,like other cognitive control abilities,also deteriorates with age.Over the past few decades,we have used a variety of neurophysiological measures to reveal the physiological mechanisms of traditional cognitive control,but the study of complex meta-control mechanisms is just beginning.In order to further study this subject,we not only need more reliable metacontrol cognitive paradigms,but also need to combine a series of electrophysiological measurement tools to observe and analyze metacontrol processes in multiple modes.However,the reliability verification scheme based on large sample size and the meta-control process monitoring and intervention scheme based on multi-mode electrophysiological technology are still lacking.Methods: Our research program serves three progressive goals.The first is the verification of meta-control paradigm based on large sample data.Whether the meta-control paradigm itself is robust and effective is the key to our stable use in different environments and populations.We use the latest network technology to build a networked experimental platform for meta-control paradigm,and take a new networked card sorting task as an example of meta-control cognitive paradigm.Large sample data collection has been carried out in Chinese community groups.In the subsequent reliability verification,we study the split-half reliability of this batch of data based on four split-half methods,followed by the physiological monitoring of the meta-control process.For the monitoring of cognitive control process,we use non-invasive brainwave monitoring technology and pupil monitoring technology,and collect multimodal physiological signals of meta-control process based on local area network communication and timestamp synchronization strategy.We preprocess the EEG data during the multi-source interference task and analyze the event correlation,and visualize the signal sequence after superposition average.finally,the meta-control process intervention.We used transcranial electrical stimulation to intervene during the meta-control task of the participants to explore the feasibility of using transcranial electrical stimulation to interfere with the meta-control process.We compared the behavioral changes of multi-source interference task and card sorting task before and after electrical stimulation,and used repeated measurement analysis of variance to explore the effect of electrical stimulation on behavioral performance.Results: A total of 259 healthy young people and elderly people in China were collected by the network experimental platform,and finally 220 people were enrolled(young people: 107,65 women,42 men,with an average age of 30.1 years and a standard deviation of 5.5 years;Elderly people: 113,53 females and 60 males,with an average age of 64.0 years and a standard deviation of 6.7 years),and the data effective rate was 84.94%.Split-half reliability’s analysis shows that the card sorting task has a reliable split-half reliability in all indicators except "failure to maintain the task set",whether in the young group or the old group.As expected,compared with the young group,the old group has lower performance on indicators indicating perfect cognitive function,but higher score on indicators indicating stubborn tendency.Automatic scoring scripts and analysis processes have been made public.The monitoring platform of metacontrol process based on multimodal electrophysiology technology collected 34 cases of multimodal physiology(18 cases in the experimental group and 16 cases in the control group).The original files of behavioral feedback of all metacontrol tasks and their event timestamps were complete,and all EEG data files and pupil data files were intact.The event-related potentials segmented and averaged by behavioral event timestamps have clear and distinctive fluctuation patterns.Repeated measure ANOVA on sessions before and after electrical stimulation shows that electrical stimulation can improve the speed of conflict response(p<0.1)and significantly reduce the reaction time of non-conflict trials(p<0.05).Conclusion: We use a network version of card sorting task as a meta-control cognitive task paradigm,with the help of computer network technology to build a network experimental platform to successfully carry out large-scale experiments in Chinese community groups,and the experimental data have achieved high efficiency.At the same time,our study on the split-half reliability of the task itself also preliminarily proves the feasibility of using the networked experimental platform to carry out large-scale meta-control task data collection and reliability and validity analysis in the Chinese community.More importantly,relying on pupil meter,EEG,meta-control process monitoring and intervention platform based on network protocol communication,we have successfully collected several multimodal data of pupil,EEG and behavior.The results of behavioral analysis were in line with expectations.Electrical stimulation had a significant effect on the response time index of multi-source interference tasks.The event-related potentials after timestamp synchronization also show clear EEG waveforms,and the EEG waveforms under different events and different conflict conditions show different characteristics.It is preliminarily proved that our multimodal electrophysiological technology scheme is feasible to monitor and intervene the meta-control process. |
PDF Full Text Request