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Neurofeedback for Traumatic Brain Injury: Current Trends

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  • Neurofeedback Therapy Services of New York
Article

Neurofeedback for Traumatic Brain Injury: Current Trends

Abstract

Traumatic brain injuries constitute significant health and societal problems which can be ameliorated with some recent developments in neurofeedback. The field of neurofeedback has evolved from single channel to multiple-site training, and with LORETA Z-score training, deeper levels of the brain can reached. Neurofeedback for traumatic brain injury patients may provide improvements never before possible.
Biofeedback ÓAssociation for Applied Psychophysiology & Biofeedback
Volume 43, Issue 1, pp. 31–37 www.aapb.org
DOI: 10.5298/1081-5937-43.1.05
Special IssueSpecial Issue
Neurofeedback for Traumatic Brain Injury: Current
Trends
J. Lawrence Thomas, PhD, BCN,
1
and Mark L. Smith, LCSW, BCN
2
1
The Brain Clinic, New York, NY;
2
Neurofeedback Services of New York, New York, NY
Keywords: neurofeedback, LORETA, Z-score training, traumatic brain injury, infraslow fluctuation neurofeedback
Traumatic brain injuries constitute significant health and
societal problems which can be ameliorated with some
recent developments in neurofeedback. The field of neuro-
feedback has evolved from single channel to multiple-site
training, and with LORETA Z-score training, deeper levels
of the brain can reached. Neurofeedback for traumatic
brain injury patients may provide improvements never
before possible.
Introduction
Traumatic brain injuries (TBIs) constitute a major health
problem, since there are from one to two million TBIs in
this country every year, mostly from car accidents and falls
(Corrigan, Selassie, & Orman, 2010; Novo-Olivas, 2014).
The majority, probably 80%, are mild brain injuries
(Bernad, 1988; Hoffman, Stockdale, Hicks, & Schwaninger,
1995); therefore, these would be the most likely candidates
for neurofeedback treatment. But this number also might
be underestimated, since many of these injuries may go
unreported (Powell, Ferraro, Dikman, Temkin, & Bell,
2008). It is estimated that it costs some $60 billion dollars
per year for this substantial public health problem
(Corrigan et al., 2010).
Other causes of brain injury have been discussed by
Thornton (2014). Concussions in football have a 72%
chance of happening in every NFL football game. Of the
veterans returning from Iraq, an estimated 22% have had a
TBI, which totals about 308,000 soldiers. Brewer et al.
(2010) estimated that there are 1.25 million emergency
room (ER) visits related to brain injuries each year, but also
pointed out that an estimated 56% of the TBIs are not
diagnosed in the ER. Added to this, Langlois, Rutland-
Brown, & Wald (2006) estimated that there were 3.8
million sports-related concussions yearly of all ages
(including children’s sports injuries) in the USA.
Mild traumatic brain injury (MTBI) is usually defined as
having a loss of consciousness of less than 20 minutes, or a
posttraumatic amnesia of less than 24 hours (meaning an
altered state of consciousness, such as confusion or
disorientation, and the time from the accident until there
is reliable and consistent memory). These indicators of
severity, however, do not predict the outcome of enduring
cognitive deficits in the patient (Zasler & Katz, 2013). In
this paper, MTBIs will be the primary focus. Severe cases of
brain injury are usually not treated with neurofeedback,
although there are exceptions (Larsen, 2009).
TBI sequelae can include problems of cognition,
behavior, emotional sensitivity, attention, and many other
symptoms. Patients can frequently become much more
impulsive, appear to have poor judgment, have memory
and word finding problems, and often are not very aware of
their problems. Planning and organizing can also be
significant deficits (Varney & Roberts, 1999).
Details of TBI physiology and neuropathology are
numerous and complex, and are beyond the scope of this
article, but can be found in other sources (Thornton, 2014;
Thornton & Carmody, 2010; Zasler & Katz, 2013). One of
the most extensive texts on TBI and its neuropsychology
and physiology is Concussive Brain Trauma (Parker, 2012).
Neurofeedback Can Help Where Other Treatments
Cannot
Neurofeedback is in the unique position of being able to
change the physiology of brain-injured patients. Most
healthcare professionals believe that once an adult has
sustained brain damage, the results are permanent, while
others believe that the vast majority of MTBIs resolve
completely within a year or two (McCrea, 2008). Thornton
(2014) has argued that those once thought to have
recovered completely from a MTBI still have biological
markers which reveal their impairments. Thatcher, Biver,
and North (2015a) has shown that a quantitative
electroencephalogram (QEEG) can reveal MTBIs with a
high degree of scientific validity (Thatcher, 1999, 2011;
Thatcher, Biver, McAlaster, & Salazar, 1998; Thatcher &
Lubar, 2009, 2014; Thatcher et al., 2001). Prodan, Vincent,
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Biofeedback |Spring 2015
and Dale (2014) have noted along with Thornton (2014)
that there are biological markers of MTBI worth noting,
especially since some professionals doubt the legitimacy of
many MTBI cases. A recent article noted that the coating of
platelets in mild brain injury lasts for a much longer time
than in normal subjects and may constitute a new biological
marker of MTBI (Prodan et al., 2014).
As this technology improves, neurofeedback could take a
central place in the rehabilitation of those with MTBI. At
present, the studies are limited in several ways. Many
studies have a small number of subjects, or are a series of
case studies. Sometimes different diagnoses are presented in
a case series (Foster & Thatcher, 2015; Smith, Collura,
Ferrara, & de Vries, 2014; Tinius & Tinius, 2000).
Randomized, placebo controlled, double blind studies are
rare in neurofeedback, and we have not found one with TBI.
Admittedly, there is an inherent problem in dealing with
MTBI and neurofeedback: there are probably no two brain
injuries alike. Also, the treatment protocols tend to be very
individualized in an attempt to match the patient’s brain
parameters, so the possibility of having a matched control
group that can be randomized is difficult. Secondly,
Hammond (2011a) has argued that the supposed ‘‘gold
standard’’ of placebo, double blind studies that are so
common in pharmacology research may not be the best way
to determine effectiveness in neurofeedback studies. Indeed,
many drug studies using these research constructs have
only demonstrated marginal benefit when scrutinized.
Basics of QEEG and Neurofeedback Protocols
Basic EEG frequencies and QEEG. Everyone has electricity
all over their body, and in the brain this electrical activity is
measured in terms of its brain waves; the unit of measure is
microvolts. Brain waves occur in different frequencies,
understood in cycles per second, or in Hertz (Hz). All
frequencies occur in all parts of the brain, but in different
conditions of the brain, the distribution of the frequencies
can take on specific proportions. The slowest brain wave
frequency is delta, which ranges from 0.5 to 4.0 Hz, and
next are theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz),
and gamma (30–45 Hz). Be aware that different researchers
define these bands in different ways.
The brain wave frequencies are measured at certain
locations or sites. The system of location, the ‘‘ 10–20
system,’’ specifies the site locations (19 or 21 sites). For
example, Cz is at the top of the head; Fpz is in the middle of
the forehead, about an inch up from the midpoint between
your eyebrows. Frontal sites include Fz, F3, F4, and
posterior sites include P3, P4, PZ. You can choose to train
some frequencies up (or to be more active in microvolts),
and some frequencies down, or to be ‘‘inhibited.’’ Thus, one
protocol could be to train Fz 12–18 Hz up and 4–7 Hz down
(or ‘‘inhibit’’ ) at the same time. In order to determine
precise protocols for doing neurofeedback, it is common to
get a quantitative electroencephalograph (QEEG), some-
times called a ‘‘brain map.’’ By converting the EEG data into
statistics, patients can be compared to a normative group,
and this can guide training of these brain waves to improve
functioning—and this is neurofeedback.
The QEEG method measures all frequencies (delta, theta,
alpha 1, alpha 2, beta 1, beta 2, beta 3, gamma) at each of the
19 (or 21) sites in terms of absolute power (microvolts) and
relative power (percentage), the ratios of each frequency to
every other frequency, plus all possible pairs of sites in
terms of the connectivity variables (coherence, asymmetry,
and phase). The result is some 2,500 variables. This
complex brain wave data is analyzed by a computer
program and compared to people the same age, and the
result is the QEEG. These variables are compared to the
normative database that contains the data for all ages;
therefore, the patient in question is compared to people the
same age. Of importance are the deviations the patient has
compared to the norms with respect to all these variables,
which is shown in terms of standard deviations and Z-
scores. What is interesting is that the QEEG patterns are
lawful and describe certain pathologies in a reliable way.
Thus, attention deficit disorder, dementia, affective disor-
der, traumatic brain injury, and obsessive–compulsive
disorder all have distinctive patterns to their QEEG. A
detailed history of this process can be found in Thatcher and
Lubar (2009, 2014).
Basics of neurofeedback training. Assessing the EEG will
render data regarding the 19 sites of the QEEG, with many
parameters available with regard to treatment. In the early
days of neurofeedback, single sites were treated (e.g.,
training 12–15 Hz at C4), and if two sites were treated, one
would follow another. Then training two sites were found
to be effective (e.g., T3 and T4). As practitioners explored
other parameters, two sites began to be trained in terms of
the coherence between the two sites. In more recent times,
several sites can be trained at once, as in Z-score training.
And now, with LORETA neurofeedback, the areas beneath
the surface of the cortex can be trained, and connections
between networks or regions can be trained. Thus, there has
been a progression over the last 20 years in neurofeedback
of being able to train and improve the electrophysiology at
more and more sites with more complexity.
The EEG electrodes can be placed in one or more sites,
and feedback is displayed to the patient on a computer
Neurofeedback for TBI: Current Trends
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Spring 2015 |Biofeedback
screen so that the dysfunctional frequencies are trained
down, and the ‘‘good’’ waves are trained up. The display can
be the brain waves themselves, a computer game generated
by the computer, or even a movie. For example, the patient
is asked to keep the animation going, and by operant
conditioning (e.g., the flickering of the movie), the patient
trains his or her brain waves to be more normal. There is a
fair amount of research regarding the effectiveness of
neurofeedback (see Monastra, 2005; Thompson & Thomp-
son, 2003; Yucha & Montgomery, 2008). Neurofeedback
has been shown to be effective for attention deficit disorder,
chronic pain, traumatic brain injury, and other brain
disorders (Yucha & Montgomery, 2008). Duffy (2000), a
neurologist, stated in a special issue of Clinical Electroen-
cephalography devoted to neurofeedback that ‘‘if any
medication had demonstrated such a wide spectrum of
efficacy, it would be universally accepted and widely used’’
(p. v). As will be seen below, there are some limitations to
the research on the effectiveness of neurofeedback with
respect to TBI.
The Early Days of Neurofeedback for Mild Traumatic
Brain Injury
The field of neurofeedback is remarkably new: The ‘‘ early
days’’ can be considered to be 20 to 30 years ago. The
current developments include some very sophisticated
methods of training brain problems that are far more
complex than the early studies. However, the early studies
are instructive, and can be reviewed to gain insights into the
issues of neurofeedback when the research was simple.
Most of the early publications were case studies, cases
series, or clinical studies; few had matched control subjects
were employed.
Ayers (1987) reported on doing neurofeedback with
brain-injured patients and compared their progress to that
of other patients doing psychotherapy alone; this could
qualify as a controlled study. There was a substantial
reduction of symptoms such as anger outbursts, mood
problems, and anxiety. Those patients who continued with
psychotherapy alone did not show improvement. Byers
(1995) treated a 58-year-old woman with MTBI at two
sites, with 31 sessions. His pre- and postmeasures showed
improvement in several areas of functioning as well as test
measures. Hoffman and his associates did studies from 1981
to 1996 (Hoffman et al., 1995; Hoffman, Stockdale, & van
Egren, 1981, 1996) showing that QEEG-guided treatment
of closed head injury patients produced 60% improvement
in symptoms and cognitive performance after 40 neuro-
feedback sessions.
Other articles that have provided brief reviews of
neurofeedback with traumatic brain-injured patients in-
clude Foster and Thatcher (2015), May, Benson, Balon, and
Boutros (2013), Novo-Olivas (2014), and Thatcher (2000).
Common criticisms include the lack of controlled studies,
mixing different diagnoses, inadequate measures beyond
self report, and weak neuropsychological testing. Nearly all
report on QEEG improvements, but unfortunately QEEG
does not correlate well to symptomatic improvement. These
reviews also point out that cognitive rehabilitation and most
other methods of helping the TBI patient are inadequate,
and that neurofeedback has a unique opportunity to help
these patients in new ways. Now let us turn to new models
of neurofeedback that are complex and exciting.
Neurofeedback Approaches Relevant for
Traumatic Brain Injury
Z-Score Neurofeedback
This is sometimes called live Z-score training.Itinvolves
using four or more sites (up to 19; the 10–20 sites) for
training up to all the variables all at once. Above, I
introduced the idea of Z scores, which indicate the standard
deviations from the normative database when comparing the
patient’s variables to the norm. The variables such as
absolute and/or relative power; ratios of two frequencies;
connectivity variables such as coherence, asymmetry, and
phase are all compared to the patient’s age group. Z-score
training is when all of these variables are coaxed to being
normal. For example, when four sites are being trained there
are 248 variables that are being trained at once, and live;
these variables are all referenced to a normative database for
the patient’s own age group. All of these data are converted
into one metric; this metric is the proportion of these Z
scores that are falling within an adjustable range of scores.
If the feedback is a DVD movie, the movie flickers as the
training stimulus. When the movie is dim, the brain is not
cooperating, and when the movie is bright, the brain is
cooperating. In this way the operant conditioning trains the
brain to become more normal; the assumption is that if the
brain EEG variables become more normal, the symptoms of
the patient’s brain dysfunction will improve. Collura
(2008a, 2008b, 2014) has given some detailed explanations
of the Z-score neurofeedback methodology; and Thatcher
and Lubar (2014) have recently published a book on Z-score
training.
LORETA Neurofeedback
LORETA stands for low-resolution electromagnetic tomog-
raphy analysis, which takes the QEEG data and renders the
Thomas and Smith
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Biofeedback |Spring 2015
sources of the EEG deep in the brain. In this way, the
underlying areas of neuropathology can be revealed in
three dimensions. Thus, LORETA images show the areas
beneath the surface of the cortex as well as well as cortical
surfaces of the brain that are the sources of the problem(s)
of the particular patient. In order to obtain data to
illuminate the three-dimensional properties of the brain, a
QEEG is done with all 19 channels. With these data,
regression equations are utilized to help locate the sources
of the problem(s) and give direct information as to how and
where to train the brain with neurofeedback. In the latest
developments, the QEEG data plus the NeuroGuide
Symptom Check List (Applied Neuroscience, Inc., Semi-
nole, FL) can indicate networks of Brodmann areas to train
that reflect the cognitive problems and emotional/behav-
ioral symptoms reported by the patients. The neurofeed-
back session can display the cortical surface and subsurface
networks being trained in a live fashion.
Foster and Thatcher (2015) presented a LORETA case
series of 11 subjects who came from the Veteran’s
Administration hospital with symptoms of both PTSD
and MTBI. Each received individualized LORETA Z-score
training, and each subject rated their symptom improve-
ment after each session for 12 to 20 sessions. The 19-
channel LORETA QEEG was done initially to select the
region of training; the LORETA methodology allows the
neurofeedback training to be three-dimensional in nature so
areas beneath the surface of the cortex can be trained. In
Thatcher’s methodology (Thatcher, Biver, & North, 2015b),
the Symptom Check List is reported by the patient, and this
is referenced to the likely areas of the brain responsible for
these symptoms, according to functional neuropsycholog-
ical literature. When both the LORETA data and the
Symptom Check List are ‘‘matched,’’ this will indicate the
training area(s). With each case, the training is unique to
the patient. A system of rating one’s goals was also
employed in this study so that the patient could rate their
progress in an ongoing fashion. All of the patients
improved in terms of their symptom reduction and positive
goal achievement.
This case series illustrates the fact that each patient is
different and needs an individualized treatment approach.
The method that Thatcher has devised utilizes the
functional neuroanatomy knowledge of the likely localiza-
tion in the brain of the reported symptoms, and combines
this knowledge with actual neurophysiological data of the
QEEG LORETA to create a highly specific neurofeedback
training/treatment plan. This is essentially personalized
medicine in training the brain to correct its own
neurophysiology. A recent book by Thatcher and Lubar
(2014) entitled Z-score Neurofeedback: Clinical Applica-
tions, details this methodology and the underlying scientific
issues. Thatcher’s QEEG software, NeuroGuide, allows the
professional to assess and conduct a variety of neurofeed-
back protocols at a number of levels (see www.
appliedneuroscience.com).
Doing cognitive remediation with neurofeedback. This
method was introduced by Tinius and Tinius (2000), and
consists of doing neurofeedback while doing cognitive
remediation at the same time. In this study, 15 MTBI
patients received neurofeedback while doing computerized
cognitive training, and their improvements were compared
to healthy controls with both groups given pre and post
measures. The MTBI patients improved on 10 out of 12
neuropsychological measures and improved to the level of
the healthy controls. A problem with this study is that it
combined TBI and learning disabled patients.
Activation QEEG neurofeedback. Thornton (2000) has
developed a model of doing neurofeedback that involves
first doing several QEEG assessments under different
cognitive conditions, then training the problematic cogni-
tive functions while doing neurofeedback. As discussed
above, a QEEG assessment involves collecting EEG data at
19 sites on the scalp, then converting this data by computer
into how a patient’s QEEG variables compare to those in his
or her age group. The usual two conditions of collecting
these data are with eyes open and eyes closed. Thornton
and Carmody (Thornton, 1996, 2000, 2003, 2014; Thornton
& Carmody, 2005, 2008, 2009, 2010) have pointed out that
the brain may reveal different patterns of EEG under
different cognitive task conditions, thus rendering the usual
QEEG brain maps eyes-open or eyes-closed conditions at
variance with the cognitive problems that may occur with
patients seeking neurofeedback treatment. Thornton does a
QEEG for each cognitive condition, a few examples being
auditory attention, visual attention, reading, and other
cognitive tasks for a total of 10 cognitive tasks. Compared to
a control group (Thornton & Carmody, 2008), the group of
brain-injured subjects improved with this method with
effect sizes above 2.0. If this work can be replicated, it could
mean a substantial contribution to the treatment of
traumatic brain-injured patients.
Hemoencephalography (HEG). HEG biofeedback trains the
patient to control a close correlate of the frontal lobe
cerebral blood flow. An infrared camera sensor, which reads
temperature (a close correlate of blood flow), is placed on
the forehead and the patient learns to control the heat by
Neurofeedback for TBI: Current Trends
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Spring 2015 |Biofeedback
watching the display. In the case of the passive infrared
hemoencephalography, the display is a movie—any DVD
the patient wishes to see. If the frontal lobe blood flow and
temperature remain high enough, or over the autothres-
hold, the patient can continue to watch the movie. When
the temperature drops (believed to be related to activity in
the anterior cingulate gyrus), the movie stops; by focusing
on a bar graph display, the cortical activity increases, the
temperature increases over the threshold, and the movie
starts again. The therapist can make the task easier or more
difficult. The autothreshold aspect of this system follows
the temperature of the frontal lobe, which naturally
fluctuates, so the movie will stop sooner or later. The
patient must then focus on a part of the computer that can
raise the frontal lobe temperature; when it goes over the
threshold, the movie continues.
The HEG method of neurofeedback is a new kind of
treatment, and there is little research as to its effectiveness,
and no studies (to our knowledge) with those with
traumatic brain injury. This biofeedback system was
originally designed for migraine headache treatment, and
has shown promising results. Carmen (2004) took 100
migraine patients that had been through many previous
treatments, including many trying several medications,
with little success. Positive results were usually seen in six
HEG sessions, and over 90% of the patients reported
significantly positive results, according to their own report.
I am including this method of neurofeedback because it is
specifically designed to train the frontal lobe cerebral blood
flow to increase, and this has been known to be a very
common area of brain injury with respect to MTBI
(Thatcher, 2011).
The LENS model and TBI. The low-energy neurofeedback
system, or LENS, is a method that measures the dominant
frequency of one or more of the 10–20 sites, and gives the
patient a tiny electrical stimulation (about one-millionth of
a microvolt) at that electrode. The frequency of this very
small and brief (from 0.01 seconds to 60 seconds)
stimulation is offset by several Hz. Ochs believes that this
‘‘offset’’ jars the brain to reregulate itself. The brain seems
to respond to the tiny stimulus, and appears to move
towards a more healthy homeostasis, sometimes with
dramatic results (Larsen, 2006), even with severe TBI.
The only controlled study of the LENS method that we
know of is the Schoenberger, Shiflett, Esty, Ochs, and
Matheis (2001) study. This study was done with a previous
version (called Flexyx) of the LENS system. In this study,
25 sessions were given to the immediate treatment group
and later to a wait-list control group, which received
treatment after the first group. Positive results were found
in several psychometric measures, as well as positive
improvements in social and occupational outcomes. In
another case report and explanation of the LENS system,
Ochs (2011) reported that a TBI patient was helped
substantially. Ochs also provides a detailed explanation of
the method and why he thinks it works. The book, The
Healing Power of Neurofeedback (Larsen, 2006), notes
several cases of TBI helped by the LENS method and other
disorders as well.
Infraslow fluctuation neurofeedback. In this new neuro-
feedback model (ISF), very slow frequencies are trained, at
the level of 0.1 and below, to as low as 0.001 Hz. Very low
frequencies have been researched for more than 40 years,
but mostly in languages other than English. Using this level
of physiology in neurofeedback has been hampered by
technological limitations, but recently, modern electronic
instrumentation has made available the use of slow
frequencies for therapeutic neurofeedback. In the Smith et
al. (2014) article, several cases are presented that report
positive results using this new technology, but these cases
are from a variety diagnostic groups and the pre and post
measures consist of mostly subjective reports. As with most
of the new models of neurofeedback, larger, controlled
studies are needed. It is clear that the innovations in
neurofeedback are outstripping the ability to do meaningful
research to prove their effectiveness.
Clinical Neurofeedback for Traumatic Brain
Injury
Overall Reviews
A detailed review of the positive effects of neurofeedback
for those with TBI is beyond the scope of this article. The
following review articles and controlled studies can serve as
evidence that neurofeedback appears to be effective for TBI
patients, but that rigorous research standards have not been
part of this progress up to this point in time.
The May et al. (2013) article recently reviewed 22
neurofeedback TBI articles, and reported that all the studies
reported benefit to the patients. However, none of these
were randomized, placebo controlled, double-blind studies.
The areas of improvement in these studies, taken as a
whole, included improvements in attention, impulse
control, and processing speed. If the studies had psycho-
metric measures, they were usually brief assessments of
cognition, such as the RBANS (repeatable battery for the
assessment of neuropsychological status; Randolph, 1998),
a very brief neuropsychological battery, or various means
Thomas and Smith
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Biofeedback |Spring 2015
of the patients reporting their symptoms or improvements.
Some studies showed improvements in QEEG variables.
While there is a growing literature of neurotherapy helping
those with brain injuries, there are some inherent problems
in the field with respect to doing controlled studies. It has
been pointed out that randomized, double-blind, placebo
controlled studies are nonexistent with regard to neuro-
therapy treatment for brain injuries (May et al., 2013;
Novo-Olivas, 2014; Thatcher, 2000), it is also likely that
this level of research design is not appropriate for this field.
Meanwhile, the landscape of neurotherapy keeps expand-
ing, and new technologies, such as LORETA, Z-score
training and infraslow frequency (ISF) are being used by
clinicians. Indeed, the technological innovation is outpacing
the ability of the research community to prove the
effectiveness of these new methods.
Neurotherapy for traumatic brain-injured patients may
be valuable for improving the physiology and cognitive
functioning of the brain—the extensive bibliography can
attest to this. However, these are people with complex and
perplexing symptoms we have in the treatment situation. It
is may be that the neurotherapy practitioner is the only
healthcare provider for the brain-injured patient. Becoming
aware of other issues is important, and some of these are
sketched out below. Further, some resources are noted after
this section so that these can be used for our professional
development.
The next developments. We saw how the progression of the
field went from training single sites, to pairs of sites, to the
connectivity variables between two sites (i.e., coherence), to
many sites (Z-score training), and then to reaching into the
deep areas of the brain (LORETA). Added to multiple sites
is Thornton’s (2014) model of doing neurofeedback while
doing a cognitive task in order to improve specific cognitive
abilities, and the Tinius and Tinius (2000) method of doing
actual cognitive remediation while doing neurofeedback.
The complexity of providing neurofeedback has increased in
the number of sites, and adding cognitive tasks while doing
neurofeedback. We have an interesting future in this field,
one that can benefit people who have never before had such
an opportunity.
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J:Lawrence Thomas Mark L:Smith
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Thomas and Smith
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... 19 Generally, NFT uses behavioral principles to train patients in the form of positive reinforcement (eg, advancement in a video game, positive auditory or visual cues) for desirable neural modulation or negative punishment (eg, setbacks in a video game, negative auditory or visual cues) for undesirable neural modulation. 20,21 Studies have demonstrated that NFT improves somatic complaints 22 and cognitive functioning [23][24][25] following TBI and that it may be particularly effective for individuals for whom pharmaceutical interventions were ineffective. 26 Furthermore, a recent review of NFT in TBI reported improvements across a number of cognitive and neuropsychiatric symptoms, such as poor attention, memory, anxiety, depression, and impulsivity. ...
... Interestingly, the cognitive functions they reported as most improved as a direct effect of treatment are memory and concentration/attention, which are two of the most commonly reported impairments following mild to moderate TBI. 40,41 Previous studies of NFT for mild TBI have indicated improvements in somatic complaints 22 and cognitive functioning. [23][24][25] Additionally, NFT has been posited to reduce symptoms associated with PTSD, [42][43][44] depression, 45 and anxiety. ...
Article
Full-text available
Introduction: Neurofeedback therapy (NFT) has demonstrated effectiveness for reducing persistent symptoms following traumatic brain injury (TBI); however, its reliance on NFT experts for administration and high number of treatment sessions limits its use in military medicine. Here, we assess the feasibility of live Z-score training (LZT)-a variant of NFT that requires fewer treatment sessions and can be administered by nonexperts-for use in a military clinical setting. Materials and methods: A single group design feasibility study was conducted to assess acceptability, tolerance, treatment satisfaction, and change in symptoms after a 6-week LZT intervention in 38 Service Members (SMs) with persistent symptoms comorbid with or secondary to mild TBI. Acceptance and feasibility were assessed using treatment completion and patients' satisfaction with treatment. To evaluate changes in symptom status, a battery of self-report questionnaires was administered at baseline, posttreatment, and 3-month follow-up to evaluate changes in psychological, neurobehavioral, sleep, pain, and headache symptoms, as well as self-efficacy in symptom management and life satisfaction. Results: Participants tolerated the treatment well and reported a positive experience. Symptom improvement was observed, including depressive, neurobehavioral, and pain-related symptoms, with effects sustained at 3-month follow-up. Conclusion: LZT treatment appears to be a feasible, non-pharmacological therapy amenable to SMs. Results from this pilot study promote further investigation of LZT as an intervention for SMs with persistent symptoms following TBI.
... Owing to its wide range of possible severity, etiology, and lesion location, cognitive impairments following ABI exhibit a high degree of variability. Nevertheless, typically affected cognitive domains include processing speed, attention, working memory, memory and learning, executive functioning, and self-regulation of emotions and behavior (Cattelani, Zettin, & Zoccolotti, 2010) -each of which have been proposed to respond well to NFT (Egner & Gruzelier, 2004;Gray, 2017;Thomas & Smith, 2015;Thompson, Thompson, & Reid-Chung, 2015;Vernon et al., 2003). ...
... A final sample of n=4 eligible studies were identified after screening. Although this final sample was significantly smaller than initially hoped for, it was not entirely unexpected given the paucity of rigorous NFT-ABI studies documented by others (May, Benson, Balon, & Boutros, 2013;Novo-Olivas, 2014;Thomas & Smith, 2015). ...
Article
Objectives Interest in neurofeedback therapies (NFTs) has grown exponentially in recent years, encouraged both by escalating public interest and the financial support of health care funding agencies. Given NFTs’ growing prevalence and anecdotally reported success in treating common effects of acquired brain injury (ABI), a systematic review of the efficacy of NFTs for the rehabilitation of ABI-related cognitive impairment is warranted. Methods Eligible studies included adult samples (18+ years) with ABI, the use of neurofeedback technology for therapeutic purposes (as opposed to assessment), the inclusion of a meaningful control group/condition, and clear cognitive–neuropsychological outcomes. Initial automated search identified n = 86 candidate articles, however, only n = 4 studies met the stated eligibility criteria. Results Results were inconsistent across studies and cognitive domains. Methodological and theoretical limitations precluded robust and coherent conclusions with respect to the cognitive rehabilitative properties of NFTs. We take the results of these systematic analyses as a reflection of the state of the literature at this time. These results offer a constructive platform to further discuss a number of methodological, theoretical, and ethical considerations relating to current and future NFT–ABI research and clinical intervention. Conclusions Given the limited quantity and quality of the available research, there appears to be insufficient evidence to comment on the efficacy of NFTs within an ABI rehabilitation context at this time. It is imperative that future work increase the level of theoretical and methodological rigour if meaningful advancements are to be made understanding and evaluating NFT–ABI applications.
... As noted above, the use of EEG biofeedback (i.e., neurofeedback)-while not the only form of biofeedback used to treat symptoms of TBI-has evolved technically and in practice to become a common and promising choice for the treatment of TBI in the field of biofeedback by measuring outputs and patterns of the organ that has been injured and comparing them to associated cognitive states and processes. 4,12,13,[17][18][19][20][21][22][23][24][25][26] The EEG, which records electrical activity of the brain over time, was introduced in 1929 and was shown to respond to volitional control via operant conditioning by 1962. 12,18,27 More recently, with the corresponding technological advances computers provided, quantitative EEG, which digitizes the EEG signal, has been introduced as the newer generation of EEG neurofeedback. ...
... 18 Although the research still lacks a large body of randomized, double-blinded, placebo-controlled studies following standardized protocols, the literature does suggest that survivors-in both civilian and military populationsof brain injuries of differing levels of severity report improvements across a wide range of complaints of problems with attention, impulse control, processing speed, shortterm memory, and mood. 4,8,[12][13][14][15][17][18][19][20][21][22][23][24][25][26][27][28][29] Research on the use of neurofeedback for veteran populations has often focused on its use when PTSD or substance abuse is comorbid with TBI from blast injuries, with significant improvements reported, once the original protocol was modified. 18,28 Generalizability from the research is complicated by not only the lack of randomized, double-blinded, placebo-controlled studies following standardized protocols, but also by the variety of types and causes of TBIs. ...
Article
Background: Neurofeedback, a type of biofeedback, is an operant conditioning treatment that has been studied for use in the treatment of traumatic brain injury (TBI) in both civilian and military populations. In this approach, users are able to see or hear representations of data related to their own physiologic responses to triggers, such as stress or distraction, in real time and, with practice, learn to alter these responses in order to reduce symptoms and/or improve performance. Objective: This article provides a brief overview of the use of biofeedback, focusing on neurofeedback, for symptoms related to TBI, with applications for both civilian and military populations, and describes a pilot study that is currently underway looking at the effects of a commercial neurofeedback device on patients with mild-to-moderate TBIs. Conclusions: Although more research, including blinded randomized controlled studies, is needed on the use of neurofeedback for TBI, the literature suggests that this approach shows promise for treating some symptoms of TBI with this modality. With further advances in technology, including at-home use of neurofeedback devices, preliminary data suggests that TBI survivors may benefit from improved motivation for treatment and some reduction of symptoms related to attention, mood, and mindfulness, with the addition of neurofeedback to treatment.
... Research efforts are underway to identify and validate effective treatments to improve a range of neurobehavioral symptoms in patients with PPCS. One promising treatment is neurofeedback therapy (NFT), with several studies reporting that NFT reduces symptoms in patients with TBI (11)(12)(13)(14)(15)(16)(17). NFT is a non-pharmacological treatment that uses operant conditioning to train patients to autonomously modulate neural activity (18,19). ...
Article
Full-text available
A specific variant of neurofeedback therapy (NFT), Live Z-Score Training (LZT), can be configured to not target specific EEG frequencies, networks, or regions of the brain, thereby permitting implicit and flexible modulation of EEG activity. In this exploratory analysis, the relationship between post-LZT changes in EEG activity and self-reported symptom reduction is evaluated in a sample of patients with persistent post-concussive symptoms (PPCS). Penalized regressions were used to identify EEG metrics associated with changes in physical, cognitive, and affective symptoms; the predictive capacity of EEG variables selected by the penalized regressions were subsequently validated using linear regression models. Post-treatment changes in theta/alpha ratio predicted reduction in pain intensity and cognitive symptoms and changes in beta-related power metrics predicted improvements in affective symptoms. No EEG changes were associated with changes in a majority of physical symptoms. These data highlight the potential for NFT to target specific EEG patterns to provide greater treatment precision for PPCS patients. This exploratory analysis is intended to promote the refinement of NFT treatment protocols to improve outcomes for patients with PPCS.
... Given the baseline QEEG readings, and the pattern of cognitive deficits, Kay Ellen appeared to be a good candidate for neurofeedback (EEG biofeedback) to modify cortical activation patterns, and hopefully to moderate both cognitive deficits and centrally mediated pain. A growing number of researchers have documented the efficacy of neurofeedback for addressing pain and cognitive deficits in TBI (15)(16)(17). Unfortunately, the case manager managing her auto insurance benefits absolutely refused any payments for neurofeedback. She was also eligible for some worker's compensation benefits for services not covered by auto insurance, but the worker's compensation office also refused to pay for neurofeedback. ...
Article
This article presents a case study in which self-hypnosis, hypnosis-assisted psychotherapy, and palliative care strategies were provided within a multi-modal integrative treatment program for a 38-year-old woman with traumatic brain injury (TBI) secondary to motor vehicle accident. Self-hypnosis was helpful in anxiety reduction and pain management. Hypnosis-assisted psychotherapy was beneficial in de-sensitizing many post-traumatic memories, and in managing post-concussion pain, including neuropathic pain and post-traumatic migraine headaches. A variety of palliative care techniques and spiritual interventions were applied to enhance sleep, moderate cognitive deficits, and enhance quality of life.
Chapter
The incidence of traumatic brain injuries (TBI) has increased in recent years, now comprising 2.5 million emergency room visits, hospitalizations, and deaths each year in the United States. TBI is frequently a chronic condition with persisting symptoms and disability. This chapter presents a case study in which self-hypnosis, hypnosis-assisted psychotherapy, and palliative care strategies were provided within a multi-modal integrative treatment program for a 38-year-old woman with TBI secondary to motor vehicle accident. Self-hypnosis was helpful in anxiety reduction and pain management. Hypnosis-assisted psychotherapy was beneficial in desensitizing many post-traumatic memories, and in managing post-concussion pain, including neuropathic pain and post-traumatic migraine headaches. A variety of palliative care techniques and spiritual interventions were applied to enhance sleep, moderate cognitive deficits, and enhance quality of life.
Chapter
Full-text available
The quantitative EEG (QEEG) has proven to be useful in the diagnosis and rehabilitation of the cognitive problems of the traumatic brain injured (TBI) subject. This chapter reviews the evidence on the use of the QEEG in discriminant analysis of TBI vs. normal individuals and the cognitive rehabilitation of the cognitive problems of the TBI patient. The research documents two cognitive activation approaches to QEEG analysis which have obtained 100 % accuracy in their diagnostic decision. Previous cognitive rehabilitation efforts have not been particularly effective in improving cognitive performance. The coordinated allocation of resource model of brain functioning was proposed as a conceptual framework to understand the brain’s electrophysiological functioning. The model employs a cognitive activation evaluation and comparison to a normative activation database approach to determine the EEG biofeedback protocols. The approach has produced an average of 2.31 standard deviation improvements in auditory and reading memory in the TBI patient. Thus, the evidence supports the use of the activation database-guided QEEG in the diagnosis and rehabilitation of the TBI patient.
Article
Each year, 1.5 million Americans suffer head injuries, and many of these injuries go untreated, while mainstream medicine uses powerful diagnostic tools and weak therapeutic ones. Neither psychopharmacology, behavioral, nor psychotherapeutic therapies hold much promise, and the symptoms of traumatic brain injury (TBI) are often misunderstood and misdiagnosed. Neurofeedback, with its EEG-based diagnostic approach and its therapies aimed at redirecting neural processing, seems ideally suited for therapy with TBI, but of the traditional neurofeedback paradigms (some going high and some low in their desired training frequencies), there is no one size that fits all. However, the flexibility bestowed by the Low Energy Neurofeedback System (LENS) form of neurofeedback breaks through entrenched maladaptive patterns and opens new possibilities for sufferers of TBI. The success of the LENS approach shows the efficiency of a specific cutting-edge technique and the efficacy of neurofeedback in general as a therapeutic modality.
Article
Neurofeedback is utilized by over 10,000 clinicians worldwide with new techniques and uses being found regularly. Z Score Neurofeedback is a new technique using a normative database to identify and target a specific individual's area of dysregulation allowing for faster and more effective treatment. The book describes how to perform z Score Neurofeedback, as well as research indicating its effectiveness for a variety of disorders including pain, depression, anxiety, substance abuse, PTSD, ADHD, TBI, headache, frontal lobe disorders, or for cognitive enhancement. Suitable for clinicians as well as researchers this book is a one stop shop for those looking to understand and use this new technique. • Contains protocols to implement Z score neurofeedback • Reviews research on disorders for which this is effective treatment • Describes advanced techniques and applications.
Article
The history and technical foundations of Z score electroencephalogram (EEG) biofeedback, including LORETA Z score biofeedback, is reviewed. The statistical standards are discussed and the step-by-step conceptual foundations of Z score biofeedback are explained. The central concept is linking symptoms to dysregulated nodes and connections between nodes in networks in the brain. The goal is to reinforce increased stability and efficiency in neural networks by reinforcing toward the center of a normal reference population. The use of Z scores for real-time or "live" biofeedback unifies different EEG metrics (e.g., power, amplitude, coherence, phase) to a single metric, i.e., the metric of the Z score with a mean=0 and a standard deviation=1 in the ideal case. Z score biofeedback also simplifies the EEG biofeedback process by providing clinicians with a "guide" or reference to determine threshold setting for biofeedback. For example, with raw score biofeedback, clinicians must guess at a threshold setting to trigger biofeedback. With Z score biofeedback, the guess work is removed since all metrics are treated the same in which the direction of biofeedback is toward Z=0.
Article
Technical Foundations of Neurofeedback provides, for the first time, an authoritative and complete account of the scientific and technical basis of EEG biofeedback. Beginning with the physiological origins of EEG rhythms, Collura describes the basis of measuring brain activity from the scalp and how brain rhythms reflect key brain regulatory processes. He then develops the theory as well as the practice of measuring, processing, and feeding back brain activity information for biofeedback training. Combining both a “top down” and a “bottom up” approach, Collura describes the core scientific principles, as well as current clinical experience and practical aspects of neurofeedback assessment and treatment therapy. Whether the reader has a technical need to understand neurofeedback, is a current or future neurofeedback practitioner, or only wants to understand the scientific basis of this important new field, this concise and authoritative book will be a key source of information.
Chapter
This chapter summarizes recent developments in neuroimaging and the neuroscience of functional networks in the brain. The linkage of low-resolution electromagnetic tomography (LORETA) source localization to structural connections in the brain as measured by diffusion tensor imaging (DTI) is presented. Methods of linking symptoms to dysregulation in nodes and connections between nodes in various brain networks are discussed with special emphasis on LORETA and sLORETA real-time neurofeedback.
Chapter
A review of recent research utilizing neurofeedback in the treatment of post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) establishes the clinical efficacy of this approach and indicates that with improved methods good clinical outcome can be achieved in fewer sessions. Preliminary studies show that improved clinical outcome can be achieved in 10 sessions or less if a symptom checklist is used to identify nodes and connections between nodes related to anxiety, memory, and frontal lobe function using low-resolution EEG tomographic analysis (LORETA) Z-score neurofeedback (LZN). PTSD is becoming understood as a set of functional neural network disturbances through the advancement of increasingly accurate and available neuroimaging techniques. Likewise, these same techniques are contributing to the understanding and treatment of mTBI. Both PTSD and mTBI involve a wide range of possible neural dysregulations, and thus, maximal treatment outcome will result from optimal specificity of assessment and treatment. Combat veterans often suffer from both PTSD and mTBI resulting in numerous complex, difficult to treat, and often disabling symptoms. This study reports on an ongoing project providing treatment to US combat veterans utilizing the 3D tomographic electroencephalogram (tEEG) technique of LZN driven by a symptom checklist, functional neural network match (SCL-FNM) method. Eleven cases are analyzed, one with a single session showing increasingly large effects of successive 2-min training rounds on the current source density of a targeted cortical region of training. Each of the other 10 cases also demonstrates specific neurophysiological normalization in the regions of training along with specific quantified progressive reduction in symptoms. Paired t-tests demonstrate learning occurred in every case. Cohen's d analyses of current source density improvements quantified large effect sizes in 9 of 10 cases and a moderate effect size in one case. A negative correlation between effect size and psychotropic medication was found along with a trend toward needing less medication as training progressed. These interactions between LZN and psychotropic drugs provide a rationale for optimal cooperation among the trainee, LZN trainer, and prescribing physicians to maximize treatment efficacy. LZN based on the SCL-FNM method is evidently both effective and specific in the treatment of PTSD and mTBI.