Methods of classifying cognitive states and traits and applications thereof

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.

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.

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.

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.

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.