Neurocranial Electrostimulation Models, Systems, Devices and Methods
US-2016228702-A1 · Aug 11, 2016 · US
US10357654B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-10357654-B1 |
| Application number | US-201615338118-A |
| Country | US |
| Kind code | B1 |
| Filing date | Oct 28, 2016 |
| Priority date | Aug 27, 2015 |
| Publication date | Jul 23, 2019 |
| Grant date | Jul 23, 2019 |
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Described is a system for computing a transcranial stimulation montage. The system obtains externally sensed brain activity representing a current brain state of a subject. Using the externally sensed brain activity, a desired brain activity change in each relevant voxel of the brain of the subject is translated into a necessary electrical field. A model the desired brain activity in relevant voxels of the brain of the subject is created. Using the model, an electrical stimulation montage is computed that can be applied by transcranial stimulation electrodes to a subject to transform the current brain state into a desired brain state.
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What is claimed is: 1. A system for computing a transcranial stimulation montage, the system comprising: one or more processors and a memory, the memory being a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations of: mapping externally sensed brain activity data representing a first brain state to voxels of brain volume; mapping externally sensed brain activity data representing a second brain state to voxels of brain volume; translating a brain activity change from the second brain state to the first brain state in each relevant voxel of the brain into a necessary electrical field based on diffusion tensor imaging (DTI) data, wherein the DTI imaging data provides an average white matter tract orientation in each relevant voxel, and wherein the translated brain activity change in each relevant voxel is translated into the necessary electrical field by aligning to the average white matter tract orientation in each relevant voxel; computing an electrical stimulation montage from the translated brain activity change; and controlling application of the electrical stimulation montage by transcranial stimulation electrodes to transform the second brain state into the first brain state, the electrical stimulation montage including the necessary electrical field. 2. The system as set forth in claim 1 , wherein the amount of current that is applied along an axis of neurons in the particular voxel is proportional to the amount of brain activity change. 3. The system as set forth in claim 2 , wherein G is a gain factor that is held constant during application of the electrical stimulation montage and ΔS is the brain activity change, and the amount of current that is applied along an axis of neurons in the particular voxel is I = Δ S G . 4. The system as set forth in claim 1 , wherein the one or more processors further perform operations of: measuring changes in brain activity after application of the electrical stimulation montage; and using the set of measured changes in brain activity, adjusting a gain factor G for induced currents to affect brain activity change in each voxel. 5. The system as set forth in claim 4 , wherein gain factors G in each voxel are scaled by the cosine of an angle between a dominant white matter tract orientation and an induced electric field. 6. The system as set forth in claim 1 , wherein the one or more processors further perform an operation of creating a model of the brain activity representing the first brain state in relevant voxels of the brain. 7. A computer program product for computing a transcranial stimulation montage, the computer program product comprising: a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of: mapping externally sensed brain activity data representing a first brain state to voxels of brain volume; mapping externally sensed brain activity data representing a second brain state to voxels of brain volume; translating a brain activity change from the second brain state to the first brain state in each relevant voxel of the brain into a necessary electrical field using based on diffusion tensor imaging (DTI) data, wherein the DTI imaging data provides an average white matter tract orientation in each relevant voxel, and wherein the translated brain activity change in each relevant voxel is translated into the necessary electrical field by aligning to the average white matter tract orientation in each relevant voxel; computing an electrical stimulation montage from the translated brain activity change; and controlling application of the electrical stimulation montage by transcranial stimulation electrodes to transform the second brain state into the first brain state, the electrical stimulation montage including the necessary electrical field. 8. The computer program product as set forth in claim 7 , wherein the amount of current that is applied along an axis of neurons in the particular voxel is proportional to the amount of brain activity change. 9. The computer program product as set forth in claim 8 , wherein G is a gain factor that is held constant during application of the electrical stimulation montage and ΔS is the brain activity change, and the amount of current that is applied along an axis of neurons in the particular voxel is I = Δ S G . 10. The computer program product as set forth in claim 7 , further comprising instructions for causing the one or more processors to further perform operations of: measuring changes in brain activity after application of the electrical stimulation montage; and using the set of measured changes in brain activity, adjusting a gain factor G for induced currents to affect brain activity change in each voxel. 11. The computer program product as set forth in claim 10 , wherein gain factors G in each voxel are scaled by the cosine of an angle between a dominant white matter tract orientation and an induced electric field. 12. The computer program product as set forth in claim 7 , further comprising instructions for causing the one or more processors to further perform an operation of creating a model of the brain activity representing the first brain state in relevant voxels of the brain. 13. A computer implemented method for computing a transcranial stimulation montage, the method comprising an act of: causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of: mapping externally sensed brain activity data representing a first brain state to voxels of brain volume; mapping externally sensed brain activity data representing a second brain state to voxels of brain volume; translating a brain activity change from the second brain state to the first brain state in each relevant voxel of the brain into a necessary electrical field based on diffusion tensor imaging (DTI) data, wherein the DTI imaging data provides an average white matter tract orientation in each relevant voxel, and wherein the translated brain activity change in each relevant voxel is translated into the necessary electrical field by aligning to the average white matter tract orientation in each relevant voxel; computing an electrical stimulation montage from the translated brain activity change; and controlling application of the electrical stimulation montage by transcranial stimulation electrodes to transform the second brain state into the first brain state, the electrical stimulation montage including the necessary electrical field.
Head-worn items, e.g. helmets, masks, headphones or goggles · CPC title
Diagnosis combined with treatment in closed-loop systems or methods (A61B5/0036 takes precedence) · CPC title
Garment electrodes worn by the patient · CPC title
Specially adapted for transcutaneous electrical nerve stimulation [TENS] · CPC title
Human Necessities · mapped topic
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