A cognitive control state evaluation system, method and medium

Abstract

The present application provides a system, method and medium for evaluating cognitive control state, and relates to the field of brain-computer interface technology. The method includes: selecting a hierarchical cognitive control paradigm from a stimulation database, presenting a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm; collecting EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulation scheme; performing a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and performing a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal; based on the focus area of ​​each stimulation subtask, aligning the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in a time scale; extracting multi-dimensional EEG features from the EEG signal after the sub-region alignment, extracting multi-dimensional eye movement features from the eye movement signal after the sub-region alignment, and extracting behavioral features from the judgment result signal, so as to evaluate the cognitive control state of the target subject.

Description

Technical Field

[0001] The present application relates to the field of brain-computer interface technology, and in particular to a system, method and medium for evaluating cognitive control state. Background Art

[0002] Cognitive Control (CC) refers to the ability of an individual to complete the current task by promoting the processing of information related to the selected task and inhibiting the processing of irrelevant information when facing interference or conflict during the execution of a task. For example, in a noisy seminar, cognitive control is used to avoid noise interference and communicate with others. Cognitive control can help individuals flexibly mobilize cognitive resources to achieve specific goals in complex and changing situations. It is a high-level cognitive function necessary for the human brain to complete cognitive activities and is closely related to daily life. Good cognitive control ability can effectively coordinate individual behavior and significantly improve the quality of life of individuals. When the cognitive control function of an individual is weakened, it will cause the individual to make mistakes or react slowly during the execution of the task, leading to destructive accidents.

[0003] Cognitive control tasks not only involve multiple complex cognitive processes, which are presented in a nested hierarchical form, but also have large individual differences. In related technologies, there is a lack of effective technical means to explore the response patterns of different individuals in cognitive control. Therefore, how to provide an evaluation method for cognitive control status, realize accurate detection and evaluation of individual cognitive control functions, and improve the accuracy of evaluating cognitive control status is of great practical significance. Summary of the invention

[0004] The embodiments of the present application provide a system, method and medium for evaluating cognitive control status, which can improve the accuracy of evaluating cognitive control status.

[0005] In a first aspect, an embodiment of the present application provides a system for evaluating cognitive control state, comprising:

[0006] A task interaction module, used to select a hierarchical cognitive control paradigm from a stimulus database, and present a stimulus scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes a plurality of stimulus subtasks; the stimulus subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas;

[0007] A data acquisition module, used to collect the EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulation scheme;

[0008] A data preprocessing module, configured to perform a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and to perform a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal;

[0009] A synchronization alignment module, used for aligning the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in different regions on a time scale based on the focus area of ​​each stimulus subtask;

[0010] A feature extraction module is used to extract multi-dimensional EEG features from the stimulus-specific effective EEG signals after regional alignment, extract multi-dimensional eye movement features from the stimulus-specific effective eye movement signals after regional alignment, and extract behavioral features from the judgment result signals, so as to evaluate the cognitive control state of the target subject.

[0011] The cognitive control state evaluation system provided in the embodiment of the present application includes: a task interaction module, which is used to select a hierarchical cognitive control paradigm from a stimulation database, and present a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; a data acquisition module is used to collect the target subject's EEG signal, eye movement signal and judgment result signal when receiving the stimulation scheme; data preprocessing A module is used to perform a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and to perform a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal; a synchronous alignment module is used to perform regional alignment on the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal on a time scale based on the focus area of ​​each of the stimulation subtasks; a feature extraction module is used to extract multi-dimensional EEG features from the stimulus-specific effective EEG signal after regional alignment, extract multi-dimensional eye movement features from the stimulus-specific effective eye movement signal after regional alignment, and extract behavioral features from the judgment result signal, so as to evaluate the cognitive control state of the target subject. The system can select a hierarchical cognitive control paradigm from a stimulation database and present a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; and then obtain stimulation-specific effective EEG signals and stimulation-specific effective eye movement signals; and then based on each of the stimulation subtasks The focus area is determined by aligning the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in terms of time scale; multi-dimensional EEG features are extracted from the stimulus-specific effective EEG signal after the regional alignment, multi-dimensional eye movement features are extracted from the stimulus-specific effective eye movement signal after the regional alignment, and behavioral features are extracted from the judgment result signal for evaluating the cognitive control state of the target subject, thereby realizing the detection of the multi-layer cognitive control state of the subject, being able to detect and evaluate the cognitive control state of the subject more comprehensively, and improving the accuracy of evaluating the cognitive control state.

[0012] In a possible implementation, the system further includes:

[0013] A comprehensive evaluation module is used to obtain an evaluation result of the cognitive control state of the target subject based on the multi-dimensional EEG features, the multi-dimensional eye movement features and the behavioral features; the evaluation result represents whether the cognitive control state of the subject is abnormal.

[0014] The cognitive control state evaluation system provided in this embodiment also includes: a comprehensive evaluation module, which is used to obtain an evaluation result of the cognitive control state of the target subject based on the multi-dimensional EEG features, the multi-dimensional eye movement features and the behavioral features; the evaluation result represents whether the cognitive control state of the subject is abnormal. The system obtains the evaluation result of the cognitive control state of the target subject based on the multi-dimensional EEG features, the multi-dimensional eye movement features and the behavioral features, and provides an evaluation mechanism for the cognitive control state of multi-feature fusion to determine whether the cognitive control state of the subject is abnormal, further improving the accuracy of evaluating the cognitive control state.

[0015] In a possible implementation, the stimulus types of the stimulus subtask include emotional stimulus and non-emotional stimulus; the stimulus subtasks of the same type have the same composition of stimulus types.

[0016] In the cognitive control state evaluation system provided by this embodiment, the stimulus types of the stimulus subtask include emotional stimulus and non-emotional stimulus; the stimulus types of the same stimulus subtask are the same. In this system, the stimulus types of the stimulus subtask include emotional stimulus and non-emotional stimulus; the stimulus subtasks of the same type have the same composition of stimulus types. This system, by including emotional stimulus and non-emotional stimulus in the stimulus subtask, achieves the fusion of emotional stimulus and non-emotional stimulus, improves the ecological validity of the system, and can further improve the accuracy of evaluating cognitive control state.

[0017] In a possible implementation, the single-layer cognitive stimulation subtask includes part or all of an emotional single-layer cognitive stimulation subtask and a non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask;

[0018] The emotional single-layer cognitive stimulation subtask represents the subject's selection of a corresponding response item based on the presented first emotional stimulation image area;

[0019] The non-emotional single-layer cognitive stimulation subtask represents the subject's selection of a corresponding response item based on the first non-emotional stimulation image area presented;

[0020] The non-emotional dual-layer cognitive stimulation subtask represents that the subject selects a response item corresponding to the presented third non-emotional stimulation image region based on the presented second non-emotional stimulation image region;

[0021] The high-level emotional dual-layer cognitive stimulation subtask represents the subject's selection of a response item corresponding to the presented fourth non-emotional stimulus image area based on the presented second emotional stimulus image area;

[0022] The low-level emotional dual-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the presented third emotional stimulation image area based on the presented fifth non-emotional stimulation image area; wherein, for the third emotional stimulation image area presented simultaneously with a portion of the fifth non-emotional stimulation image area, the subject performs non-emotional cognition to select a reaction item.

[0023] The embodiment provides an evaluation system for cognitive control state, wherein the single-layer cognitive stimulation subtask includes part or all of an emotional single-layer cognitive stimulation subtask and a non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask; the emotional single-layer cognitive stimulation subtask represents the subject's selection of a corresponding reaction item based on the presented first emotional stimulation image area; the non-emotional single-layer cognitive stimulation subtask represents the subject's selection of a corresponding reaction item based on the presented first non-emotional stimulation image area; the non-emotional double-layer cognitive stimulation subtask includes part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask. The high-level emotional double-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the third non-emotional stimulation image area based on the second non-emotional stimulation image area presented; the high-level emotional double-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the fourth non-emotional stimulation image area based on the second emotional stimulation image area presented; the low-level emotional double-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the third emotional stimulation image area presented based on the fifth non-emotional stimulation image area presented; wherein, for the third emotional stimulation image area presented simultaneously with a part of the fifth non-emotional stimulation image area, the subject performs non-emotional cognition to select a reaction item. In this system, the single-layer cognitive stimulation subtask includes part or all of the emotional single-layer cognitive stimulation subtask and the non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of the non-emotional double-layer cognitive stimulation subtask, the high-level emotional double-layer cognitive stimulation subtask, and the low-level emotional double-layer cognitive stimulation subtask, which can realize the integration of emotional cognitive factors and non-emotional cognitive factors, and can further improve the accuracy of evaluating cognitive control status.

[0024] In a possible implementation, the task interaction module is further used to: send a synchronization event tag to the data acquisition module when presenting the stimulation scheme to the target subject;

[0025] The data acquisition module is specifically used to collect the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme based on the synchronization event tag.

[0026] The cognitive control state evaluation system provided in this embodiment, the task interaction module is also used to: send a synchronization event tag to the data acquisition module when presenting the stimulation scheme to the target subject; the data acquisition module is specifically used to collect the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme based on the synchronization event tag. The system can accurately ensure the synchronization of data by sending a synchronization event tag to the data acquisition module when presenting the stimulation scheme to the target subject, and collecting the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme based on the synchronization event tag, and can further improve the accuracy of evaluating the cognitive control state.

[0027] In a possible implementation, the first preprocessing operation includes part or all of electrode positioning, variable reference, bandpass filtering, notch filtering, downsampling, and artifact removal; the variable reference is to change the left ear mastoid reference to the average reference of the mastoids of both ears; the first preprocessing operation also includes segmented interception of the EEG signal according to the synchronization event tag;

[0028] The second preprocessing operation includes merging gaze points and deleting some or all of the invalid eye movement sampling points; the gaze point merging is to merge the gaze points adjacent in space and time based on a preset merging rule; the invalid eye movement sampling point deletion is to remove the gaze points whose duration is less than a preset gaze duration; the second preprocessing operation also includes segmenting and intercepting the eye movement signal according to the synchronization event tag.

[0029] The system, the first preprocessing operation, also includes segmenting and intercepting the EEG signal according to the synchronization event label; the second preprocessing operation also includes segmenting and intercepting the eye movement signal according to the synchronization event label; by segmenting and intercepting the EEG signal and the eye movement signal respectively according to the synchronization event label, the synchronization of the data can be accurately ensured, and the accuracy of the assessment of the cognitive control state can be further improved.

[0030] In a possible implementation, the synchronization alignment module is specifically used to:

[0031] Determining the regional fixation time range corresponding to the stimulus-specific eye movement signal according to the focus area of ​​each stimulus subtask; the regional fixation time range is the time period when the fixation point of the target subject falls into different focus areas;

[0032] Based on the regional gaze time range, the stimulus-specific effective EEG signals and the stimulus-specific effective eye movement signals corresponding to each of the regional gaze time ranges are determined to perform regional alignment.

[0033] The cognitive control state evaluation system provided in this embodiment, the synchronization alignment module, is specifically used to: determine the regional gaze time range corresponding to the stimulus-specific eye movement signal according to the focus area of ​​each of the stimulus subtasks; the regional gaze time range is the time period when the gaze point of the target subject falls into different focus areas; based on the regional gaze time range, determine the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal corresponding to each of the regional gaze time ranges, so as to perform regional alignment. The system provides a mechanism for aligning signals by region based on the focus area of ​​each of the stimulus subtasks, which can improve the synchronization of data and further improve the accuracy of the evaluation of cognitive control state.

[0034] In a possible implementation, the multi-dimensional EEG features include part or all of the EEG power spectral density PSD, the phase-locked value PLV and the phase-amplitude coupling PAC; the multi-dimensional eye movement features include part or all of the proportional fixation time, the proportional number of fixations and the pupil size; the behavioral characteristics include part or all of the accuracy rate and the reaction time; the reaction time characterizes the time it takes for the subject to make a cognitive response to the stimulus.

[0035] This embodiment provides an evaluation system for cognitive control state, wherein the multi-dimensional EEG features include part or all of EEG power spectrum density PSD, phase-locked value PLV, and phase amplitude coupling PAC; the multi-dimensional eye movement features include part or all of proportional fixation time, proportional fixation times, and pupil size; the behavioral features include part or all of accuracy and reaction time; the reaction time characterizes the time it takes for the subject to make a cognitive response to a stimulus. The system provides a variety of feature extraction options to detect the multi-layer cognitive control state of the subject, and can more comprehensively detect and evaluate the cognitive control state of the subject, which can improve the accuracy of evaluating the cognitive control state.

[0036] In a second aspect, an embodiment of the present application provides a method for evaluating a cognitive control state, the method comprising:

[0037] A hierarchical cognitive control paradigm is selected from a stimulation database, and a stimulation scheme is presented to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes a plurality of stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas;

[0038] collecting the EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulation scheme;

[0039] Performing a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and performing a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal;

[0040] Based on the focus area of ​​each of the stimulation subtasks, aligning the stimulation-specific effective EEG signal and the stimulation-specific effective eye movement signal in different regions on a time scale;

[0041] Multi-dimensional EEG features are extracted from the EEG signals after the sub-region alignment, multi-dimensional eye movement features are extracted from the eye movement signals after the sub-region alignment, and behavioral features are extracted from the judgment result signals, so as to evaluate the cognitive control state of the target subject.

[0042] In a possible implementation, the method further includes:

[0043] Based on the multi-dimensional EEG features, the multi-dimensional eye movement features and the behavioral features, an evaluation result of the cognitive control state of the target subject is obtained; the evaluation result represents whether the cognitive control state of the subject is abnormal.

[0044] In a possible implementation, the stimulus types of the stimulus subtask include emotional stimulus and non-emotional stimulus; the stimulus subtasks of the same type have the same composition of stimulus types.

[0045] In a possible implementation, the single-layer cognitive stimulation subtask includes part or all of an emotional single-layer cognitive stimulation subtask and a non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask;

[0046] The emotional single-layer cognitive stimulation subtask represents the subject's selection of a corresponding response item based on the presented first emotional stimulation image area;

[0047] The non-emotional single-layer cognitive stimulation subtask represents the subject's selection of a corresponding response item based on the first non-emotional stimulation image area presented;

[0048] The non-emotional dual-layer cognitive stimulation subtask represents that the subject selects a response item corresponding to the presented third non-emotional stimulation image region based on the presented second non-emotional stimulation image region;

[0049] The high-level emotional dual-layer cognitive stimulation subtask represents the subject's selection of a response item corresponding to the presented fourth non-emotional stimulus image area based on the presented second emotional stimulus image area;

[0050] The low-level emotional dual-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the presented third emotional stimulation image area based on the presented fifth non-emotional stimulation image area; wherein, for the third emotional stimulation image area presented simultaneously with a portion of the fifth non-emotional stimulation image area, the subject performs non-emotional cognition to select a reaction item.

[0051] In a possible implementation, the method further includes: when presenting the stimulation scheme to the target subject, sending a synchronization event tag to the data acquisition module;

[0052] The collecting of the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme includes:

[0053] Based on the synchronization event tag, the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme are collected.

[0054] In a possible implementation, the first preprocessing operation includes part or all of electrode positioning, variable reference, bandpass filtering, notch filtering, downsampling, and artifact removal; the variable reference is to change the left ear mastoid reference to the average reference of the mastoids of both ears; the first preprocessing operation also includes segmented interception of the EEG signal according to the synchronization event tag;

[0055] The second preprocessing operation includes merging gaze points and deleting some or all of the invalid eye movement sampling points; the gaze point merging is to merge the gaze points adjacent in space and time based on a preset merging rule; the invalid eye movement sampling point deletion is to remove the gaze points whose duration is less than a preset gaze duration; the second preprocessing operation also includes segmenting and intercepting the eye movement signal according to the synchronization event tag.

[0056] In a possible implementation, the step of aligning the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in different regions on a time scale based on the focus region of each stimulus subtask includes:

[0057] Determining the regional fixation time range corresponding to the stimulus-specific eye movement signal according to the focus area of ​​each stimulus subtask; the regional fixation time range is the time period when the fixation point of the target subject falls into different focus areas;

[0058] Based on the regional gaze time range, the stimulus-specific effective EEG signals and the stimulus-specific effective eye movement signals corresponding to each of the regional gaze time ranges are determined to perform regional alignment.

[0059] In a possible implementation, the multi-dimensional EEG features include part or all of the EEG power spectral density PSD, the phase-locked value PLV and the phase-amplitude coupling PAC; the multi-dimensional eye movement features include part or all of the proportional fixation time, the proportional number of fixations and the pupil size; the behavioral characteristics include part or all of the accuracy rate and the reaction time; the reaction time characterizes the time it takes for the subject to make a cognitive response to the stimulus.

[0060] The method provided in the above embodiment includes: selecting a hierarchical cognitive control paradigm from a stimulus database, presenting a stimulus scheme to a target subject based on the hierarchical cognitive control paradigm; collecting EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulus scheme; performing a first preprocessing operation on the EEG signals to obtain stimulus-specific effective EEG signals, and performing a second preprocessing operation on the eye movement signals to obtain stimulus-specific effective eye movement signals; based on the focus areas of each stimulus subtask, aligning stimulus-specific effective EEG signals and stimulus-specific effective eye movement signals in different regions on a time scale; extracting multi-dimensional EEG features from the EEG signals after the alignment of different regions, extracting multi-dimensional eye movement features from the eye movement signals after the alignment of different regions, and extracting behavioral features from the judgment result signals for evaluating the cognitive control state of the target subject. This method can detect the multi-layer cognitive control state of the subject, can detect and evaluate the cognitive control state of the subject more comprehensively, and can improve the accuracy of evaluating the cognitive control state.

[0061] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the second aspects is implemented.

[0062] The technical effects brought about by any one of the implementation methods of the second aspect to the third aspect can refer to the technical effects brought about by the implementation method of the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0064] Figure 1One of the structural block diagrams of a cognitive control state evaluation system provided in an embodiment of the present application;

[0065] Figure 2 A second structural block diagram of a cognitive control state evaluation system provided in an embodiment of the present application;

[0066] Figure 3 A schematic diagram of a stimulation subtask of a cognitive control state evaluation system provided in an embodiment of the present application;

[0067] Figure 4 A schematic diagram of a focus area of ​​a stimulation subtask of a cognitive control state evaluation system provided in an embodiment of the present application;

[0068] Figure 5 One of the flow charts of a method for evaluating a cognitive control state provided in an embodiment of the present application;

[0069] Figure 6 The second flowchart of a method for evaluating cognitive control state provided in an embodiment of the present application. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0071] Cognitive Control (CC) refers to the ability of an individual to complete the current task by promoting the processing of information related to the selected task and inhibiting the processing of irrelevant information when facing interference or conflict during the execution of a task. For example, in a noisy seminar, cognitive control is used to avoid noise interference and communicate with others. Cognitive control can help individuals flexibly mobilize cognitive resources to achieve specific goals in complex and changing situations. It is a high-level cognitive function necessary for the human brain to complete cognitive activities and is closely related to daily life. Good cognitive control ability can effectively coordinate individual behavior and significantly improve the quality of life of individuals. When the cognitive control function of an individual is weakened, it will cause the individual to make mistakes or react slowly during the execution of the task, leading to destructive accidents.

[0072] Cognitive control tasks not only involve multiple complex cognitive processes, which are presented in a nested hierarchical form, but also have large individual differences. In related technologies, there is a lack of effective technical means to explore the response patterns of different individuals in cognitive control. Therefore, how to provide an evaluation method for cognitive control status, realize accurate detection and evaluation of individual cognitive control functions, and improve the accuracy of evaluating cognitive control status is of great practical significance.

[0073] Based on this, the embodiments of the present application provide a system, method and medium for evaluating cognitive control status. Among them, the system for evaluating cognitive control status includes: a task interaction module, which is used to select a hierarchical cognitive control paradigm from a stimulation database, and present a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; a data acquisition module is used to collect the target subject's EEG signals, eye movement signals and judgment result signals when receiving the stimulation scheme; data pre-processing A processing module is used to perform a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and to perform a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal; a synchronization alignment module is used to align the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in a time scale based on the focus area of ​​each stimulation subtask; a feature extraction module is used to extract multi-dimensional EEG features from the stimulus-specific effective EEG signal after the regional alignment, extract multi-dimensional eye movement features from the stimulus-specific effective eye movement signal after the regional alignment, and extract behavioral features from the judgment result signal, so as to evaluate the cognitive control state of the target subject. The system can present a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm by selecting a hierarchical cognitive control paradigm from a stimulation database; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; and then obtain stimulation-specific effective EEG signals and stimulation-specific effective eye movement signals; then, based on the focus areas of each stimulation subtask, the stimulation-specific effective EEG signals and stimulation-specific effective eye movement signals are aligned in different regions on a time scale; multi-dimensional EEG features are extracted from the stimulation-specific effective EEG signals after the sub-region alignment, multi-dimensional eye movement features are extracted from the stimulation-specific effective eye movement signals after the sub-region alignment, and behavioral features are extracted from the judgment result signal, so as to evaluate the cognitive control state of the target subject, thereby detecting the subject's multi-layer cognitive control state, and more comprehensively detecting and evaluating the subject's cognitive control state, thereby improving the accuracy of evaluating the cognitive control state.

[0074] In order to make the invention purpose, technical scheme and advantages of the embodiments of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0075] Figure 1 A structural block diagram of a cognitive control state evaluation system according to an embodiment of the present application is shown, which comprises Figure 1 As can be seen from the structural block diagram, the cognitive control state evaluation system 10 includes:

[0076] The task interaction module 101 is used to select a hierarchical cognitive control paradigm from a stimulus database, and present a stimulus scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulus subtasks; the stimulus subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas;

[0077] The data acquisition module 102 is used to collect the EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulation scheme;

[0078] The data preprocessing module 103 is used to perform a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and to perform a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal;

[0079] A synchronization alignment module 104 is used to align the stimulus-specific effective EEG signals and the stimulus-specific effective eye movement signals in different regions on a time scale based on the focus regions of each stimulus subtask;

[0080] The feature extraction module 105 is used to extract multi-dimensional EEG features from the stimulus-specific effective EEG signals after regional alignment, extract multi-dimensional eye movement features from the stimulus-specific effective eye movement signals after regional alignment, and extract behavioral features from the judgment result signals, so as to evaluate the cognitive control state of the target subject.

[0081] In specific implementation, in an embodiment of the present application, the synchronization alignment module 104 is used to align the stimulus-specific effective EEG signals and the stimulus-specific effective eye movement signals on a time scale based on the focus area of ​​each stimulation subtask, that is, to lock the timing of the stimulus-specific effective EEG signals and the stimulus-specific effective eye movement signals.

[0082] In an embodiment of the present application, a data acquisition module is used to collect EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulation scheme. Specifically, the data acquisition module is used to collect EEG signals, eye movement signals and judgment result signals of the target subject when reactively receiving the stimulation scheme; wherein, when the target subject reactively receives the stimulation scheme, the target subject makes a cognitive judgment based on the received stimulation scheme.

[0083] In some embodiments, the data acquisition module includes an electrode cap, an eye tracker, and an EEG amplifier. The data acquisition module may also include other data acquisition devices, which are not specifically limited in this application.

[0084] The cognitive control state evaluation system provided by this embodiment includes: a task interaction module, which is used to select a hierarchical cognitive control paradigm from a stimulation database, and present a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; a data acquisition module is used to collect the target subject's EEG signal, eye movement signal and judgment result signal when receiving the stimulation scheme; the data prediction ... A processing module is used to perform a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and to perform a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal; a synchronous alignment module is used to align the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in a time scale based on the focus area of ​​each stimulation subtask; a feature extraction module is used to extract multi-dimensional EEG features from the stimulus-specific effective EEG signal after the sub-region alignment, extract multi-dimensional eye movement features from the stimulus-specific effective eye movement signal after the sub-region alignment, and extract behavioral features from the judgment result signal, so as to evaluate the cognitive control state of the target subject. The system can present a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm by selecting a hierarchical cognitive control paradigm from a stimulation database; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; and then obtain stimulation-specific effective EEG signals and stimulation-specific effective eye movement signals; then, based on the focus areas of each stimulation subtask, the stimulation-specific effective EEG signals and stimulation-specific effective eye movement signals are aligned in different regions on a time scale; multi-dimensional EEG features are extracted from the stimulation-specific effective EEG signals after the sub-region alignment, multi-dimensional eye movement features are extracted from the stimulation-specific effective eye movement signals after the sub-region alignment, and behavioral features are extracted from the judgment result signal, so as to evaluate the cognitive control state of the target subject, thereby detecting the subject's multi-layer cognitive control state, and more comprehensively detecting and evaluating the subject's cognitive control state, thereby improving the accuracy of evaluating the cognitive control state.

[0085] In some embodiments of the cognitive control state assessment system 10, Figure 2As shown, the cognitive control state evaluation system 10 also includes: a comprehensive evaluation module 201, which is used to obtain an evaluation result of the cognitive control state of the target subject based on multi-dimensional EEG features, multi-dimensional eye movement features and behavioral characteristics; the evaluation result represents whether the cognitive control state of the subject is abnormal.

[0086] The cognitive control state evaluation system provided in this embodiment also includes: a comprehensive evaluation module, which is used to obtain the evaluation result of the cognitive control state of the target subject based on multi-dimensional EEG features, multi-dimensional eye movement features and behavioral features; the evaluation result represents whether the cognitive control state of the subject is abnormal. The system obtains the evaluation result of the cognitive control state of the target subject based on multi-dimensional EEG features, multi-dimensional eye movement features and behavioral features, and provides a multi-feature fusion cognitive control state evaluation mechanism to determine whether the cognitive control state of the subject is abnormal, further improving the accuracy of evaluating the cognitive control state.

[0087] In some embodiments of the cognitive control state assessment system 10 , the stimulus types of the stimulus subtask include emotional stimuli and non-emotional stimuli; and the stimulus subtasks of the same type have the same composition of stimulus types.

[0088] In a specific implementation, in the evaluation system of cognitive control state, the stimulus types of the stimulus subtask include emotional stimulus and non-emotional stimulus; for the same type of stimulus subtask, the composition structure of the stimulus types is the same.

[0089] In the embodiment of the present application, the composition structure of the stimulus types includes the stimulus types corresponding to the respective stimulus image regions presented in the stimulus subtask.

[0090] In the embodiments of the present application, for stimulation subtasks of the same type, the composition structure of the stimulation types is the same. Specifically, for any two stimulation subtasks of the same type, the stimulation types corresponding to the stimulation image areas at the same position presented in the two stimulation subtasks are the same.

[0091] Exemplarily, stimulation subtask M01 and stimulation subtask M02 are stimulation subtasks of the same type. For example, stimulation subtask M01 and stimulation subtask M02 are both "first emotion dual-layer cognitive stimulation subtasks". The composition structure of the stimulation types of stimulation subtask M01 and stimulation subtask M02 is the same, that is, for two stimulation subtasks of the same type: stimulation subtask M01 and stimulation subtask M02, the stimulation types corresponding to the stimulation image areas at the same position presented in stimulation subtask M01 and stimulation subtask M02 are the same. For example, assuming that the stimulation subtasks of the type "first emotion dual-layer cognitive stimulation subtask" can both include a first stimulation image area at the first position above the horizontal midline of the screen and a second stimulation image area at the second position below the horizontal midline of the screen, then the stimulation types corresponding to the first stimulation image area at the first position presented in stimulation subtask M01 and stimulation subtask M02 are the same, and the stimulation types corresponding to the second stimulation image area at the second position presented in stimulation subtask M01 and stimulation subtask M02 are also the same.

[0092] In the cognitive control state evaluation system provided by this embodiment, the types of stimulation in the stimulation subtask include emotional stimulation and non-emotional stimulation; the types of stimulation in the same stimulation subtask are the same. In this system, the types of stimulation in the stimulation subtask include emotional stimulation and non-emotional stimulation; the same type of stimulation subtasks have the same composition of stimulation types. In this system, by including emotional stimulation and non-emotional stimulation in the types of stimulation subtasks, emotional stimulation and non-emotional stimulation are integrated, which can further improve the accuracy of evaluating cognitive control state.

[0093] In some embodiments of the cognitive control state assessment system 10, the single-layer cognitive stimulation subtask includes part or all of the emotional single-layer cognitive stimulation subtask and the non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of the non-emotional double-layer cognitive stimulation subtask, the high-level emotional double-layer cognitive stimulation subtask, and the low-level emotional double-layer cognitive stimulation subtask;

[0094] The emotional single-layer cognitive stimulation subtask represents that the subjects select the corresponding response item based on the first emotional stimulus image area presented;

[0095] The non-emotional single-layer cognitive stimulation subtask represents that the subjects select the corresponding response item based on the first non-emotional stimulus image area presented;

[0096] The non-emotional dual-layer cognitive stimulation subtask involves the subject selecting a response item corresponding to the third non-emotional stimulus image area based on the second non-emotional stimulus image area presented;

[0097] The high-level emotional dual-layer cognitive stimulation subtask represents that the subjects select the response item corresponding to the presented fourth non-emotional stimulus image area based on the presented second emotional stimulus image area;

[0098] The low-level emotional dual-layer cognitive stimulation subtask characterizes the subjects' selection of a response item corresponding to the presented third emotional stimulus image area based on the presented fifth non-emotional stimulus image area; wherein, for the third emotional stimulus image area presented simultaneously with a part of the fifth non-emotional stimulus image area, the subjects perform non-emotional cognition to select a response item.

[0099] Figure 3 A schematic diagram of a stimulation subtask of a cognitive control state evaluation system provided in an embodiment of the present application. Figure 3 The stimulation subtask shown in FIG. 1 may be a stimulation subtask of the cognitive control state evaluation system 10. Figure 3 As shown, the single-layer cognitive stimulation subtask includes subtask one and subtask two, among which subtask one is a non-emotional single-layer cognitive stimulation subtask, and subtask two is an emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes subtask three, subtask four and subtask five, among which subtask three is a non-emotional double-layer cognitive stimulation subtask, subtask four is a high-level emotional double-layer cognitive stimulation subtask, and subtask five is a low-level emotional double-layer cognitive stimulation subtask.

[0100] Among them, the emotional single-layer cognitive stimulation subtask represents the subject's selection of the corresponding reaction item based on the presented first emotional stimulation image area; the non-emotional single-layer cognitive stimulation subtask represents the subject's selection of the corresponding reaction item based on the presented first non-emotional stimulation image area; the non-emotional double-layer cognitive stimulation subtask represents the subject's selection of the reaction item corresponding to the presented third non-emotional stimulation image area based on the presented second non-emotional stimulation image area; the high-level emotional double-layer cognitive stimulation subtask represents the subject's selection of the reaction item corresponding to the presented fourth non-emotional stimulation image area based on the presented second emotional stimulation image area; the low-level emotional double-layer cognitive stimulation subtask represents the subject's selection of the reaction item corresponding to the presented third emotional stimulation image area based on the presented fifth non-emotional stimulation image area; among them, for the third emotional stimulation image area presented simultaneously with a part of the fifth non-emotional stimulation image area, the subject performs non-emotional cognition to select the reaction item.

[0101] In one embodiment of the present application, the single-layer cognitive stimulation subtask includes an emotional single-layer cognitive stimulation subtask and a non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask. Specifically,

[0102] The first emotional stimulus image area can be as follows Figure 3The second subtask includes 301 facial images; the emotional single-layer cognitive stimulation subtask represents the subject's Figure 3 Subtask 2 includes selecting a corresponding reaction item for the face image 301 shown; for example, during implementation, the face image 301 may include faces with four emotions, and subtask 2 requires the target subject User1 to memorize the faces with four emotions and the corresponding buttons in advance (for example, happy faces correspond to button 1, sad faces correspond to button 2, angry faces correspond to button 3, and fearful faces correspond to button 4). After the formal experiment begins, the target subject User1 needs to judge the emotions of the faces in the face image 301 and select the corresponding buttons as reaction items.

[0103] The first non-emotional stimulus image area can be Figure 3 The subtask 1 in the embodiment includes a color-specific geometric image 302; the color-specific geometric image 302 includes a geometric figure with a preset recognition feature; wherein the preset recognition feature can be color, shape, etc.; the non-emotional single-layer cognitive stimulation subtask represents the subject's based on the presentation of Figure 3 Subtask 1 includes selecting a corresponding reaction item from the color-coded geometric image 302 shown; for example, during implementation, the color-coded geometric image 302 may include squares of four colors; subtask 1 requires the target subject User1 to memorize the four colors of squares and the corresponding buttons in advance (for example, the yellow square corresponds to button 1, the green square corresponds to button 2, the blue square corresponds to button 3, and the red square corresponds to button 4). After the formal experiment begins, the user needs to judge the color of the square and select the corresponding button as a reaction item.

[0104] The second non-emotional stimulus image area can be Figure 3 The subtask three in the embodiment includes a color-specific geometric image 303; the color-specific geometric image 303 includes a geometric figure having a preset identification feature; wherein the preset identification feature may be color, shape, etc.; the third non-emotional stimulus image area may be as follows Figure 3 The subtask three in the embodiment includes an information symbol image 304; the information symbol image 304 includes an information symbol with a preset dual recognition feature; wherein the information symbol may be a number, and the preset dual recognition feature may be an odd or even number and a numerical value; the non-emotional dual-layer cognitive stimulation subtask represents the subject's Figure 3 Subtask three in the above includes color-coded geometric images 303, selecting and presenting the Figure 3Subtask 3 in the experiment includes the reaction items corresponding to the information symbol image 304; for example, when implementing, the color-specific geometric image 303 may include squares of 4 colors, and the information symbol image 304 may include numbers located below the color-specific geometric image 303; Subtask 3 requires the target subject User1 to memorize the squares of 4 colors in advance and judge the parity / size of the numbers below according to the colors, as well as the corresponding keys. Among them, the squares of 2 colors (for example, yellow and green) correspond to judging the parity of the numbers below the squares (odd numbers correspond to key 1, and even numbers correspond to key 2), and the squares of the other 2 colors (for example, blue and red) correspond to judging the size of the numbers below the squares (less than 5 corresponds to key 3, and greater than 5 corresponds to key 4). After the formal experiment begins, the user needs to first judge the color of the square, then judge the number, and finally select the corresponding key as the reaction item.

[0105] The second emotional stimulus image area can be as follows Figure 3 The fourth subtask 4 includes a face image 305; the fourth non-emotional stimulus image area can be as follows Figure 3 The subtask 4 in the embodiment includes an information symbol image 306; the information symbol image 306 includes an information symbol with a preset dual recognition feature; wherein the information symbol may be a number, and the preset dual recognition feature may be an odd or even number and a numerical value; the high-level emotional dual-layer cognitive stimulation subtask represents the subject's Figure 3 Subtask 4 in the embodiment includes selecting and presenting face image 305 as follows: Figure 3 Subtask four includes reaction items corresponding to the information symbol image 306; for example, during implementation, the face image 305 may include faces with four emotions, and the information symbol image 306 may include numbers located below the face image 305; subtask four requires the target subject User1 to memorize the faces with four emotions in advance and judge the parity / size of the numbers below, and the corresponding buttons, based on the facial emotions. Two of the faces with emotions (such as happy and sad) correspond to judging the parity of the numbers below the faces (happy corresponds to button 1, and sad corresponds to button 2), and the other two faces with emotions (such as angry and fearful) correspond to judging the size of the numbers below the faces (less than 5 corresponds to button 3, and greater than 5 corresponds to button 4). After the formal experiment begins, the user needs to first judge the facial emotion, then judge the number, and finally select the corresponding button as the reaction item;

[0106] The fifth non-emotional stimulus image area can be as follows Figure 3 Subtask 5 in the embodiment includes a color-specific geometric image 307; the color-specific geometric image 307 includes a geometric figure having a preset identification feature; wherein the preset identification feature may be color, shape, etc.; the fourth non-emotional stimulus image area may be as follows Figure 3Subtask 5 in the task includes a head face image 308; the head face image 308 includes head face information of the person with a preset dual facial recognition feature; wherein the head face information of the person can be a face, and the preset dual facial recognition feature can be a high-recognition emotion and non-emotional information of the person, for example, the high-recognition emotion can include two easily recognizable emotions of happiness and sadness, and the non-emotional information of the person can include easily recognizable gender information, such as male and female; the low-level emotional dual-layer cognitive stimulation subtask represents the subject's based on the presentation of Figure 3 Subtask 5 includes color-coded geometric images 307, selecting and presenting the Figure 3 Subtask 5 in the embodiment includes a response item corresponding to the head face image 308; wherein, for a part of Figure 3 Subtask 5 in the experiment includes a color-specific geometric image 307 and a head face image 308, and the subject performs non-emotional cognition to select a response item. For example, the color-specific geometric image 307 may include squares of four colors, and the head face image 308 includes a head face of a person located below the color-specific geometric image 307. Subtask 5 requires the target subject User1 to memorize the squares of four colors in advance and judge the emotions / gender of the head face of the person below according to the color, as well as the corresponding buttons. Two colors of squares (such as yellow and green) correspond to judging the emotions of the head face of the person below the square (happy corresponds to button 1, sad corresponds to button 2), and the other two colors of squares (such as blue and red) correspond to judging the gender of the head face of the person below the square (male corresponds to button 3, female corresponds to button 4). After the formal experiment begins, the user needs to judge the color of the square first, then judge the face, and finally select the corresponding button as the response item.

[0107] The cognitive control state evaluation system provided in this embodiment comprises a single-layer cognitive stimulation subtask including part or all of an emotional single-layer cognitive stimulation subtask and a non-emotional single-layer cognitive stimulation subtask; a double-layer cognitive stimulation subtask including part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask; an emotional single-layer cognitive stimulation subtask represents that the subject selects a corresponding response item based on the presented first emotional stimulation image area; a non-emotional single-layer cognitive stimulation subtask represents that the subject selects a corresponding response item based on the presented first non-emotional stimulation image area; a non-emotional double-layer cognitive stimulation subtask includes part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask; an emotional single-layer cognitive stimulation subtask represents that the subject selects a corresponding response item based on the presented first non-emotional stimulation image area; a non-emotional double-layer cognitive stimulation subtask includes part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask; a The cognitive stimulation subtask represents the subject's selection of a response item corresponding to the third non-emotional stimulation image area based on the second non-emotional stimulation image area; the high-level emotional double-layer cognitive stimulation subtask represents the subject's selection of a response item corresponding to the fourth non-emotional stimulation image area based on the second emotional stimulation image area; the low-level emotional double-layer cognitive stimulation subtask represents the subject's selection of a response item corresponding to the third emotional stimulation image area based on the fifth non-emotional stimulation image area; wherein, for the third emotional stimulation image area presented simultaneously with a part of the fifth non-emotional stimulation image area, the subject performs non-emotional cognition to select a response item. In this system, the single-layer cognitive stimulation subtask includes part or all of the emotional single-layer cognitive stimulation subtask and the non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of the non-emotional double-layer cognitive stimulation subtask, the high-level emotional double-layer cognitive stimulation subtask, and the low-level emotional double-layer cognitive stimulation subtask, which can realize the integration of emotional cognitive factors and non-emotional cognitive factors, have higher ecological validity, and can further improve the accuracy of evaluating cognitive control status.

[0108] In some embodiments of the present application, the stimulation types of the same stimulation subtask are the same.

[0109] In a specific implementation, the stimulus types of the stimulus subtask include emotional stimuli and non-emotional stimuli; the stimulus types of the same stimulus subtask are the same. That is, for a stimulus subtask, the stimulus types of the stimulus image areas presented may all be emotional stimuli, or the stimulus types of the stimulus image areas presented may all be non-emotional stimuli.

[0110] The system of this embodiment can identify deep emotional cognitive factors for emotional stimuli, or deep non-emotional cognitive factors for non-emotional stimuli, has higher ecological validity, and can further improve the accuracy of evaluating cognitive control status.

[0111] Tasks involving cognitive control in daily life are composed of multiple steps, which are represented as nested hierarchical structures, in which the decision on the superior goal determines the execution of a series of sub-goals. The hierarchical cognitive control state evaluation system provided in the embodiment of the present application has the advantage of being closer to actual cognitive needs and life scenarios, and is more suitable for the corresponding brain spatial hierarchical model, so that it can detect the multi-layer cognitive control state of an individual and better evaluate the cognitive control ability of an individual when facing complex tasks.

[0112] In some embodiments of the present application, each stimulation subtask includes a total of 36 trials. In a single trial, 0.5-1.5s of rest and 3s of stimulation are presented, and the 1.5s rest time is set to ensure that the information between the stimulations of each trial does not cross-influence and enhance the subject's attention. During the stimulation of the stimulation subtask, the user's body and head should be kept as still as possible while staying awake. A proper rest can be taken between each subtask.

[0113] The hierarchical cognitive control paradigm was implemented by using Matlab's dedicated toolbox Psychtoolbox, including the setting of parameters such as the location of task stimuli and the duration of task stimuli. Visual stimuli were presented on a 27-inch monitor with a display resolution of 1920*1080 pixels.

[0114] In some embodiments of the present application, in order to ensure the synchronization of data, a synchronization event tag is sent to the EEG device and the eye movement device while the task stimulus is presented.

[0115] In some embodiments of the cognitive control state assessment system 10, the task interaction module 101 is further used to: send a synchronization event tag to the data acquisition module when presenting the stimulation scheme to the target subject;

[0116] The data acquisition module 102 is specifically used to collect the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme based on the synchronization event tag.

[0117] The cognitive control state evaluation system provided in this embodiment, the task interaction module, is also used to: send a synchronization event tag to the data acquisition module when presenting the stimulation scheme to the target subject; the data acquisition module is specifically used to collect the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme based on the synchronization event tag. The system can accurately ensure the synchronization of data by sending a synchronization event tag to the data acquisition module when presenting the stimulation scheme to the target subject, and collecting the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme based on the synchronization event tag, and can further improve the accuracy of evaluating the cognitive control state.

[0118] In some embodiments of the cognitive control state assessment system 10, the first preprocessing operation includes part or all of electrode positioning, reference change, bandpass filtering, notch filtering, downsampling, and artifact removal; the reference change is to change the left ear mastoid reference to the average reference of the mastoids of both ears; the first preprocessing operation also includes segmenting and intercepting the EEG signal according to the synchronous event label;

[0119] The second preprocessing operation includes merging gaze points and deleting some or all of the invalid eye movement sampling points; merging gaze points is to merge the gaze points adjacent in space and time based on the preset merging rules; deleting invalid eye movement sampling points is to remove the gaze points whose duration is less than the preset gaze duration; the second preprocessing operation also includes segmenting and intercepting the eye movement signal according to the synchronization event label.

[0120] Exemplarily, the function of the data preprocessing module 103 is to perform data preprocessing on the collected EEG signals and eye movement signals. Among them, the preprocessing of EEG signals includes: electrode positioning; reference change, that is, changing the left ear mastoid reference 'M1' to the average reference of the mastoids of both ears [('M1'+'M2') / 2], so as to reduce the influence of the lateral position of the reference electrode; then performing a 1-150Hz bandpass filter, and performing 50Hz, 100Hz and 150Hz notches to remove the 50Hz power frequency interference and its frequency doubling effect; then, downsampling and using the independent component analysis method to remove artifact components; further, segmenting the EEG signal data according to the synchronous event label induced by the stimulus, and deleting abnormal trials with an amplitude ≥100μV. The preprocessing of eye movement signals is to use filters to filter out valid information and delete invalid eye movement sampling points; then, the fixation points that are adjacent in space and time are merged, and the fixation points with a duration of less than 60ms are removed; finally, the data of the eye movement signals are segmented and intercepted according to the synchronous event labels induced by the stimulus for subsequent analysis.

[0121] In the system of this embodiment, the first preprocessing operation also includes segmenting and intercepting the EEG signal according to the synchronization event label; the second preprocessing operation also includes segmenting and intercepting the eye movement signal according to the synchronization event label; by segmenting and intercepting the EEG signal and the eye movement signal respectively according to the synchronization event label, the synchronization of the data can be accurately ensured, and the accuracy of the assessment of the cognitive control state can be further improved.

[0122] In some embodiments of the cognitive control state assessment system 10, the synchronization alignment module 104 is specifically configured to:

[0123] According to the attention area of ​​each stimulus subtask, the regional fixation time range corresponding to the stimulus-specific eye movement signal is determined; the regional fixation time range is the time period when the fixation point of the target subject falls into different attention areas;

[0124] Based on the regional fixation time range, the stimulus-specific effective EEG signals and stimulus-specific effective eye movement signals corresponding to the fixation time range of each region are determined to perform regional alignment.

[0125] The purpose of the synchronization alignment module is to achieve synchronization alignment of the preprocessed EEG signals and eye movement signals in the time dimension. This key step ensures the timing lock of different modal data in the hierarchical cognitive control task, so that the interaction between the modal signals and the signals can be finely analyzed when the user processes the stimulation of each stimulation subtask. This analysis method can improve the accuracy of evaluating the user's cognitive control state.

[0126] In the embodiment of the present application, the focus area may also be referred to as an area of ​​interest (AOI). It can be understood that in the embodiment of the present application, the area of ​​interest and the focus area are the same.

[0127] In the specific implementation, first, the area of ​​interest AOI of the hierarchical cognitive control paradigm is delineated. Figure 4 A schematic diagram of a focus area of ​​a stimulation subtask of a cognitive control state evaluation system provided in an embodiment of the present application, such as Figure 4 As shown in Figure 1, the single-layer cognitive stimulation subtask has one AOI (subtask 1: square, subtask 2: face); the double-layer cognitive stimulation subtask has two AOIs, namely the high-level AOI (subtask 3: square, subtask 4: face, subtask 5: square) and the low-level AOI (subtask 3: number, subtask 4: number, subtask 5: head and face of a person). The specific structure of the focus area of ​​the stimulation subtask is shown in Figure 1. Figure 4 As shown. Secondly, the AOI analysis method is used to accurately extract the user's gaze time in different AOIs of each stimulation subtask, and calibrate its time range. These time points will be used for alignment on the EEG signal. The AOI-based gaze time is a response indicator for post-stimulus processing, reflecting the subject's gaze pattern of different AOIs of the presented stimulus, indicating the process of user attention participation and maintenance in this area. Next, using the gaze time range in different AOIs in each stimulation subtask calibrated in the eye movement data, the corresponding time period is found in the EEG signal to achieve accurate matching between eye movement and EEG modalities on a time scale. Finally, the eye movement signals and EEG signals in different AOIs in each stimulation subtask are extracted respectively.

[0128] The cognitive control state evaluation system provided in this embodiment and the synchronous alignment module are specifically used to: determine the regional fixation time range corresponding to the stimulus-specific eye movement signal according to the focus area of ​​each stimulus subtask; the regional fixation time range is the time period when the target subject's fixation point falls into different focus areas; based on the regional fixation time range, determine the stimulus-specific effective EEG signal and stimulus-specific effective eye movement signal corresponding to each regional fixation time range, so as to perform regional alignment. The system provides a mechanism for regional alignment of signals based on the focus area of ​​each stimulus subtask, which can improve the synchronization of data and further improve the accuracy of the evaluation of cognitive control state.

[0129] In some embodiments of the cognitive control state assessment system 10, the multi-dimensional EEG features include part or all of the EEG power spectral density PSD, the phase-locked value PLV and the phase-amplitude coupling PAC; the multi-dimensional eye movement features include part or all of the proportional fixation time, the proportional number of fixations and the pupil size; the behavioral characteristics include part or all of the accuracy and reaction time; the reaction time characterizes the length of time it takes the subject to make a cognitive response to a stimulus.

[0130] In specific implementation, the feature extraction module extracts features from the EEG signals and eye movement signals in each AOI at different levels after being processed by the synchronization alignment module.

[0131] The characteristic parameters extracted from EEG signals mainly include PSD, PLV and PAC features. Among them, PSD is mainly used to measure the response power changes at different levels; PLV is mainly used to measure the degree of signal phase synchronization between brain regions at different levels; PAC is mainly used to measure the modulation relationship between oscillation activities in different frequency bands between brain regions.

[0132] The characteristic parameters extracted from eye movement signals mainly include proportional fixation time, proportional fixation count and pupil size. Among them, proportional fixation time is mainly used to measure the processing time of different levels of AOI; the fixation count is mainly used to measure the number of fixation points in different levels of AOI; pupil size is mainly used to measure the diameter of the pupil of the eye in different levels of AOI.

[0133] In some embodiments of the present application, PSD feature extraction includes using the Welch spectrum estimation method to calculate the PSD of the EEG signals of different AOIs in each trial.

[0134] In some embodiments of the present application, the Welch spectrum estimation method is an improvement on the average periodogram method, which first uses calculation steps including signal overlapping segmentation, windowing function and fast Fourier algorithm on the data, and then calculates the power spectrum of the signal. The calculation process is as follows:

[0135] First, the data is segmented, and the original signal x(r) is divided into K segments (where r is the index of the signal sampling point, ranging from 0 to N-1), and the length of each segment is M. Therefore, each signal segment is recorded as x i (n), where i = 0, 1, ..., K-1; n represents the segment index within the signal segment, ranging from 0 to M-1; thus, x i (n) represents the sample value of the i-th signal segment in the time domain.

[0136] Secondly, for each signal segment x i (n) Apply the window function w(n) to get the windowed signal: x i (n)w(n), where n represents the segment index within the signal segment, ranging from 0 to M-1.

[0137] Then, the windowed signal is Fourier transformed to convert the time domain signal into the frequency domain signal X i (m):

[0138]

[0139] Wherein, m is the frequency index, m = 0, 1, ..., M-1;

[0140] X i (m) is the frequency domain representation of the i-th windowed signal segment at frequency index m;

[0141] n represents the segment index within the signal segment, ranging from 0 to M-1;

[0142] Represents the kernel function of the Fourier transform, which is a complex exponential function, where j is an imaginary unit.

[0143] Next, calculate the power spectral density P of each signal segment i (m), which is the square of the modulus of the Fourier transform result, divided by the energy normalization factor U of the window function:

[0144]

[0145] Among them, P i (m) represents the power spectral density of the i-th signal segment;

[0146] U is the energy normalization factor of the window function, defined as:

[0147]

[0148] Where M represents the length of each signal segment;

[0149] n represents the segment index within the signal segment, ranging from 0 to M-1.

[0150] Finally, the power spectral density of all signal segments is averaged to obtain the final power spectrum estimate P(m), which is the PSD feature:

[0151]

[0152] Where K represents the number of segments of the original signal;

[0153] P i (m) represents the power spectral density of each signal segment.

[0154] During the implementation process, the process of power spectrum calculation can specifically be to calculate the power spectrum values ​​of 6 frequency bands (delta: 1-4Hz; theta: 4-8Hz; alpha: 8-13Hz; beta: 13-30Hz; low-gamma: 30-50Hz; mid-gamma: 50-100Hz; high-gamma: 100-150Hz) respectively.

[0155] In some embodiments of the present application, the PLV during PLV feature extraction is used to measure the phase synchronization degree between signals in a specific frequency band. The calculation formula of PLV is as follows:

[0156]

[0157] Where M represents the number of signal sampling points;

[0158] represents the instantaneous phase of channel x and channel y at time t after the Hilbert change;

[0159] Expressed as the phase difference between two signals;

[0160] i represents the imaginary unit.

[0161] The calculation of the phase value of the signal can be obtained by the following formula:

[0162]

[0163] Among them, x(t) represents the EEG signal of channel x at time t;

[0164] arctan is the inverse tangent function;

[0165] H[x(t)] represents the Hilbert transform of x(t), that is:

[0166]

[0167] Where PV stands for Cauchy principal value;

[0168] x(t′) represents the EEG signal of channel x at time t′.

[0169] The calculated result of PLV is between 0 and 1, where 0 means there is no synchronization between the two signals and 1 means there is complete synchronization between the two signals.

[0170] In some embodiments of the present application, PAC feature extraction includes calculating the PAC between two frequency bands using a modulation index (MI) method based on KL (Kullback-Leibler) divergence.

[0171] The calculation process of the MI method is to first perform low-frequency filtering (such as delta band, 1-4Hz) and high-frequency filtering (such as beta band, 13-30Hz) on the target EEG signal to obtain EEG signals in two frequency bands. Further, the Hilbert transform is used to extract the phase time series P(t) of the low-frequency signal and the amplitude time series A(t) of the high-frequency signal. Subsequently, the low-frequency phase is divided into N phase boxes, and the average amplitude of A(t) is calculated in each phase box and normalized. Next, the KL divergence is used to calculate the difference between the data distribution and the uniform distribution. Finally, the MI value is calculated, and its calculation formula is as follows:

[0172]

[0173] Among them, KL(U,X) means using KL divergence to measure the difference between two distributions;

[0174] U means uniform distribution;

[0175] X represents the data distribution;

[0176] N represents the number of phase boxes;

[0177] The calculation formula of KL divergence is as follows:

[0178] KL(U,X)=logN-H(P),

[0179] Among them, H(P) represents Shannon entropy, and its calculation formula is:

[0180]

[0181] in, It means that each phase box is calculated to obtain the average amplitude of the high-frequency amplitude and normalize it.

[0182] The calculation result of MI is between 0 and 1. The larger the MI value, the more obvious the coupling modulation relationship between the signals in the two frequency bands; conversely, the less obvious the coupling modulation relationship between the two frequency bands.

[0183] The proportional fixation time based on AOI is a response indicator for post-stimulus processing, which reflects the subject's fixation pattern on different AOIs of visual stimulation and indicates the process of attention involvement and maintenance in this area. In some embodiments of the present application, when extracting the proportional fixation time feature, the proportional fixation time for different levels of AOI is defined as:

[0184] Single-layer cognitive stimulation subtask: The proportion of the user's gaze time falling into the AOI (subtask 1: square, subtask 2: face) to the total time the subject gazes at the entire stimulation interface.

[0185] Dual-layer cognitive stimulation subtask: The user's gaze time in the high-level AOI (subtask three: square, subtask four: face, subtask five: square) and low-level AOI (subtask three: number, subtask four: number, subtask five: head and face of a person) areas respectively accounts for the proportion of the total time the subject gazes at the entire stimulation interface.

[0186] The number of gazes based on the AOI can reflect the user's attention or interest in a specific area or information. In some embodiments of the present application, the number of gazes for different levels of AOI is defined as:

[0187] Single-layer cognitive stimulation subtask: The number of times the user's gaze falls into the AOI (subtask 1: square, subtask 2: face) accounts for the total number of times the subject gazes at the entire stimulation interface;

[0188] Dual-layer cognitive stimulation subtask: The number of times the user's gaze falls into the high-level AOI (subtask three: square, subtask four: face, subtask five: square) and low-level AOI (subtask three: number, subtask four: number, subtask five: head and face of a person) areas respectively accounts for the proportion of the total number of times the subject gazes at the entire stimulation interface.

[0189] Pupil size refers to the diameter of the pupil of the eye, which changes with the change of light and the cognitive load of the user. Pupil size based on AOI can reflect the cognitive load and emotional changes of the user on a specific area or information. In some embodiments of the present application, the number of fixations on different levels of AOI is defined as:

[0190] Single-layer cognitive stimulation subtasks: the average pupil diameter size of users falling into the AOI (subtask 1: square, subtask 2: face).

[0191] Dual-layer cognitive stimulation subtask: The average pupil diameter of users falling into the high-level AOI (subtask three: square, subtask four: face, subtask five: square) and low-level AOI (subtask three: number, subtask four: number, subtask five: head and face of a person) areas respectively.

[0192] The cognitive control state evaluation system provided in this embodiment has multi-dimensional EEG features including part or all of EEG power spectrum density PSD, phase-locked value PLV and phase amplitude coupling PAC; multi-dimensional eye movement features including part or all of proportional fixation time, proportional fixation times and pupil size; behavioral features including part or all of accuracy and reaction time; reaction time characterizes the time it takes for the subject to make a cognitive response to a stimulus. The system provides a variety of feature extraction options to detect the multi-layer cognitive control state of the subject, can detect and evaluate the cognitive control state of the subject more comprehensively, and can improve the accuracy of evaluating the cognitive control state.

[0193] In some embodiments of the cognitive control state evaluation system 10, the comprehensive evaluation module 201, specifically through the multi-dimensional EEG features, multi-dimensional eye movement features and behavioral features (accuracy, reaction time) calculated by the feature extraction module, uses a support vector machine classifier to perform multi-feature fusion and evaluates the user's cognitive state. The support vector machine classifier is used to directly classify the input data to evaluate whether the user's cognitive state is abnormal. The cognitive control state evaluation system can also feed back the final test results and evaluation report to the user, and the user can save or print his or her test results.

[0194] Based on the same inventive concept as the cognitive control state evaluation system provided in the above embodiment, the embodiment of the present application further provides a cognitive control state evaluation method, which is applied to the cognitive control state evaluation system 10, such as Figure 5 As shown, the method for evaluating the cognitive control state comprises the following steps:

[0195] S501, select a hierarchical cognitive control paradigm from a stimulus database, and present a stimulus scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas.

[0196] S502, collecting the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme.

[0197] S503, performing a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and performing a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal.

[0198] S504, based on the focus area of ​​each stimulation subtask, align the stimulation-specific effective EEG signals and the stimulation-specific effective eye movement signals in different regions on a time scale.

[0199] S505, extracting multi-dimensional EEG features from the EEG signals after the regional alignment, extracting multi-dimensional eye movement features from the eye movement signals after the regional alignment, and extracting behavioral features from the judgment result signals, so as to evaluate the cognitive control state of the target subject.

[0200] The method includes: selecting a hierarchical cognitive control paradigm from a stimulus database, presenting a stimulus plan to a target subject based on the hierarchical cognitive control paradigm; collecting EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulus plan; performing a first preprocessing operation on the EEG signals to obtain stimulus-specific effective EEG signals, and performing a second preprocessing operation on the eye movement signals to obtain stimulus-specific effective eye movement signals; based on the focus areas of each stimulus subtask, aligning stimulus-specific effective EEG signals and stimulus-specific effective eye movement signals in different regions on a time scale; extracting multi-dimensional EEG features from the EEG signals after the alignment of different regions, extracting multi-dimensional eye movement features from the eye movement signals after the alignment of different regions, and extracting behavioral features from the judgment result signals for evaluating the cognitive control state of the target subject, so as to more comprehensively detect and evaluate the cognitive control state of the subject and improve the accuracy of evaluating the cognitive control state.

[0201] In one possible implementation, Figure 6 As shown, the method for evaluating cognitive control status includes the following steps:

[0202] S601, select a hierarchical cognitive control paradigm from a stimulus database, and present a stimulus scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas.

[0203] S602, collecting the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme.

[0204] S603, performing a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and performing a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal.

[0205] S604, based on the focus area of ​​each stimulation subtask, align the stimulation-specific effective EEG signals and the stimulation-specific effective eye movement signals in different regions on a time scale.

[0206] S605, extracting multi-dimensional EEG features from the EEG signals after the regional alignment, extracting multi-dimensional eye movement features from the eye movement signals after the regional alignment, and extracting behavioral features from the judgment result signals, so as to evaluate the cognitive control state of the target subject.

[0207] S606, based on the multi-dimensional EEG features, multi-dimensional eye movement features and behavioral features, obtain an evaluation result of the cognitive control state of the target subject; the evaluation result indicates whether the cognitive control state of the subject is abnormal.

[0208] In a possible implementation, the stimulus types of the stimulus subtask include emotional stimuli and non-emotional stimuli; and the stimulus subtasks of the same type have the same composition of stimulus types.

[0209] In a possible implementation, the single-layer cognitive stimulation subtask includes part or all of the emotional single-layer cognitive stimulation subtask and the non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of the non-emotional double-layer cognitive stimulation subtask, the high-level emotional double-layer cognitive stimulation subtask, and the low-level emotional double-layer cognitive stimulation subtask;

[0210] The emotional single-layer cognitive stimulation subtask represents that the subjects select the corresponding response item based on the first emotional stimulus image area presented;

[0211] The non-emotional single-layer cognitive stimulation subtask represents that the subjects select the corresponding response item based on the first non-emotional stimulus image area presented;

[0212] The non-emotional dual-layer cognitive stimulation subtask involves the subject selecting a response item corresponding to the third non-emotional stimulus image area based on the second non-emotional stimulus image area presented;

[0213] The high-level emotional dual-layer cognitive stimulation subtask represents that the subjects select the response item corresponding to the presented fourth non-emotional stimulus image area based on the presented second emotional stimulus image area;

[0214] The low-level emotional dual-layer cognitive stimulation subtask characterizes the subjects' selection of a response item corresponding to the presented third emotional stimulus image area based on the presented fifth non-emotional stimulus image area; wherein, for the third emotional stimulus image area presented simultaneously with a part of the fifth non-emotional stimulus image area, the subjects perform non-emotional cognition to select a response item.

[0215] In a possible implementation, the method further includes: when presenting the stimulation scheme to the target subject, sending a synchronization event tag to the data acquisition module;

[0216] Collect the target subject's EEG signals, eye movement signals, and judgment result signals when receiving the stimulation scheme, including:

[0217] Based on the synchronous event tags, the EEG signals, eye movement signals and judgment result signals of the target subjects when they receive the stimulation scheme are collected.

[0218] In a possible implementation, the first preprocessing operation includes part or all of electrode positioning, variable reference, bandpass filtering, notch filtering, downsampling, and artifact removal; the variable reference is to change the left ear mastoid reference to the average reference of the mastoids of both ears; the first preprocessing operation also includes segmenting and intercepting the EEG signal according to the synchronization event tag;

[0219] The second preprocessing operation includes merging gaze points and deleting some or all of the invalid eye movement sampling points; merging gaze points is to merge the gaze points adjacent in space and time based on the preset merging rules; deleting invalid eye movement sampling points is to remove the gaze points whose duration is less than the preset gaze duration; the second preprocessing operation also includes segmenting and intercepting the eye movement signal according to the synchronization event label.

[0220] In a possible implementation, the process of aligning the stimulus-specific effective EEG signals and the stimulus-specific effective eye movement signals in different regions on a time scale based on the focus regions of each stimulus subtask in S504 is implemented by the following steps:

[0221] Step A01, determining the regional fixation time range corresponding to the stimulus-specific eye movement signal according to the focus area of ​​each stimulus subtask; the regional fixation time range is the time period when the fixation point of the target subject falls into different focus areas.

[0222] Step A02, based on the regional gaze time range, determine the stimulus-specific effective EEG signals and stimulus-specific effective eye movement signals corresponding to each regional gaze time range, so as to perform regional alignment.

[0223] In a possible implementation, the multi-dimensional EEG features include part or all of the EEG power spectral density PSD, the phase-locked value PLV, and the phase-amplitude coupling PAC; the multi-dimensional eye movement features include part or all of the proportional fixation time, the proportional number of fixations, and the pupil size; the behavioral characteristics include part or all of the accuracy rate and the reaction time; the reaction time represents the time it takes for the subject to make a cognitive response to the stimulus.

[0224] The method for evaluating the cognitive control state of the above embodiment includes: selecting a hierarchical cognitive control paradigm from a stimulation database, and presenting a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; collecting the target subject's EEG signal, eye movement signal and judgment result signal when receiving the stimulation scheme; performing a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and performing a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal; based on the focus areas of each stimulation subtask, aligning the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in a time scale by region; extracting multi-dimensional EEG features from the stimulus-specific effective EEG signal after the region alignment, extracting multi-dimensional eye movement features from the stimulus-specific effective eye movement signal after the region alignment, and extracting behavioral features from the judgment result signal, so as to evaluate the cognitive control state of the target subject. The method can present a stimulation scheme to a target subject based on the hierarchical cognitive control paradigm by selecting a hierarchical cognitive control paradigm from a stimulation database; the hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; and then obtain stimulation-specific effective EEG signals and stimulation-specific effective eye movement signals; then, based on the focus areas of each stimulation subtask, the stimulation-specific effective EEG signals and stimulation-specific effective eye movement signals are aligned in different regions on a time scale; multi-dimensional EEG features are extracted from the stimulation-specific effective EEG signals after the sub-region alignment, multi-dimensional eye movement features are extracted from the stimulation-specific effective eye movement signals after the sub-region alignment, and behavioral features are extracted from the judgment result signal, so as to evaluate the cognitive control state of the target subject, thereby detecting the subject's multi-layer cognitive control state, and more comprehensively detecting and evaluating the subject's cognitive control state, thereby improving the accuracy of evaluating the cognitive control state.

[0225] An embodiment of the present application also provides a computer storage medium, in which computer executable instructions are stored. The computer executable instructions are used to implement the method for evaluating the cognitive control state of any embodiment of the present application.

[0226] According to one aspect of the present application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions, which are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the evaluation method of the cognitive control state in any of the above embodiments. The program product can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0227] The above are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A cognitive control state evaluation system, characterized in that: include: A task interaction module, used for selecting a hierarchical cognitive control paradigm from a stimulus database, and presenting a stimulus scheme to a target subject based on the hierarchical cognitive control paradigm; The hierarchical cognitive control paradigm includes multiple stimulation subtasks; the stimulation subtasks include single-layer cognitive stimulation subtasks and double-layer cognitive stimulation subtasks; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; the stimulation types of the stimulation subtasks include emotional stimulation and non-emotional stimulation; the stimulation subtasks of the same type have the same composition of stimulation types; the single-layer cognitive stimulation subtask includes part or all of the emotional single-layer cognitive stimulation subtask and the non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of the non-emotional double-layer cognitive stimulation subtask, the high-level emotional double-layer cognitive stimulation subtask, and the low-level emotional double-layer cognitive stimulation subtask; the emotional single-layer cognitive stimulation subtask represents the subject's The first emotional stimulus image area presented selects a corresponding reaction item; the non-emotional single-layer cognitive stimulation subtask represents the subject's selection of a corresponding reaction item based on the first non-emotional stimulus image area presented; the non-emotional double-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the third non-emotional stimulus image area presented based on the second non-emotional stimulus image area presented; the high-level emotional double-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the fourth non-emotional stimulus image area presented based on the second emotional stimulus image area presented; the low-level emotional double-layer cognitive stimulation subtask represents the subject's selection of a reaction item corresponding to the third emotional stimulus image area presented based on the fifth non-emotional stimulus image area presented; wherein, for the third emotional stimulus image area presented simultaneously with a part of the fifth non-emotional stimulus image area, the subject performs non-emotional cognition to select a reaction item; A data acquisition module, used to collect the EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulation scheme; A data preprocessing module, configured to perform a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and to perform a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal; A synchronization alignment module, used for aligning the stimulus-specific effective EEG signal and the stimulus-specific effective eye movement signal in different regions on a time scale based on the focus area of ​​each stimulus subtask; A feature extraction module is used to extract multi-dimensional EEG features from the stimulus-specific effective EEG signals after regional alignment, extract multi-dimensional eye movement features from the stimulus-specific effective eye movement signals after regional alignment, and extract behavioral features from the judgment result signals, so as to evaluate the cognitive control state of the target subject.

2. The system according to claim 1, characterized in that The system further comprises: A comprehensive evaluation module is used to obtain an evaluation result of the cognitive control state of the target subject based on the multi-dimensional EEG features, the multi-dimensional eye movement features and the behavioral features; the evaluation result represents whether the cognitive control state of the subject is abnormal.

3. The system according to claim 1, characterized in that The task interaction module is further used to: send a synchronization event tag to the data acquisition module when presenting the stimulation scheme to the target subject; The data acquisition module is specifically used to collect the EEG signal, eye movement signal and judgment result signal of the target subject when receiving the stimulation scheme based on the synchronization event tag.

4. The system according to claim 3, characterized in that The first preprocessing operation includes part or all of electrode positioning, variable reference, bandpass filtering, notch filtering, downsampling, and artifact removal; the variable reference is to change the left ear mastoid reference into the average reference of the mastoids of both ears; The first preprocessing operation further includes segmenting and intercepting the EEG signal according to the synchronization event tag; The second preprocessing operation includes merging fixation points and deleting some or all of the invalid eye movement sampling points; the fixation point merging is to merge the fixation points adjacent in space and time based on a preset merging rule; the deleting of invalid eye movement sampling points is to remove the fixation points whose duration is less than a preset fixation duration; The second preprocessing operation also includes segmenting and intercepting the eye movement signal according to the synchronization event tag.

5. The system according to claim 1, characterized in that The synchronization alignment module is specifically used for: Determining the regional fixation time range corresponding to the stimulus-specific eye movement signal according to the focus area of ​​each stimulus subtask; the regional fixation time range is the time period when the fixation point of the target subject falls into different focus areas; Based on the regional gaze time range, the stimulus-specific effective EEG signals and the stimulus-specific effective eye movement signals corresponding to each of the regional gaze time ranges are determined to perform regional alignment.

6. The system according to claim 1, characterized in that The multi-dimensional EEG features include part or all of the EEG power spectrum density PSD, phase-locked value PLV and phase-amplitude coupling PAC; the multi-dimensional eye movement features include part or all of proportional fixation time, proportional fixation number and pupil size; the behavioral characteristics include part or all of accuracy and reaction time; the reaction time characterizes the time it takes for the subject to make a cognitive response to a stimulus.

7. A method for evaluating cognitive control state, characterized in that: The method comprises: A hierarchical cognitive control paradigm is selected from a stimulus database, and a stimulus scheme is presented to a target subject based on the hierarchical cognitive control paradigm; the hierarchical cognitive control paradigm includes a plurality of stimulus subtasks; the stimulus subtasks include a single-layer cognitive stimulation subtask and a double-layer cognitive stimulation subtask; the single-layer cognitive stimulation subtask is used to detect the subject's memory cognition based on one focus area; the double-layer cognitive stimulation subtask is used to detect the subject's logical cognition based on two focus areas; the stimulus types of the stimulus subtask include emotional stimuli and non-emotional stimuli; the same type of stimulus subtasks have the same composition of stimulus types; the single-layer cognitive stimulation subtask includes part or all of an emotional single-layer cognitive stimulation subtask and a non-emotional single-layer cognitive stimulation subtask; the double-layer cognitive stimulation subtask includes part or all of a non-emotional double-layer cognitive stimulation subtask, a high-level emotional double-layer cognitive stimulation subtask, and a low-level emotional double-layer cognitive stimulation subtask ; The emotional single-layer cognitive stimulation subtask represents the subject's selection of the corresponding reaction item based on the presented first emotional stimulation image area; the non-emotional single-layer cognitive stimulation subtask represents the subject's selection of the corresponding reaction item based on the presented first non-emotional stimulation image area; the non-emotional double-layer cognitive stimulation subtask represents the subject's selection of the reaction item corresponding to the presented third non-emotional stimulation image area based on the presented second non-emotional stimulation image area; the high-level emotional double-layer cognitive stimulation subtask represents the subject's selection of the reaction item corresponding to the presented fourth non-emotional stimulation image area based on the presented second emotional stimulation image area; the low-level emotional double-layer cognitive stimulation subtask represents the subject's selection of the reaction item corresponding to the presented third emotional stimulation image area based on the presented fifth non-emotional stimulation image area; wherein, for the third emotional stimulation image area presented simultaneously with a part of the fifth non-emotional stimulation image area, the subject performs non-emotional cognition to select a reaction item; collecting the EEG signals, eye movement signals and judgment result signals of the target subject when receiving the stimulation scheme; Performing a first preprocessing operation on the EEG signal to obtain a stimulus-specific effective EEG signal, and performing a second preprocessing operation on the eye movement signal to obtain a stimulus-specific effective eye movement signal; Based on the focus area of ​​each of the stimulation subtasks, aligning the stimulation-specific effective EEG signal and the stimulation-specific effective eye movement signal in different regions on a time scale; Multi-dimensional EEG features are extracted from the EEG signals after the sub-region alignment, multi-dimensional eye movement features are extracted from the eye movement signals after the sub-region alignment, and behavioral features are extracted from the judgment result signals, so as to evaluate the cognitive control state of the target subject.

8. The method according to claim 7, characterized in that The method further comprises: Based on the multi-dimensional EEG features, the multi-dimensional eye movement features and the behavioral features, an evaluation result of the cognitive control state of the target subject is obtained; the evaluation result represents whether the cognitive control state of the subject is abnormal.

9. A computer-readable storage medium having a computer program stored therein, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 7 to 8 is implemented.

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