Obtaining information about brain activity

• US 8,626,264 B1
• Filed: 04/08/2009
• Issued: 01/07/2014
• Est. Priority Date: 04/09/2008
• Status: Expired due to Fees

• Current Assignee: James T Beran Revocable Tyrust
• Original Assignee: James T Beran Revocable Tyrust
• Inventors: Beran, James T.
• Primary Examiner(s): Jung, Unsu
• Assistant Examiner(s): Huynh, Phong K
• Application Number:
  US12/384,730
• Time in Patent Office: 1,735 Days
• Field of Search: 600/300, 600/407, 600/410, 600/411, 600/436, 600/544, 600/545, 324/300, 324/309
• US Class Current: 600/407
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 6/037 Emission tomography
• CPC Class Codes: A61B 6/501 for diagnosis of the head, e.g. neuroimaging or craniography
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A brain imaging system can be operated to obtain brain image signals indicating activity at brain locations, and information can be extracted from the brain image signals. For example, for each of a set of living human brain regions that can have two or more possible activity features such as qualia features, feature values can be obtained indicating activity features of the region. The feature values can be more explicit than brain image data indicating activity at brain locations. A data structure can be produced that includes data indicating extracted information, such as qualia value data for a quale activity feature that can occur in a region. Such a data structure can be stored on a storage medium and used in diagnosis and/or treatment of detrimental conditions of consciousness.

Claims

1. A method of operating a system having:

a processor,

receiving circuitry that, in operation, receives brain image signals indicating activity at locations in brains, and

memory circuitry that, in operation, stores;

program data indicating a program, and

a data structure,

the method comprising;

operating the receiving circuitry to obtain brain image signals indicating activity at locations in a conscious human'"'"'s brain;

the brain image signals including electrical/magnetic signals obtained using at least one of positron emission tomography, functional magnetic resonance imaging, electroencephalography, and magnetoencephalography;

operating the processor to perform the program;

in performing the program, the processor extracting information from the brain image signals and including at least part of the extracted information in the data structure; and

using the data structure in at least one of;

diagnosis of a detrimental condition of consciousness; and

treatment of a detrimental condition of consciousness;

the act of operating the processor including;

for each of a set of two or more brain parts, performing a respective part level iteration;

each part'"'"'s respective part level iteration including;

obtaining region identifying data indicating regions of the brain part; and

for each of a set of the regions indicated by the part'"'"'s region identifying data, performing a respective region level iteration that obtains feature values indicating activity features of the region;

the respective region level iteration of one or more regions including;

obtaining respective qualia information based on a portion of the brain image signals that indicates activity levels of locations in the region;

at least one region'"'"'s qualia information including, for each quale activity feature in a set of one or more activity features that can occur in the region, a respective qualia value indicating the human'"'"'s current experience corresponding to the quale activity feature; and

including in the data structure qualia value data indicating, for at least one quale activity feature that can occur in one of the set of regions, the respective qualia value.

2. The method of claim 1 in which the act of performing a respective region level iteration includes at least one of:

applying a threshold to activity levels at positions within the region;

obtaining probabilities for activity levels at positions within the region; and

obtaining frequencies from time varying activity levels at positions within the region.

3. The method of claim 1 in which at least one of the set of qualia activity features includes a respective combination of two or more qualia;

the act of including qualia value data in the data structure further including in the data structure;

for one of the respective combinations of two or more qualia, a qualia combination node corresponding to the combination; and

linked to the qualia combination node, a respective item for each of the qualia in the combination, at least one respective item including a descriptor of the respective one of the qualia in the combination.

4. A system comprising:

a storage medium;

stored by the storage medium, a data structure;

a processing component that includes one or more processors; and

connecting circuitry that can receive brain image data indicating activity at locations in a living brain and through which the processing component can access the data structure stored by the storage medium;

the data structure including;

for each of a set of regions of a living brain, qualia feature value data indicating, for each of a set of one or more qualia activity features the region can have, a respective qualia value, the qualia value indicating a conscious experience of the brain corresponding to the qualia activity feature;

at least one of the set of qualia activity features including a respective combination of two or more qualia;

a node-link structure that includes;

a qualia combination node corresponding to one of the respective combinations of two or more qualia; and

a region node that represents an active qualia map region of the living brain, the region node being linked to the qualia combination node; and

linked to the qualia combination node, a respective item for each of the qualia in the combination, at least one respective item including a descriptor of the respective one of the qualia in the combination;

the processing component including a combination of one or more processors programmed;

to use the brain image data to obtain feature value data indicating feature values of active regions of the living brain;

the feature value data for the active qualia map region including, for a quale activity feature that can occur in the active qualia map region, a value indicating the living brain'"'"'s current experience corresponding to the quale activity feature; and

to include in the data structure the value indicating the living brain'"'"'s current experience corresponding to the quale activity feature.

5. The system of claim 4 in which the combination of one or more processors includes only one programmed processor.

6. The system of claim 4, further comprising an imaging system that provides the brain image data to the connecting circuitry;

the imaging system obtaining the brain image data by at least one of positron emission tomography, functional magnetic resonance imaging, electroencephalography, and magnetoencephalography.

7. The system of claim 4 in which the combination of two or more qualia includes at least one of a color, a smell, and a sound.

8. The system of claim 4 in which the data structure further includes a table, the table including:

for each of the qualia in the combination, the respective item.

9. A method of operating the system of claim 4, comprising:

operating the combination of one or more processors as programmed;

the act of operating the combination of one or more processors as programmed comprising;

performing a respective part level iteration for each of a set of two or more brain parts;

each part'"'"'s respective part level iteration obtaining region identifying data indicating regions of the brain part;

the active qualia map region being one of the regions indicated by the region identifying data of one of the brain parts in the set;

the node-link structure including a respective brain part node that represents the one of the brain parts, the respective brain part node being linked to the region node that represents the active qualia map region; and

for each of a set of the regions indicated by the part'"'"'s region identifying data, performing a respective region level iteration that obtains feature values indicating activity features of the region;

the respective region level iteration of the active qualia map region obtaining respective qualia information based on a portion of the brain image signals that indicates activity levels of locations in the active qualia map region;

the respective qualia information including, for each quale activity feature in a set of one or more activity features that can occur in the active qualia map region, a respective qualia value;

the value indicating the living brain'"'"'s current experience being the respective qualia value of one of the quale activity features in the set of activity features that can occur in the active qualia map region.

10. The method of claim 9 in which the brain is a conscious human'"'"'s brain.

11. A method of operating the system of claim 4, comprising:

using the active qualia map region'"'"'s portion of brain image data to obtain a set of qualia values based on a mathematical model of consciousness; and

determining whether the data structure includes an existing node corresponding to the set of qualia values by testing whether the qualia values in the set correspond to the qualia combination node.

12. A method of operating the system of claim 4, the method comprising:

operating the connecting circuitry to receive brain image data indicating activity at locations in the living brain;

operating the combination of one or more processors to extract information from the brain image data;

the act of operating the combination of one or more processors to extract information including;

obtaining one or more respective feature values indicating activity features of the active qualia map region.

13. The method of claim 12 in which the act of obtaining feature values includes:

obtaining active region data that indicate the active regions; and

for each of the active regions indicated by the active region data, performing a respective iteration, each active region'"'"'s iteration including;

obtaining the active region'"'"'s feature values.

14. The method of claim 13 which the active region data indicate two or more active regions, the respective iterations of the active regions being performed in a series;

after each preceding iteration in the series, a respective following iteration combining the feature values it obtains with a combined feature value data structure from the preceding iteration.