Systems, methods, and visualization tools for stimulation and sensing of neural systems with system-level interaction models

• US 10,350,413 B2
• Filed: 01/17/2017
• Issued: 07/16/2019
• Est. Priority Date: 11/14/2013
• Status: Active Grant

• Current Assignee: Boston Scientific Neuromodulation Corporation (Boston Scientific Corporation)
• Original Assignee: Boston Scientific Neuromodulation Corporation (Boston Scientific Corporation)
• Inventors: Moffitt, Michael A., Carbunaru, Rafael
• Primary Examiner(s): Fairchild, Mallika D
• Application Number:
  US15/408,205
• Publication Number:
  US 20170120054A1
• Time in Patent Office: 910 Days
• CPC Class Codes: A61N 1/0534 Electrodes for deep brain stimulation
• CPC Class Codes: A61N 1/36025 for treating a mental or cerebral condition
• CPC Class Codes: A61N 1/3605 Implantable neurostimulators for stimulating central or peripheral nerve system
• CPC Class Codes: A61N 1/36135 using physiological parameters
• CPC Class Codes: A61N 1/36185 Selection of the electrode configuration
• CPC Class Codes: A61N 1/37264 Changing the program; Upgrading firmware

Abstract

A computer implemented system and method generates a patient-specific model of patient response to stimulation on a neural element basis, receives user-input of target neuromodulation sites, and, based on the patient-specific model, determines which stimulation paradigm and settings, including stimulation sites, would result in the target neuromodulation, where the stimulation sites are not necessarily the same as the resulting neuromodulation sites. The system outputs a visual representation of the stimulation sites that would result in the target neuromodulation. The system monitors a system state and/or patient state and dynamically changes which stimulation program to implement based on the state.

Claims

1. A computer-implemented method comprising:

receiving, by a processor and for each of a plurality of candidate stimulation sites, an indication of an indirect neuromodulation response for direct stimulation at each other of the candidate stimulation sites, wherein each of the candidate stimulation sites represents a portion of a brain that is distant from each other of the candidate stimulation sites;

receiving, by a processor, a user-input of a desired stimulation response;

determining, by the processor using the indications of the indirect neuromodulation responses for the candidate stimulation sites, at least one of the candidate stimulation sites for implantation of at least one electrode leadwire to stimulate the determined at least one of the candidate stimulation sites;

determining or receiving, by the processor, electrode neuromodulation settings for performing neuromodulation on the brain of a patient using the at least one electrode leadwire implanted at the determined at least one of the candidate stimulation sites; and

communicating the electrode neuromodulation settings for reception by an implantable pulse generator to perform neuromodulation in the brain of the patient using the at least one electrode leadwire coupled to the implantable pulse generator.

2. The method of claim 1, wherein the indication of the indirect neuromodulation responses for the candidate stimulation sites is a change in a local field potential, an action potential of at least one neuron, a mean neuron firing rate, a change in power at a particular frequency band, or a neuro-activation spike.

3. The method of claim 1, wherein receiving the indication of the indirect neuromodulation responses for the candidate stimulation sites comprises measuring the indication using at least one sensor.

4. The method of claim 3, wherein the at least one sensor is a bio-potential sensor, a chemical sensor, a temperature sensor, an accelerometer, or a goniometer.

5. The method of claim 1, wherein receiving the indication of the indirect neuromodulation responses for the candidate stimulation sites comprises estimating the indirect neuromodulation response at the candidate stimulation site using a probabilistic tractography model or a biopotential response model.

6. The method of claim 5, wherein estimating the indirect neuromodulation response comprises estimating the indirect neuromodulation response at the candidate stimulation site using the probabilistic tractography model, wherein the probabilistic tractography model is based on diffusing tensor imaging or susceptibility weighted imaging.

7. The method of claim 5, wherein estimating the indirect neuromodulation response comprises estimating the indirect neuromodulation response at the candidate stimulation site using the probabilistic tractography model, wherein the probabilistic tractography model is based on functional magnetic resonance imaging.

8. The method of claim 1, wherein receiving the user-input of a desired stimulation response comprises providing, by the processor, a user interface wherein a user can indicate, for each candidate stimulation site, a stimulation objective.

9. The method of claim 8, wherein the stimulation objective indicates an increase in neural activity or a reduction in neural activity.

10. The method of claim 1, receiving the indication of the indirect neuromodulation responses for the candidate stimulation sites comprises

performing a neuromodulation at at least one of the candidate stimulation sites;

and

recording a neuromodulation response occurring at at least one of the candidate stimulation sites.

11. The method of claim 10, wherein performing the neuromodulation comprises performing a plurality of neuromodulations at at least one of the candidate stimulation sites using a plurality of different stimulation settings and

wherein recording the neuromodulation response comprises recording a neuromodulation response, for each of the plurality of different stimulation settings, occurring at at least one of the candidate stimulation sites.

12. The method of claim 11, wherein determining or receiving the electrode neuromodulation settings comprises determining the electrode neuromodulation settings based on the recorded neuromodulation responses.