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Using Neurofeedback to Lower Anxiety Symptoms Using Individualized qEEG Protocols: A Pilot Study

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Abstract and Figures

Introduction: Anxiety disorders affect approximately 40 million Americans ages 18 and over (NIMH, 2015). Although qualitative and small-scale quantitative neurofeedback (NF) studies show reduction in anxiety symptoms, large-scale studies and quantitative electroencephalogram (qEEG) driven protocols are non-existent. This retrospective pilot study intended to assess whether qEEG guided amplitude NF is viable in symptom reduction of anxiety. Methods: Nineteen clients were assessed for anxiety, 14 were included in the data. Demographics include age ranges from 11–61 (M = 31.71, SD = 16.33), 9 male and 5 female; six identified as Caucasian, five as Hispanic/Latino, and three Caucasian/Hispanic ethnicity. Pre- and post-assessments included the Zung Self-Rating Anxiety Scale, Screen for Child Anxiety Related Disorders (SCARED), and the Achenbach System of Empirically Based Assessment (ASEBA). Clients received 30-min qEEG guided NF treatment sessions, twice a week. The range of attended session was 7–28 (M = 12.93, SD = 6.32). Results: Enhancement in clients’ well-being was evidenced by statistically significant improvement in symptom measures scores. Although improvements for the two most anxiety-related categories on the ASEBA were not significant, other anxiety-related categories did show significant improvement. Yet, qEEG findings were not statistically significant. Directions for future research are discussed. Keywords: anxiety; anxiety symptoms; qEEG guided amplitude neurofeedback; neurofeedback; z-scores Citation: Dreis, S. M., Gouger, A. M., Perez, E. G., Russo, G. M., Fitzsimmons, M. A., & Jones, M. S. (2015). Using Neurofeedback to Lower Anxiety Symptoms Using Individualized qEEG Protocols: A Pilot Study. NeuroRegulation, 2(3), 137–148.
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137!|! Vol. 2(3):137148 2015 doi:10.15540/nr.2.3.137
Using Neurofeedback to Lower Anxiety Symptoms Using
Individualized qEEG Protocols: A Pilot Study
Stephanie M. Dreis, Angela M. Gouger, Edward G. Perez, G. Michael Russo, Michael A.
Fitzsimmons, and Mark S. Jones*
The University of Texas at San Antonio, San Antonio, Texas, USA
Introduction: Anxiety disorders affect approximately 40 million Americans ages 18 and over (NIMH, 2015).
Although qualitative and small-scale quantitative neurofeedback (NF) studies show reduction in anxiety
symptoms, large-scale studies and quantitative electroencephalogram (qEEG) driven protocols are non-existent.
This retrospective pilot study intended to assess whether qEEG guided amplitude NF is viable in symptom
reduction of anxiety. Methods: Nineteen clients were assessed for anxiety, 14 were included in the data.
Demographics include age ranges from 1161 (M = 31.71, SD = 16.33), 9 male and 5 female; six identified as
Caucasian, five as Hispanic/Latino, and three Caucasian/Hispanic ethnicity. Pre- and post-assessments included
the Zung Self-Rating Anxiety Scale, Screen for Child Anxiety Related Disorders (SCARED), and the Achenbach
System of Empirically Based Assessment (ASEBA). Clients received 30-min qEEG guided NF treatment
sessions, twice a week. The range of attended session was 728 (M = 12.93, SD = 6.32). Results:
Enhancement in clients’ well-being was evidenced by statistically significant improvement in symptom measures
scores. Although improvements for the two most anxiety-related categories on the ASEBA were not significant,
other anxiety-related categories did show significant improvement. Yet, qEEG findings were not statistically
significant. Directions for future research are discussed.
Keywords: anxiety; anxiety symptoms; qEEG guided amplitude neurofeedback; neurofeedback; z-scores
Citation: Dreis, S. M., Gouger, A. M., Perez, E. G., Russo, G. M., Fitzsimmons, M. A., & Jones, M. S. (2015). Using Neurofeedback to Lower
Anxiety Symptoms Using Individualized qEEG Protocols: A Pilot Study. NeuroRegulation, 2(3), 137148.
*Address correspondence to: Dr. Mark Jones, Department of
Counseling, The University of Texas at San Antonio, 501 Cesar Chavez
Blvd., Durango Building 3.304E, San Antonio, TX 78207, USA. Email:
Copyright: © 2015. Dreis et al. This is an Open Access article
distributed under the terms of the Creative Commons Attribution License
Edited by:
Rex Cannon, PhD, Neural Potential, Florida, USA
Reviewed by:
John Davis, PhD, McMaster University, Ontario, Canada
Randall Lyle, PhD, Mount Mercy University, Iowa, USA
According to the National Institute of Mental Health
(NIMH), anxiety disorders rank as the top leading
diagnosis by clinicians within the mental health field.
Anxiety disorders affect approximately 18% of the
United States population, or 40 million individuals
within a given year (NIMH, 2015). While the majority
of Americans experience stress periodically within
their lifespan, individuals diagnosed with anxiety
have severe pervasive symptoms that interfere with
their daily lives. Three of the most commonly
diagnosed types of anxiety disorders are:
generalized anxiety disorder, 6.8 million adult
Americans; panic disorder, 6 million adult
Americans; and social phobia, 15 million adult
Americans (NIMH, 2015). Psychotherapy, cognitive
behavioral therapy (CBT), exposure-based
treatment, stress management techniques,
meditation, and aerobic exercise are various
therapeutic modalities that may or may not be used
in conjunction with medication in the treatment of
anxiety disorders (NIMH, 2015).
With the onset frequently developing during
childhood, many anxiety disorders can be persistent
if not treated and present more frequently in women
at a 2:1 ratio (American Psychiatric Association,
2013). A variety of symptoms are reported by
individuals with anxiety disorders including: trouble
falling asleep and staying asleep, fatigue,
headaches, and muscle tension (NIMH, 2015).
More severe symptoms can include sudden and
repeated attacks of fear, pounding and racing heart,
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and purposely excluding oneself from certain people
or places.
Literature Review
Various biofeedback modalities have been
implemented by clinicians in the treatment of anxiety
including: electromyography (EMG), peripheral
temperature, and electrodermal response (EDR)
prior to neurofeedback’s (NF) popularization (Price &
Budzynski, 2009). NF, a subcategory of
biofeedback, is a method of self-regulation which
uses a brain-computer interface to promote neural
plasticity, by providing feedback to an individual
about their brain's electrical activity at a specific
scalp location in a specified frequency range
(Cannon, 2015). NF has been used to lower anxiety
symptoms in a variety of populations, as addressed
throughout the following reviewed literature.
A study by Kerson, Sherman, and Kozlowski (2009)
illustrates how the various modalities of earlobe
temperature training, alpha suppression, and alpha
symmetry training were used in eight adults who
either were diagnosed with generalized anxiety
disorder or presented with multiple anxious
behaviors. Participants were assessed for high
alpha frequency at the International 1020 Electrode
system sites Fp1, Fp2, F3, F4, F7, and F8. A 5-min
baseline electroencephalogram (EEG) of the
participants was recorded with their eyes open for
the initial measurement and with their eyes closed
for the secondary measurement. Post-baseline
measures were also recorded 1 week after the last
NF training occurred. The initial six sessions were
used to increase the participant’s earlobe
temperature. The following 616 sessions consisted
of decreasing alpha magnitude by 10% in the
anterior lobes for 30 or more minutes. Once alpha
was suppressed, the protocol shifted to
improvement of alpha symmetry by a 15% increment
for 30 minutes or more during 832 sessions. All
sessions were conducted on a biweekly basis.
Continued assessment of participants was
conducted throughout the study by means of The
State-Trait Anxiety Inventory (STAI; Spielberger,
1983) in which a significant improvement in scores
resulted. The pre- and post-mean change in EEG
was 1.41 z-scores towards the mean. Limitations
mentioned within the study include: a limited amount
of participants, lack of variance in protocols, and the
lack of a control group.
A study conducted by Cheon et al. (2015)
researched NF implemented on 77 adults diagnosed
with various psychiatric disorders within a psychiatric
setting. The following disorders are listed in order of
prevalence according to the research: depressive
disorders, anxiety disorders, sleep disorders,
somatoform disorders, adjustment disorders, bipolar
disorder, schizophrenia, attention-
deficit/hyperactivity disorder, alcohol dependence,
game addiction, and impulse control disorder.
Protocols were designed depending on the
participant’s chief complaint (e.g., anxiety, emotional
instability, lethargy, etc.), the opinion of the attending
psychiatrist, neuropsychiatric evaluation results, and
the subjective-symptom-rating scale. The clinical
Global Impression-Severity Scale (CGI-S; Busner &
Targum, 2007) and the Hill-Castro (2002) checklist
were also implemented on a weekly basis as a
measure of treatment effectiveness. NF protocols
included training sensorimotor rhythm (SMR), beta,
and/or also contained alpha-theta training. The
various frequency bandwidths which were rewarded
during training, included: SMR from 12 to 15 Hz,
beta from 15 to 18 Hz, theta from 5 to 8 Hz, and
alpha between 8 and 12 Hz. The individualized site
locations in which training was implemented
included: Fp1, Fp2, F3, F4, F7, F8, T3, T4, C3, C4,
P1, P2, O1, O2, and Oz based on the International
1020 Electrode system. Alpha-theta training was
conducted at the PZ site location. Protocols were
evaluated and finalized during weekly NF meetings,
which included a team of three psychiatrists trained
in NF, as well as a trained NF therapist. The
number of appointments for a client’s training ranged
from 1 to 20 or more sessions. The Hill-Castro
Checklist score showed an improvement in multiple
symptom areas including anxiety (p = .0001). The
pre- and post-CGI score showed a significant
reduction in the severity of symptoms (p < .001).
Limitations mentioned within the study included
having a heterogeneous group and no control group,
as well as not utilizing the quantitative
electroencephalography (qEEG) to determine
Singer (2004) used NF on two female dancers, 27
and 52 years of age, who had persistent levels of
performance anxiety. A STAI assessment was
taken by each participant before a NF session and
before each of their major dance performances. The
course of NF treatment included 20 sessions at the
time interval of 30 min per session. Sensors were
placed on site locations T3 and T4 and thresholds
were adjusted during each session dependent upon
the participant’s response. Post assessments
indicated a significant decrease in anxiety symptoms
associated with performance. The trait anxiety
portion of the first participant’s assessment indicated
a decrease in score from 59 to 43.5, while the state
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portion underwent a decrease in score of 66 to 44.
The trait anxiety portion of the second participant's
assessment indicated a decrease in score as well
from 52 to 36, while the state portion underwent a
decrease in score of 56 to 30. Limitations to this
study included: a small sample size, lack of
individualized protocols, and no control group.
Walker (2009) implemented a study based upon
whether NF could lower anxiety symptoms for 19
clients diagnosed with post-traumatic stress disorder
(PTSD). Four clients, who were originally diagnosed
with PTSD and in the NF group, but had dropped out
after the qEEG, were included in the control group.
Each client received a qEEG using the NeuroGuide
software. Results were compared to the Lifespan
Normative database. Excessive high frequency beta
(2130 Hz) was then downtrained for five to seven
sessions for each site that presented excessive high
frequency beta; 10 Hz activity was uptrained at the
same sites. The sites were in various and multiple
areas depending on where the excessive beta was
located, as protocols were determined by a qEEG.
A self-rated anxiety Likert scale from 1 to 10 was
also used to determine the presence of anxiety
symptoms each participant had felt. The number of
sessions per individual ranged from five to seven.
Participants who had NF training had a significant
reduction in self-rated anxiety with a pre-treatment
score of 5/10 to 7/10, to a post-treatment score of
0/10 to 2/10, and 1 month after NF training the
scores remaining between 0/10 to 2/10. Subjects
who did not have NF training had little or no
reduction in self-rated anxiety 3 months after their
qEEG. Limitations with this study include using a
self-rating scale for anxiety rather than an evidence-
based assessment.
A study by Scheinost et al. (2013) evaluated 10
subjects with contamination anxiety to undergo
functional magnetic resonance imaging (fMRI) NF
training and compared their neural connectivity with
real-time functional magnetic resonance imaging (rt-
fMRI). A matched control group of 10 subjects that
received sham fMRI-NF (SNF) of their matched pair
was used. Subjects had an initial fMRI to localize
their activity in the orbitofrontal cortex (OFC) from
contamination anxiety. They then met with a
psychologist to discuss strategies for manipulating
brain activity that could later be refined during fMRI-
NF. There were eight sessions total where subjects
were shown contamination-related photos and
asked to rate their anxiety on a scale of 1 to 5. The
first and the last session consisted of subjects being
asked to implement the personal coping
mechanisms, which they would typically use to try to
lessen their anxiety. The middle six sessions
consisted of 90 min of fMRI-NF. The fMRI-NF
sessions consisted of subjects receiving cues of
when to increase activity their OFC area, when to
decrease activity, and when to rest based on their
OFC output. Resting cues included a neutral image.
Between-group differences in fMRI’s were identified
using Wilcoxon’s rank-sum test. The fMRI-NF group
reported greater self-reported reduction in anxiety (p
= 0.02) compared to the SNF group (p = 0.45). The
fMRI-NF group had significant (p < 0.05) neural
changes compared to the SNF group as recorded by
the last fMRI taken several days after the last fMRI-
NF session. The fMRI-NF group had significant
decrease in connectivity for the brain regions
associated with emotion processing, including: the
insula and adjacent regions, the hippocampi,
parahippocampal and entorhinal cortex, the right
amygdala, the brain stem in the vicinity of the
substantia nigra, the temporal pole, superior
temporal sulcus, thalamus, and fusiform gyrus. The
fMRI-NF group also had an increased degree of
connectivity that was seen in prefrontal areas
associated with emotion regulation and cognitive
control, including: right lateral prefrontal cortex and
bilateral portions of Brodmann’s area 8. This study
illustrated how changes directly resulting from fMRI-
NF were possible and how structural changes can
last days after a fMRI-NF session. This study also
supported the idea of finding and confirming a
localized area related to a symptom and using that
area for fMRI-NF. Limitations to this study include
low number of fMRI-NF sessions and a small sample
These studies illustrate how NF can be a viable tool
in lowering anxiety symptoms. They each have their
strengths and limitations. A substantial limitation is
either using the same protocol for each patient
and/or using a protocol based on symptoms alone.
Protocols based on symptoms alone and/or using
the same protocol for each patient bypasses the
time, cost, and training of running a qEEG
(Thompson & Thompson, 2003). Hammond (2010)
expresses the importance of using a qEEG to
identify heterogeneity in brain wave patterns, finding
comorbidities, and looking for effects from
Krigbaum and Wigton (2014) argue the importance
of qEEG guided and z-score NF as it allows the
clinician to develop a more individualized treatment
plan which encompasses a qEEG baseline, history,
and clinical status of the client. Wigton and
Krigbaum (2015a) further assert how 19-channel z-
score NF (19ZNF) protocols facilitate identifying the
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link between localized cortical dysfunctions and
connectivity issues associated with mental health
symptoms. In this modality, qEEG metrics are
compared to a normative database to create z-
scores; then, those z-scores are incorporated into
the NF protocol in real time during the session. This
allows for pre-treatment assessment, a helpful tool
in measuring progress with the client, and combining
real-time assessment with the operant conditioning
of NF. Thus, 19ZNF training is used to bring these
scores closer to the mean, otherwise known as
normalizing. Moreover, 19ZNF protocols also
reduce the number of sessions, which is more
economical for the clients. Wigton and Krigbaum’s
pilot study used 19ZNF to train the deviant z-scores.
Unlike Wigton and Krigbaum (2015a), this research
is a pilot study which used single-channel qEEG
guided amplitude training, rather than z-score
training, for three reasons: (1) it is commonly used
by many practitioners, (2) it is a straightforward
method for students in training to learn before
advancing to other modalities, and (3) the numerous
one- or two-channel qEEG-guided amplitude training
studies which exist in the literature, as reviewed by
Wigton and Krigbaum (2015b). Therefore, based on
the literature review, this retrospective pilot study
sought to assess whether individualized qEEG-
guided protocol amplitude NF is viable in symptom
reduction of anxiety-related disorders.
Clients contacted the Sarabia Family Counseling
Center at the University of Texas at San Antonio
(UTSA) to receive therapy and NF treatment free of
charge. Clients learned about the clinic through
community referral sources and/or university media
relations. Upon calling, clients were screened by
clinically licensed, doctoral-level students in the
UTSA Department of Counseling to determine if they
met the criteria for anxiety-spectrum disorders. If the
individual satisfied the clinical criteria, as well as the
required biweekly availability and willingness to
complete the treatment requirements on an ongoing
basis, the clients were then scheduled to meet with
a NF student clinician. Prior to completing any
formal assessments of anxiety, student clinicians
acquired a comprehensive informed consent from
each client. As retrospective research, the study
was deemed to be exempt from review by the UTSA
Institutional Review Board.
The pilot study started with 19 clients that were seen
over a period between one or two semesters;
however, the average number of sessions that
clients acquired was approximately 12.9 sessions.
In order to preserve our sample size we relaxed the
inclusion criteria to a minimum of seven sessions
per client. Three clients were excluded from the
study because they dropped out without completing
the full round of sessions or completing the final
assessments. The data sets of two clients were
excluded from the study; of the two clients that were
excluded, one client had previously received a
regimen of NF treatment and the other admitted to
daily use of cannabis. A total of 14 clients are
represented in the data. Of the included clients,
demographics consisted of 9 males and 5 females.
Clients ranged in age from 11 to 61 years of age
with the average age being 31.71 (SD = 16.33)
years of age. Six clients identified as Caucasian,
five as Hispanic/Latino, and three identified as mixed
Caucasian and Hispanic ethnicity (see Table 1).
Table 1
Client Demographics
Number of
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The student clinicians consisted of master’s-level
students within a program certified by the nationally
accredited Council for Accreditation of Counseling
and Related Education Programs (CACREP).
These students are also in the supervision phase of
pursuing their Board Certification in NF (BCN); thus,
were overseen by a certified and licensed
supervisor. Students had previously completed the
required didactic coursework that is recognized by
The Biofeedback Certification International Alliance
A within-subjects research design was implemented,
which included the following pre-conditional and
post-conditional assessments: the Screen for Child
Anxiety-Related Disorders (SCARED) for children
and adolescents, the Zung Self-Rating Anxiety Scale
for adults, the age-appropriate self-reports for the
Achenbach System of Empirically Based
Assessment (ASEBA), and qEEG. The symptom
measurements were selected on: the bases of their
focus on anxiety symptoms, widespread acceptance
in the therapeutic community, and standardization.
The qEEG measures assessed deviances from a
normative database, which were then used to
develop individualized protocols for training. Pre-
and post-assessment comparisons were made using
z-score changes, where improvement is assumed
when scores move toward the mean (z = 0). Some
of the challenges related to this form of measure are
discussed below, but z-score comparisons provide
one form of common reference with which to
compare individualized protocols across the
treatment group (Wigton & Krigbaum, 2015a).
The qEEGs were acquired via 19-channel
recordings in the eyes-closed and eyes-open
conditions in a resting state, using a BrainMaster
(BrainMaster Technologies, Inc., Bedford, Ohio)
Discovery 24 high-impedance amplifier and
NeuroGuide (Applied NeuroScience, Inc., Largo,
Florida) software. Recordings utilized correct size
Electro-Cap (Electro-Cap International, Inc., Eaton,
Ohio) 1020 electrode appliances, which were fitted
as per manufacturer’s guidelines and ear-clip leads
placed. Preparation of electrodes was performed in
a manner adequate to achieve impedance levels of
less than 5,000 Ω (Jones, 2015). NF was provided
utilizing BrainMaster Atlantis two-channel amplifiers
and BioExplorer (CyberEvolution, Inc., Seattle,
Washington) software. Electrode site preparation
was done by cleaning site, ground, and reference
locations with rubbing alcohol and abrading using
PCI prep pads and Nuprep. Gold-plated electrodes
were attached to the clients using Ten-20 paste.
Impedance measurements were taken to insure that
interelectrode impedance was less than 5,000 Ω
(Jones, 2015).
Clients agreed to attend a minimum total number of
15 NF training sessions that were to be held at the
same time, twice per week, and free of charge.
Participants were instructed to discontinue the
consumption of caffeine or any other non-essential
substances that may alter the qEEG significantly,
such as supplements or medications. At least a 24-
hour window prior to the qEEG recording was
suggested for clients to restrict consumption for non-
essential substances, unless otherwise medically
directed. All medically directed substances were
factored into qEEG interpretation and protocol
Collectively, participants underwent an average of
12.93 sessions of NF with a range of 7 to 28 total
sessions. Participants that did not meet our original
set threshold of 15 sessions were included due to
the aspect of increasing our client size for a
sufficient statistical interpretation. A total of 181
sessions were completed between all of the
participants (see Table 1). These training protocols
consisted of amplitude uptraining and/or
downtraining of selected frequency bands based on
qEEG findings. Protocol selections were based on
current research and reflect markers found to be
associated with anxiety issues (Dantendorfer et al.,
1996; Demerdzieva & Pop-Jordanova, 2011; Gold,
Fachner, & Erkkilä, 2013; Gunkelman, 2006;
Gurnee, 2000; Heller, Nitschke, Etienne, & Miller,
1997; Johnstone, Gunkelman, & Lunt, 2005;
Machleidt, Gutjahr, Muegge, & Hinrich, 1985; Price
& Budzynski, 2009; Savostyanov et al., 2009;
Siciliani, Schiavon, & Tansella, 1975; Stern, 2005, p.
196; Tharawadeepimuk & Wongsawat, 2014;
Walker, 2009).
Based on the preferences of the clients and clinical
judgment of the practitioners, feedback was
presented using a variety of formats: games,
animations, sounds, and analogical presentations
(such as the size of boxes representing the
amplitude of the respective bandpass filtered EEG
signals). Thresholds were set manually at the
beginning of the session based on the aimed
percentage of a successful reward rate of
approximately 50% of the time. Periodic
adjustments were made to the threshold settings
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within and between sessions as needed to shape
behavior towards the client’s specific treatment
goals. Records were made for each session, which
included: frequency bands, threshold settings,
session average amplitude levels, type of feedback
utilized, and significant details from client reports
and clinician impressions. EEG data was recorded
for each session.
Table 2
Training Sites and Frequency Bands for Each Client
Client #
Note. Combined sites = two 10/20 sites adjacent to selected 10/10 site. Client number column omits clients whose data was
Statistical Analysis
The statistical analysis for the symptom measure
assessments were paired t-tests using IBM SPSS
Statistics Version 22. Quantitative analysis was
performed using NeuroGuide software, which was
exported in by topographical and tabular form.
Further analysis was done using Microsoft Excel
2010 and IBM SPSS Statistics Version 22.
Computations were done for the frequency bands
trained for each client. Given sites, number of
bands, and frequency range of bands were unique
to each client (see Table 6), it was not feasible to
compare simple amplitude changes across clients.
As such, the absolute values of the positive and
negative z-scores were used instead as a way to
compare a common metric of pre- and post-changes
across clients. The process involved calculating z-
scores using NeuroGuide software, exporting the
results in tabular form using 1 Hz bins, transforming
the z-scores to use absolute value, then averaging
the transformed values for the respective frequency
band(s) used for each client. If more than one
frequency band was trained at a time (such as
downtraining and/or uptraining), the z-score values
for the bands trained were then averaged for each
client and the statistical analysis was completed
between the pre- and post-assessments as a group
using paired t-tests. As opposed to merely
averaging the absolute power at each of the
treatment sites, z-score results were used in order to
provide a common measure that was applicable
across all frequency bands. Due to the 1/frequency
characteristic of the EEG spectrum, with typical
alpha peaks, power measures are not consistent
across the frequency spectrum. In addition, alpha
power measures typically vary significantly between
eyes-closed and eyes-open recording conditions.
For example, if the power of the frequency band of
8–12 Hz changes by 1 µV, such a change may not
be comparable to a 1 µV change in the frequency
band of 2025 Hz.
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Symptom Measures
All grouped averaged pre-post comparisons of the
three assessments resulted in improvements. A
cumulative summary of these results are presented
in Table 3.
On the Zung Anxiety Scale, for 11 adult clients, the
mean of the pre-scores was 46.00 (SD = 9.07) and
the mean of the post-scores was 38.83 (SD = 7.37).
The t-test yielded a statistically significant
improvement, with t(10) = 4.59, p < 0.001. While
nine clients reported a decrease in their scores, 2 of
the 11 clients, reported an increase. See Table 4 for
the pre-post scores for each client.
For the SCARED, for three minor clients, the mean
of the pre-scores was 37.22 (SD = 14.47) and the
mean of the post-scores was 21.33 (SD = 13.65).
The t-test resulted a statistically significant
improvement, with t(2) = 27.71, p < 0.001. All clients
had improved self-report scores. See Table 5 for
the individual pre-post scores.
On the ASEBA, for all categories averaged, the
mean of the pre-scores was 63.27 (SD = 6.51) and
the mean of the post-scores was 59.33 (SD = 6.35).
The results of the t-test was a statistically significant
improvement, with t(17) = 8.75, p < 0.001.
Moreover, scores on all 18 categories of the ASEBA
improved; see Table 6 the pre-post scores for each
category. Improvements in the categories most
specific to anxiety symptoms, that is,
Anxious/Depressed and Anxiety Problems, were not
statistically significant. The checklists do, however,
assess for symptoms frequently associated with
anxiety, such as withdrawal, somatic issues, thought
problems, internalizing, and avoidance; and
improvements in these areas were statistically
Table 3
Group Averaged Pre-Post Assessment Results
Zung Anxiety
Scale (n = 11)
< 0.001
Scale (n = 3)
< 0.001
ASEBA Across
All Categories
(n = 14)
< 0.001
Table 4
Zung Anxiety Scale
Client #
Mean (SD)
46.00 (9.07)
38.83 (7.37)
Note. t(10) = 4.59, p < 0.001.
Table 5
Client #
Mean (SD)
37.22 (14.47)
21.33 (13.65)
Note. t(2) = 27.71, p < 0.001.
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Table 6
Achenbach Behavior Checklists (ASEBA)
Somatic Complaints
Thought Problems
Attention Problems
Aggressive Behavior
< .001
Critical Items
Total Problems
Depressive Problems
Anxiety Problems
Somatic Problems
ADHD Problems
Avoidant Personality
Problems (DSM)
Antisocial Personality
Problems (DSM)
Category Mean (SD)
Note. Bolded values are statistically significant.
Quantitative EEG Results
While not all clients realized improvements in z-
scores, the difference between pre- and post-
measurement showed a decrease in absolute z-
score values, averaged across all cases, from 1.21
(SD = 0.73) to 1.10 (SD = 0.62). The improvement
was not statistically significant, however. Table 7
provides the pre-post average z-scores for each
client. It should be noted that one-channel
amplitude training was employed as the method of
NF, not z-score training.
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Table 7
Results Pre-Post qEEG Z-scores
Client #
Mean (SD)
1.21 (0.73)
1.10 (0.62)
Note. Z-score pre-post difference was not statistically
Symptom improvement was shown with various
assessments including: the self-report ASEBA, Zung
Anxiety Scale, and SCARED. While two of the most
anxiety-specific categories of the ASEBA yielded
improvements that were not statistically significant,
other anxiety-related categories resulted in
significant improvement, and overall the
improvement in averaged scores across categories
were statistically significant. Taken together, the
symptom scales present evidence of a significant
improvement in the client’s sense of wellbeing.
Interestingly, two categories of the ASEBA that
showed robust improvement were Rule-Breaking
and Antisocial Personality. A number of researchers
have examined the comorbidity of anxiety disorders
and Antisocial Personality Disorder or Conduct
Disorder, with some evidence of a correlation
(Galbraith, Heimberg, Wang, Schneier, & Blanco,
2014; Goodwin & Hamilton, 2003; Hodgins, De Brito,
Chhabra, & Côté, 2010). This relationship may
serve as an added dimension to the ongoing study
based on this pilot, or as an additional focus of
The parent rating version of the SCARED was
administered, but results presented some problems
in interpretation. In one instance, the parents rated
their child in opposite waysone parent reported a
large improvement, while the other parent reported a
large worsening of symptoms. In this case there
was significant parental conflict and one parent
divulged that they were divorcing. Due to the
confounding nature of the parental reports, only self-
reports on the assessments were included for
analysis. Parental ratings can be included as the
size of the sample increases in the future.
A small sample size and the lack of a control group
was a roadblock to an effective research design in
some aspects of the study. There were also
limitations based on clients receiving therapeutic
care (as self-reported) and experimenter bias/skill
level. This experimenter bias could have resulted in
a response-expectancy effect (Kirsch, 2009).
Furthermore, some clients experienced confounding
life stressors that could have influenced treatment
and medication effects that were not present during
the pre- and post-qEEG. Treatment was provided to
clients who clearly had characteristics that
compromised the quality of data that might be
gained from them. They included clients who were
inconsistent in attendance, exhibited substance
abuse issues (data was excluded), experienced
significant life events (such as relational or financial
crises), or had mental or medical disorders that
possibly reduced the effect of the treatment. This
may have resulted in spending a portion of the
sessions engaged in active listening and numerous
client-centered or CBT therapeutic interventions in
different ways and to various extents with the clients.
The relative merits of various strategies of
controlling for these variations in the future are being
Quantitative designs are descriptive or experimental
in nature. A descriptive study establishes only
associations between variables and an experimental
usually establishes causality. Unfortunately, many
variables were not accountable or annotatable. One
such effect was positive reinforcement. The
presentation and style of secondary reinforcers
varied based on student-clinician decisions and
were not directly addressed in this study. Operant
and classical conditioning techniques were
employed to make the feedback as much of a
positive reinforcement as possible. This included
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the selection of feedback type based on client
preference. Some clients expressed preferences for
one or more of available options or classes of
options, which included: games, animations, sounds
(including music), or analogical feedback (such as
boxes that grow and shrink in size based on which
wave analysis was trained). Positive reinforcement
was also provided via verbal prompts and coaching.
As the study progresses in the future with additional
clients, it may be possible to analyze these
variations for significant differences in treatment
There was variability in the skill and experience
levels of the student counselors. Students were at
various levels in their studies within their degree
program. Some students had significant experience
with NF, while most were novices. Student
counselors who were taking an advanced NF
course, as an elective to their counseling degree
program, saw clients in the counseling department's
center. In addition to an introductory course, some
of the students had completed one or two semesters
of advanced practical and theoretical applications in
NF. During the previous courses, the students had
worked with one or more NF software systems, had
practiced performing NF on other students, and had
NF procedures designed for themselves, which were
based on qEEG analysis. Some of the students had
completed counseling skills courses, practicum and
internship hours, while others were novices to
counseling. In one case, the student had been the
counselor for the client they were seeing for NF
treatment as part of a counseling practicum course
one semester prior. Controls for the effect of
student bias and skill level differences were:
supervision from the professor who monitored via
informal verbal reports from students and clients,
session notes, closed-circuit television, and weekly
case conferences.
"Neurofeedback training is all about learning. Each
person's rate of learning is unique; some respond
more quickly than others do" (Demos, 2005, p. 127).
As such, a combined client-centered and
quantitative approach is best used in the future. In
this case, a quasi-experimental approach needs to
be designed. Clients would need to previously be
scored on self-efficacy, anxiety scores, and
education of basic NF principles. If all scales can be
quantified, then limitations, placebo effect, and
counselor technique can be assessed during the
design phase, and several uncontrolled variables
can be at least factored. Excluding students from
treating clients with whom they have any previous
clinical or personal relationship (e.g., previous
student and talk therapy clients they may have had
in practicum or internship portions of degree path).
Other client variables to control for, as affecting
possible treatment outcomes, would include: adjunct
therapies (concurrently used or attending),
medications, familial/financial/extraneous life
stressors and major life events, injuries/illnesses,
changes in sleep, and other therapeutic lifestyle
changes, that is, diet, exercise, meditation. Future
considerations need to assess whether counselor-
client therapeutic modalities need to be standardized
amongst clinicians to established protocols of
breathing techniques, mindfulness, and meditation in
hopes of decreasing variability.
A few clients in the study were taking psychotropic
medications, such as benzodiazepine-class
anxiolytics and SSRIs. While these effects on the
EEG were assessed as part of the qEEG analysis,
they remain as a confounding variable for treatment
outcomes. As the study continues with the addition
of more clients each semester, accounting for this
variable will make statistical analysis more robust.
This will be accomplished by (1) setting up a
comparison between medicated and non-medicated
clients, and (2) excluding medicated client data.
Training was conducted using amplitude measures
and monopolar site placements only. While this was
by design, it excluded other forms of NF which may
be based on connectivity measures and multiple site
placements. As noted above in the results section,
while z-score calculations were used in the statistical
analysis of EEG changes, the training did not utilize
z-score training, but qEEG-guided protocols. Two
clients, for example, were given posterior alpha
enhancement training based on qEEGs that
reflected the low-amplitude fast phenotype. One of
these clients had a fast alpha peak frequency,
showing an elevated z-score in the 1112 Hz range
with normal z-scores for 810 Hz. But, the protocol
for this client included uptraining 810 Hz (and
downtraining 2530 Hz). In this case, it was
expected that the absolute z-score might actually
show an increase, which turned out to be the case.
Although the client successfully modified the
amplitudes of both frequency bands, with
accompanying symptom improvement, these results
present a confounding factor in the z-score analysis.
The study may have also been strengthened by the
addition of a learning curve. This will be added in
future analyses.
Finally, it is worth emphasizing that the setting of the
study is a community counseling center, located on
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a university campus, operated as part of a graduate
counseling educational program. As such, the
prevailing values in the treatment are (1) the well-
being and therapeutic needs of clients, and (2) the
learning opportunities for students. Students in the
NF program are taught an integrative model of NF
and psychotherapy; as such, they naturally carried
this approach into their sessions with clients. It
became obvious to the professor and students that
these priorities, at times, took precedence over a
purely NF-based research design in ways that may
have compromised the acquisition of “clean” data. It
is hoped that as the study continues, the ongoing
addition of more clients and students will enable the
clearer identification of the sole effects of NF.
Nonetheless, the study may replicate the common
practices of most NF practitioners and hold value in
that regard.
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Received: August 5, 2015
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Published: October 8, 2015
... Overall, the study indicated that participants' anxiety symptoms based on the BAI and the GAD-7 scores reduced significantly. This result is consistent with other studies done by other researchers on different samples and different neurofeedback protocol [39], [45], [46], [47]. ...
... EEG is a tool for knowing brain waves that appear and are captured by certain electrodes (Ismail, Hanif, Mohamed, Hamzah, & Rizman, 2016;Nidal & Malik, 2014;Urigüen & Garcia-Zapirain, 2015). As a result, the five channels in the EEG found that there was significant dysregulation in Occipital lobe, which still found high anxiety in the counselee's brain (Dreis et al., 2015). The evaluation is then carried out and the counseling session is resumed by the counselee. ...
Full-text available
Counselors are striving to make sure that their counseling process is scientifically based. A new Counseling paradigm that related to neuroscience, called Neurocounseling, is acknowledged by the American Counseling Association (ACA) and became a new branch of Counseling in 2015. This study is used Neurocounseling paradigm to understanding the psychological condition of the client (student) in the counseling stage. Preliminary study showed us that 46 students from 80 students had showed phobia symptom. It means that 50% students are suffering learning disorder with various levels. We designed our research to record students with phobia symptom’s brainwaves through Electroencephalography (EEG). The record of counselee brainwave will make counselors achieve a better result of counseling because it will help them to choose the right counseling technique. We used qualitative approach and case study to find out student with phobia symptom’s brainwave and mental condition. We used some data collecting techniques: interview, observation, and documentation. The finding showed us that the main brain wave of counselee with phobia symptom is Beta wave in frequency 20-30Hz, it means counselee has a high level of anxiety. Counselee also had a deep tension on nerves and muscles during brainwaves record in the counseling process.
... Observing non-significant results in QEEG recordings between pre-and post-treatment seems to be common in NFT trials of anxiety DO (e.g., Vanathy et al., 1998;Dreis et al., 2015), and especially the older reviewed RCT studies did not even use pre-and post-treatments QEEG to measure improvements, such as Garrett & Silver (1978), Glueck & Strobel (1975), Peniston & Kulkosky (1991), Egner et al. (2002 and, Gruzelier et al. (2013 and, and However, Dadashi et al. (2015) used a waitlist group as their CG which is not able to take a placebo effect into consideration which, as elucidated in chapter 1.3.2, contributes significantly to people's perception of treatment success, as well as to changes in physiological parameters for participants of a CG. ...
Full-text available
Introduction: Alpha/Theta neurofeedback treatment (A/T NFT) has been administered to adults with anxiety disorders since the late 1960s, yet the efficacy of this treatment remains unclear. The present, single-blind study, for the first time, uses an active placebo NFT control group to test the A/T NFT protocol for trait anxiety on prodromal and clinical adult female participants. The effects this treatment has on activation and arousal states, self-perceived anxiety levels, neural oscillations, and other parameters were assessed. Methods: Twenty-seven women ranging in age from 19 through 69 who had scored higher than the 66th percentile in the STAI trait anxiety sub-scale (75% of whom had previously been diagnosed with an anxiety disorder) were randomly assigned to either the experimental (EG) or the control group (CG). The EG (n = 14) received ten sessions of A/T NFT in which alpha and theta EEG amplitudes were uptrained at Pz. The CG (n = 13) received ten sessions of active placebo NFT at Pz. During successive sessions beta- (15–19 Hz) and high beta amplitudes (20- 24 Hz) were uptrained or downtrained. Growth curve modeling (GCM) and traditional 2x5 repeated measures ANOVA were performed on the NFT sessions data to model individual and average group learning curves. Cognitive variables, such as treatment outcome expectancy, personal attribution styles, use, types, and efficacy of cognitive strategies in NFT, and correlations between NFT learning performance, time of day the NFT sessions were held, and a participant’s best or worst time to learn, were also investigated. Results: The analysis of individual learning curves, GCM, and ANOVA all confirmed that the majority of participants of the EG up-regulated absolute and relative A+T amplitudes within a NFT session, but so did the participants of the CG. However, a non-significant trend for the EG to have steeper learning curves was observed. Participants of both the EG and the CG felt significantly more deactivated by the end of a NFT session and reduced their self-perceived anxiety on all anxiety measures (STAI, BAI, GAD-7) by the end of the NFT trial. Although a trend could be observed that the EG reduced anxiety scores more than the CG, these differences did not rise to statistical significance. Lastly, no significant changes in the pre-post trial QEEG were found, although a trend of higher combined relative A+T power at the end of the trial was observed in the EG. In the EG the use of mental strategies was correlated with lower T/A ratio difference scores between the beginning and the end of the NFT trial but not with increased relative and absolute T+A amplitudes. The Time-of-day participants prefer or avoid learning did not correlate significantly with alpha or theta NFT amplitudes, i.e., NFT sessions being held during sub-optimal times of day were not associated with poorer learning performance. Conclusions: For both EG and CG absolute and relative T+A amplitudes increased within sessions and absolute and relative alpha increased across sessions although the CG protocol had not included an uptraining of alpha or theta amplitudes, nor low beta amplitudes (below 15 Hz) which may have represented upper alpha peak frequency in some of the younger participants. Thus, upregulation of beta and upper beta in NFT may be associated with alpha frequency uptraining due to functional coupling of alpha and beta EEG frequencies or it may be due to placebo and other non-specific effects such as EEG frequency drifts, alpha’s idling mode and inhibitory role during task performance, or perhaps simply that some frequency bands (alpha) are more susceptible to change and easier to train. Especially the inhibition of flanking bands in the NFT protocol, i.e., beta bands in A+T training, to prevent frequency drifts, will be necessary along with detailed GCM modeling of all frequency bands to see if and how the bands change over time and how those processes relate to NFT learning curves. Keywords: neurofeedback, EEG biofeedback, quantitative EEG, trait / state anxiety, anxiety disorders, active placebo control, alpha/theta protocol, growth curve modeling.
... The last NFT session was completed a week before the semester break, hence it was not possible to continue with more than fifteen sessions. The next study will consider an average seven to twelve hours of NFT training (17-19 sessions) as suggested by Hammond (2005b) and increasing the time This study only employed eighteen minutes per session and increasing the time to 20-30 minutes per session may yield significant improvement ( Dreis et al., 2015;Yucha & Montgomery, 2008). Since this study involved a small sample, a bigger sample will be needed for the next phase of this study by taking into account effect size to ensure a more reliable evidence of the effects of NFT on anxiety symptoms among non-clinical samples. ...
Full-text available
Anxiety is a common, universal human emotion, but excessive feelings of anxiety can negatively affect one’s life satisfaction and quality of life. Psychotherapy and medication are the most common forms of intervention for anxiety disorders. In a recent development, researchers suggested that neurofeedback training (NFT) has the potential to reduce symptoms of anxiety, claiming to be less invasive while carrying fewer side effects compared to medication. Therefore, this preliminary study sought to assess whether neurofeedback training is a viable method to improve symptoms of anxiety in the nonclinical sample. Participants were randomly assigned to two groups (neurofeedback training group or a control group). Anxiety symptoms were assessed using the Depression, Anxiety and Stress Scale (DASS-21), the Beck Anxiety Inventory (BAI), and the State-Trait Anxiety Inventory (STAI). The findings showed an overall improvement in all of the psychological measurements in the neurofeedback group hence provide additional evidence to the field of neurotherapy that neurofeedback training is a viable option to improve anxiety symptoms among university students.
... Self-regulation is related to neuroplasticity, the capacity of the brain to develop new neural pathways in response to experience and changes in the environment, and neural efficiency, which refers to a decrease in the amount of energy/resources dedicated to performing a given task. [6] Neurofeedback is reported to improve pain and fatigue of fibromyalgia, [7,8] depression and fatigue in multiple sclerosis, [9] posttraumatic stress disorder (PTSD) symptoms, [10] stress and anxiety, [11,12] and to improve athletic performance. [13] Many conditions reported to improve with neurofeedback also improve with regular meditation. ...
Objective: Cancer survivors may experience persistent physical and psychological symptoms following completion of cancer treatment. Neurofeedback is a noninvasive form of brain training reported to help with symptoms including pain, fatigue, depression, anxiety, insomnia, and cognitive decline; however, there is a lack of research exploring its use with cancer survivors. The objective of this study was to describe the experiences of neurofeedback and its impact on the lives of posttreatment cancer survivors as perceived by neurofeedback providers and cancer survivor clients. Methods: This qualitative descriptive study employed semi-structured interviews and thematic analysis of interview transcripts. A convenience sample of twelve neurofeedback providers and five cancer survivor clients participated in this study. Results: Thematic analysis revealed seven overarching themes as follows: (1) paying it forward; (2) transforming lives; (3) regaining control; (4) brain healing itself; (5) comforting experience, (6) accessibility, and (7) failure to respond. The first five themes related to benefits of neurofeedback, and the final two related to challenges of using neurofeedback with cancer survivors. Conclusions: Results support the use of neurofeedback to improve quality of life for cancer survivors; however, more research is needed to determine which neurofeedback systems and protocols are most effective for this population with persistent symptoms.
... This retrospective study intended to assess whether qEEG-guided amplitude neurofeedback (NF) is viable in symptom reduction of anxiety. This presentation updates a previously presented and published pilot study on treating anxiety symptoms with neurofeedback, based on data from 2014 to 2015 (Dreis et al., 2015). The pilot study involved a retrospective assessment of the efficacy of qEEG-guided one-channel neurofeedback for reduction of anxiety symptoms. ...
Full-text available
The Neurofeedback technique has focused on the modification of brain wave patterns for the treatment of psychological pathologies of various etiologies. This article presents the researchers' experience in the application of this technique in a case of post-traumatic stress disorder in an adult woman. In the selection of the case there was the voluntary participation of the person, the absence of previous treatment and compliance with the necessary diagnostic criteria to configure the psychopathological picture. Researchers worked with the consultant during five intervention sessions and three follow-up sessions, under a pretest - posttest design. Quantitative changes were observed in the Beta and Theta brain wave recordings, as well as qualitative changes in the reduction of symptoms associated with the disorder.
Full-text available
La técnica del Neurofeedback se ha centrado en la modificación de patrones de ondas cerebrales para el tratamiento de patologías psicológicas de diversas etiologías. Este artículo presenta la experiencia de los investigadores en la aplicación de esta técnica en un caso de Trastorno de estrés postraumático en una mujer adulta. En la selección del caso se tuvieron la participación voluntaria de la persona, inexistencia de tratamiento previo y cumplimiento de criterios diagnósticos necesarios para configurar el cuadro psicopatológico. Se trabajó con la consultante durante de cinco sesiones de intervención y tres de seguimiento, bajo un diseño pretest – postest. Se observaron cambios cuantitativos en los registros de ondas cerebrales Beta y Theta, así como cualitativos en la disminución de la sintomatología asociada al trastorno.
Despite the documented efficacy of neurofeedback (NFB) in the treatment of people with anxious symptomatology, many insurance companies identify NFB as experimental, which prohibits individuals from utilizing benefits to obtain this therapeutic treatment. In order to examine this discrepancy, the present meta‐analyses were conducted to examine the overall effectiveness of NFB, examine the impact of participant characteristics, and identify the extent of the differences in anxiety‐spectrum outcomes. Twenty‐six articles were divided based on design (12 single group (SG); 14 between‐group (BG)) and analyzed in separate meta‐analyses. Overall, results indicated that anxiety‐spectrum self‐report assessments were reduced by nearly one (SG SDM= −0.94; BG g = −0.87) standard deviation unit with relatively small degrees of bias. This study reports findings from the first exhaustive search of the literature, which included articles coming from a total of 17 databases/repositories. Applications of the findings are limited to Caucasian adults with symptoms of anxiety or PTSD.
College students experience high levels of anxiety and stress, resulting in academic, interpersonal, and functional challenges. Despite awareness of anxiety and stress amongst students, universities and colleges fail to meet their mental health needs. Neurofeedback (NFB) training, a noninvasive approach designed to regulate brain processes to mitigate anxiety and stress-based symptoms, is an innovative option to help college students. A pre-posttest control group quasi-experimental design was implemented to measure whether a treatment group reported differences in anxiety and stress (as measured by the Beck Anxiety Inventory [BAI], Perceived Stress Scale [PSS], and Social Anxiety Thought [SAT] questionnaire) as compared to a waitlist control group. Results indicated significant decreases in SAT and PSS scores between groups, with no significant difference for BAI scores. Additionally, no significant differences were found over time between groups, regardless of gender. Limitations and future recommendations are explored.
Full-text available
While there are literature reviews and meta-analytic coverage of neurofeedback (NF) studies that focus on traditional amplitude NF and slow cortical potential NF, the same is not true for quantitative electroencephalographic (qEEG)-guided NF (qNF). To that end, this is a literature review of several qNF research articles. Generally, most are found in clinical settings, address a wide variety of symptoms and diagnoses, use clinical assessments as outcome measures, employ individualized NF protocols based on qEEG findings, and define efficacy in terms of improvement on pre-post outcome measures. However, few report pre-post qEEG metrics as outcome measures. Suggestions for future research are presented.
Full-text available
Neurofeedback is gaining widespread attention across clinical and research domains. As our knowledge of the brain and its enigmatic mechanisms increase, so does the interest in harnessing these mechanisms to promote improved mental processes and reduce symptomatic issues. Neuroscience advances and neurofeedback will continue to evolve into a primary focus for learning, performance, and reduction of symptoms in psychopathology. Likewise, electroencephalographic (EEG) and source localization techniques will improve our understanding and identification of biomarker EEG patterns to better identify and ultimately classify specific patterns associated with psychological and neurological syndromes. As technology and production of devices become more prevalent, there is a growing need to define the parameters used in neurofeedback, as well as to classify the processes into specific or nonspecific factors to avoid further confounds and problems across disciplines.
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Electroencephalograph (EEG) electrode impedance measurements of 5,000 ohms or less are required by common standards of practice to minimize artifacts due to electro-magnetic interference (EMI). Some manufacturers of amplifiers geared toward the neurofeedback market do not provide on-board impedance monitoring, but provide direct current (DC) offset measurements. To examine if DC offset is a reliable measure of connection quality, measurements of DC offset and impedance, each independently taken by students in a university graduate level course in neurofeedback over a one year period were analyzed retrospectively. DC offset was not found to have predictive value of a standard impedance level. Additionally, 19 channel EEGs collected within manufacturer recommended parameters of DC offset using a high-impedance amplifier were analyzed to assess the level of EMI pollution of quantitative EEG (QEEG) data. Visible peaks of EMI in the spectra in at least one channel in each of these recordings were identified. A sample of EMI pollution of QEEG results is presented. Together, these findings suggest that DC offset is not a reliable measure of electrode connection quality. Keywords: EEG, electrode, interference, impedance, DC offset, QEEG
There were two objectives of this paper. The first objective of this paper was to observe the brain activity of Asian athletes before the match. Second, the paper aimed to study the anxiety symptom showing on the brain via QEEG (Quantitative Electroencephalography) maps. The anxiety level for Asian athletes can be classified using the index of brain topographic map (Absolute power) relative to the normative database used for analysis. Firstly, Asian athletes have to complete revised competitive state anxiety inventory-2 (CSAI-2R) questionnaires. The Asian athletes then were recorded for their QEEG twice in 2 weeks (1 time/week) before competing in a match. In the competition, the anxiety symptom and performance of Asian athletes are observed and their feedbacks from the coach are asked. Lastly, the anxiety level is classified from results of QEEG maps, the CSAI-2R questionnaires and condition in the competition. The result of anxiety level showed that the quantity of alpha frequency band in posterior head region (parietal and occipital lobes) is less than the normal condition in term of brain topographic map. In addition, amateur Asian athletes have lower quantity of alpha frequency band than the experienced Asian athletes when the time of competition becomes nearer. Furthermore, the focal area that showed in brain connectivity (Coherence) was presented in lower interactions between position to position in the frontal lobe.
This chapter briefly reviews definitions of anxiety and anxiety disorders, identifies specific EEG and QEEG patterns which in clinical practice and/or research have been found to be correlates of some anxiety disorders, and cites neurofeedback protocols for treating anxiety as suggested by experienced clinicians and/or by research. Augmenting procedures such as breathwork, muscle relaxation, heart rate variability training, AVE, EMDR, cognitive behavioral therapy, and other psychotherapy forms are given only a brief mention. That anxiety states are complex disorders is obvious, not only because of the multiple patterns of differences displayed by QEEG, fMRI and SPECT, but also due to the disparate manifest emotional/behavioral symptoms that may or may not correlate with the above physiological measurements. Despite the diversity of EEG anxiety patterns, clusters of them often occur, constituting an emotional/behavioral clinical picture such as obsessive-compulsive disorder. There are some QEEG patterns found by research, and/or through clinical experience, to be associated with general or specific anxiety disorders, and there are some neurofeedback training protocols rather consistently cited by expert clinicians as efficacious for treatment of these disorders. For example, given a fairly clear anxiety-related behavioral state, or given one or more specific EEG/QEEG pattern, attention to increasing posterior alpha power and/or decreasing beta power in frontal or temporal sites is a commonly reported approach.
Neurofeedback (NF) is gaining recognition as an evidence-based intervention grounded in learning theory, and 19-channel z-score NF (19ZNF) is a new NF model. This pilot study sought to evaluate the efficacy of 19ZNF in a clinical setting. Outcome measures framed groups such that 19ZNF was evaluated, as it relates to the neuropsychological constructs of attention (n = 10), executive function (n = 12), behavior (n = 14), and electrocortical functioning (n = 21). One-tailed t tests compared pre-post difference scores. For all pre-post comparisons, the direction of change was in the predicted direction, and differences were statistically significant (p = .000 to p = .008, effect sizes 1.29 to 3.42). Results suggest 19ZNF improved attention, executive function, behavior, and electrocortical function. This study provides beginning evidence of 19ZNF's efficacy, adds to what is known about 19ZNF, and offers an innovative approach for using quantitative electroencephalographic (QEEG) metrics as outcome measures. © 2015 SAGE Publications.
Over the years, several new models and variations of neurofeedback (NF) have been developed. As such, NF has grown from traditional amplitude based modalities to now include slow cortical potential NF, as well as various approaches grounded in QEEG technology, including z-score NF models. These differing modalities have important implications in terms of outcomes, the number of sessions required, and treatment specificity. This, in turn, impacts clinical practice, research, and marketing considerations. In an effort to gain some perspective for where the field is today, a comparative review is presented to illustrate the importance of noting what particular modality is being referenced when discussing NF.