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Patent No. 6996261
Methods for physiological monitoring, training, exercise and regulation (deCharms,
Feb 7, 2006)
Abstract:
Computer executable software and device for guiding brain activity training comprising: 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.
Notes
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.
DESCRIPTION OF RELATED ART
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 resistent 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 Lubar, 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 OF THE INVENTION
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.times.22.times.12 cm, 11.times.11.times.6 cm,
6.times.6.times.6 cm, 3.times.3.times.3 cm, 1.times.1.times.1 cm, 0.5.times.0.5.times.0.5
cm, 1.times.1.times.1 mm, 100.times.100.times.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.
__________________________________________________________________________
14.
Behavioral Training
Using this invention, subjects may be trained in a variety of tasks. Training
corresponds to performing a task with the intent to improve at a desired outcome,
and is typically repeated. Tasks may include covert behavioral tasks in which
a subject performs a cognitive or mental activity such as imagining a movement
in order to activate a brain region, or overt behavioral tasks in which a subject
performs a physically observable action such as making a prescribed movement
or responding to a question. In either case, the task may lead to changes in
the activity of the brain of the subject, and these changes may be measured
as provided for in this invention. Overt and covert tasks may be performed separately,
or substantially concurrently.
One example of behavioral training is
covert training of a subject to activate a brain region of interest. In this
example, the subject may be provided with information about the level of activity
in a brain region of interest, such as an activity map including the region,
or an activity metric that measures the activity in the region of interest.
This training may be with the intent of increasing the activity in the region
of interest, decreasing it, changing its pattern, or altering it in other ways
as measured by the activity pattern metrics described in Examples section 1.
The subject may also be presented with stimuli, which may additionally serve
to activate a brain region of interest. The subject may also be presented with
performance information indicating his or her level of performance at the task
being performed. The subject may monitor these types of measured information,
stimuli, and performance information, and may respond to them. One response
of the subject may be to select or modify a cognitive strategy that the subject
uses to activate the brain region. For example, if the subject is performing
the covert task of imagining a given hand movement in an attempt to activate
the motor cortex, the subject may observe that one particular imagined hand
movement is more effective at activating the motor cortex than another particular
imagined hand movement. The subject may then select the more effective movement
for use in future trials. This monitoring of information and response may take
place in combination with performing training. While the results of a covert
task may be observed using physiological measurement equipment, they are not
observable in the sense of producing an overt, physically observable, visibly
viewable action of the subject.
Another example of behavioral training is overt training of a subject to perform
a physically observable, overt task. The subject may engage in overt tasks such
as psychological, learning, motor, or psychophysical tasks. These may include
such as things as making a computer selection of which of two stimuli presented
has a particular feature, or making a prescribed motion, or answering a stated
question. The subject may additionally be given performance information regarding
their performance at these covert tasks, such as whether they performed tasks
correctly or incorrectly. The performance of covert tasks may take place substantially
concurrently with overt tasks. For example, the subject may be instructed to
make selections between different stimuli or to perform particular movements
while the subject also attempts to increase the level of activation in a brain
region of interest.
It will be apparent to those skilled
in the art that various modifications and variations can be made to the methods,
software and systems of the present invention. The foregoing examples and figures
are presented for purposes of illustration and description. It is not intended
to be exhaustive or to limit the invention to the precise forms disclosed. Many
modifications and variations will be apparent to practitioners skilled in this
art and are intended to fall within the scope of the invention.
All publications and patent applications cited in this specification are herein
incorporated by reference as if each individual publication or patent application
were specifically and individually indicated to be incorporated by reference.
The citation of any publication is for its disclosure prior to the filing date
and should not be construed as an admission that the present invention is not
entitled to antedate such publication by virtue of prior invention.