Methods for physiological monitoring, training, exercise and regulation   

This application is a continuation of patent application Ser. No. 11/270,064, filed Nov. 8, 2005, which is a continuation of Ser. No. 10/062,627 filed Jan. 30, 2002, and claims the benefit of U.S. Provisional Patent Application No. 60/265,204, filed Jan. 30, 2001; U.S. Provisional Patent Application No. 60/265,214, filed Jan. 30, 2001; and U.S. Provisional Patent Application No. 60/350,211, filed Nov. 2, 2001, each of which are incorporated herein in their entirety.

FIELD OF THE INVENTION

The present invention relates to methods, software and systems for monitoring physiological activity, particularly in the human brain and nervous system and therapeutic applications relating thereto.

A variety of different brain scanning methodologies have been developed that may be used to identify changes of mental states or conditions including Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT), electroencephalogram (EEG) based imaging, magnetoencephalogram (MEG) based imaging, and functional magnetic resonance imaging (fMRI).

For example, magnetic resonance imaging (MRI) has been used successfully to study blood flow in vivo. U.S. Pat. Nos. 4,983,917, 4,993,414, 5,195,524, 5,243,283, 5,281,916, and 5,227,725 provide examples of the techniques that have been employed. These patents are generally related to measuring blood flow with or without the use of a contrast bolus, some of these techniques referred to in the art as MRI angiography. Many such techniques are directed to measuring the signal from moving moieties (e.g., the signal from arterial blood water) in the vascular compartment, not from stationary tissue. Thus, images are based directly on water flowing in the arteries, for example. U.S. Pat. No. 5,184,074, describes a method for the presentation of MRI images to the physician during a scan, or to the subject undergoing MRI scanning.

In the brain, several researchers have studied perfusion by dynamic MR imaging using an intravenous bolus administration of a contrast agent in both humans and animal models (See, A. Villringer et al, Magn. Reson, Med., Vol. 6 (1988), pp 164-174; B. R. Rosen et al, Magn. Reson. Med., Vol. 14 (1999), pp. 249-265; J. W. Belliveau et al, Science, Vol. 254 (1990), page 716). These methods are based on the susceptibility induced signal losses upon the passage of the contrast agent through the microvasculature. Although these methods do not measure perfusion (or cerebral blood flow, CBF) in classical units, they allow for evaluation of the related variable rCBV (relative cerebral blood volume). For example, in U.S. Pat. No. 5,190,744 to Rocklage, quantitative detection of blood flow abnormalities is based on the rate, degree, duration, and magnitude of signal intensity loss which takes place for a region following MR contrast agent administration as measured in a rapid sequence of magnetic resonance images.

With the advent of these brain scanning methodologies, blood flow in various brain areas has been effectively correlated with various brain disorders such as Attention Deficit Disorder (ADD), Schizophrenia, Parkinson\'s Disease, Dementia, Alzheimers Disease, Endogenous Depression, Oppositional Defiant Disorder, Bipolar Disorder, memory loss, brain trauma, Epilepsy and others.

The prior art also describes a variety of inventions dating back to the 1960\'s have provided a way allowing subjects to learn to control muscle, autonomic or neural activity through processes. Examples and descriptions are included in U.S. Pat. No. 4,919,143. U.S. Pat. No. 4,919,143, U.S. Pat. No. 5,406,957, U.S. Pat. No. 5,899,867 and U.S. Pat. No. 6,097,981.

Considerable research has also been directed to biological feedback of brainwave signals known as electroencephalogram (EEG) signals. One conventional neurophysiological study established a functional relationship between behavior and bandwidths in the 12-15 Hz range relating to sensorimotor cortex rhythm EEG activity (SMR). Sterman, M. B., Lopresti, R. W., & Fairchild, M. D. (1969). Electroencephalographic and behavioral studies of monomethylhdrazine toxicity in the cat. Technical Report AMRL-TR-69 3, Wright-Patterson Air Force Base, Ohio, Air Systems Command. A cat\'s ability to maintain muscular calm, explosively execute precise, complex and coordinated sequences of movements and return to a state of calm was studied by monitoring a 14 cycle brainwave. The brainwave was determined to be directly responsible for the suppression of muscular tension and spasm. It was also demonstrated that the cats could be trained to increase the strength of specific brainwave patterns associated with suppression of muscular tension and spasm. Thereafter, when the cats were administered drugs which would induce spasms, the cats that were trained to strengthen their brainwaves were resistant to the drugs.

The 12-15 Hz SMR brainwave band has been used in EEG training for rectifying pathological brain underactivation. In particular the following disorders have been treated using this type of training: epilepsy (as exemplified in M. B. Sterman\'s, M. B. 1973 work on the “Neurophysiologic and Clinical Studies of Sensorimotor EEG Biofeedback Training: Some Effects on Epilepsy” L. Birk (Ed.), Biofeedback: Behavioral Medicine, New York: Grune and Stratton); Giles de la Tourette\'s syndrome and muscle tics (as exemplified in the inventor\'s 1986 work on “A Simple and a Complex Tic (Giles de la Tourette\'s Syndrome): Their response to EEG Sensorimotor Rhythm Biofeedback Training”, International Journal of Psychophysiology, 4, 91-97 (1986)); hyperactivity (described by M. N. Shouse, & J. F. Lubar\'s in the work entitled “Operant Conditioning of EEG Rhythms and Ritalin in the Treatment of Hyperkinesis”, Biofeedback and Self-Regulation, 4, 299-312 (1979); reading disorders (described by M. A. Tansey, & Bruner, R. L.\'s in “EMG and EEG Biofeedback Training in the Treatment of a 10-year old Hyperactive Boy with a Developmental Reading Disorder”, Biofeedback and Self-Regulation, 8, 25-37 (1983)); learning disabilities related to the finding of consistent patterns for amplitudes of various brainwaves (described in Lubaro, Bianchini, Calhoun, Lambert, Brody & Shabsin\'s work entitled “Spectral Analysis of EEG Differences Between Children with and without Learning Disabilities”, Journal of Learning Disabilities, 18, 403-408 (1985)) and; learning disabilities (described by M. A. Tansey in “Brainwave signatures—An Index Reflective of the Brain\'s Functional Neuroanatomy: Further Findings on the Effect of EEG Sensorimotor Rhythm Biofeedback Training on the Neurologic Precursors of Learning Disabilities”, International Journal of Psychophysiology, 3, 85-89 (1985)). In sum, a wide variety of disorders, whose symptomology includes impaired voluntary control of one\'s own muscles and a lowered cerebral threshold of overload under stress, were found to be treatable by “exercising” the supplementary and sensorimotor areas of the brain using EEG biofeedback.

U.S. Pat. No. 5,995,857 describes an apparatus and method for providing biofeedback of human central nervous system activity using radiation detection. In this patent, radiation from the brain resulting either from an ingested or injected radioactive material or radio frequency excitation or light from an external source impinging on the brain is measured by suitable means and is made available to the subject on which the measurement is being made for his voluntary control. The measurement may be metabolic products of brain activity or some quality of the blood, such as its oxygen content. The system described therein utilizes red and infrared light to illuminate the brain through the translucent skull and scalp.

SUMMARY

The present invention is directed to various methods relating to the use of behaviors performed by a subject and/or perceptions made by a subject that alter the activity of one or more brain regions of interest. It should be recognized that this alteration in activation may be a decrease or increase in activity at the different regions of interest.

One particular aspect of the invention relates to the use of behaviors performed by a subject and/or perceptions made by a subject that alter the activity of one or more regions of interest in combination with measuring the activation of the one or more regions of interest. Preferably, the measurement is performed in substantially real time relative to the behavior or perception. Activation metrics may be calculated based on the measured activity and used to monitor changes in activation.

Another particular aspect of the invention relates to the communication of information to a subject in combination with measuring the activation of the one or more regions of interest of the subject where the what, when, and/or how the information is communicated is determined, at least partially, based on the measured activity. Preferably, activity measurements are made continuously so that what, when, and/or how information is communicated to a subject in view of the activity measurements can be continuously determined. Examples of types of information that may be controlled in this manner include, but are not limited to instructions, stimuli, physiological measurement related information, and subject performance related information.

The present invention also relates to software that is designed to perform one or more operations employed in combination with the methods of the present invention. The various operations that are or may be performed by software will be understood by one of ordinary skill, in view of the teaching provided herein.

The present invention also relates to systems that may be used in combination with performing the various methods according to the present invention. These systems may include a brain activity measurement apparatus, such as a magnetic resonance imaging scanner, one or more processors and software according to the present invention. These systems may also include mechanisms for communicating information such as instructions, stimulus information, physiological measurement related information, and/or subject performance related information to the subject or an operator. Such communication mechanisms may include a display, preferably a display adapted to be viewable by the subject while brain activity measurements are being taken. The communication mechanisms may also include mechanisms for delivering audio, tactile, temperature, or proprioceptive information to the subject. In some instances, the systems further include a mechanism by which the subject may input information to the system, preferably while brain activity measurements are being taken.

In one embodiment, a method is provided for selecting how to achieve activation of one or more regions of interest of a subject, the method comprising: evaluating a set of behaviors that a subject separately performs regarding how well each of the behaviors in the set activate the one or more regions of interest; and selecting a subset of the behaviors from the set found to be effective in activating the one or more regions of interest. In one variation, evaluating the set of behaviors comprises calculating and comparing activation metrics computed for each behavior based on measured activities for the different behaviors. In one variation, the behaviors evaluated are overt behaviors involving a physical motion of the body of the subject. In another variation, the behaviors are covert behaviors only cognitive processes which do not lead to a physical motion of the body of the subject.

In another embodiment, a method is provided for selecting how to achieve activation of one or more regions of interest of a subject, the method comprising: evaluating a set of stimuli that a subject is separately exposed to regarding how well each of the different stimuli cause the subject to have a perception that activates the one or more regions of interest; and selecting a subset of the stimuli from the set found to be effective in causing activation of the one or more regions of interest. In one variation, evaluating the set of stimuli comprises calculating and comparing activation metrics computed for each stimuli based on measured activities for the different stimuli.

In another embodiment, a method is provided, the method comprising: evaluating a set of perceptions that a subject may have regarding how well each of the perceptions activate the one or more regions of interest; and selecting a subset of the perceptions from the set found to be effective causing activation of the one or more regions of interest. In one variation, evaluating the set of perceptions comprises calculating and comparing activation metrics computed for each stimuli based on measured activities for the different perceptions.

In another embodiment, computer executable logic is provided for selecting how to achieve activation of one or more regions of interest of a subject, the software comprising: logic for calculating activation metrics for activity measured for one or more regions of interest; and logic for comparing a set of calculated activation metrics and selecting a subset of the activation metrics having a superior activation of the one or more regions of interest.

In another embodiment, computer executable logic is provided for selecting how to achieve activation of one or more regions of interest of a subject, the software comprising: logic for calculating activation metrics for activity measured for one or more regions of interest during for a plurality of different behaviors; and logic for comparing the calculated activation metrics for the plurality of behaviors and selecting behaviors from the plurality based on the comparison of activation metrics.

In another embodiment, a method is provided for selecting a behavior for causing activation of one or more regions of interest of a subject, the method comprising: employing computer executable logic to select in substantially real time a next behavior for a subject to perform during training based, at least in part, on activity measurements made at or before the time the selection is made.

In another embodiment, a method is provided for directing behavior, the method comprising: employing computer executable logic to select in substantially real time a next behavior for a subject to perform during training based, at least in part, on activity measurements made at or before the time the selection is made.

In another embodiment, a method is provided for selecting a behavior for causing activation of one or more regions of interest of a subject, the method comprising: employing computer executable logic to select a next behavior for a subject to perform during training based, at least in part, on one or more behaviors previously used during training. In a variation, the selection is based on a combination of the one or more behaviors previously used during training and the activity measurements associated with the behaviors.

In another embodiment, a method is provided for selecting a behavior for causing activation of one or more regions of interest of a subject, the method comprising: employing computer executable logic to select a next behavior for a subject to perform during training based, at least in part, on measured activities of one or more regions of interest in response to the performance of one or more earlier behaviors. In a variation, the selection is based on a combination of the measured activity and the identity of the one or more earlier behaviors. It is noted that the computer executable logic may optionally compute activity metrics from the measured activity for the one or more earlier behaviors and base the selection on the activity metrics. Optionally, the computed activity metrics are based on a comparison with a rest state.

In another embodiment, a method is provided for selecting a stimulus for causing activation of one or more regions of interest of a subject, the method comprising: employing computer executable logic to select in substantially real time a next stimulus to communicate to a subject during training based, at least in part, on activity measurements made at the time the selection is made.

In another embodiment, a method is provided for selecting a stimulus for causing activation of one or more regions of interest of a subject, the method comprising: employing computer executable logic to select a next stimulus to communicate to a subject during training based, at least in part, on one or more stimuli previously communicated during training. In a variation, the selection is based on a combination of the one or more stimuli previously communicated and the activity measurements associated with the stimuli.

In another embodiment, a method is provided for selecting a stimulus for causing activation of one or more regions of interest of a subject, the method comprising: employing computer executable logic to select a next stimulus to communicate to a subject during training based, at least in part, on measured activities of one or more regions of interest in response to the communication of one or more earlier stimuli. In a variation, the selection is based on a combination of the measured activity and the identity of the one or more earlier stimuli. It is also noted that the computer executable logic may optionally compute activity metrics from the measured activity for the one or more earlier stimuli and base the selection on the activity metrics. Optionally, the computed activity metrics are based on a comparison with a rest state.

In regard to the above embodiments, it is noted that the next behavior or stimulus that is selected may be the same or different than the one or more earlier behaviors or stimuli.

In another embodiment, a computer assisted method is provided for guiding brain activity training comprising: measuring activity of one or more regions of interest of a subject; employing computer executable logic to select a behavior or stimulus for activating the one or more regions of interest based, at least in part, on the measured brain activity; and employing computer executable logic to communicate the selected behavior or stimulus to the subject. In one variation, the method further comprises communicating information to the subject regarding the measured brain activity.

In another embodiment, software is provided for guiding brain activity training, the software comprising: computer executable logic for selecting a behavior or stimulus for activating one or more regions of interest of a subject based, at least in part, on a measured brain activity; and logic for communicating the selected behavior or stimulus to the subject. In one variation, the software further comprises logic that communicates information to the subject regarding the measured brain activity.

In another embodiment, a computer assisted method is provided for guiding brain activity training comprising: having a subject perform a first behavior or be exposed to a first stimulus; measuring activity of one or more regions of interest of the subject in response to the first behavior or first stimulus; and employing computer executable logic to select a second behavior or a second stimulus for activating the one or more regions of interest based, at least in part, on the measured brain activity; and having the subject perform the second behavior or be exposed to the second stimulus. Optionally, the method further comprises employing computer executable logic to communicate to the subject the selected second behavior or second stimulus.

In another embodiment, a computer assisted method is provided for guiding brain activity training comprising: instructing a subject to perform a first behavior or communicating a first stimulus to the subject; measuring activity of one or more regions of interest of the subject in response to the first behavior or first stimulus; and employing computer executable logic to select a second behavior or a second stimulus for activating the one or more regions of interest based, at least in part, on the measured brain activity; and instructing the subject to perform the second behavior or communicating the second stimulus to the subject. Computer executable software is provided for guiding brain activity training, the software comprising: logic for communicating instructions to a subject to perform a first behavior and/or a first stimulus to the subject; logic for taking activity measurements of one or more regions of interest of the subject in response to the first behavior or first stimulus and selecting a second behavior or a second stimulus for activating the one or more regions of interest based, at least in part, on the measured brain activity; and logic for communicating instructions to the subject to perform the second behavior and/or the second stimulus to the subject.

In another embodiment, computer executable software is provided for guiding brain activity training, the software comprising: logic for measuring activity of one or more regions of interest of the subject in response to a first behavior or first stimulus; logic for selecting a second behavior or a second stimulus for activating the one or more regions of interest based, at least in part, on a measured brain activity; logic for communicating to the subject the selected second behavior or second stimulus.

In another embodiment, a method is provided for directing training of one or more regions of interest of a subject, the method comprising: continuously measuring activity in the one or more regions of interest of the subject; and employing computer executable logic to determine when to communicate information to the subject based, at least in part, on the measured activities. It is noted that the computer executable logic may optionally compute activity metrics from the measured activity and base the selection on the activity metrics. The computer executable logic may determine when to communicate information based on when the computed activity metric satisfies a predetermined condition, such as a target activity metric. It is noted that the information may be instructions, stimuli, physiological measurement related information, and/or subject performance related information. In one variation, the instructions are instructions to perform a behavior.

In another embodiment, a method is provided for directing training of one or more regions of interest of a subject, the method comprising: measuring activity in the one or more regions of interest of the subject; determining one or more activity metrics for the measured activity; determining when the one or more activity metrics satisfy a predetermined condition; and communicating information to the subject; wherein these steps are repeatedly performed in substantially real time.

In another embodiment, software is provided for directing training of one or more regions of interest of a subject, the software comprising: logic for taking measurements of activity of the one or more regions of interest of the subject and determining one or more activity metrics for the measured activity; logic for determining when the one or more activity metrics satisfy a predetermined condition; and logic for causing information to be communicated to the subject; wherein the software is able to determine the activity metrics from the activity measurements and cause information to be communicated in substantially real time.

In another embodiment, a method is provided for directing training, the method comprising: measuring activities of one or more regions of interest; determining when the measured activities have reached a desired state; and communicating information to a subject regarding when to perform a next behavior when the measured activities have reached the desired state.

In another embodiment, a method is provided for directing training, the method comprising: measuring activities of one or more regions of interest; determining when the measured activities have reached a desired state; and communicating a stimulus to a subject when the measured activities have reached the desired state.

In another embodiment, computer executable software is provided, the software comprising: logic for taking activities of one or more regions of interest and determining when the measured activities have reached a desired state; and logic for causing information to be communicated to a subject regarding when to perform a next behavior when the measured activities have reached the desired state.

In another embodiment, computer executable software is provided, the software comprising: logic for taking measuring activities of one or more regions of interest and determining when the measured activities have reached a desired state; and logic for causing a stimulus to be communicated to a subject when the measured activities have reached the desired state.

In another embodiment, a method is provided for directing training of one or more regions of interest of a subject, the method comprising: measuring activity in the one or more regions of interest of the subject; determining one or more activity metrics for the measured activity; determining when the one or more activity metrics satisfy a predetermined condition; and communicating a performance reward to the subject; wherein these steps are repeatedly performed in substantially real time. In one variation, the activity metrics measure a similarity between the spatial pattern of activity within the region of interest and a target spatial pattern of activity.

In another embodiment, software is provided for directing training of one or more regions of interest of a subject, the software comprising: logic for taking measurements of activity of the one or more regions of interest of the subject and determining one or more activity metrics for the measured activity; logic for determining when the one or more activity metrics satisfy a predetermined condition; and logic for causing a performance reward to be communicated to the subject; wherein the software is able to determine the activity metrics from the activity measurements and cause information to be communicated in substantially real time.

In another embodiment, a method is provided for directing training of one or more regions of interest of a subject, the method comprising: measuring activity in the one or more regions of interest of the subject; determining what information is to be communicated to the subject based, at least in part, on the measured activity; wherein these steps are repeatedly performed in substantially real time. In one variation, the communicated information is a representation of the measured activity. In another variation, the communicated information is an instruction to the subject.

In another embodiment, a method is provided for directing training of one or more regions of interest of a subject, the method comprising: measuring activity in the one or more regions of interest of the subject; determining one or more activity metrics for the measured activity; determining when the one or more activity metrics satisfy a predetermined condition; and selecting information to be communicated to the subject based on the satisfaction of the predetermined condition. In a preferred embodiment, these steps are continuously performed. In one variation, the communicated information is a representation of the measured activity. In another variation, the communicated information is an instruction to the subject.

In another embodiment, software is provided for directing training of one or more regions of interest of a subject, the software comprising: logic taking measurements of activity of the one or more regions of interest of the subject and determining what information is to be communicated to the subject based, at least in part, on the measured activity; wherein the software is capable of taking the measurements of activity and determining what information is to be communicated in substantially real time. In one variation, the communicated information is a representation of the measured activity. In another variation, the communicated information is an instruction to the subject.

In another embodiment, software is provided for directing training of one or more regions of interest of a subject, the software comprising: logic taking measurements of activity of the one or more regions of interest of the subject and determining one or more activity metrics for the measured activity; logic for determining when the one or more activity metrics satisfy a predetermined condition; and logic for selecting information to be communicated to the subject based on the satisfaction of the predetermined condition. In a preferred embodiment, the software is capable of taking the measurements of activity and selecting the information to be communicated in substantially real time.

In another embodiment, a computer assisted method is provided for guiding brain activity training comprising: measuring activity of one or more regions of interest of a subject; employing computer executable software to determine information to communicate to the subject based, at least in part, on the measured brain activity; and employing computer executable software to communicate the information to the subject.

In another embodiment, a computer assisted method is provided for guiding brain activity training, the method comprising: measuring activity of one or more regions of interest of a subject; employing computer executable software to determine instructions based, at least in part, on the measured brain activity; and employing computer executable software to communicate the instructions to the subject. In one variation, measuring activity comprises recording activity data from a scanner, converting the recorded activity data to image data, and preprocessing the image data; and communicating the information comprises displaying images derived from the preprocessing image data.

In another embodiment, a method is provided for directing training of one or more regions of interest of a subject, the method comprising: measuring activity in the one or more regions of interest of the subject; determining how to communicate information to the subject based, at least in part, on the measured activity; wherein these steps are repeatedly performed in substantially real time.

In another embodiment, software is provided for directing training of one or more regions of interest of a subject, the software comprising: logic taking measurements of activity of the one or more regions of interest of the subject and determining how information is to be communicated to the subject based, at least in part, on the measured activity; wherein the software is capable of taking the measurements of activity and determining how information is to be communicated in substantially real time.

In another embodiment, a method is provided for selectively activating one or more regions of interest, the method comprising: (a) communicating one or more stimuli to a subject and/or having the subject perform one or more behaviors that are directed toward activating the one or more regions of interest without measuring activation of the one or more regions of interest; and (b) communicating the same one or more stimuli to the subject and/or having the subject perform the same behaviors as in step (a) in combination with measuring brain activity in the one or more regions of interest as the subject is exposed to stimuli and/or performs the behaviors. In one variation, information is displayed to the subject in step (a) that simulates the information that is displayed to the subject during step (b).

In another embodiment, software is provided for use in training, the software comprising logic for communicating information to guide a subject in the performance of a training exercise during which activation is not measured; and logic for communicating information to guide a subject in the performance of a training exercise during which activation of one or more regions of interest is measured; wherein information is displayed to the subject when activity is not measured that simulates activity measurements that are displayed when activity is measured.

In another embodiment, a method is provided for selectively activating one or more regions of interest, the method comprising: communicating information to a subject that instructs a subject to perform a sequence of behaviors or have a series of perceptions that are adapted to cause the selective activation of one or more regions of interest.

In another embodiment, a method is provided for selectively activating one or more regions of interest, the method comprising: identifying information that instructs a subject to perform a sequence of behaviors or have a series of perceptions that selectively causes activation of one or more brain regions in a subject; communicating the identified information to a same or different subject; and measuring activation of one or more regions of interest in response to the communicated information.

In another embodiment, software is provided for use in training, the software comprising logic for communicating information to guide a subject in the performance of a training exercise during which activation of one or more regions of interest is not measured, the logic displaying information that simulates activity measurements of the one or more regions of interest.

In another embodiment, software and information is provided for use in training, the software comprising logic for communicating information to guide a subject in the performance of a training exercise during which activation is not measured, and the information comprising stimuli, instructions, and/or measured information having been determined based in part upon activity in a region of interest during a training period when activity was measured and communicated to the same or a different subject in substantially real time.

In another embodiment, a method is provided for selecting how to achieve activation of one or more regions of interest, the method comprising: (a) having a subject perform a set of behaviors; (b) measuring how well each of the behaviors in the set activate the one or more regions of interest; (c) selecting a subset of the behaviors from the set found to be effective in activating the one or more regions of interest; and (d) after step (c) and in the absence of measuring activation, determining what information to communicate to the same or a different subject based, at least in part, on the activity measurements of step (b). In one variation, evaluating the set of behaviors comprises calculating and comparing activation metrics computed for each behavior based on measured activities for the different behaviors. In another variation, the behaviors evaluated are overt behaviors involving a physical motion of the body of the subject. In another variation, the behaviors are covert behaviors only cognitive processes which do not lead to a physical motion of the body of the subject. In the case when the subject in step (a) is different than the subject in step (d), the subject in step (d) may have a commonality with the subject of step (a) in relation to the one or more regions of interest upon which the behaviors were selected.

In another embodiment, computer executable logic is provided for selecting how to achieve activation during training of one or more regions of interest of a subject, the software comprising: logic for calculating activation metrics for activity measured for one or more regions of interest in a first subject; logic for comparing a set of calculated activation metrics and selecting a subset of the activation metrics having a superior activation of the one or more regions of interest in that first subject; logic that takes the measured brain from the first subject and determines for a second subject one or more members of the group consisting of: a) what next stimulus to communicate to the second subject, b) what next behavior to instruct the second subject to perform, c) when the second subject is to be exposed to a next stimulus, d) when the second subject is to perform a next behavior, e) one or more activity metrics computed from the measured activity in the first subject, f) a spatial pattern computed from the measured activity in the first subject, g) a location of a region of interest computed from the measured activity of the first subject, h) performance targets that the second subject is to achieve computed from the measured activity in the first subject, i) a performance measure the second subject\'s success computed from the measured activity in the first subject; and logic for communicating information based on the determinations to the second subject. In one variation, the information communicated to the second subject is communicated during a process of training. In another variation, the information communicated to the second subject is a set of instructions and/or stimuli to be used by the second subject in performing training trials. In another variation, the information communicated to the second subject is a set of instructions and/or stimuli to be used by the second subject in performing training trials for the activation of a brain region of interest in the second subject.

In another embodiment, computer executable logic is provided for selecting how to achieve activation during training of one or more regions of interest of a subject, the software comprising: logic for calculating activation metrics for activity measured for one or more regions of interest during each of several behaviors in a first subject; logic for comparing a set of calculated activation metrics corresponding to the set of behaviors and selecting a subset of the activation metrics and their corresponding behaviors having a superior activation of the one or more regions of interest in that first subject; logic that takes the measured brain activity from the first subject and determines information to communicate to a second subject; and logic for communicating the determined information to the second subject. In one variation, the logic communicates the determined information to the first subject in substantially real time relative to when the activity is measured.

In another embodiment, a method is provided for selecting how to achieve activation during training of one or more regions of interest of a subject, the method comprising: calculating activation metrics for activity measured for one or more regions of interest during each of several behaviors in a first subject; and comparing a set of calculated activation metrics corresponding to the set of behaviors and selecting a first subset of the activation metrics and their corresponding behaviors having a superior activation of the one or more regions of interest in that first subject; at a later time: (a) having a second subject perform a behavior adapted to selectively activate one or more regions of interest in the first subject; and (b) optionally communicating information to the second subject based on the measured brain activity in the first subject; wherein steps (a)-(b) are repeated multiple times, the second subject using the communicated information to guide the second subject in the subsequent performance of the behavior. In one variation, computer executable logic is employed to select the information communicated to the subject. In another variation, computer executable logic is employed to cause the information to be communicated to the second subject. In one variation, the first subject and the second subject are the same subject. In another variation, the first subject and the second subject are different subjects. In the case when the first and the second subject are different subjects, the second subject may additionally have been selected based upon having a condition likely to benefit from similar training as that received by first subject.

In another embodiment, a computer assisted method is provided for guiding brain activity training comprising: measuring activity of one or more internal voxels of a brain; employing computer executable logic that takes the measured brain activity and determines one or more members of the group consisting of: a) what next stimulus to communicate to the subject, b) what next behavior to instruct the subject to perform, c) when a subject is to be exposed to a next stimulus, d) when the subject is to perform a next behavior, e) one or more activity metrics computed from the measured activity, f) a spatial pattern computed from the measured activity, g) a location of a region of interest computed from the measured activity, h) performance targets that a subject is to achieve computed from the measured activity, i) a performance measure of a subject\'s success computed from the measured activity, j) a subject\'s position relative to an activity measurement instrument; and communicating information based on the determinations to the subject in substantially real time relative to when the activity is measured.

Computer executable software for guiding brain activity training is also provided that comprises: logic which takes data corresponding to activity measurements of one or more internal voxels of a brain and determines one or more members of the group consisting of: a) what next stimulus to communicate to the subject, b) what next behavior to instruct the subject to perform, c) when a subject is to be exposed to a next stimulus, d) when the subject is to perform a next behavior, e) one or more activity metrics computed from the measured activity, f) a spatial pattern computed from the measured activity, g) a location of a region of interest computed from the measured activity, h) performance targets that a subject is to achieve computed from the measured activity, i) a performance measure of a subject\'s success computed from the measured activity, j) a subject\'s position relative to an activity measurement instrument; and logic for communicating information based on the determinations to the subject in substantially real time relative to when the activity is measured.

Computer executable software is also provided for guiding brain activity training that comprises logic which takes a measurement of brain activity in one or more regions of interest of a subject while the subject has one or more perceptions and/or performs one or more behaviors that are directed toward activating the one or more regions of interest and determines one or more members of the group consisting of a) what next stimulus to expose the subject to, b) what next behavior to have the subject perform, c) what information to communicate to the subject, d) when a subject is exposed to the next stimulus, e) when the subject is to perform the next behavior, f) when new information is to be communicated to the subject, g) how a subject is exposed to the next stimulus, h) how the subject is to perform the next behavior, and i) how new information is to be communicated to the subject. In one variation, the software performs the determinations in substantially real time relative to when the brain activity measurement is taken. In another variation, the determined information is communicated to the subject.

In another embodiment, a method for guiding brain activity training is provided that comprises: having a subject perform a behavior or be exposed to a stimulus; measuring activity of the one or more regions of interest as the behavior is performed or the subject is exposed to the stimulus; and communicating information to the subject based on the measured brain activity in substantially real time relative to when the behavior is performed or the subject is exposed to the stimulus.

In another embodiment, computer executable software is provided for guiding brain activity training, the software comprising: logic for instructing a subject to perform a behavior; logic for taking activity measurements of one or more regions of interest as the behavior is performed and communicating information to the subject based on the measured brain activity in substantially real time relative to when the behavior is performed.

In another embodiment, a method is provided for guiding brain activity training, the method comprising: (a) having a subject perform a behavior adapted to selectively activate one or more regions of interest; (b) measuring activity of the one or more regions of interest as the behavior is performed; and (c) communicating information to the subject based on the measured brain activity in substantially real time relative to when the behavior is performed; wherein steps (a)-(c) are repeated multiple times, the subject using the communicated information to guide the subject in the subsequent performance of the behavior. In one variation, computer executable logic is employed to select the information communicated to the subject. In another variation, computer executable logic is employed to cause the information to be communicated to the subject.

In another embodiment, computer executable software is provided for guiding brain activity training, the software comprising: logic for taking activity measurements of one or more regions of interest as a behavior is performed; and logic for communicating information to the subject based on the measured brain activity in substantially real time relative to when the behavior is performed; wherein the logic takes new activity measurements as they are received and communicates new information based on the new activity measurements. In one variation, the software is able to take the activity measurements and cause the information to be communicated in substantially real time. In another variation, the software further includes logic for selecting what information is to be communicated.

In another embodiment, a method is provided for diagnosing a condition of a subject associated with particular activation in one or more regions of interest, the method comprising: having the subject perform a behavior or have a perception adapted to selectively activate one or more regions of interest associated with the condition; measuring activity of the one or more regions of interest as the behavior is performed or the subject has the perception; and diagnosing a condition associated with the one or more regions of interest based on the activity in response to the behavior or perception.

In another embodiment, a computer assisted method is provided for diagnosing a condition of a subject associated with particular activation in one or more regions of interest, the method comprising: having computer executable logic cause instructions to perform a behavior and/or a stimulus be communicated to the subject, the behavior and/or stimulus being adapted to selectively activate one or more regions of interest associated with the condition; having computer executable logic take activity measurements of the one or more regions of interest in response to the behavior and/or stimulus and diagnose whether the condition is present based on the activity response to the behavior and/or stimulus.

In another embodiment, a method is provided for designing a treatment for a condition of a subject, the method comprising: identifying a behavior or stimulus adapted to selectively activate one or more regions of interest associated with a condition to be treated; having the subject perform the selected behavior or exposing the subject to the selected stimulus; measuring activity of the one or more regions of interest as the behavior is performed or the subject is exposed to the stimulus in order to evaluate the effectiveness of the treatment. In one variation, the method further comprises identifying the one or more regions of interest of a subject associated with the condition to be treated.

In another embodiment, computer executable software is provided for designing a treatment for a condition of a subject, the software comprising: logic for identifying a behavior or stimulus adapted to selectively activate one or more regions of interest associated with a condition to be treated; logic for instructing the subject to perform the selected behavior and/or communicating the selected stimulus to the subject; and logic for taking activity measurements of the one or more regions of interest as the behavior is performed or the subject is exposed to the stimulus and evaluating the effectiveness of the treatment. In one variation, the software further comprises logic for identifying the one or more regions of interest of a subject associated with the condition to be treated.

In another embodiment, a method is provided for treating one or more regions of interest of a brain of a subject, the method comprising: having a subject perform a behavior or have a perception adapted to activate one or more regions of interest where the resulting activity of the one or more regions of interest is measured as the behavior is performed or the subject is exposed to the stimulus. In one variation, information selected from the group consisting of instructions, stimuli, physiological measurement related information, and subject performance related information is communicated to the subject as the behavior is performed or the perceptions are being made.

In another variation, information selected from the group consisting of instructions, stimuli, physiological measurement related information, and subject performance related information is communicated to the subject as the behavior is performed or the perceptions are being made, the information communicated to the subject is selected based, at least in part, on the measured activity. In one variation, the one or more regions of interest selected are implicated in the etiology of a condition that the subject has. In another variation, the one or more regions of interest selected are related to a disease state. In another variation, the one or more regions of interest selected have an abnormality related to a disease state. In another variation, the one or more regions of interest are adjacent to a region of the brain that has been injured.

In another variation, a method is provided for selecting a brain region of interest, the method comprising: having a subject perform a behavior or have a perception adapted to activate one or more localized regions of the brain; measuring activity of the localized regions of the brain of the subject as the behavior is performed or the perception is made; and identifying one or more localized regions of the brain of the subject whose activation changes in response to the behavior or perception. In one variation, the method further comprises storing a location of the identified one or more regions of interest to memory. In one variation, identifying the one or more localized regions of the brain is performed less than 10, 5, 1, 0.1 minutes after the behavior is performed or the perception is had.

In another variation, computer executable software is provided for selecting a brain region of interest, the software comprising: logic for instructing a subject perform a behavior adapted to activate one or more localized regions of the brain; logic for taking activity measurements of the regions of interest of the subject as the behavior is performed and identifying one or more regions of interest of the subject whose activation changes in response to the behavior or perception. In one variation, the software further comprises logic for selecting coordinates corresponding to the identified one or more regions of interest. In another variation, the software further comprises logic for selecting coordinates corresponding to the identified one or more regions of interest and storing the selected coordinates to memory.

In another embodiment, a method is provided for selecting a brain region of interest, the method comprising: having a subject perform a behavior or have a perception; measuring activity of the regions of interest of the subject as the behavior is performed or the perception is made; and identifying one or more regions of interest of the subject whose activation changes in response to the behavior or perception.

In another embodiment, a computer assisted method is provided for evaluating an effectiveness of brain activity training comprising: selecting a target level of activation for one or more regions of interest of a subject; having the subject perform a behavior or have a perception; measuring activity of one or more regions of interest of a subject; employing computer executable software to compare the measured activity to the target level of activity. In one variation, the target level of activity is communicated to the subject. In another variation, the target level of activity is displayed to the subject as the subject performs the behavior or has the perception. In yet another variation, the comparison between the measured activity and the target level of activity is communicated to the subject. In yet another variation, the comparison between the measured activity and the target level of activity is displayed to the subject. In yet another variation, the computer executable software selects information to be communicated to the subject based on the comparison between the measured and target levels of activity. In yet another variation, the software selects instructions to be communicated to the subject based on the comparison between the measured and target levels of activity. In yet another variation, the software selects a behavior to be performed or a stimulus to expose the subject to based on the comparison between the measured and target levels of activity. In yet another variation, comparing comprises computing one or more members of the group consisting of a vector difference, a vector distance, and a dot product between two vectorized spatial patterns of physiological activity.

In another embodiment, computer executable software is provided for evaluating an effectiveness of brain activity training, the software comprising: logic for selecting a target level of activation for one or more regions of interest of a subject; logic for communicating instructions to the subject to perform a behavior and/or communicate a stimulus to the subject; logic for taking activity measurements of one or more regions of interest of a subject and comparing the measured activity to the target level of activity. In one variation, the software comprises logic for communicating the target level of activity to the subject. In another variation, the software comprises logic for causing the target level of activity to be displayed to the subject as the subject performs the behavior or as the stimulus is communicated. In yet another variation, the software comprises logic that communicates the comparison between the measured activity and the target level of activity to the subject. In yet another variation, the software comprises logic for displaying the comparison between the measured activity and the target level of activity to the subject. In yet another variation, the software comprises logic for selecting information to be communicated to the subject based on the comparison between the measured and target levels of activity. In yet another variation, the software comprises logic for selecting instructions to be communicated to the subject based on the comparison between the measured and target levels of activity. In yet another variation, the software comprises logic for selecting a behavior to be performed or a stimulus to communicate to the subject based on the comparison between the measured and target levels of activity. In yet another variation, the logic for comparing comprises logic for computing one or more members of the group consisting of a vector difference, a vector distance, and a dot product between two vectorized spatial patterns of physiological activity.

In another embodiment, a training method is provided that comprises: having a subject perform a behavior or be exposed to a stimulus; measuring activity of the one or more regions of interest as the behavior is performed or the subject is exposed to the stimulus; and having the subject estimate the measured activity. In one variation, no behavior or stimulus may be used. In another variation, the behavior used is the cognitive process of forming an estimate of measured activity. In one variation, the method further comprises communicating information to the subject regarding how well the subject estimated the measured activity. In another variation, the subject inputs his or her estimate into a system. In another variation, the method further comprises recording to memory how well the subject estimated the measured activity. In another variation, an activity metric is calculated based on the measured activity and the subject estimates the activity metric. It is noted that the subject\'s estimate of the measured activity can be a qualitative estimate (e.g., higher than a value, lower than a value) or quantitative (e.g., a numerical estimate).

In another embodiment, computer executable software is provided that comprises: logic for taking activity measurements for one or more regions of interest; and logic for receiving a subject\'s estimate of activation of one or more regions of interest in response to a behavior or perception and comparing that estimate to the measured activation for one or more regions of interest. In one variation, the software further comprises logic for creating a displayable image illustrating the comparison of the subject\'s estimate. In another variation, the software further comprises logic for communicating information to the subject regarding how well the subject estimated the measured activation. In another variation, the logic stores the estimate and activation measurements to memory. In another variation, the logic calculates an activity metric based on the measured activation. In another variation, the subject\'s estimate is an estimated activity metric and the logic compares an activity metric based on the measured activation to the subject\'s estimated activity metric. It is noted that the subject\'s estimate of the measured activity can be a qualitative estimate (e.g., higher than a value, lower than a value) or quantitative (e.g., a numerical estimate).

Also according to any of the above embodiments, the behavior may optionally be selected from the group consisting of sensory perceptions, detection or discrimination, motor activities, cognitive processes, emotional tasks, and verbal tasks.

Also according to any of the above embodiments, the methods are optionally performed with the measurement apparatus remaining about the subject during the method.

According to any of the above embodiments, in one variation, measuring activation is performed by fMRI.

According to any of the above embodiments, in one variation, the activity measurements are made using an apparatus capable of taking measurements from one or more internal voxels without substantial contamination of the measurements by activity from regions intervening between the internal voxels being measured and where the measurement apparatus collects the data.

Also according to any of the above embodiments, pretraining is optionally performed as part of the method.

Also according to any of the above embodiments, in one variation, at least one of the regions of interest is an internal region of the brain.

Also according to any of the above embodiments, in one variation, the one or more localized regions are all internal relative to a surface of the brain.

Also according to any of the above embodiments, in one variation, the one or more regions of interest comprise a voxel.

Also according to any of the above embodiments, in one variation, the one or more regions of interest comprise a plurality of different voxels.

According to any of the above embodiments, in one variation, the one or voxels measured has a two dimensional area. The two dimensional area optionally has a diameter of 50, 30, 20, 15, 10, 5, 4, 3, 2, 1, 0.5, 0.1 mm or less.

According to any of the above embodiments, in one variation, the one or more voxels measured has a three dimensional volume. The three dimensional volume optionally has a volume of 22×22×12 cm, 11×11×6 cm, 6×6×6 cm, 3×3×3 cm, 1×1×1 cm, 0.5×0.5×0.5 cm, 1×1×1 mm, 100×100×100 microns or less.

Also according to any of the above embodiments, in one variation, measurements are made from at least 100 separate internal voxels, and these measurements are made at a rate of at least once every five seconds.

Also according to any of the above embodiments, in one variation, measurements are made from a set of separate internal voxels corresponding to a scan volume including the entire brain.

According to any of the above embodiments, the one or more regions of interest optionally include one or members of the group consisting of neuromodulatory centers or plasticity centers.

Also according to any of the above embodiments, the methods may be performed in combination with the administration of an agent for enhancing measurement sensitivity of the one or more regions of interest. For example, in one variation, the method is performed in combination with the administration of a fMRI contrast agent.

In another variation, the method is performed in combination with the administration of an agent that enhances activity in the one or more regions of interest.

According to any of the above embodiments, measuring brain activity is optionally performed continuously as the subject performs a behavior, has a perception and/or is exposed to a stimulus. For example, measuring brain activity is optionally performed at least every 10, 5, 4, 3, 2, or 1, 0.1, 0.01 seconds or less as the subject performs a behavior, has a perception and/or is exposed to a stimulus.

According to any of the above embodiments, the subjects performs one or more behaviors during measurement that constitute training to activate one or more brain region of interest.

According to any of the above embodiments, the method is used to guide brain activity training by instructing a subject to modulate a brain region of interest.

According to any of the above embodiments, an action is performed in response to a brain activity measurement in substantially real time. For example, an action is optionally performed in response to a brain activity measurement at least every 10, 5, 4, 3, 2, or 1, 0.1, 0.01 seconds or less.

Also according to any of the above embodiments, the behavior is optionally a cognitive task the subject is to perform based on an image displayed to the subject.

Also according to any of the above embodiments, in one variation, communicating information to the subject (for example: instructions, stimuli, physiological measurement related information, and subject performance related information) is performed by one or more of the members selected from the group consisting of providing audio to the subject, providing a smell to the subject, displaying an image to the subject.

Also according to any of the above embodiments, a desired activity metric to be achieved optionally is determined and/or communicated.

Also according to any of the above embodiments, whether a desired activity metric is achieved optionally is determined and/or communicated.

Also according to any of the above embodiments, an activity metric is optionally determined and/or communicated from measured activity. In one variation, the activity metric is modified relative to a baseline level of activation. In another variation, the activity metric is normalized relative to a baseline level of activation. In another variation, a comparison between an activity metric and a reference activity metric is performed.

Also according to any of the above embodiments, a measured activity metric may optionally be determined and/or communicated. In one variation, the activity metric is modified relative to a baseline level of activation. In another variation, the activity metric is normalized relative to a baseline level of activation. In another variation, a comparison between an activity metric and a reference activity metric is performed.

Also according to any of the above embodiments, a measured activation image or volume may optionally be determined and/or communicated. In one variation, the activation image or volume is modified relative to a baseline level of activation. In another variation, the activation image or volume is normalized relative to a baseline level of activation. In another variation, a comparison between an activation image or volume and a reference activation image or volume is performed.

Also according to any of the above embodiments, in one variation, the subject performs a behavior, has a perception and/or is exposed to a stimulus repeatedly for a period of at least 1, 5, 10, 20, 30, 60 or more minutes.

Also according to any of the above embodiments, in one variation, the subject performs a behavior, has a perception and/or is exposed to a stimulus repeatedly at least 2, 3, 4, 5, 10, 20, 100 or more minutes.

Also according to any of the above embodiments, in one variation, activity measurements are recorded to memory during the method. Optionally, activity measurements and the behaviors and/or stimuli used are recorded to memory during the method. Optionally, any information communicated to the subject is also recorded to memory.

Also according to any of the above embodiments, in one variation, activity measurements may be communicated to a remote location. Optionally, activity measurements and the behaviors and/or stimuli used communicated to a remote location during the method. Optionally, any information communicated to the subject is also communicated to a remote location. In one example, this communication to a remote location takes place via internet communication. In another example, this communication to a remote location takes place via wireless communication.

According to any of the above embodiments where information is communicated, in one variation, the information is communicated by a manner selected from the group consisting of providing audio to the subject, providing tactile stimuli to the subject, providing a smell to the subject, displaying an image to the subject.

According to any of the above embodiments wherein information is determined, in one variation, the information is determined while the instrument used for measurement remains positioned about the subject.

Also according to any of the above embodiments wherein information is communicated, in one variation, the information communicated is an instruction to the subject.

Also according to any of the above embodiments wherein information is communicated, in one variation, the instruction is a text or iconic indication denoting an action that a subject is to perform.

Also according to any of the above embodiments wherein information is communicated, in one variation, the instruction identifies a task to be performed by the subject.

Also according to any of the above embodiments wherein information is communicated, in one variation, some of the information communicated to the subject is material to be learned.

Also according to any of the above embodiments wherein an instruction is determined, in one variation, the instruction is determined by computer executable logic.

Also according to any of the above embodiments wherein an instruction is communicated, in one variation, the instruction communicated is selected from a set of instructions stored in memory, the selection being based upon the brain activity measured.

Also according to any of the above embodiments, the subject may optionally input information to the system while brain activity measurements are being taken or while the subject is in a position where brain activity measurements may be taken.

Also according to any of the above embodiments, in one variation, the method further comprises selecting one or more of the internal voxels to correspond to a region of interest for a particular subject and using the selected internal voxels of the region of interest to make the one or more determinations.

Also according to any of the above embodiments, in one variation, the region of interest is selected from the group consisting of one of the regions listed in FIG. 14, including the substantia nigra, subthalamic nucleus, nucleus accumbens, locus coeruleus, periaqueductal gray matter, nucleus raphe dorsalis, nucleus basalis of Meynert, dorsolateral pre-frontal cortex.

Also according to any of the above embodiments, in one variation, the region of interest has a primary function of releasing a neuromodulatory substance, where the neuromodulatory substance is selected from the group consisting of: dopamine, acetyl choline, noradrenaline, serotonin, an endogenous opiate.

Also according to any of the above embodiments, in one variation, the subject has one or more of the following conditions: Parkinson\'s disease, Alzheimer\'s disease, attention & attention deficit disorder, depression, substance abuse & addiction, schizophrenia.

These and other embodiments and variations of the methods, software and systems of the present invention are described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an overview diagram of methods, components and processes of this invention.

FIG. 2 is a table of brain regions.

FIG. 3 is a table of neurological, psychological and other conditions.

FIG. 4 is a diagram of methods and apparatus for displaying information to a subject in a measurement apparatus.

FIG. 5 is a table of functional MRI scanning parameters.

FIG. 6 is an example display screen that may be presented.

FIG. 7 is an example of a display screen that may be used for localizing a region of interest.

FIG. 8 shows examples of display panels that may be presented.

FIG. 9 shows further examples of display panels that may be presented.

FIG. 10 shows an example time progression of displays on an ROI panel, and the structure of an example trial.

FIG. 11 shows examples of display panels that may be presented.

FIG. 12 shows further examples display panels that may be presented.

FIG. 13 shows a diagram of an apparatus for stabilizing the head of a subject, which may be particularly suited for use in early and experimental implementations of the device when free head-movement technology is not available.

FIG. 14 shows a table of brain regions that may be used as regions of interest.

Activity, as used herein, refers to physiological activity associated with one or more voxels of the brain whose physiological activity may be monitored. Examples of types of physiological activity include, but are not limited to, neuronal activity, blood flow, blood oxygenation, electrical activity, chemical activity, tissue perfusion, the level of a nutrient or trophic factor, the production or distribution of a trophic factor, the production, release, or reuptake of a neurotransmitter or neuromodulator, the growth of tissue such as neurons or parts of neurons, neural plasticity, and other physiological processes. Other examples are provided herein.

Activation, as used herein, refers to a change in activity in one or more voxels of the brain whose physiological activity may be monitored. This change may include an increase or decrease. It is noted that this change may also include a change where some voxels increase in activation at the same time that other voxels decrease in activation.

Activity metric, as used herein, refers to any computed measure of activity of one or more regions of interest of the brain.

Altering activity, as used herein, refers to an alteration in activity levels in one or more regions of interest of the brain. It is noted that altering activity can be an increase and/or a decrease in activation. When a plurality of voxels of the brain are involved, all or only some may have increased activity and all or only some may have decreased activity. It should be recognized that some voxels may have increased activity while other voxels have decreased activity.

Anti-nociceptive regions, as used herein, refers to areas of the brain which, when active, may produce a decrease or modulation in the sensation of experienced severity of pain.

Behavioral training, as used herein, refers to training a subject to generate an overt action in response to a form of information that is communicated to the subject. It is noted that behavioral training may take place in combination with training a subject to alter activity in one or more regions of interest.

Behavior, as used herein, refers to a physical or mental task or exercise engaged in by a subject, which may be in order to activate one or more regions of interest of the brain. Examples of different types of behaviors include, but are not limited to sensory perception, detection or discrimination, motor activities, cognitive processes such as mental imagery or mental manipulation of an imagined object, reading, emotional tasks such as attempting to create a particular affect or mood, verbal tasks such as listening to, comprehending, or producing speech. Other examples of behaviors are provided herein.

BOLD, as used herein refers to Blood Oxygen Level Dependent signal. This signal is typically measured using a functional magnetic resonance imaging device.

Condition, as used herein, refers to any physiological, psychological or health condition that may be treated according to the present invention by changing a level of activity in one or more regions of interest associated with that condition. Numerous examples of conditions that may be treated according to the present invention are provided herein. It is noted that a condition may additionally refer to a normal state of a subject that one may desire to alter, such as the condition of a subject\'s mood.

Device operator, as used herein, refers to an individual who controls the functioning of apparatus or software associated with this invention. It is to be noted that the device operator may be a person other than the subject, may be the subject, or may be a remotely located party using appropriate communication technology such as an internet connection.

Endopharmacology or endomedication, as used herein, refers to the activation or modulation of a brain region that releases endogenous neuromodulatory substances or neurotransmitters onto one or more target regions, and thereby regulates neuronal function.

Event related, as used herein, refers to an event that is related to a physiological activity which is caused by a known event, or takes place immediately preceding or subsequent to that event. In a typical example, a stimulus or behavior event is repeated many times, and the average event related activity is the average activity level at a set of defined times relative to the onset time of the event. This may be computed using a PETH.

Exemplar, as used herein, refers to an instance that serves as a member of a set. Exemplar stimuli are stimuli taken as instances from a set, such as a set of stimuli, the perception of which are thought to engage a particular region of interest. Exemplar behaviors are behaviors taken as instances from a set, such as a set of behaviors, the performance of which are thought to engage a particular region of interest.

Exercise, as used herein, refers to repeated training, such as training designed to activate a brain region.

Existing MRI/fMRI/PET data processing packages, as used herein refers to the following packages, their documentation, websites, and cited literature references contained in their documentation and websites: SPM99 (and the SPM99 manual written by Dick Veltman and Chloe Hutton, May 2001), Brain Voyager from Brian Innovation, AIR by Roger Woods, MRICro by Chris Rorden, AFNI by RW Cox, and other packages that may be developed to perform related functions.

Information, as used herein, refers to anything communicated to the subject, whether by sight, sound, smell, contact with the subject, etc., relating to the performance of the various methods of the present invention. Examples of various types of information that may be communicated to the subject include, but are not limited to, instructions, physiological measurement related information, subject performance related information, and stimulus information that causes the subject to have a perception. Examples of ways of communicating information include, but are not limited to displaying information to the subject, playing audio for the subject, providing an agent for the subject to smell, applying a physical force to the subject (e.g., a pressure or vibration or proprioceptive stimulus), and causing a physical sensation for the subject (e.g., cold, hot, pain, electrical charge, etc.). Specific examples of information include, but are not limited to images of the subject\'s brain activity pattern, charts of the timecourse of physiological activity in a region of interest, or an activity metric from a region of interest, instructions to perform a task or how to perform a task, movies, or stereoscopic virtual reality stimuli viewed through stereo viewers and designed to simulate certain circumstances or experiences. Further examples include games played by the subject, such as computer games.

Instructions, as used herein, refers to any instruction to perform a physical or mental action that is communicated to a subject or an operator assisting a subject. Examples of instructions include, but are not limited to instructions to a subject to perform a behavior; instructions to a subject to rest; instructions to a subject to move; instructions to a subject to make a computer input; instructions to a subject to activate a brain region, such as to a designated level. Further examples of instructions are provided herein.

Localized region, as used herein refers to any region of the brain with a defined spatial extent. In one variation, a localized region measured by this invention may be internal relative to a surface of the brain.

Measurement information, as used herein, refers to any information that communicates a measurement to a subject. Examples of types of measurements include, but are not limited to anatomical measurements, physiological measurements, activity measurements, activity metrics computed from activity measurements, and activation images.

Measurement of activity, as used herein, refers to the detection of activity in one or more voxels of the brain. Once measured, activity metrics may be computed from these measurements. Activity measurements may be performed by any measurement technology that is capable of measuring activity in one or more voxels of the brain, or by combinations of such technologies with other forms of measurement. Various suitable measurement technologies are described herein.

Neuromoanatomical texts, as used herein refers to any of a variety of texts describing the structures of the brain, including but not limited to Fundamental Neuroanatomy by Nauta and Feirtag, and in the Co-Planar Steriotaxic Atlas of the Human Brain by Jean Talairach and Pierre Tournoux, Magnetic Resonance Imaging of the Brain and Spine (2 Volume Set) by Scott W., Md. Atlas.

Neuromodulator or neuromodulatory substance, as used herein, refers to compounds which can alter activity or responsiveness in one or more localized regions of the brain. Examples of neuromodulators include, but are not limited to: opioids, neuropeptides, acetylcholine, dopamine, norepinephrine, serotonin and other biologic amines, and others. Many pharmacologic agents such as morphine, caffeine and prozac are exogenous mimics of these neuromodulatory substances.

Neuromodulatory centers, as used herein, refers to regions of the brain or nervous system that serve to regulate or alter responsiveness in other parts of the nervous system. Examples include regions that contain neurons that release neuromodulatory transmitters such as catecholamines, acetylcholine, other biologic amines, neuropeptides, serotonin, norepinephrine, dopamine, adrenaline. These centers and the actions produced through their modulation are described in neuroanatomy texts and The Biochemical Basis of Neuropharmacology, Cooper, Bloom and Roth. Examples include but are not limited to the nucleus raphe magnus, substantia nigra (pars compacta and reticulata), nucleus accumbens, periaqueductal gray, locus coeruleus, nucleus basalis, red nucleus, nucleus accumbens.

PETH, as used herein, refers to a peri-event time histogram. This is a measure of the average value of an activity pattern metric based upon multiple trials, for each of a set of fixed time intervals after a conditioning event such as a stimulus or the onset of a behavior.

Perception, as used herein, refers to a cognitive response by a subject that may result in the activation of one or more localized regions of the brain. In some instances, the perception is in response to stimulus information that is communicated to the subject. However, the perception may also be independent of stimulus being communicated to the subject.

Performance target, as used herein, refers to an activity metric that a subject may be instructed to achieve. The performance target may be communicated to the subject in some manner before, during or after a trial.

Pharmacological treatment, as used herein, refers to the administration of any type of drug, remedy, or medication.

Region of interest or ROI or volume of interest, as used herein, refers to a particular one or more voxels of the brain of a subject. An ROI may occasionally be referred to as an area or volume of interest since the region of interest may be two dimensional (area) or three dimensional (volume). Frequently, it is an object of the methods of the present invention to monitor, control and/or alter brain activity in the region of interest. For example, the one or regions of interest of the brain associated with a given condition may be identified as the region of interest for that condition. In one variation, the regions of interest targeted by this invention are internal relative to a surface of the brain.

Regulation or modulation, as used herein, refers to a subject performing a behavior or having a perception that controls activity in a region of interest. Regulation may cause the activity to increase or decrease relative to a desired level, or to change spatial pattern. Regulation may be monitored using one or more activity metric, for example by monitoring for an increase, decrease, or maintenance in the activity metric. Preferably, regulation provides control over activity for at least a selected period of time (e.g. seconds, minutes, days, or longer).

Reward centers or pleasure centers, as used herein, refers to areas of the brain which, when active, produce pleasurable or rewarding experiences or sensations. These include, but are not limited to certain limbic structures, the nucleus accumbens, locus coeruleus, septal nuclei, and others. These may also include areas that have been associated with addictive behaviors.

Reward, as used herein, refers to information, incentives, or objects given or promised to subjects to encourage their positive performance in a task. These include numerical values of performance level such as percent correct, encouragement, enjoyable activities, or monetary or other enticements toward correct performance.

Scan volume, as used herein, refers to a three dimensional volume within which brain activity is measured. This volume may be divided into an array of voxels. For example, in the case of fMRI, a scanning volume may correspond to a 3-D cube (e.g., 22×22×12 cm) that comprises the volume of the head of a subject. This volume may be divided into a 64×64×17 array of subvolumes (voxels).

Single point, as used herein, refers to an individual geometric locus or small area of volume, such as a single small geometric volume from which a physiological measurement will be made, with the volume being 0.1, 0.5, 1, 2, 3, 4, 5, 10, 15, 20, 30, 50, 100 mm in diameter. A device making a measurement from a single point is contrasted with a device making scanned measurements from an entire volume comprised of many single points.

Spatial array, as used herein, refers to a contiguous or non-contiguous set of location points, areas or volumes in space. The spatial array may be two dimensional in which case elements of the array are areas or three dimensional in which case elements of the array are volumes.

Spatial pattern, or spatial activity pattern, or vectorized spatial pattern, as used herein, refers to the measured activities of the set of voxels forming a two dimensional or three dimensional spatial array such as a scan volume or portion of a scan volume. A vector comprising a rational or real value for each voxel in a three dimensional spatial array is one example of a spatial pattern. Since activity associated with each voxel is represented, a spatial pattern contains much more information than a single activity metric for the entire localized region. It is noted that a spatial pattern may be defined either in geometric space as physically measured, or may be defined in a transformed space or standard coordinate space intended to allow the geometric points in the brain of one subject to be aligned with anatomically or physiologically corresponding points in another subject or group of subjects.

Stimulus information, as used herein, refers to any information which when communicated to a subject may cause the subject to have a perception, and/or to alter activity in one or more regions of interest of the subject\'s brain. Examples of stimulus information include but are not limited to: displays of static or moving images, sounds, and tactile sensations. It should be recognized that certain types of information may perform a dual function of being stimulus information and also communicating another type of information.

Stimulus set or behavior set, as used herein, refers to a defined set of stimuli or behaviors that are to be used to activate one or more particular regions of interest of a subject\'s brain. The exemplars forming the set may constitute either a set of discrete exemplars (such as a set of digitized photographic images of faces, instructions, or words), or a continuum from which particular exemplars can be drawn (such as the sound frequencies from 2000-8000 Hz or visual gratings with spatial frequency from 0.01-10 cycles/degree of arc). As will be described herein, a set of exemplars may be used to identify a subset that are found to more effectively activate the particular one or more particular regions of interest.

Subject, as used herein, refers to a person whose brain activity is to be measured in conjunction with performing the methods of the present invention. It is noted that the subject is the person who has the condition being treated by the methods of the present invention.

Subject performance related information, as used herein, refers to any information relating to how effectively a subject is altering activity in one or more regions of interest of the subject\'s brain being targeted, for example, in response to the subject performing a behavior or having a perception that is directed toward altering activity in one or more particular regions of interest.

Substantially real time, as used herein, refers to a short period of time between process steps. Preferably, something occurs in substantially real time if it occurs within a time period of less than 10 seconds, more preferably less than 5, 4, 2, 1, 0.5, 0.2, 0.1, 0.01 seconds or less. In one particular embodiment, computing an activity metric is performed in substantially real time relative to when the brain activity measurement used to compute the activity metric was taken. In another particular embodiment, communicating information based on measured activity is performed in substantially real time relative to when the brain activity measurement was taken. Because activity metrics and information communication may be performed in substantially real time relative to when brain activity measurements are taken, it is thus possible for these actions to be taken while the subject is still in position to have his or her brain activity measured.

Task, as used herein, refers to a perceptual, cognitive, behavioral, emotional, or other activity undertaken by a subject, typically repetitively as part of a trial.

Treatment, as used herein, refers to the application of this invention to a subject with the intent of improving a condition of the subject.

Trial, as used herein, refers to a period of time that may include one or more rest periods and one or more instances or attempts to perceive a stimulus or perform a behavior. Trials may be typically repeated in blocks, and blocks may be repeated in sessions.

Training, as used herein, refers to the process of a subject perceiving a stimulus or performing a behavior in combination with having activity be measured of a region of interest to be activated by the perception or behavior.

Vectorized brain states, as used herein, refers to a measured state of the brain where the activity in each voxel of the brain may be separately measured, as in a spatial activity pattern.

Voxel, as used herein, refers to a point or three dimensional volume from which one or more measurements are made. A voxel may be a single measurement point, or may be part of a larger three dimensional grid array that covers a volume.

DETAILED DESCRIPTION

The brain is the seat of psychological, cognitive, emotional, sensory and motoric activities. By its control, each of these elements may be controlled as well. Many psychological and neurological conditions arise because of inadequate levels of activity or inadequate control over discretely localized regions within the brain. The regulatory or neuromodulatory brain regions provide control over other brain regions. These regulatory or neuromodulatory brain regions cause many disease states when they fail to produce their intended regulation, and exogenous drugs often seek to re-apply this missing internal regulation.

The present invention provides methods, software, and systems that may be used to provide and enhance the activation and control of one or more regions of interest, particularly through training and exercising those regions of interest. An overview diagram depicting the components and process of the invention is presented in FIG. 1. As illustrated, a scanner and associated control software 100 initiates scanning pulse sequences, makes resulting measurements, and communicates electronic signals associated with data collection software 110 that produces raw scan data from the electronic signals. The raw scan data is then converted to image data corresponding to images and volumes of the brain by the 3-D image/volume reconstruction software 120. The resultant images or volume 125 is passed to the data analysis/behavioral control software 130. The data analysis/behavioral control software performs computations on the image data to produce activity metrics that are measures of physiological activity in brain regions of interest. These computations include pre-processing 135, computation of activation image/volumes 137, computation of activity metrics from brain regions of interest 140, and selection, generation, and triggering of information such as measurement information, stimuli or instructions based upon activity metrics 150, as well as the control of training and data 152, using the activity metrics and instructions or stimuli 160 as inputs. The results and other information and ongoing collected data may be stored to data files of progress and a record of the stimuli used 155. The selected instruction, measured information, or stimulus 170, is then presented via a display means 180 to a subject 190. This encourages the subject to engage in imagined or performed behaviors or exercises 195 or to perceive stimuli. If the subject undertakes overt behaviors, such as responding to questions, the responses and other behavioral measurements 197 are fed to the data analysis/behavioral control software 130.

Through the use of the present invention, a subject is able to be trained to control the activation of a region of interest of that subject\'s brain, and then exercise the use of that region to further increase the strength and control of its activation. This training and exercise can have beneficial effects for the subject. In the case of regions that release endogenous neuromodulatory agents, this control can serve a role similar to that of externally applied drugs.

The exercise of regions of interest according to the present invention is analogous to the exercise provided by specialized training equipment for weight lifting that isolates the activation of a particular set of muscles in order to build strength and control in those muscles.

In addition to training and exercise, knowledge of the activation pattern in discrete brain regions can be used to enhance certain aspects of a subject\'s behavioral performance, such as the subject\'s abilities at perception, learning and memory, and motoric skills. This enhancement takes place by cueing a subject to perform a behavior at a point when a measured pattern of brain activation is in a state correlated with enhanced performance. Alternatively, the behavior that the subject will undertake or the stimulus that the subject will perceive can be selected based upon the measured pattern of neural activation.

Methods have been described previously in the literature that correspond to measuring a physiological property, and presenting the measured result to the subject so that the subject can engage in biofeedback. The present invention differs substantially from those methods. As described above, biofeedback has been employed in conjunction with certain brain recording methodologies, namely EEG (U.S. Pat. Nos. 4,919,143, 4,919,143, 5,406,957, 5,899,867 and 6,097,981) and light (U.S. Pat. No. 5,995,857) to try to treat select brain disorders by allowing a subject to monitor his or her own brain functions (e.g., blood flow or blood oxygenation or tissue metabolism) as the subject attempts to alter a level of globalized brain function in response. These methods have typically been directed to monitoring of overall brain activity of the entire brain or large areas of the brain using signals such as EEG brainwaves, and thereby allowing the subject to view their own globalized activity level to try to learn relaxation, better attention, or control over another global process.

The present invention is substantially different from the prior art, focusing upon using the discretely localized measurements emanating from brain regions with very specific functions to control the stimuli and instructions presented to a subject. This control can be used in training and exercise methods directed specifically to the functions controlled by the regions of interest being measured.

As will be explained herein, any brain measurement methodology may be used in conjunction with the present invention so long as the physiological activity of one or more discretely localized regions of the brain can be effectively monitored in substantially real time.

In one particularly important embodiment that will be described in greater detail, the brain scanning methodology used is functional magnetic resonance imaging (fMRI).

In one variation, the regions of interest targeted by this invention are internal relative to a surface of the brain. By using brain scanning technology, such as MRI/fMRI that is able to make measurements from internally localized regions of the brain, the present invention is able to treat those internal localized regions of the brain. Some other technologies are limited because their measurements are made from surface points based upon current or voltage recorded at the brain or scalp surface, or based upon radiation emitted from the brain or scalp surface. A single signal emitted from any one localized brain region internal to the brain will propagate through the brain according to its conductivity to many points on the brain surface. This signal will be mixed with the signals from all other active brain regions as it propagates. Once mixed, this large number of competing signals cannot be completely separated based upon a finite number of surface measurements. Some analysis methods have attempted ‘source separation approximations’ to attempt to infer what point generated a given signal in the presence of many other signals, but none can completely and definitively determine the signal from a particular discretely localized brain region due to the underlying physics of the problem. This is based upon a limitation of the measurement technique: the electrical or radiation signal used to make the measurements is contaminated by the tissue through which the signal must pass to enter and exit the brain between the transmitter and the receiver, and by adjacent tissue.

A major advance in measuring the activity in discretely localized brain regions was the advent of brain scanning technologies, such as fMRI, PET, and SPECT. These technologies overcome the obstacle of measuring the activity in localized regions internal to the brain without substantial contamination from surrounding and intervening tissue. For example, an MRI/fMRI scanner uses a different magnetic field strength at each point in space, which corresponds to a different RF center frequency for measurement. MRI/fMRI is therefore able to make measurements from only a single point (based upon field strength) by recording RF at the relevant center frequency. This measurement is not significantly contaminated by activity from surrounding regions, or be regions between the point being measured and the surface of the brain.

By using brain scanning technology that can accurately measure internal localized regions of the brain, the present invention is able to monitor and treat internal, localized brain regions. This is an important distinction from merely controlling activity in the brain as a whole, or in a large brain region as a whole. The brain is a structure with hundreds of individual regions, some extremely small, and each with its own function. In order to control the brain\'s actions in a meaningful way, it is important to spatially localize which regions are measured, which regions are activated, and which regions are de-activated. This invention allows the control of small, discretely localized brain regions. This invention also allows the control of the pattern of activity within a brain region to create a 2-D or 3-D pattern of activation that can include sub-regions of increased activation and sub-regions of neutral or decreased activation.

This invention can employ measurements made using a scanning methodology that records data from each point in a predefined volume. In another variation, the localized brain region that is monitored is as small as a single voxel. Taking measurements from a single point or small volume allows data collection to be concentrated on the single volume of measurement, rather than being divided across multiple measurement points across a larger volume. This also can obviate the need for elements of the technology that enable scanning of the measurement point.

The present invention may be applied to any disease or condition involving inappropriate activity in one or more discretely localized brain region. For example, the present invention can be used to address a decrease in activation of the substantia nigra that leads to a decrease in the release of the endogenous neuromodulator dopamine in Parkinson\'s disease with resulting changes in activation in target areas, the decrease in activation in the nucleus basalis of Meynert that leads to a decrease in the release of the endogenous neuromodulator acetylcholine to regulate the cerebral cortex in Alzheimer\'s disease, or the decrease in frontal cortical activity in Major Depression that can be positively impacted by increased release of the endogenous neuromodulator serotonin from serotonergic nuclei.

The present invention can also be applied to subject-specific conditions involving a decrease in activity within a particular discretely localized region, such as the decrease in activity in the still-living tissue adjacent to tissue destroyed by ischemic brain injury (CVA/stroke).

Examples of regions of interest of the brain which may be targeted according to the present invention include, but are not limited to those listed in FIG. 2.

The present invention is particularly well-suited for the treatment of conditions that have a cause directly related to an inappropriate level or pattern of neural activation within a discretely localized brain region. This is because the invention utilizes technology that allows these discretely localized brain regions to be directly spatially targeted, controlled, trained, and exercised.

The present invention is also particularly well-suited for the treatment of conditions positively impacted by endogenous neuromodulatory compounds emanating from localized brain regions. This is because this invention allows the regions that produce or respond to these compounds to be directly spatially targeted, controlled, trained, and exercised.

A feature of the methods, software and systems of the present invention is the communication to a subject through visual, auditory or other information, including measured information, instructions, or stimuli that are based upon the measured activity of discretely localized regions of his or her brain. This measurement can be based upon substantially real time brain scanning technologies such as functional magnetic resonance imaging (fMRI) or other physiological measurement methods. By measuring physiological activity levels of discretely localized regions of the brain and communicating instructions or stimuli that are based upon those activity levels to the subject in substantially real time, the subject is able to regulate, train, and exercise the physiological activity levels of those discretely localized regions of the brain.

A further feature of the methods, software and systems of the present invention is the identification of certain training exercises that the subject can use to regulate the physiological activity levels of those discretely localized regions of the brain. By first identifying what training exercises are most effective for a selected localized portion of a given subject\'s brain, the localized activation provided by the present invention is enhanced. Furthermore, by then performing the selected training exercise where the subject\'s effectiveness in activating the selected localized portion of the subject\'s brain is monitored and communicated to the subject, the effectiveness of the training exercise is maintained and improved upon.

By performing the methods of the present invention, desired levels and patterns of physiological activation can be achieved within regions of interest. Achievement of these levels and patterns can be used to achieve a variety of highly desirable results including, but not limited to, the treatment of a number of conditions or psychiatric or neurologically-based diseases, improvement in performance or learning, and improvement of mood or affect. For example, the methods allow monitoring and control over many aspects of neurological and psychological disease, as well as improvements in mental performance and improvement of psychological and emotional states and learning. A partial list of diseases or conditions which may be addressed by the present invention include, but are not limited to Parkinson\'s disease, Alzheimer\'s disease, depression, psychosis, epilepsy, dementia, migraine, others described in FIG. 3, and those described in: Adams & Victor\'s Principles Of Neurology by Maurice Victor, Allan H. Ropper, Raymond D. Adams.

Different aspects of the present invention, including more specific methods, software, and systems are provided herein. The following paragraphs provide an overview of an embodiment of training and exercise according to the invention. Further embodiments and details are provided in the sections that follow.

One step toward providing treatment using this invention is to determine the primary region(s) of interest that mediates the condition to be treated so that treatment can be focused upon this region of interest. An initial set of stimuli or instructions for behaviors may be selected that will selectively engage the brain region of interest, and that may be used in training and exercise. It is also important to localize the region of interest within the brain of the subject using anatomical and physiological scanning methods. Once the region of interest is localized for the subject, particular stimuli or instructions for behaviors may be selected from the initially defined set to be used for training the subject. The stimuli or instructions for behaviors are typically selected that produce the highest level of activation of the brain region of interest during the particular stimulus or behavior.

At this point, training of the subject begins using the optimized stimulus set. The subject takes part in multiple training trials in training blocks. The training blocks take place within repeated or daily training sessions. The goal of the training is for the subject to gain increased control over the region of interest, and to exercise that region to achieve greater activation. The exemplar stimuli/behaviors isolate activation of particular brain regions, and the subject is given information about the progress of their training.

For a particular training trial, while inside the scanning apparatus the subject is given the instruction to observe a particular stimulus or engage in a particular behavior. For example, the subject receives the instruction to make a particular movement of the hand. The resultant activity level in the region of interest is measured by the scanning apparatus. This is analogous to an athlete lifting the weights on a particular weight-lifting machine using an isolated set of muscles. The subject is then given information about the activation that they were able to achieve, analogous to an athlete observing how much weight they were able to lift. Over training, the subject practices and exercises and gradually builds greater control and higher activation in the region of interest. Training typically takes place over a number of sessions on separate days. This training can be supplemented with additional training outside of the scanner (when the subject would not receive the information about their performance level) using the selected stimuli. The training can also be provided as an adjunct to additional therapies such as pharmaceuticals or physical therapy.

Additional embodiments are described in the examples section.

The detailed discussion that follows through section 6 describes aspects of an embodiment of this invention that allows training and exercise of a subject for the purpose of treatment of a condition through the regulation of certain brain regions.

1. Determining a Treatment Method for a Given Condition

This section describes a process by which treatment methods for different conditions may be developed. It is noted that the subjects referred to in this section are not necessarily subjects that are being treated according to the present invention. Instead, the subjects referred to in this section are people who are used to evaluate how well given stimuli, instructions for behaviors activate certain brain regions.

Developing treatment methods for different conditions may be performed by evaluating a likely effectiveness of treating a given condition by understanding whether there is an association between a given condition and a particular brain region; determining the one or more regions of interest to be trained for the given condition; determining one or more classes of exercises likely to engage those brain regions; determining a set of exemplar exercises from the one or more classes for use in training; and testing the subject to ensure that the set of exemplar exercises are effective in activating the regions of interest.

A. Evaluating a Likely Effectiveness of Treating a Given Condition

Numerous different conditions may benefit from training according to the present invention. For example, Parkinson\'s disease is caused largely by insufficient activity of the brain\'s substantia nigra, and resultant patterns of activity in its neural target zones. The activity in the substantia nigra and its target zones can be increased through training and exercise of this region of interest. In the case of stroke, regions adjacent to the zone destroyed by ischemia can be trained to achieve improvements in neural activation and regulation. Many other examples of conditions that may benefit from training according to the present invention are described in the Examples section herein.

The likelihood of success for a given condition to be treated according to the present invention can be evaluated from knowledge of the etiology and variety of causal factors contributing to the condition as understood at the time of treatment. More specifically, when considering whether treatment will be effective for a given condition, attention should be given to whether the condition is related to brain activity. If there is a correlation between the presence of the condition and a level or pattern of brain activity in one or more regions of interest, then, the methods of the present invention are likely capable of improving that condition by altering the level or pattern of brain activity in the one or more particular brain regions.

B. Determining One or More Regions of Interest to be Trained for the Given Condition

As noted above, the brain comprises thousands of individual regions, each with its own function. Thus, in order to treat a given condition, it is important to identify the one or more regions of interest associated with the condition. It should be noted that the precise location of these regions can vary subject to subject. Hence, it is also important to identify the one or more regions of interest to be treated for a given subject. This ultimately makes the treatment methods of the present invention highly individualized.

Determining the one or more discretely localized brain regions to be trained for a given condition may be performed through a combination of general knowledge about what regions are associated with the given condition and thus need to be exercised, and information about the particular subject.

For a given condition, the scientific and clinical literature will typically have information regarding which localized brain regions are associated with the given condition. For example, the literature may have information associated with a given condition regarding human and animal neural lesion data, pathology, histochemistry, pharmacology, brain stimulation studies, neural recording studies, and functional and anatomical imaging studies. Using this information, one is able to take a subject with a given condition, and determine which brain areas are most relevant.

Once brain regions associated with a given condition are identified in the abstract, it is important to then identify these regions in a given subject\'s brain. It is noted that treatment will be performed over a period of several days, weeks, month or even years. Therefore, it is advantageous to store information regarding the location of the relevant brain regions for a given once they are identified so that less time and effort is needed to relocate them for subsequent treatments.

In the case of fMRI scans, the regions of interest can either lie within a single plane of section, or they can form contiguous or non-contiguous volumes consisting of regions on multiple planes of a section. Software allows the definition of standard-sized regions of interest, centered on a location selected by the device operator or based upon anatomical boundaries or measured physiological activation patterns. Once particular regions of the brain are identified for a given subject, the regions may be saved numerically to some form of memory (e.g., a computer disk) so they can be recalled for separate scanning runs, or for scans conducted in different sessions at later dates.

C. Determining One or More Classes of Instructions or Stimuli Likely to Engage the Brain Regions of Interest

Different regions of the brain are associated with different functions, and may thereby be engaged and exercised by particular types of stimuli, or by particular behaviors associated with those functions. Hence, by understanding what function a given region of the brain performs, exercises can be designed which activate those brain regions. Through trial and error, exercises can be varied and thereby fine tuned both with regard to their effectiveness in activating a given region in general, and with regard to their effectiveness in activating a given region for a given subject.

Numerous physiological studies on many different brain regions have been performed and have yielded a wealth of information regarding the different kinds of stimuli or behaviors that can be used to engage different specific brain regions. Many areas of the brain have already been ‘mapped’ in their functionality, in that particular zones are activated by particular types of stimuli or behaviors, with adjacent zones activated by similar stimuli or behaviors. These types of studies have allowed for the determination of what classes of stimulus or behavior are likely to activate particular brain regions by selecting the stimulus or behavior that are appropriate to the type of map and the point on the map being considered.

For example, countless detailed studies have determined frontal cortical regions that subserve movements, the motor cortex. Thus, a lesion that partially inactivates the cortical hand representation will destroy tissue engaged in hand movements. Adjacent tissue will be involved with the other hand, wrist, and arm movements. Therefore, in order to treat the lesion, exercises to employ will include exercises that engage the brain region where the lesion is located as well as adjacent regions. In this instance, such exercises will likely encompass movements of the relevant extremity, whether physically or mental thoughts of their movement.

D. Determining a Set of Exemplar Instructions or Stimuli from the One or More Classes of Examples

Once a general class of exercises has been determined for a given region of the brain, actual instances of specific stimuli or behaviors are created that are able to exercise the brain region of interest.

The stimuli or instructions for behaviors to be used may be created from within the class of stimuli or instructions for behaviors that will engage the brain region of interest. The exemplars created may be real stimuli that will be presented to subjects, or real instructions that will lead the subject to engage in behaviors. These stimuli and instructions may be created via computer to be presented digitally. Visual stimuli may be presented on a monitor viewed by the subject, auditory stimuli may be presented via speakers controlled by a computer, and tactile or other sensory stimuli may be presented via computer-controlled sensory stimulation devices as needed. For example, in order to engage certain regions of the temporal lobe involved in the processing of faces, a set of digitized photographic images of faces is used. In order to engage the primary motor cortical representation of the hand, a set of digitized images or movies depicting particular hand movements is uses. Typically, the stimuli to be presented can be based on stimuli that have previously been demonstrated to be successful in activating the brain region of interest.

Instructions can include text instructions that will inform the subject of what to do and be presented either on the monitor, or they can include verbal instructions presented via digital audio, or the instructions can include icons or movies presented to the subject.

E. Testing Subjects to Ensure that the Set of Exemplar Instructions or Stimuli are Effective