Neuron signal analysis system and method

• US 7,136,696 B2
• Filed: 05/03/2002
• Issued: 11/14/2006
• Est. Priority Date: 04/05/2002
• Status: Expired due to Fees

• Current Assignee: Cleveland Clinic Foundation
• Original Assignee: Cleveland Clinic Foundation
• Inventors: Montgomery, Erwin B. Jr.
• Primary Examiner(s): Hindenburg, Max F.
• Assistant Examiner(s): TOWA, RENE T
• Application Number:
  US10/138,987
• Publication Number:
  US 20030191408A1
• Time in Patent Office: 1,656 Days
• Field of Search: 600/544, 600/545, 600/547, 600/554
• US Class Current: 600/544
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/685 Microneedles

Abstract

Electrical signal data from a target location are recorded and collected. A signal analyzer analyzes the signal data and determines whether characteristics of the signal data resemble noise data or whether a departure from noise is present. If the characteristics show a departure from noise, neuronal activity at the target location is indicated.

Claims

1. A system for positioning a microelectrode within a tissue, the system comprising:

a microelectrode for collecting electrical signals;

a computer readable medium having;

distribution logic that causes a computer to generate a statistical distribution of the electrical signals; and

identification logic that that causes a computer to identify whether the statistical distribution resembles a noise distribution without neuronal discharge; and

a position controller for controlling the position of microelectrode, the position controller moving or not moving the microelectrode based on the identification of whether the statistical distribution resembles a noise distribution without neuronal discharge.

2. The system as set forth in claim 1 wherein the statistical distribution is based on voltage amplitude values of the electrical signals.

3. The system as set forth in claim 1 wherein the noise distribution without neuronal discharge is a bell-shaped curve.

4. The system as set forth in claim 1 wherein the identification logic (i) includes logic for determining when the statistical distribution differs from the noise distribution without neuronal discharge, and (ii) generates a signal indicating possible neuron cell discharges are present in the electrical signals.

5. The system as set forth in claim 4 wherein the position controller moves the microelectrode within the brain until receipt of the signal indicating possible neuron cell discharge.

6. The system as set forth in claim 4 further including count logic for analyzing tails of the statistical distribution and indicating a quantity of neuron cell discharges in the electrical signals.

7. The system as set forth in claim 1 wherein the identification logic includes means for analyzing the statistical distribution.

8. The system as set forth in claim 1 wherein the identification logic includes logic for determining a kurtosis value of the statistical distribution.

9. The system as set forth in claim 1 further including correlation logic that correlates the statistical distribution with an applied stimulus.

10. A software product for analyzing electrical signal data collected from within tissue, the software product comprising:

a computer readable medium including;

logic that causes a computer to obtain electrical signal data from an microelectrode configured to be positioned within tissue;

first computer executable instructions that cause a computer to generate a statistical distribution of the electrical signal data where the statistical distribution has a first shape which represents noise signal data without neuronal activity or a second shape that represents noise data with neuronal activity; and

second computer executable instructions that cause a computer to analyze the statistical distribution and indicate whether neuronal activity is present in the electrical signal data based on the shape of the statistical distribution.

11. The software product as set forth in claim 10 wherein the computer readable medium further includes third computer executable instructions that cause a computer to exaggerate the electrical signal data to increase values that depart from a mean value of the statistical distribution.

12. The software product as set forth in claim 11 wherein the instructions to exaggerate include instructions that apply a fourth order moment about the mean to the electrical signal data.

13. The software product as set forth in claim 10 wherein the first shape is generally a bell shaped curve and the second shape is a curve with a departure from the bell shaped curve.

14. The software product as set forth in claim 10 wherein the statistical distribution is generated from voltage values of the electrical signal data.

15. The software product as set forth in claim 10 further including fourth computer executable instructions that cause a computer to determine an amount of neuron activity based on tails of the statistical distribution.

16. The software product as set forth in claim 10 further including fifth computer executable instructions that cause a computer to determine a kurtosis value from the statistical distribution which is used to indicate the shape of the statistical distribution.

17. The software product as set forth in claim 10 further including computer executable instructions that cause a computer to determine a correlation between neuronal activity and an applied stimulus.

18. A method of determining a nerve discharge from a plurality of electrical signals, the method comprising the steps of:

obtaining a plurality of electrical signals via a microelectrode positioned within tissue and providing a computer to;

statistically analyze at least one characteristic of the plurality of electrical signals and generate a distribution curve from the at least one characteristic;

determine a statistical characteristic of the distribution curve;

determine whether at least one nerve discharge signal occurs within the plurality of electrical signals based on the statistical characteristic of the distribution curve; and

determine whether noise data with no neuronal discharge signal occurs within the plurality of electrical signals based on the statistical characteristic of the distribution curve; and

provide an output indicative of whether at least one nerve discharge signal occurs or whether no neuronal discharge signal occurs.

19. The method as set forth in claim 18 further including:

automatically moving the electrode to a different location and collecting another set of electrical signals when the statistical characteristic of the distribution curve represents a noise distribution without a neuronal discharge signal.

20. The method as set forth in claim 18 wherein the distribution curve is generated from voltage values of each of the plurality of electrical signals.

21. The method as set forth in claim 18 further including collecting the plurality of electrical signals over a predetermined time period.

22. The method as set forth in claim 18 wherein the statistically analyzing step includes generating a generally bell-shaped distribution curve when the plurality of electrical signals represent noise signals without neuronal activity, and generating a distribution curve different from the generally bell-shaped distribution curve when the plurality of electrical signals contain neuronal activity.

23. The method as set forth in claim 18 wherein the step of determining a statistical characteristic includes:

determining a central tendency of the plurality of electrical signals; and

measunng an amount of signal dispersion from the central tendency.

24. The method as set forth in claim 18 further including determining an amount of nerve discharge signals within the plurality of electrical signals by a size of a tail of the distribution curve.

25. The method as set forth in claim 18 further including determining whether at least one nerve discharge signal occurs within the electrical signal data simultaneously with an applied stimulation.

26. The method as set forth in claim 18 wherein the step of determining a statistical characteristic of the distribution curve includes determining a kurtosis value from the distribution curve.

27. The method as set forth in claim 18 wherein the step of determining a statistical characteristic of the distribution curve includes determining a size of tails of the distribution curve.

28. The method as set forth in claim 18 wherein the step of determining a statistical characteristic of the distribution curve includes determining a plurality of statistical characteristics.

29. A device for analyzing electrical signal data collected from tissue, the device comprising:

a microelectrode adapted to be positioned in a tissue for collecting electrical signal data;

computer readable medium containing first computer executable instructions that cause a computer to generate a statistical distribution of the electrical signal data wherein the statistical distribution is one selected from a first shape which represents noise signal data without neuronal activity and a second shape that represents noise signal data with neuronal activity;

computer readable medium containing second computer executable instructions that cause a computer to analyze the statistical distribution and indicate whether neuronal activity is present in the electrical signal data based on the shape of the statistical distribution; and

an indicator for controlling the position of the microelectrode, the indicator issuing commands for moving or not moving the microelectrode based on the shape of the statistical distribution.

30. The device as set forth in claim 29 further including third computer executable instructions that cause a computer to exaggerate the electrical signal data to increase values that depart from a mean value of the statistical distribution.

31. The device as set forth in claim 30 wherein the instructions to exaggerate include instructions that apply a fourth order moment about the mean to the electrical signal data.

32. The device as set forth in claim 29 wherein the first shape is generally a bell shaped curve and the second shape is a curve with a departure from the bell shaped curve.

33. The device as set forth in claim 29 wherein the statistical distribution is generated from voltage values of the electrical signal data.

34. The device as set forth in claim 29 wherein the computer readable medium further include fourth computer executable instructions that cause a computer to determine an amount of neuron activity based on tails of the statistical distribution.

35. The device as set forth in claim 29 wherein the computer readable medium further include fifth computer executable instructions that cause a computer to determine a kurtosis value from the statistical distribution which is used to indicate the shape of the statistical distribution.

36. The device as set forth in claim 29 wherein the computer readable medium further include computer executable instructions that cause a computer to determine a correlation between neuronal activity and an applied stimulus.

37. A method of determining one or more nerve discharge signals from a plurality of electrical signals, the method comprising the steps of:

obtaining a plurality of electrical signals from a microelectrode positioned within tissue and providing computer to;

statistically analyze at least one characteristic of the plurality of electrical signals and generating a distribution curve from at least one characteristic;

determine a statistical characteristic of the distribution curve;

determine whether at least one nerve discharge signals occurs within the plurality of electrical signals based on the statistical characteristic of the distribution curve;

determine whether no neuronal discharge signal occurs within the plurality of electrical signals based on the statistical characteristic of the distribution curve; and

provide an output indicative of whether at least one nerve discharge signal occurs or whether no neuronal discharge signal occurs.

38. The method as set forth in claim 37 wherein the distribution curve is generated from voltage values of each of the plurality of electrical signals.

39. The method as set forth in claim 37 further including providing the computer to collect the plurality of electrical signals over a predetermined time period.

40. The method as set forth in claim 37 wherein the statistically analyzing step includes providing the computer to generate a generally bell-shaped distribution curve when the plurality of electrical signals represent noise signals without neuronal activity, and generating a distribution curve different from the generally bell-shaped distribution curve when the plurality of electrical signals contain neuronal activity.

41. The method as set forth in claim 37 wherein the step of determining a statistical characteristic includes:

determining a central tendency of the plurality of electrical signals; and

measuring an amount of signal dispersion from the central tendency.

42. The method as set forth in claim 37 further including providing the computer to determine an amount of nerve discharge signals within the plurality of electrical signals by a size of a tail of the distribution curve.

43. The method as set forth in claim 37 wherein the step of determining a statistical characteristic of the distribution curve includes determining a kurtosis value from the distribution curve.

44. The method as set forth in claim 37 wherein the step of determining a statistical characteristic of the distribution curve includes determining a size of tails of the distribution curve.