CSF Charge Distribution for Neural Stimulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for selecting parameters for electrical stimulation of neural tissues, such as electrode locations, often rely on trial and error and lack consistency or repeatability, despite advancements in combining tissue geometry and electromagnetic field simulations.
Innovation Solution
The use of computed cerebrospinal fluid (CSF) charge distributions on the bounding surfaces of sulci to select stimulation protocols, allowing for a more intuitive understanding and prediction of electrical stimulation effects by focusing on the interaction of charged molecules with neural tissue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trial and error methods are used to select electrode locations for electrical stimulation, then flexibility in exploration is maintained, but reliability and repeatability of stimulation results deteriorate
Solution Approach 1:
The patent applies preliminary action by pre-computing charge distributions on sulcal bounding surfaces before actual stimulation. The method calculates charge distributions using finite element models of brain tissue and CSF, then uses these pre-computed distributions to identify optimal electrode locations, eliminating the need for trial-and-error placement during actual stimulation procedures.
Solution Approach 2:
The patent replaces the mechanical trial-and-error approach with a computational electromagnetic field-based system. Instead of physically testing different electrode locations, the method uses finite element simulations to compute charge distributions and automatically identifies optimal locations based on mathematical criteria, substituting computational analysis for mechanical exploration.
2Reliability
If computed CSF charge distributions are used to select electrode locations, then reliability and repeatability improve, but computational complexity and method complexity increase
Solution Approach 1:
The patent applies the extraction principle by isolating and focusing computation on the cerebrospinal fluid charge distributions specifically, rather than computing entire brain field distributions. By extracting and analyzing only the CSF charge patterns on sulcal surfaces, the method reduces computational burden while maintaining accuracy in identifying optimal electrode locations.
Solution Approach 2:
The patent uses computed charge distributions as an intermediary between the complex electromagnetic field simulations and the simple task of electrode location selection. The charge distributions serve as a intermediate representation that translates complex field data into actionable guidance for electrode placement, simplifying the decision-making process.
3Loss of information
If traditional electromagnetic field simulations are used, then tissue geometry information is utilized, but intuitive understanding of stimulation effects is limited
Solution Approach 1:
The patent applies the color changes principle by visualizing charge distributions with distinct positive and negative polarities represented by different colors or signs. This visualization method makes the abstract electromagnetic field patterns intuitive and interpretable, allowing practitioners to easily understand which regions will experience excitatory versus inhibitory effects from electrical stimulation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a more reliable and repeatable method for selecting electrode locations, enhancing the ability to achieve desired physiological responses by leveraging the unique electrical properties of CSF and its interaction with neural tissues.
Implementation Method 1
the present state of the art uses a combination of (1) tissue geometry and electrical properties obtained from, for example, CT and MRI images including diffusion tensor magnetic resonance images, and (2) electric field distributions and their associated current density distributions obtained from computer simulations
Data Source
AI summary
This disclosure relates to methods for modifying neural activity by applying electrical current to a neural tissue, e.g., in a transcranial DC stimulation procedure (tDCS), a transcranial AC stimulation procedure (tACS), a transcranial random noise stimulation procedure (tRNS), a deep brain stimulation procedure (DBS), a transcutaneous electrical nerve stimulation procedure (TENS), or the like. Historically, computed potential, electrical field, and/or current density distributions have been used to select the locations of the electrodes that apply the electrical current. In the present disclosure, a computed charge distribution on the bounding surface of one or more sulci filled with cerebrospinal fluid (CSF) is used in selecting the electrode locations. In one embodiment, the sulcus's bounding surface is divided into pixels and each pixel's charge is determined by the pixel functioning as a sensor for the charges surrounding it, including the charges of other pixels and the charges on the electrodes.