Cognitive function training system

Abstract

The invention discloses a cognitive function training system, which comprises a multi-lead nerve stimulation channel, the multi-lead nerve stimulation channel comprises electrode point positions covering a prefrontal lobe, and the electrode point positions comprise an FP1 electrode point position, an FP2 electrode point position, an F3 electrode point position, an F4 electrode point position, an F7 electrode point position and an F8 electrode point position; and the multi-channel control module is used for regulating and controlling the multi-lead nerve stimulation channel to execute multi-channel cooperative training, and the multi-channel cooperative training comprises single-point training, multi-point balance training, connectivity training, stability training and network training. Compared with the prior art, the accuracy and comprehensiveness of cognitive function training are effectively improved, and efficient training of complex integrated cognitive competence is achieved.

Description

Technical Field

[0001] This invention relates to the field of neurotraining technology, and in particular to a cognitive function training system. Background Technology

[0002] The prefrontal cortex is a core area of ​​the brain responsible for higher cognitive functions such as executive control, attention, working memory, language processing, and emotion regulation. Cognitive impairment is commonly seen in patients with ADHD, anxiety and depression, stroke rehabilitation, neurodegenerative diseases (such as early-stage Alzheimer's disease), and traumatic brain injury, and also affects the cognitive performance of healthy individuals.

[0003] Existing cognitive function training techniques have the following defects and limitations:

[0004] Ambiguous / sparse localization: Many existing cognitive training devices (such as single-point or few-point devices) cannot accurately cover multiple functional subregions of the prefrontal cortex, resulting in insufficient training targeting and limited effectiveness.

[0005] Single mode: Existing devices focus on a single function (such as attention) or single-point stimulation, lacking the simulation of the brain's networked collaborative working mode, making it difficult to improve complex integrative cognitive abilities (such as decision-making, problem-solving, and social interaction).

[0006] Poor portability: Professional-grade multi-channel brain cognition devices are usually bulky, complex to operate, and expensive, requiring use in laboratories or specialized medical institutions, which limits their accessibility and feasibility for daily training.

[0007] Systemic shortcomings: Existing technologies lack comprehensive solutions for training the overall cognitive function network of the prefrontal cortex in a complete and systematic manner.

[0008] Therefore, there is an urgent need to invent a new cognitive function training scheme to solve the problems of insufficient targeting, inability to train integrative cognitive abilities, poor portability, and inability to conduct systematic training in existing cognitive training technologies. Summary of the Invention

[0009] In view of this, embodiments of the present invention provide a cognitive function training system that at least partially solves the problems existing in the prior art.

[0010] Other features and advantages of the invention will become apparent from the following detailed description, or may be learned in part by practice of the invention.

[0011] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0012] According to a first aspect of the present invention, a cognitive function training system is provided, the system comprising:

[0013] A multi-lead neural stimulation channel, the multi-lead neural stimulation channel including electrode points covering the prefrontal cortex, the electrode points including FP1 electrode point, FP2 electrode point, F3 electrode point, F4 electrode point, F7 electrode point and F8 electrode point;

[0014] A multi-channel control module is used to regulate the multi-lead neural stimulation channels to perform multi-channel collaborative training, which includes single-point training, multi-point balance training, connectivity training, stability training, and network training.

[0015] Furthermore, the FP1 electrode sites are used to train primary attention and visual memory;

[0016] The FP2 electrode points are used to train emotion control, social awareness, self-perception, impulse inhibition, and anxiety management.

[0017] The F3 electrode points are used to train secondary attention and working memory;

[0018] The F4 electrode points are used to train third attention and impulse inhibition;

[0019] The F7 electrode point is used to train language expression and auditory memory;

[0020] The F8 electrode points are used to train emotional expression, fourth attention, emotion management, and visuospatial memory.

[0021] Furthermore, the first attention includes the ability to execute planning, organization, and decision-making.

[0022] The second attention includes the ability to perform language tasks and writing-related skills;

[0023] The third attention includes alertness and inhibition-related abilities;

[0024] The fourth level of attention includes the ability to maintain mental focus.

[0025] Furthermore, the multi-point balance training involves simultaneously or alternately stimulating symmetrical electrode points on both sides.

[0026] Furthermore, the connectivity training involves stimulating multiple functionally closely related asymmetric electrode sites.

[0027] Furthermore, the stability training involves stimulation of preset specific electrode sites or combinations of electrode sites used to stabilize neural states.

[0028] Furthermore, the network training is a multi-dimensional collaborative training of a preset neural network;

[0029] The multi-dimensional collaborative training includes time-dimensional collaboration and spatial-dimensional collaboration.

[0030] Furthermore, the time-dimensional coordination includes synchronous activation, sequential activation, and oscillatory coupling;

[0031] The synchronous activation means simultaneously stimulating all electrode points of the preset neural network.

[0032] The sequence activation involves stimulating the electrode points of the preset neural network according to a preset task flow sequence;

[0033] The oscillatory coupling is achieved by applying phase-synchronized θ-band or β-band stimulation to the electrode points in the preset neural network.

[0034] Furthermore, the spatial dimension coordination includes dynamic intensity ratio and closed-loop feedback adjustment;

[0035] The dynamic intensity ratio is used to automatically adjust the stimulation intensity of each electrode point according to the task requirements corresponding to the network training.

[0036] The closed-loop feedback regulation is used to dynamically optimize stimulation parameters based on real-time monitored EEG connectivity indicators. The stimulation parameters include stimulation intensity and stimulation frequency.

[0037] This invention provides a cognitive function training system, comprising: a multi-lead neural stimulation channel, including electrode points covering the prefrontal cortex, comprising FP1, FP2, F3, F4, F7, and F8 electrode points; and a multi-channel control module for regulating the multi-lead neural stimulation channel to perform multi-channel collaborative training, including single-point training, multi-point balance training, connectivity training, stability training, and network training. Compared with existing technologies, this invention effectively improves the accuracy and comprehensiveness of cognitive function training, achieving efficient training of complex integrative cognitive abilities. Attached Figure Description

[0038] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of the structure of a cognitive function training system provided in an embodiment of the present invention. Detailed Implementation

[0040] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0041] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or apparatus.

[0042] like Figure 1 As shown, the cognitive function training system according to an embodiment of the present invention includes a multi-lead neural stimulation channel and a multi-channel control module.

[0043] Specifically, the above-mentioned multi-lead neural stimulation channel adopts a six-channel (lead) design, and the electrode placement strictly follows the international EEG 10-20 system standard, including electrode points covering the prefrontal cortex. The electrode points include FP1 electrode point, FP2 electrode point, F3 electrode point, F4 electrode point, F7 electrode point and F8 electrode point.

[0044] Each electrode point is specifically trained to train a particular, defined cognitive function:

[0045] The aforementioned FP1 electrode sites are used to train primary attention and visual memory. Primary attention includes the ability to perform planning, organization, and decision-making.

[0046] The aforementioned FP2 electrode points are used to train emotion control, social awareness, self-perception, impulse inhibition, and anxiety management.

[0047] The aforementioned F3 electrode sites are used to train secondary attention and working memory. Secondary attention includes executive language skills and writing-related skills.

[0048] The aforementioned F4 electrode points are used to train third attention and impulse inhibition. Third attention includes alertness and inhibition-related abilities.

[0049] The aforementioned F7 electrode points are used to train language expression (simulating Broca's area function, vocalizing language output) and auditory memory.

[0050] The aforementioned F8 electrode points are used to train emotional expression, fourth attention, emotion management, and visuospatial memory. Fourth attention includes the ability to maintain mental focus.

[0051] This invention, through its multi-lead neural stimulation channels, ensures that neural training can be applied precisely and regionally to specific sub-regions of the prefrontal cortex responsible for different higher cognitive functions, comprehensively covering the main cognitive sub-regions of the prefrontal cortex and avoiding the limitations of single-point or sparse-point methods. This invention effectively improves the accuracy and comprehensiveness of neurocognitive function training, significantly outperforming non-systematic solutions on the market that target only a single function or use single-point / few-point devices.

[0052] Specifically, the aforementioned multi-channel control module is used to regulate the multi-lead neural stimulation channels to perform multi-channel collaborative training, which includes single-point training, multi-point balance training, connectivity training, stability training, and network training.

[0053] The above single-point training is the basic model, which strengthens the specific function corresponding to a single point. For example, focus training focuses on FP1, and emotion stability training focuses on FP2.

[0054] The aforementioned multi-point balance training involves simultaneously or alternately stimulating symmetrical electrode points on both sides, such as left and right hemisphere balance (F3 / F4, FP1 / FP2). Multi-point balance training aims to improve coordination and balance between cerebral hemispheres and address functional lateralization issues.

[0055] The aforementioned connectivity training involves stimulating multiple asymmetric electrode sites that are closely related to functions. For example, FP1 and F7 are used to strengthen the connection between planning and language expression, while F4 and F8 are used to strengthen the connection between inhibitory control and emotion management. Connectivity training aims to enhance the intrinsic connectivity strength of specific neural pathways or functional networks.

[0056] The aforementioned stability training involves stimulating specific electrode points or combinations of electrode points (such as maintaining the FP2 point) that focus on stabilizing neural states, in order to improve the stability and resistance to interference of cognitive functions.

[0057] The aforementioned network training represents the most complex high-level mode, involving multi-dimensional collaborative training of a pre-defined neural network. For example, it may simultaneously or sequentially activate FP1, F3, and F4 to simulate and train a high-level executive function network; or activate F7, F8, and FP2 to simulate and train a language-emotion integration network. The aim of this network training is to enhance the collaborative operation of the entire prefrontal cortex functional network, thereby improving the efficiency of solving complex cognitive tasks.

[0058] Furthermore, the aforementioned preset neural network may include:

[0059] The higher executive network (FP1 / F3 / F4) involves the dorsolateral prefrontal cortex (DLPFC) in coordinating goal planning (FP1), working memory caching (F3), and inhibitory control (F4). The task of the higher executive network is multi-goal planning and decision-making. FP1 activation: The user creates a shopping list (goal planning) → the device enhances FP1 with gamma-wave stimulation (40Hz). F3 intervention: The price of goods is memorized (working memory) → F3 receives theta-wave stimulation to reinforce and temporarily store the information. F4 regulation: Unnecessary purchasing impulses are suppressed → F4 applies high-frequency beta stimulation (20Hz) to enhance inhibitory control. Higher executive network integration: Synchronized mid-frequency alpha wave (10Hz) stimulation of FP1 / F3 / F4 strengthens network coordination.

[0060] The Language-Emotion Integration Network (F7 / F8 / FP2): The ventrolateral prefrontal cortex (VLPFC) coordinates language generation (F7), emotion recognition (F8), and emotion regulation (FP2). The task of the Language-Emotion Integration Network is communication in emotional scenarios. F7 initiation: The user describes an angry event → The device enhances F7 low-frequency theta stimulation (6Hz) to promote language organization. F8 response: The user recognizes their own angry emotion → F8 applies high-frequency gamma stimulation (40Hz) to enhance emotional awareness. FP2 regulation: Anger is regulated to calm → FP2 continuous beta stimulation (15Hz) stabilizes the emotion. Language-Emotion Integration Network coupling: F7 / F8 and FP2 perform cross-band phase synchronization (F7θ-FP2β) to optimize emotion expression control.

[0061] Preferably, embodiments of the present invention further include an AI task engine and a biofeedback module. The AI ​​task engine is used to adaptively adjust the network node activation strategy based on user performance (reaction time / accuracy).

[0062] The biofeedback module is used to display the FP1-F3-F4 coherence index in real time and quantify the network connection strength (e.g., 0.8 indicates high coherence).

[0063] Network training can induce long-term potentiation (LTP) through multi-node collaborative stimulation, thereby enhancing synaptic connection efficiency and improving information integration capabilities.

[0064] The aforementioned multi-dimensional collaborative training includes time-dimensional collaboration and spatial-dimensional collaboration.

[0065] Among them, time-dimensional coordination includes synchronous activation mode, sequential activation mode and oscillatory coupling mode. The time-dimensional coordination mechanism is shown in Table 1.

[0066] Table 1. Schematic diagram of time-dimensional collaboration mechanism

[0067] model Implementation Neural mechanism goals Synchronous activation Simultaneously stimulate FP1 / F3 / F4 (execution network) Enhance instantaneous synchronization of network nodes Sequence activation Stimulate in task flow order: FP1 (Planning) → F3 (Memory) → F4 (Execution) Simulate the real cognitive process to enhance information delivery Oscillation Coupling Phase-synchronized theta band (4-8Hz) stimulation is applied to F7 / F8, while β band (15-30Hz) stabilization modulation is applied to FP2. Optimize cross-brain region oscillation synchronization

[0068] The aforementioned spatial dimensional coordination includes dynamic intensity matching and closed-loop feedback adjustment.

[0069] The dynamic intensity ratio is used to automatically adjust the stimulation intensity of each electrode point according to the task requirements corresponding to network training. For example, for decision-making tasks: FP1 intensity > F4; for social tasks: F8 intensity ≈ F7.

[0070] Closed-loop feedback regulation is used to dynamically optimize stimulation parameters based on real-time monitored EEG connectivity indicators (such as coherence and phase lock value). Stimulation parameters include stimulation intensity and stimulation frequency.

[0071] The cognitive function training system provided in this embodiment of the invention has the following advantages:

[0072] Precise positioning and function mapping: In this embodiment of the invention, a 6-lead design is adopted, and the electrodes are strictly placed at the six core cognitive function points of the prefrontal cortex, namely FP1, FP2, F3, F4, F7, and F8, of the international EEG 10-20 system. The specific cognitive function sub-items (attention, executive function, working memory, language, emotion regulation, memory, etc.) corresponding to each point are clearly defined.

[0073] Original Collaborative Training Mode: This invention innovatively proposes and implements a multi-point collaborative training mode, including single-point, multi-point balance, connectivity, stability, network training and other modes, which simulate the brain's networked working mode and aim to improve integrative cognitive ability.

[0074] Systematic prefrontal cortex coverage: Provides a comprehensive training solution for the entire prefrontal cortex cognitive function system, rather than single or partial functional training.

[0075] Portable design enables widespread adoption: The key advantage of this invention is its portability (miniaturization, wireless, and ease of operation), which enables professional multi-lead prefrontal cortex cognitive training to break through the limitations of laboratory / hospital scenarios and achieve convenient daily applications, greatly expanding its scope of application and user base.

[0076] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, or alterations made by those skilled in the art using the disclosed technical content shall fall within the protection scope of the present invention.

Claims

1. A cognitive function training system, characterized in that, The system includes: A multi-lead neural stimulation channel, the multi-lead neural stimulation channel including electrode points covering the prefrontal cortex, the electrode points including FP1 electrode point, FP2 electrode point, F3 electrode point, F4 electrode point, F7 electrode point and F8 electrode point; A multi-channel control module is used to regulate the multi-lead neural stimulation channels to perform multi-channel collaborative training, which includes single-point training, multi-point balance training, connectivity training, stability training, and network training.

2. The cognitive function training system according to claim 1, characterized in that, The FP1 electrode points are used to train primary attention and visual memory; The FP2 electrode points are used to train emotion control, social awareness, self-perception, impulse inhibition, and anxiety management. The F3 electrode points are used to train secondary attention and working memory; The F4 electrode points are used to train third attention and impulse inhibition; The F7 electrode point is used to train language expression and auditory memory; The F8 electrode points are used to train emotional expression, fourth attention, emotion management, and visuospatial memory.

3. The cognitive function training system according to claim 1, characterized in that, The first aspect of attention includes the ability to execute planning, organize, and make decisions; The second attention includes the ability to perform language tasks and writing-related skills; The third attention includes alertness and inhibition-related abilities; The fourth level of attention includes the ability to maintain mental focus.

4. The cognitive function training system according to claim 1, characterized in that, The multi-point balance training involves simultaneously or alternately stimulating symmetrical electrode points on both sides.

5. A cognitive function training system according to claim 1, characterized in that, The connectivity training involves stimulating multiple functionally closely related asymmetric electrode sites.

6. A cognitive function training system according to claim 1, characterized in that, The stability training involves stimulating specific electrode points or combinations of electrode points pre-set to stabilize the neural state.

7. A cognitive function training system according to claim 1, characterized in that, The network training is a multi-dimensional collaborative training of a preset neural network; The multi-dimensional collaborative training includes time-dimensional collaboration and spatial-dimensional collaboration.

8. A cognitive function training system according to claim 7, characterized in that, The time-dimensional coordination includes synchronous activation, sequence activation, and oscillatory coupling; The synchronous activation means simultaneously stimulating all electrode points of the preset neural network. The sequence activation involves stimulating the electrode points of the preset neural network according to a preset task flow sequence; The oscillatory coupling is achieved by applying phase-synchronized θ-band or β-band stimulation to the electrode points in the preset neural network.

9. A cognitive function training system according to claim 7, characterized in that, The spatial dimension coordination includes dynamic intensity ratio and closed-loop feedback adjustment; The dynamic intensity ratio is used to automatically adjust the stimulation intensity of each electrode point according to the task requirements corresponding to the network training. The closed-loop feedback regulation is used to dynamically optimize stimulation parameters based on real-time monitored EEG connectivity indicators. The stimulation parameters include stimulation intensity and stimulation frequency.

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