Brain Stimulation Tool Configuration via Network Activity Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for configuring brain stimulation tools lack the ability to selectively target specific neural representations of behaviorally important stimuli while ignoring irrelevant stimuli, due to the complexity of brain mechanisms and the lack of effective techniques for synchronizing spatiotemporal flow patterns among brain regions.
Innovation Solution
A method and system that utilize brain network activity (BNA) patterns to configure local brain stimulation tools by comparing reference and current-state BNA patterns, allowing for targeted stimulation at specific frequencies, locations, and synchronization based on node-wise comparisons, using techniques like Cortical Potential Imaging (CPI) and Cortical Source Density (CSD), to treat chronic brain disorders and conditions such as brain concussion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional brain stimulation methods are used, then stimulation can be applied to the brain, but the ability to selectively target specific neural representations of behaviorally important stimuli while ignoring irrelevant stimuli is limited
Solution Approach 1:
The patent segments the brain into discrete functional regions and neural representations, allowing targeted stimulation of specific areas. By dividing the complex brain into manageable segments (functional regions, neural representations), the system can selectively apply stimulation to specific segments while ignoring others, resolving the contradiction between selectivity and complexity.
Solution Approach 2:
The patent implements local quality by applying different stimulation parameters to different brain regions based on their functional characteristics. Each region receives customized stimulation tailored to its specific neural representation, enabling selective targeting of behaviorally important stimuli while maintaining overall system manageability despite brain complexity.
2Reliability
If brain stimulation is applied without BNA pattern comparison, then stimulation can be delivered, but synchronization among brain regions and treatment effectiveness are reduced
Solution Approach 1:
The patent employs feedback by continuously comparing current-state BNA patterns with reference patterns to guide stimulation delivery. This closed-loop approach uses the comparison results to adjust stimulation parameters in real-time, improving treatment effectiveness and reliability while managing complexity through automated feedback-based configuration.
Solution Approach 2:
The patent changes stimulation parameters dynamically based on BNA pattern comparisons. By adjusting frequency, location, and synchronization parameters according to the compared patterns, the system optimizes treatment effectiveness without requiring manual intervention, thereby improving reliability while controlling complexity through automated parameter adjustment.
3Productivity
If manual configuration of brain stimulation parameters is used, then device complexity is lower, but productivity and treatment optimization are reduced
Solution Approach 1:
The patent implements self-service by enabling the system to automatically configure stimulation parameters based on BNA pattern comparisons without requiring manual input. The system performs self-configuration through automated pattern analysis and parameter selection, significantly improving productivity and treatment optimization speed while managing complexity through standardized automated algorithms.
Solution Approach 2:
The patent uses copying by referencing standardized BNA patterns and templates to automatically configure stimulation parameters. Instead of manual configuration, the system copies proven effective parameter settings from reference patterns and adapts them to current patient data, rapidly optimizing treatment while reducing complexity through template-based automation.
Data Source
AI summary
A method of configuring a local brain stimulation tool is disclosed. The method comprises: obtaining a reference brain network activity (BNA) pattern, and a BNA pattern describing a neurophysiological state of the subject, each of the BNA patterns having a plurality of nodes and each node representing a brain location and at least one brain wave frequency. The method further comprises comparing the BNA patterns; and configuring the local brain stimulation tool to apply local brain stimulation at a frequency selected based on the comparison.