Methods of classifying cognitive states and traits and applications thereof

• US 20110301431A1
• Filed: 06/05/2011
• Published: 12/08/2011
• Est. Priority Date: 06/05/2010
• Status: Abandoned Application

• Current Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford Management Co.)
• Original Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford Management Co.)
• Inventors: Greicius, Michael D., Menon, Vinod
• Application Number:
  US13/153,465
• Publication Number:
  US 20110301431A1
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: G01R 33/4806 Functional imaging of brain activation
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30016 Brain
• CPC Class Codes: G06T 7/0012 Biomedical image inspection

Abstract

The present invention provides for improved brain imaging and decoding methods that test subjects under authentic, natural conditions that allow for regular patterns of free-flowing thought and perception, as they occur in everyday life, while taking into account brain activities that were measured over spatially diverse regions of the whole-brain (whole-brain connectivity signatures). From such whole-brain connectivity signatures, specific cognitive traits and states are decoded and classified in a whole-brain connectivity analysis which takes into account the full pattern of brain activity. Such methods find applications in clinical diagnosis and monitoring of neuropsychiatric diseases and in nonclinical areas such as neuromarketing and neuroeconomics.

Claims

1. A method of classifying specific cognitive states in a subject, the method comprising

(a) obtaining whole-brain functional images from a subject during resting state (resting state matrix), before or after whole brain functional images were obtained from said subject during at least one state of task;

(b) obtaining whole-brain functional images from a subject during at least one state of task (task state matrix);

(c) defining regions of interest (ROIs) from said whole-brain functional images during resting state;

(d) creating a difference matrix by overlaying and subtracting said resting state matrix from said task state matrix;

(e) obtaining whole-brain connectivity markers through correlating said regions of interest;

(f) analyzing said whole-brain connectivity markers;

(g) physical transformation of said whole-brain connectivity markers into information for graphical display or output to a computer-readable medium, computer or computer network.

2. A method of diagnosing a neuropsychiatric disease in a subject using whole-brain connectivity signatures, the method comprising

(a) obtaining whole-brain functional images from a subject during resting state (resting state matrix),

(b) assessing connectivity between a set of regions of interest (ROIs) from said whole-brain functional images during resting state to obtain whole-brain connectivity markers from said subject;

(c) analyzing said whole-brain connectivity markers in said subject in comparison to whole-brain connectivity markers obtained from a group of healthy control subjects and a group of subjects suffering from a given neuropsychiatic disease for variations as a basis for diagnosing a neuropsychiatric disease;

(d) physical transformation of said whole-brain connectivity markers into information for graphical display or output to a computer-readable medium, computer or computer network.

3. The method of claim 2, wherein the neuropsychiatric disease is a neurodegenerative disease such as Alzheimer'"'"'s disease, Parkinson'"'"'s disease, Lewy body dementia, Huntington'"'"'s disease, a tauopathy, a serpinopathy, a prion disease, frontotemporal or vascular dementia.

4. The method of claim 2, wherein the neuropsychiatric disease is chronic pain, depression or anxiety.

5. A method of monitoring progression of a neuropsychiatric disease in a subject using whole-brain connectivity signatures, the method comprising, over a predetermined period of time and repeatedly,

(a) obtaining whole-brain functional images from a subject during resting state (resting state matrix).

(b) assessing connectivity between a set of regions of interest (ROIs) from said whole-brain functional images during resting state to obtain whole-brain connectivity markers from said subject;

(c) analyzing said whole-brain connectivity markers to monitor progression of a neuropsychiatric disease in said subject in comparison to whole-brain connectivity markers obtained from said subject at one or more earlier timepoints and optionally in comparison to whole-brain connectivity markers obtained from a group of healthy control subjects;

(d) physical transformation of said whole-brain connectivity markers into information for graphical display or output to a computer-readable medium, computer or computer network.

6. The method of claim 5, wherein the neuropsychiatric disease is a neurodegenerative disease such as Alzheimer'"'"'s disease, Parkinson'"'"'s disease, Lewy body dementia, Huntington'"'"'s disease, a tauopathy, a serpinopathy, a prion disease, frontotemporal or vascular dementia.

7. The method of claim 5, wherein the neuropsychiatric disease is chronic pain, depression or anxiety.

8. A method of monitoring treatment success of a neuropsychiatric disease in a subject using whole-brain connectivity signatures, the method comprising, over a predetermined period of time and repeatedly,

(a) obtaining whole-brain functional images from a subject during resting state (resting state matrix);

(b) assessing connectivity between a set of regions of interest (ROIs) from said whole-brain functional images during resting state to obtain whole-brain connectivity markers from said subject;

(c) analyzing said whole-brain connectivity markers to monitor treatment success of a neuropsychiatric disease in said subject in comparison to whole-brain connectivity markers obtained from said subject at one or more later timepoints following a treatment intervention and optionally in comparison to whole-brain connectivity markers obtained from a group of healthy control subjects;

(e) physical transformation of said whole-brain connectivity markers into information for graphical display or output to a computer-readable medium, computer or computer network.

9. The method of claim 8, wherein the neuropsychiatric disease is a neurodegenerative disease such as Alzheimer'"'"'s disease, Parkinson'"'"'s disease, Lewy body dementia, Huntington'"'"'s disease, a tauopathy, a serpinopathy, a prion disease, frontotemporal or vascular dementia.

10. The method of claim 8, wherein the neuropsychiatric disease is chronic pain, depression or anxiety.

11. A method of predicting consumer behavior by classifying specific cognitive states in a subject, the method comprising

(a) obtaining whole-brain functional images from a subject during resting state (resting state matrix), before or after whole-brain functional images were obtained from said subject during exposure to images of a commercial product;

(b) obtaining whole-brain functional images from a subject during exposure to images of a commercial product (product matrix);

(c) defining regions of interest (ROIs) from said whole-brain functional images during resting state;

(d) creating a difference matrix by overlaying and subtracting said resting state matrix from said product matrix;

(e) obtaining whole-brain connectivity markers through correlating said regions of interest;

(f) analyzing said whole-brain connectivity markers;

(g) physical transformation of said whole-brain connectivity markers into information for graphical display or output to a computer-readable medium, computer or computer network.

12. A method of predicting financial decision making by classifying specific cognitive states in a subject, the method comprising

(a) obtaining whole-brain functional images from a subject during resting state (resting state matrix), before or after whole-brain functional images were obtained from said subject during at least one state of financial decision making task (task state matrix;

(b) obtaining whole-brain functional images from a subject during at least one state of financial decision making task (task state matrix;

(c) defining regions of interest (ROIs) from said whole-brain functional images during resting state;

(d) creating a difference matrix by overlaying and subtracting said resting state matrix from said task state matrix;

(e) obtaining whole-brain connectivity markers through correlating said regions of interest;

(f) analyzing said whole-brain connectivity markers;

(g) physical transformation of said whole-brain connectivity markers into information for graphical display or output to a computer-readable medium, computer or computer network.