ArticlePDF Available

EEG Changes in Traumatic Brain Injured Patients After Cognitive Rehabilitation

Authors:
Article

EEG Changes in Traumatic Brain Injured Patients After Cognitive Rehabilitation

Abstract and Figures

Background. Little research has addressed cognitive rehabilitation and changes in the electroencephalogram (EEG) following training of traumatic brain injured (TBI) patients suffering from attention deficits because of their injury. This study focuses on changes in relative and absolute power in frontal, central and posterior regions of the TBI patients' brain following training on attention skills using a software program called Captain's Log.Methods. The five participants–aged 20 to 45 years–received 22 sessions of training on their attention skills. Their attention skills were assessed at the beginning and end of the research study through a variety of psychometrics as well as through scaled self-reports. Their EEG was also recorded before and after training, during eyes-open resting baseline, eyes-closed resting baseline, eight cognitive tasks and a post-tasks eyes-open resting condition. Only the first two baselines were analyzed in the present study. (The rest of the conditions will be analyzed in another study.) The hypotheses that the participants' delta, theta, and alpha relative and absolute power would decrease and that their beta power would increase following training were analyzed.Results. Although there were significant post-task changes in four out of the five case studies in relative and absolute power, both in eyes-closed and eyes-open conditions, the most systematic change was the decrease of alpha in the eyes-closed condition.Conclusion. These new findings link training in cognitive processes with EEG changes.
Content may be subject to copyright.
EEG Changes
in Traumatic Brain Injured Patients
After Cognitive Rehabilitation
Stamatina Stathopoulou, PhD
Joel F. Lubar, PhD
ABSTRACT. Background. Little research has addressed cognitive re-
habilitation and changes in the electroencephalogram (EEG) following
training of traumatic brain injured (TBI) patients suffering from atten-
tion deficits because of their injury. This study focuses on changes in rel-
ative and absolute power in frontal, central and posterior regions of the
TBI patients’ brain following training on attention skills using a soft-
ware program called Captain’s Log.
Methods. The five participants–aged 20 to 45 years–received 22 ses-
sions of training on their attention skills. Their attention skills were
assessed at the beginning and end of the research study through a variety
of psychometrics as well as through scaled self-reports. Their EEG was
also recorded before and after training, during eyes-open resting base-
line, eyes-closed resting baseline, eight cognitive tasks and a post-tasks
eyes-open resting condition. Only the first two baselines were analyzed
in the present study. (The rest of the conditions will be analyzed in an-
other study.) The hypotheses that the participants’ delta, theta, and alpha
relative and absolute power would decrease and that their beta power
would increase following training were analyzed.
Results. Although there were significant post-task changes in four out
of the five case studies in relative and absolute power, both in eyes-closed
Please note that this electronic prepublication galley may contain typographical errors and may be missing
artwork, such as charts, photographs, etc. Pagination in this version will differ from the published version.
Stamatina Stathopoulou received Masters and PhD degrees in Experimental Psy-
chology from the University of Tennessee, Knoxville, Tennessee, where she worked
under the supervision of Joel F. Lubar, Professor of Psychology.
Address correspondence to: Stamatina Stathopoulou (E-mail: tinastath@mailcity.
com) or Joel F. Lubar (E-mail: jlubar@utk.edu).
Journal of Neurotherapy, Vol. 8(2) 2004
http://www.haworthpress.com/web/JN
2004 by The Haworth Press, Inc. All rights reserved.
Digital Object Identifier: 10.1300/J184v08n02_03 21
and eyes-open conditions, the most systematic change was the decrease
of alpha in the eyes-closed condition.
Conclusion. These new findings link training in cognitive processes
with EEG changes. [Article copies available for a fee from The HaworthDoc-
ument Delivery Service: 1-800-HAWORTH. E-mail address: <docdelivery@
haworthpress.com> Website: <http://www.HaworthPress.com> 2004 by The
Haworth Press, Inc. All rights reserved.]
KEYWORDS. Traumatic brain injury, EEG, cognitive rehabilitation,
attention deficits, software programs
INTRODUCTION
Despite the fact that research already exists concerning electroenceph-
alographic (EEG) changes followed by behavior changes (Kuhlman &
Kaplan, 1979; Lantz & Sterman, 1988; Lubar & Lubar, 1984), little research
has addressed the issue of behavior changes followed by EEG changes. The
purpose of this study is to investigate this relatively new area–one type of cog-
nitive rehabilitation for traumatic brain injured (TBI) patients.
Traumatic Brain Injury
The National Head Injury Foundation (1985) defines head injury as a “trau-
matic insult to the brain capable of producing physical, intellectual, emo-
tional, social, and vocational changes.” This definition implies brain damage
and associated dysfunction such as the inability to coordinate movements,
speech, memory, reasoning, or modulation of behavior. While not denying
that pathology may be diffuse, research suggests that lacerations, contusions
and hemorrhages as well as diffuse axonal injury (DAI), which is the diffuse
degeneration of the cerebral white matter, are more prominent in the frontal
and temporal regions (Sohlberg & Mateer, 1989). Finally, the shearing, tear-
ing, and stretching of axons may also result in true disconnections between
prefrontal, limbic, and association cortices leading to disturbances of the
cognitive and executive processes (Langfitt & Gennarelli, 1982). Executive
and cognitive disturbances can be treated with different kinds of therapy,
cognitive rehabilitation training being the most commonly cited successful
training (Prigatano, 1986; Adamovich, Henderson & Auerbach, 1985;
Goldstein & Ruthven, 1983).
Cognitive Rehabilitation and Spontaneous Recovery
Cognitive rehabilitation refers to the therapeutic process of increasing or
improving an individual’s capacity to process and use incoming information
so as to allow increased functioning in everyday life. This includes both meth-
ods to restore and compensate for cognitive functions. Assessment of a treat-
22 JOURNAL OF NEUROTHERAPY
ment’s efficacy constitutes a difficult task with the most fundamental obstacle
arising from individual differences in spontaneous recovery. The individual
differences most relevant to recovery include intraspecies differences in brain
organization, location of lesion, rate of improvement immediately following
injury, premorbid level of functioning, extent of neurological damage, time
post-onset and age at injury (Sohlberg & Mateer, 1989).
A primary executive function in need of cognitive rehabilitation is atten-
tion. Mild to severe dysfunction of the attention skills of the individual consti-
tutes one of the main complications due to damage to the frontal and temporal
lobes (Finlayson & Garner, 1994).
Types of Attentional Dysfunction and Their Representation
in the Brain
There are different types of attention that may be disrupted. Sustained at-
tention involves the duration over time one is able to maintain performance, as
well as the consistency of performance over that period. Selective attention is
defined as the ability to focus on relevant stimuli in the presence of distracting
stimuli and select information for conscious processing. Divided attention is
defined as the ability to either do more than one activity simultaneously, or to
attend multiple stimuli. Alternating attention constitutes the ability to switch
from one stimulus or activity to another (Ashley & Krych, 1995).
Starting with sustained attention, it has been noted that prefrontal and pari-
etal areas, preferentially in the right hemisphere, are frequently engaged
(Lewin et al., 1996; Pardo, Fox & Raichle, 1991; Haxby et al., 1994). Coull,
Frackowiak, and Frith (1998) confirmed earlier reports of fronto-parietal-
thalamic network associated with sustained attention and prefrontal cortex
and anterior cingulate activation associated with selective responding. Their
work showed that the right inferior frontal and parietal cortices are differen-
tially activated by increasing time on task during the selective (S) vs. non-se-
lective (NS) task. Specifically, they showed that regional cerebral blood flow
(rCBF) decreases with increasing time spent performing the NS task but not
the S task. Thus, it seems that Coull et al. identified the neuroanatomical corre-
lates of each process separately, and provided the neuroanatomical location of
the functional interaction between sustained attention and the process of selec-
tively monitoring for target objects.
Selective attention is characterized by increased activity in posterior re-
gions involved in stimulus processing. Different regions seem to be involved
depending on the specific attribute that is attended to (Corbetta, Miezin,
Dobmeyer, Shulman & Petersen, 1990). Recent examples of attentional mod-
ulation of auditory regions are provided in Woodruff et al. (1996) and Pugh et
al. (1996) where the role of parietal cortex, especially the inferior parietal lobe,
is suggested to control selective attention. Several of the studies on selective
attention are based on the Stroop test, which is associated with activations in
Scientific Articles 23
the anterior cingulate cortex and the left prefrontal cortex (Taylor, Komblum,
Lauber, Minoshima & Koeppe, 1997). Studies by Rees and Lavie (2001), as
well as Saenz, Buracas, and Boynton (2002), point to the role of the occipital
cortex in selective attention. Other studies suggest that the cerebellum may be
part of the selective attention network as well (Vandenberghe, Gitelman,
Parrish & Mesulam, 2001; Sevostianov, Fromm, Nechaev, Horwitz & Braun,
2002).
As far as divided attention is concerned, it seems that when two tasks are
performed simultaneously, performance often deteriorates, with simultaneous
increases in reaction time and error rate. Klingberg (1998) considered three
potential neurophysiological mechanisms behind this deterioration in perfor-
mance: (a) dual-task performance requires additional cognitive operations and
activation of cortical areas in addition to those active during single-task per-
formance, (b) two tasks interfere if they require activation of the same part of
cortex, and (c) cross-modal inhibition causes interference between two tasks
involving stimuli from different sensory modalities. Klingberg concluded that
there is no separate cortical area that gets activated due to any dual task, but
that the area activated depends on the type of the specific cognitive process. In
addition, according to the studies of Le, Pardo and Hu (1998) and Ravizza and
Ivry (2001), the cerebellum has been implicated in alternating attention. An-
other brain structure which gets also activated during alternating attention is
the prefrontal cortex (Ravizza & Ciranni, 2002; Koski & Petrides, 2001). Table
1 summarizes the three types of attentional dysfunction, their representation in
the brain and the best tests to measure these specific types of attention.
Figure 1 depicts the three types of attention portrayed on the brain repre-
sented in the right and left hemisphere.
Cognitive Tests and EEG as Assessment Measures
for TBI and ADD
Several kinds of cognitive tests or subtests are currently used in order to as-
sess attention. The WAIS-R Digit Span subtest (Weschler, 1981) is commonly
used to test immediate or working memory, the WAIS-R Digit Symbol subtest
(Weschler, 1981) to test information processing speed performance, the Paced
Auditory Serial Addition Test (PASAT; Gronwall, 1977) to assess divided at-
tention skills, and the Stroop Test (Stroop, 1935), to test distractibility atten-
tion capacities. The Integrative Visual and Auditory Continuous Performance
Test (IVA CPT; Sandford & Turner, 1995) tests all types of attention deficits
(Solberg & Mateer, 1989).
On the other hand, the quantitative electroencephalogram (QEEG)–the re-
cordings from electrodes of the electric brain potentials–constitutes different
methodology for the study of the dynamic functional aspects of brain function
(Hudspeth & Pribram, 1992). QEEG is a highly validated method for assess-
ing attention deficit disorders.
24 JOURNAL OF NEUROTHERAPY
TABLE 1. Types of Attention, Associated Brain Regions and Related Psychometrics
Types of attention Representation on the brain Tests
Sustained Prefrontal/Parietal right hemisphere IVA-Scales on Consistency, Focus, Stamina; Digit Span and PASAT
Selective Parietal cortex, inferior parietal lobe
prefrontal, occipital
IVA-Scales on Prudence, Vigilance, Comprehension; Digit Symbol
Divided Depends on cognitive task IVA-Scales on Prudence and Speed
Alternating Prefrontal, cerebellum IVA-Scales on Speed, Balance, Readiness, Consistency and Focus; PASAT
25
26 JOURNAL OF NEUROTHERAPY
Selective attention Sustained attention Alternating attention
FIGURE 1. Types of attention represented on two hemispheres. Upper image:
Left hemisphere. Lower image: Right hemisphere.
Chabot, Orgill, Crawford, Harris, and Serfontein (1999) studied a sample
of 130 children with attention disorders. The children were evaluated with the
Conners and DSM III rating scales and with Neurometric QEEG before and 6
to 14 months after treatment with stimulants. Significant QEEG differences
were found between the non-clinical control group and the children with atten-
tion problems (p < .001) before treatment. QEEG abnormalities involved in-
creased theta or alpha power greatest in frontal regions, frontal theta/alpha
hypercoherence, and posterior interhemispheric power asymmetry. Coher-
ence is analogous to a cross-correlation coefficient in the frequency domain
and thus is a metric of the amount of shared activity between the two regions.
The degree of correspondence between behavioral and QEEG changes after
the stimulant treatment was 78.5 percent. Research on Attention Deficit Disor-
der (ADD) patients has shown an increase of the slow wave theta and more
specifically an increase in the theta-beta ratio in the frontal or central regions,
depending on the age of the patient (Monastra et al., 1999).
In a study conducted by Thatcher, Cantor, McAlaster, Geisler, and Krause
(1991), a number of variables were used to study the development of prognos-
tic equations for patients with closed-head injury one year after the accident.
The variables studied were: EEG recording from 19 scalp locations, Computed
Transaxial Tomography (CT) scan, Glasgow Coma Scale (GCS) and the
Rappaport Disability Rating Scale (DRS). According to the results, the best
predictors of outcome in both the discriminant analyses and the regression
analyses were the EEG measures, coherence, and phase. More specifically, in
another study conducted by Thatcher, Walker, Gerson and Geisler (1989),
head injured patients showed increased coherence and decreased phase in
frontal and frontal-temporal regions, decreased power differences between
posterior and anterior cortical regions and reduced alpha power in posterior
cortical regions.
On the other hand, prior research regarding QEEG and TBI (Randolph &
Miller, 1988) has shown that the head injured group displays higher ampli-
tudes, except in the alpha band of 8-12 Hz, and greater variance than the con-
trol group in the occipital and especially the temporal placements. The
increased amplitudes, amplitude variance, and reduced correlation coeffi-
cients at the temporal sites of the closed-head injured patients are presumed to
reflect areas of dysfunctional cortex. The same patients when asked to partici-
pate in cognitive tasks demanding increased arousal showed increases in am-
plitude in delta (0-4 Hz) and beta bands (12-32 Hz) and decreases in alpha and
theta (4-8 Hz) bands.
Increased theta power in brain-injured patients was also reported by Mont-
gomery et al. (1991) even after a six-month period following the accident. A
predominance of slow waves was also reported by Enomoto, Ono, Nose, Maki
and Tsukada (1986) from 280 cases of minor head-injured patients.
Scientific Articles 27
EEG Biofeedback
Almost 25 years ago, a treatment procedure called EEG biofeedback was
developed. It constitutes an operant conditioning procedure, where the indi-
vidual modifies the amplitude, frequency or coherence of the neurophys-
iological dynamics of his/her own brain (Lubar, 1989). It has been found to be
effective in treating attention deficit problems both in ADD individuals
(Shouse & Lubar, 1979; Lubar & Lubar, 1984; Linden, Habib & Radojevic,
1996; Tansey, 1993; Lubar, Swartwood, Swartwood & O’ Donnell, 1995) and
TBI patients with attentional problems (Ramos, 1998). Different paradigms
have been used including Sensory Motor Rhythm (SMR) biofeedback (Tan-
sey & Bruner, 1983; Lubar & Lubar 1984), alpha training (Nall, 1973), hemi-
sphere-specific biofeedback (Patmon & Murphy, 1978) and theta-beta
training (Lubar et al., 1995; Alhambra, Fowler & Alhambra, 1995). Theta-
beta training, where individuals are trained to increase beta and decrease theta,
seems to give the most promising results (Ramirez, Desantis & Opler, 2001).
Effective results were also seen in the training of TBI patients with attentional
deficits. In Ramos’ (1998) study, TBI patients were trained to decrease their
theta and increase their beta waves, leading in less than 20 sessions to a signifi-
cant improvement in their attention deficit problems. Similarly, in Hamilton’s
research study (1997), 23 TBI participants were trained using EEG biofeed-
back to increase beta and decrease theta wave activity, leading in 24 sessions
to an increase in their level of vigilance and an improvement in their global
functioning.
Software Programs for Training Attention Skills
EEG biofeedback is not the only method for treating attention deficits.
Computerized attention training is another promising approach. A number of
studies have found evidence for the efficacy of a microcomputer-based
approach to the rehabilitation of attention skills in brain injury (Baribeau, Ethier &
Braun, 1989; Skinner & Trachman, 1985; Sohlberg & Mateer, 1989). Most of
the programs used in these studies use the Process-Specific Approach to cog-
nitive rehabilitation, where repeated administration of hierarchically orga-
nized treatment tasks target distinct, theoretically derived components of a
cognitive process. Initial studies on the Process-Specific Approach are en-
couraging (Solberg & Mateer, 1987). Microcomputer use fits well within the
context of the Process-Specific Approach. Furthermore, some of the advan-
tages of microcomputer use in cognitive rehabilitation are: consistent, often
adjustable, rate of stimulus presentation; automatic collection and tabulation
of performance data; efficient administration of tedious practice tasks; objec-
28 JOURNAL OF NEUROTHERAPY
tive feedback; freeing of clinicians to observe and record valuable qualitative
data that may be lost or forgotten in the course of administration (Solberg &
Mateer, 1989).
Using a group experimental design, Baribeau et al. (1989) examined the ef-
fects of computerized cognitive rehabilitation on selective attention in closed-
head injury patients using auditory event related potentials (ERP) as a depend-
ent variable. Improvements on ERP measures as a function of computerized
cognitive rehabilitation were attributed to “improved motivation, more effort,
and better capacity to follow experimental instructions” as opposed to improvement
in selective attention mechanisms. Skinner and Trachman (1985) also found
improvements in motivation which could, in part, explain the increases in at-
tention that were found. On the other hand, Tinius and Tinius (2000) found
significant improvement on full scale attention and full scale response accu-
racy of a continuous performance task in the TBI and ADHD group following
EEG biofeedback and cognitive retraining with a software program, The Cap-
tain’s Log.
The equivocal results in this area of computerized cognitive rehabilitation
have been attributed to differences in the definition and measurement of atten-
tion skills, as well as various treatment and patient parameters (Ponsford &
Kinsella, 1988).
Rationale, Purpose and Hypotheses of the Study
The literature on EEG biofeedback (mentioned above) suggests that
improvement of attentional deficits follows training of different frequency bands.
This training consists of either increasing or decreasing those frequencies that
are outside of the normative range based on QEEG with a normative database.
The rationale behind this study is that while EEG biofeedback constitutes a di-
rect way to alter brain waves, computerized cognitive rehabilitation may
achieve the same results in a more indirect way: the training of attentional def-
icits will evoke modification of the amplitude of frequency bands. The pur-
pose of this study is to test the relationship between cognitive rehabilitation
and changes in the EEG patterns of TBI patients with attentional deficits.
There are indications that people with attentional problems have increased
power in delta, theta and alpha frequency bands (i.e., the bands involved in
drowsier conditions) and decreased power in the beta frequency band (i.e., the
band more active during cognitive processes). By training TBI patients with
attentional deficits with a software program called Captain’s Log, effectively
used by Tinius and Tinius (2000), reduction in the patients’ delta, theta and al-
pha relative and absolute power is expected as well as an increase in beta in both
relative and absolute power. These changes are expected to be seen both in eyes-
Scientific Articles 29
closed and eyes-open conditions. The psychometrics as well as their scaled
self-reports have been used in order to assess the participants’ post-training im-
provement or deterioration in different types of attention.
METHOD
Participants
The proposal was distributed to the Association of Brain Injured Patients of
Knoxville, to the Disability Service of the University of Tennessee and to the
local newspaper, the Knoxville News-Sentinel. The five patients who partici-
pated in the project were instructed regarding the scope and the procedures of
the study, signed the consent form and agreed to participate in exchange for
the free therapy sessions offered to them. Their ages ranged from 20 to 45.
There were two males and three females. The participants who were accepted
for the study had experienced the accident causing their brain injury at least
one year prior to their selection for this study. The experimenter wanted to
avoid any effects resulting from spontaneous recovery, which usually occur
during the first six months after the accident. Their accidents had occurred at
different time periods, starting from one and a half to twenty-three years be-
fore coming to the study. None of the participants were engaged in any therapy
or medication during the period of the study. All of the post-injury information
mentioned below comes from medical records.
M. F. was a 48-year-old female. She had a motor accident one and a half
years prior to the study. Her left hemisphere was injured. She did not stay in a
coma. She was in the emergency room for four hours and in the hospital for
two and a half months. She had post-traumatic amnesia for the first two
months following the accident.
D. S. was a 38-year-old female. She had a motor accident 23 years ago.
Damage occurred in her frontal lobe, especially the left frontal, and the left
temporal. She also had some lacerations in the occipital area. She did not stay
in coma but she had post-traumatic amnesia and was not aware of her sur-
roundings for seven days. She stayed in the Intensive Care Unit for seven days
and in the hospital for 14 days.
S. M. was a 40-year-old male. He had a motor accident eight years ago.
Damage occurred in the left temporal/hippocampal area. He stayed in coma
for three months and in the hospital for four and a half months. He reported
still having post-traumatic amnesia.
R. M. was a 32-year-old male. He had his motor accident 14 years ago.
Damage occurred to the right hemisphere, frontal lobe and optical nerve. He
had a massive right to left shift, with a right subdural hematoma two cm in di-
ameter. He later developed a small subdural hydroma in the left frontal region
and in the right occipital region. He stayed in coma for 10 weeks, in an emer-
30 JOURNAL OF NEUROTHERAPY
gency room for six weeks and in the hospital for a year and a half. At the time
of the study he suffered both from anterograde and retrograde amnesia.
R. Q. was a 20-year-old female. She had a motor vehicle accident six years
ago. Damage occurred mainly in the right posterior lobe and left thalamic area.
She stayed in coma for 24 days, in the emergency room for three hours, in the
Intensive Care Unit for 72 hours and in the hospital for four months. She re-
ported still having post-traumatic amnesia.
Assessment
All participants took the WAIS-R Digit Span subtest (Weschler, 1981), the
WAIS-R Digit Symbol subtest (Weschler, 1981), the PASAT (Gronwall,
1977), and the Integrated Visual and Auditory Continuous Performance Test
(IVA CPT; Sandford & Turner, 1995). Digit Span assesses working memory,
short-term memory, sequential processing, learning ability, sustained and se-
lective attention. Digit Symbol assesses perceptual organization, sequential
processing, learning ability, visual short-term memory, visual-motor coordi-
nation, sustained and selective attention. PASAT assesses information pro-
cessing skills, sustained and selective attention and the IVA CPT assesses all
different types of attention capacities for both audition and vision. More spe-
cifically, the IVA CPT scales for Prudence and Vigilance assess focused atten-
tion; the scales for Stamina, Consistency and Focus assess sustained attention;
the scales for Prudence, Vigilance and Comprehension assess selective atten-
tion; the scales for Speed, Balance, Readiness, Consistency and Focus assess
alternating attention, and the scales for Prudence and Speed assess divided at-
tention.
In the WAIS-R Digit Span subtest, the administrator orally presents num-
bers and the test-taker repeats them. In the first part, the numbers have to be re-
peated in the same order as presented; however, in the second part they have to
be repeated backwards. In the WAIS-R Digit Symbol there are nine symbols
paired with nine digits. The examinee has one and a half minutes to fill in as
many symbols as he can under the numbers on the answer sheet. In the PASAT
numbers are orally presented from a tape; the individual has to add each num-
ber he/she hears to the previous number and orally present the total. In the IVA
CPT test, the participant hears or sees on the screen either the number “1” or
the number “2” and must click the mouse only when he hears or sees number
“1.”
A scaled self-report (questionnaire) regarding attention and memory skills
was given to each participant individually during the first session. The possi-
ble answers ranged from one to five, with “one” meaning “no problem at all”
and “five” meaning “severe problem.” The experimenter created this ques-
tionnaire based on a review of different types of attention and memory by
Solberg and Mateer (1989).
Scientific Articles 31
The four different assessment tools and the scaled self-report were adminis-
tered in order to assess different kinds of attention and the actual improvement
or deterioration of the participants’ attention skills after intervention. The cog-
nitive rehabilitation software program used to train the TBI patients with
attentional deficits for the remediation of their attentional deficits was the
Captain’s Log program, Version 1992 (Sandford, 1992).
In the Captain’s Log “Attention Skills Tasks,” different kinds of tasks were
involved. They included tasks on vigilance, inattention, prudence, impulsivity, fo-
cus, variability and speed. The participants usually have to accurately select,
discriminate or match visual pictures or sounds.
Apparatus
EEG was recorded with a Lexicor Neuro-Search 24 channel EEG recorder,
using an Electro-Cap with electrodes set according to the 10/20 international
standard. The Captain’s Log program was presented on a computer screen 50
cm from the participants’ eyes. The participants responded using the computer
mouse. Speakers with adjustable volume were also used.
Procedure
A series of five single-subject experiments was conducted. During the first
session, the participants signed the consent form, took their assessment tests
and their scaled self-reports. The assessment tests and the scaled self-reports
together lasted for about two hours. The experimenter also examined their
medical records to verify and get information about their brain injury condi-
tion. During the second session, an eyes-open/eyes-closed EEG baseline, a re-
cording during eight cognitive tasks and a second post-task eyes-open
recording took place. EEG activity was recorded using a 19-channel electrode
cap to measure the participants’ brain electrical activity for deviations from a
normative database. EEG was recorded according to the 10/20 system con-
nected to a Lexicor Neuro-Search 24 EEG recorder. Cap electrodes were filled
with electrolyte gel, gently rubbed into the scalp until impedance reached less
than 5K ohms. Recording was referenced to the two ear lobes with additional
electrodes. In the eyes-open baseline recording, the participants had to fixate
their eyes on a point on the screen for three minutes, while in the eyes-closed
baseline they just had to close their eyes and relax. The setup up period lasted
for 40 minutes, the learning period to familiarize the participant with the
eyes-open and eyes-closed baseline recording lasted for about five minutes,
and the actual recording for about 35 minutes.
Training started in the third meeting. Twenty-two training sessions were
given individually to each one of the participants. They were trained three
times per week for the remediation of their attention skills, 50 minutes per ses-
sion.
32 JOURNAL OF NEUROTHERAPY
For each TBI participant his/her degree of attentional deficit differed
slightly from the others. However, the five participants show all four types of
attentional deficits: sustained, selective, divided and alternating attention.
These deficits were assessed through the use of the psychometric tests and
scaled self-reports. Thus, all five of them were trained principally on the same
tasks of the Captain’s Log program. More specifically, the skills they were
trained on were: visual spatial memory, visual motor skills, visual alternating
attention, verbal memory, auditory memory, working memory, memory for
figures, choice reaction time, auditory discrimination and perceptual skills.
The EEG recording, the psychological assessments and the training were
conducted in the Brain Research Laboratory of the University of Tennessee,
Knoxville. The two rooms used for the study were specifically designed to be
free of visual and auditory distraction. There were no windows. Two chairs, a
table and a computer were placed in the room. During assessment, recording
and training no one else was allowed in the room except the participant and the
experimenter.
At the end of the intervention, all the assessment tests and scaled-self re-
ports were administered again. In the next two meetings, two EEG recordings
took place. In the pre-training EEG recording as well as in the first post-train-
ing EEG recording, the participants’ eyes-open and eyes-closed baselines
were measured and they were also engaged at the “beginner” level (level 1) of
the Captain’s Log cognitive tasks. On the second post-training recording, they
were engaged in the “advanced” level (level 3) of the cognitive tasks.
Independent Variable
The variable to be manipulated was the time period before and after train-
ing.
Dependent Variables
The dependent variables are the differences in psychometrics and scaled
self-reports before and after training. The psychometrics used were the
WAIS-R Digit Span Subtest (Weschler, 1981), the WAIS-R Digit Symbol
Subtest (Weschler, 1981), the PASAT (Gronwall, 1977), and the IVA CPT
(Sandford & Turner, 1995). Other dependent variables were the differences
before and after training in the frequency bands delta, theta, alpha and beta,
relative and absolute power in the frontal, central and posterior regions during
eyes-open and eyes-closed baseline conditions. In order to avoid influence by
the main confounding factor in EEG recording (i.e., muscle artifact) the pe-
ripheral electrode sites were not included in the analysis of the results. Only
the central sites were included. Thus, when the frontal areas were compared
F3, F4 and FZ were averaged together and compared before and after training.
The same holds true for the central areas (C3, C4 and CZ) as well as for the
Scientific Articles 33
posterior areas (P3, P4 and PZ). The rest of the EEG recording conditions
(cognitive tasks and second eyes-open resting condition) will be analyzed in
another paper. The purpose of this study is to determine whether EEG differ-
ences are obvious just by comparing the eyes-open and eyes-closed resting
conditions before and after treatment.
Statistical Analyses
Multiple t-tests were used comparing the average of all epochs before and
after training for each subgroup of recording areas (frontal, central, posterior)
and frequencies (delta, theta, alpha and beta) for both relative and absolute
power for eyes-closed and eyes-open conditions: frontal-delta, frontal-theta,
frontal-alpha, frontal-beta, central-delta, central-theta, central-alpha, cen-
tral-beta, posterior-delta, posterior-theta, posterior-alpha, and posterior-beta.
Since there were 240 combinations of variables (five case studies, three corti-
cal areas, four frequencies, absolute and relative power, eyes-open/
eyes-closed conditions) the alpha level 0.05 was corrected with the Bonferoni
method by being divided by 240, thus giving a p-value of 0.0002. A two-tailed
t-test was performed with a p-value of 0.0001.
The results of the psychometrics were also examined and their standard de-
viation differences were reported. Significant results were considered any dif-
ferences that were two or more standard deviations below or above their
pre-training scores. The scaled self-report differences before and after training
were also examined and reported but were not statistically analyzed.
RESULTS
Individual Case Study Results
Following training M. F. showed a significant decrease in theta (in central
and posterior areas) in eyes-closed absolute power and an alpha decrease in
eyes-closed absolute and relative power. She also showed a significant de-
crease in delta frontal areas in eyes-open absolute power and a decrease in beta
in frontal and central areas in eyes-open relative power. She also showed an in-
crease in beta in frontal areas in eyes-open absolute and relative power (Tables
2 and 3). According to her self-rated questionnaire, choice reaction time and
alternating attention were the types of skills improved after training. Accord-
ing to psychometrics, sustained attention was the type of attention that im-
proved the most after training (Table 12).
Following training D.S. showed a significant decrease in theta (in central
and posterior areas) in eyes-closed absolute power and an alpha decrease in
eyes-closed absolute and relative power. She also showed a significant de-
crease in beta (in central and posterior areas) in eyes-closed absolute power
34 JOURNAL OF NEUROTHERAPY
and in all areas in eyes-closed relative power. She also showed an increase in
delta in central and posterior areas in eyes-closed relative power (Tables 4 and 5).
According to her self-report questionnaire, selective and divided attention
were the types of skills improved after training According to psychometrics,
alternating attention and information processing were the skills that improved
the most after training (Table 12).
Following training S. M. showed a significant decrease in alpha in the pos-
terior areas in eyes-closed absolute power, an increase in theta and a decrease
in alpha in the frontal area in eyes-closed relative power (Tables 6 and 7). Ac-
cording to the self-rated questionnaire, choice reaction and simple reaction
time were the types of skills improved after training. According to psycho-
metrics, selective attention was the type of attention that improved the most af-
ter training (Table 12).
Scientific Articles 35
TABLE 2. M. F. Eyes-Open
EYES-OPEN
ABS. POWER (uV2) RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta 3.35 *2.39 7.34 5.43 *3.92
Theta
Alpha
Beta 2.01 *0.85 2.72 *1.48
Bold: p-value < 0.0002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value < 0.001
Minus () significant increase after training
No significant decrease after training
TABLE 3. M. F. Eyes-Closed
EYES-CLOSED
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta *2.75 *2.23 *1.94
Theta 1.50 2.13 23.44
Alpha 5.09 7.27 1.35 5.25 6.48 10.27
Beta **1.52 *1.68 **1.83 1.52*
Bold: p-value < 0.0002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value < 0.001
Minus () sign: increase after training
No sign: decrease after training
Following training R. M. showed a significant increase in delta in central
and posterior areas in eyes-closed relative power (Tables 8 and 9). According
to the self-rated questionnaire, simple reaction time, divided, sustained and se-
lective attention was the types of skills improved after training. According to
psychometrics, sustained, alternating and selective attention constituted the
types of attention that improved the most after training (Table 12).
Following training R. Q. did not show any significant EEG changes (Tables
10 and 11). According to the self-report questionnaire, choice reaction time
and divided attention were the types of skills improved after training. Accord-
ing to psychometrics, sustained, alternating attention and information process-
ing constituted the skills that improved the most after training (Table 12).
General Results for All Five Cases
Psychometrics. Three out of the five case studies showed sustained atten-
tion as their first (or among their first) ability to show improvement. Exactly
the same results (three out of the five cases) held for alternating attention.
Third was selective attention, with five out of five cases showing improve-
ment, but only as second in order. Divided attention (three out of the five
cases) and finally focused attention (two out of the five cases) constituted the
last measured skill to show changes. Auditory working memory (two out of
the five cases), auditory short-term memory and processing of numerical se-
quences (one out of five cases) and visual short-term memory as well as vi-
sual-motor coordination, (one out of five cases) constituted the last measured
skills to improve after training (Table 12). Improvement was equally divided
in the visual and auditory field for all five case studies.
Questionnaire (Scaled Self-Report)
In their self-reports participants scored higher by one point (indicating im-
provement) in choice-reaction time (three subjects), divided attention (three
subjects), selective (two subjects), confusion (two subjects), simple-reaction
time (two subjects), alternating attention (one subject), verbal memory (one
subject), non-verbal memory impairment (one subject), long-term memory
(one subject), sustained attention (one subject), and anterograde memory (one
subject).
Quantitative Electroencephalogram
Each of the four conditions: eyes-closed absolute power (Table 13), eyes-
closed relative power (Table 14), eyes-open absolute power (Table 15), and
eyes-open relative power (Table 16) have some cortical areas and frequencies
that showed significant changes. For example, in the eyes-closed absolute
power theta, alpha and beta frequencies showed the most prevalent significant
36 JOURNAL OF NEUROTHERAPY
Scientific Articles 37
TABLE 4. D. S. Eyes-Open
EYES-OPEN
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta
Theta
Alpha *2.45
Beta 2.24*
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value < 0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 5. D. S. Eyes-Closed
EYES-CLOSED
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta 6.04 6.58
Theta *2.67 3.29 4.82
Alpha 8.07 8.08 11.52 4.85 3.42 4.38
Beta .341 6.41 7.35 *1.49 3.02 2.74
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value < 0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 6. S. M. Eyes-Open
EYES-OPEN
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta
Theta *1.58 *2.07
Alpha
Beta
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value < 0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 7. S. M. Eyes-Closed
EYES-CLOSED
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta
Theta *2.85 *2.80 *2.36 4.57 4.32 5.03
Alpha **3.36 *2.13 3.37 3.84 *2.70
Beta **2.01
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value <0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 8. R. M. Eyes-Open
EYES-OPEN
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta *3.41
Theta *2.70 *2.39
Alpha
Beta *1.53
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value < 0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 9. R. M. Eyes-Closed
EYES-CLOSED
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta *5.41 2.64* 4.12 4.34
Theta
Alpha
Beta *1.81 *
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value <0.001
Minus () sign: increase after training
No sign: decrease after training
changes. In the eyes-closed relative power, delta, alpha and posterior beta
showed the most prevalent significant changes; the same was true for the
eyes-open absolute power for frontal and central beta.
DISCUSSION
M. F., whose accident was the most recent, showed the most prominent
EEG changes. Her results were also the ones most consistent with the experi-
menter’s hypothesis, with the exception of the decrease in beta in absolute
power eyes-closed recording. She was also the only one who showed sig-
nificant changes in the eyes-open recording. Her psychometrics, however,
in comparison to the remaining four cases showed the least significant re-
sults. D. S. who had similar age, same gender and area of brain injury as M. F.,
Scientific Articles 39
TABLE 10. R. Q. Eyes-Open
EYES-OPEN
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta
Theta *1.73 2.10*
Alpha
Beta *1.00
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value < 0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 11. R. Q. Eyes-Closed
EYES-CLOSED
ABS. POWER uV2 RELAT. POWER
Frontal Central Posterior Frontal Central Posterior
Delta
Theta
Alpha
Beta 1.94* *
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value <0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 12. Psychometrics Pre-Post
TBI Participants
Psychometrics
MF DS SM RM RQ
Pre Post Pre Post Pre Post Pre Post Pre Post
PASAT 129 144 106 128 (a) 103 120 166 152 67 104 (b)
Digit Span 1111111111117767a
Digit Symbol 10 10 9 10 (a) 997788
Consistency Audit. 117 127 114 110 91 86 153 126 113 118
Consistency Visual 114 123 124 134 70 91 (a) 110 124 90 106 (a)
Stamina Audit 92 107 (a) 93 106 103 105 0 114 (g) 100 120*
Stamina Visual 94 94 96 93 83 92 88 101 108 103
Prudence Audit 118 118 109 109 37 45 117 82 109 115
Prudence Visual 84 104 (a) 92 104 38 59 (a) 85 71 106 106
Focus Audit 124 127 111 110 90 90 143 122 121 123
Focus Visual 97 122 (a) 121 131 89 85 79 107 97 115 (a)
Speed Audit 58 51 50 73 (a) 65 58 38 86 (C) 27 39
Speed Visual 80 77 83 84 75 80 88 100 34 52 (a)
Readiness Audit 109 106 104 95 102 103 0 100 (f) 106 112
Readiness Visual 107 103 107 107 77 84 88 65 103 111
Persistence Audit 104 100 100 95 98 106 97 96 97 90
Persistence Visual 107 95 108 99 100 104 86 106 (a) 106 97
Sensorimotor Audit 79 68 73 80 73 79 53 66 47 57
Sensorimotor Visual 92 86 72 76 87 84 93 86 68 66
Vigilance Audit. 105 105 94 103 86 65 0 107 (g) 83 106
40
Vigilance Visual. 106 106 100 104 105 105 80 80 105 105
Comprehension Audit 107 107 99 94 77 98* 0 109 (g) 99 110
Comprehension Visual 107 107 101 101 39 110 (d) 106 106 93 109 (a)
Scores Audit 125 125 123 123 121 122 2 125 (h) 123 125
Scores Visual 124 125 123 124 123 123 124 124 124 125
Balance 88 86 66 87 (a) 100 88 66 86 (a) 96
Hyperactivity mild none (a) none none mild none (a) none none none none
(a): 1 standard deviation difference after training
(b): 2 standard deviation difference after training
(c): 3 standard deviation difference after training
(d): 4 standard deviation difference after training
(e): 5 standard deviation difference after training
(f): 6 standard deviation difference after training
(g): 7 standard deviation difference after training
(h): 8 standard deviation difference after training
41
shared with her the same EEG changes after training in direction, topography
and frequency. D. S. also showed a significant increase in delta relative power
eyes-closed. S. M., who had similar age, same area of brain injury, but differ-
ent gender as M. F. and D.S., shared with them the same EEG changes after
training in direction, topography and frequency. S. M. also recorded a signifi-
cant increase in theta relative power eyes-closed. R. M., who had the most se-
rious accident affecting the right hemisphere, portrayed the most significant
changes in the psychometrics, but among the least significant changes in the
EEG. His most significant change was the increased delta relative power
eyes-closed. R. Q., the youngest participant (in her 20s), an undergraduate stu-
dent, with right hemisphere damage showed no significant EEG changes at all,
but showed the most significant changes compared to the other four cases in
42 JOURNAL OF NEUROTHERAPY
TABLE 13. Eyes-Closed Absolute Power: Significant Changes After Training
for All Five Cases.
Delta Theta Alpha Beta
Frontal m* m*/m*/s* m/d/s** m**/d/r*
Central m*/r* m/d/s* m/d/s* m*/d/q*
Posterior m* m/d/s* m/d/sm**/d/s**
m: M.F.
d: D.S.
r: R.M.
q: R.Q.
s: S.M.
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value <0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 14. Eyes-Closed Relative Power: Significant Changes After Training
for All Five Cases.
Delta Theta Alpha Beta
Frontal r* sm/d/s d*
Central d/-r sm/d/d
Posterior d/-r sm/d/s* m**/d
m: M.F.
d: D.S.
r: R.M.
q: R.Q.
s: S.M.
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value <0.001
Minus () sign: increase after training
No sign: decrease after training
the psychometrics. Sustained and alternating attention improvement seemed
to be more prevalent in the R. M. and R. Q. cases, whose accidents occurred on
the right hemisphere.
One point of interest was the similarity in the EEG changes after training
among M. F., D. S., and S. M (Figures 2, 3 and 4, respectively). All of them
were similar in age (in their 40s), and their area of accident was the left hemi-
sphere (the other two case studies were right hemisphere). M. F. and D. S.
were also of the same gender (females) and shared the most common EEG
changes after training. These common EEG changes after training for these
three cases occurred mainly in the eyes-closed absolute power, in theta, alpha
and beta, and in the eyes-closed relative power in alpha and posterior beta. An-
Scientific Articles 43
TABLE 15. Eyes-Open Absolute Power: Significant Changes After Training for
All Five Cases.
Delta Theta Alpha Beta
Frontal mr* m/r*/q*
Central m* q* d* m*/d*
Posterior s*
m: M.F.
d: D.S.
r: R.M.
q: R.Q.
s: S.M.
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value <0.001
Minus () sign: increase after training
No sign: decrease after training
TABLE 16. Eyes-Open Relative Power: Significant Changes After Training for
All Five Cases.
Delta Theta Alpha Beta
Frontal m/r* r* m
Central mm*
Posterior m* s*
m: M.F.
d: D.S.
r: R.M.
q: R.Q.
s: S.M.
Bold: p-value < 0.002 and significant after correction for multiple comparisons
*: p-value < 0.01
**: p-value <0.001
Minus () sign: increase after training
No sign: decrease after training
other aspect of similarity was between R. M. and S. M. (the two males in the
study) who showed an increase in delta and theta in eyes-closed absolute and
relative power, respectively.
It looks like the area of brain injury, age, gender and time of injury have
some interaction with the EEG results, but less with the psychometrics. The
person with the most significant changes in EEG after training was the person
whose injury was the most recent. For the other participants, who had their ac-
cidents more than one and a half years ago, time did not seem to influence their
rate of improvement.
According to the self-reporting questionnaires, the changes in different
cognitive skills reported to have taken place after training did not coincide
with the responses on the psychometrics. Moreover, the amount of significant
44 JOURNAL OF NEUROTHERAPY
MF Eyes-Closed Absolute Power
Absolute Power
(uV2)
30
25
20
15
10
5
Pre
Post
Front/Delta
Centr/Delta
Post/Delta
Front/Delta
Centr/Theta
Post/Theta
Front/Alpha
Centr/Alpha
Post/Alpha
Front/Beta
Centr/Beta
Post/Beta
Area/Band
FIGURE 2. M. F. Eyes-closed absolute power.
DS Eyes-Closed Absolute Power
Absolute Power
(uV2)
40
30
20
10
Pre
Post
Front/Delta
Centr/Delta
Post/Delta
Front/Delta
Centr/Theta
Post/Theta
Front/Alpha
Centr/Alpha
Post/Alpha
Front/Beta
Centr/Beta
Post/Beta
Area/Band
FIGURE 3. D. S. Eyes-closed absolute power.
EEG changes for each participant did not seem to be correlated with the
amount of significant changes on his/her psychometric results. Two examples
are M. F., who had the most prominent EEG changes but the least psycho-
metric changes, and R. M., who had the most prominent psychometric changes
but among the least EEG changes.
The hypothesis that the low frequencies, delta and theta, would decrease af-
ter training, was partially supported since there were some mixed results. The
two males, R. M. and S. M., contradicted the hypothesis by showing an in-
crease after training. As far as beta is concerned, the hypothesis that it would
increase after training was again partially supported, since there was a signifi-
cant decrease in eyes-closed absolute power while in the three remaining con-
ditions there were mixed results. Only M. F., the participant who had her
accident the most recently, showed a consistent increase in beta in all four con-
ditions, except in eyes-closed absolute power.
The decrease in alpha in the left hemisphere injured participants, in the
eyes-closed condition and less in the eyes-open, was the most important find-
ing of the research. This was even more obvious when the right versus the left
hemisphere cases were averaged and compared together (Figures 5, 6 and 7).
This decrease in alpha was much less prevalent in the right hemisphere cases.
What is obvious looking at Figure 1 is that all three types of attention coincide
in the right frontal area. A hypothesis which could be made is that for left
hemisphere injured people, the right hemisphere is still intact and thus they are
still able to use it and train their attention skills. This is not the case, however,
with the right hemisphere injured patients who do not have the opportunity to
train their right brain area.
Frontal and posterior alpha and posterior beta in eyes-closed absolute
power, as well as frontal alpha in eyes-closed relative power, constituted the
most prevalent EEG changes (decreases) after training. It seems that in gen-
Scientific Articles 45
SM Eyes-Closed Absolute Power
Absolute Power
(uV2)
25.00
20.00
15.00
10.00
Pre
Post
Front/Delta
Centr/Delta
Post/Delta
Front/Delta
Centr/Theta
Post/Theta
Front/Alpha
Centr/Alpha
Post/Alpha
Front/Beta
Centr/Beta
Post/Beta
Area/Band
FIGURE 4. S. M. Eyes-closed absolute power.
eral, eyes-closed more than eyes-open and mostly absolute rather than relative
power gave the most significant results.
The fact that alpha frequency decreased after training coincides with
Chabot’s and Serfontein’s study (1996) which identified that in children with
attention problems QEEG abnormalities involve increased alpha power great-
est in frontal regions. Logically then, when attention problems diminish, alpha
decreases. These results coincide also with the study conducted by Jackson
and Eberly (1982) that trained five mentally challenged adults, aged 22 to 29,
to suppress alpha amplitude. The resulting attenuation in alpha was correlated
with improvement in attention skills. The decreased alpha after training in
frontal as well as in posterior regions coincides with the improvement in the
attention abilities of the participants, shown through the psychometrics. Ac-
cording to the literature in the case of sustained attention, it has been noted that
prefrontal and parietal areas are frequently engaged, while in the case of selec-
46 JOURNAL OF NEUROTHERAPY
All Five Cases: Eyes-Closed Absolute Power
Absolute Power
(uV2)
30.00
25.00
20.00
15.00
10.00
Pre
Post
Front/Delta
Centr/Delta
Post/Delta
Front/Delta
Centr/Theta
Post/Theta
Front/Alpha
Centr/Alpha
Post/Alpha
Front/Beta
Centr/Beta
Post/Beta
Area/Band
FIGURE 5. All 5 cases: Eyes-closed absolute power.
Three Left Hemisphere Injured Ss:
Eyes-Closed Absolute Power
Absolute Power
(uV2)
30.00
25.00
20.00
15.00
10.00
Pre
Post
Front/Delta
Centr/Delta
Post/Delta
Front/Delta
Centr/Theta
Post/Theta
Front/Alpha
Centr/Alpha
Post/Alpha
Front/Beta
Centr/Beta
Post/Beta
Area/Band
FIGURE 6. Left-hemisphere cases: Eyes-closed absolute power.
tive attention, increased activity in posterior regions is involved (Lewin et al.,
1996; Pardo et al., 1991; Haxby et al., 1994). Carlson (2001) has also cited nu-
merous studies regarding the role of prefrontal cortex in attentional modula-
tion. Moreover, the fact that improvement in attention skills are followed by
changes on EEG, not just in the frontal areas, but also in the central and poste-
rior ones may be explained by the neuropsychological theories of attentional
processing by Mesulam (1981). This work considered the role of the reticular
activating system and the cingulate gyrus in the regulation of information to be
attended to, the posterior parietal lobe system in focusing conscious attention,
and the frontal lobes in directing attentional resources.
Delta and theta frequencies are more prevalent in drowsy conditions while
beta frequency is prevalent in more aroused, highly cognitive conditions. A
common protocol for the improvement of attention deficit disorder in EEG
biofeedback is the reduction of theta or delta frequencies and the increase of
beta frequency. In this project it was expected that cognitive rehabilitation,
through a software program designed to improve attention, concentration and
memory skills, could achieve this improvement using the same brain wave
patterns as the one achieved through operant conditioning technique (i.e.,
EEG biofeedback) when used to improve concentration and attention.
However, in this project, even though the psychometrics showed an im-
provement in attention for all participants, the EEG changes that followed,
though significant, were only partially the ones expected. Only the reduction
in alpha frequency was consistent with the hypothesis in most cases. White
(2001) finds increased frontal alpha to be the most prominent difference be-
tween adults with ADD and the non-clinical population.
The decrease in alpha frequency after implementation of the cognitive re-
habilitation as well as the other significant QEEG results constitute interesting
findings. A larger sample size is needed in order to corroborate these results.
Scientific Articles 47
Two Right Hemisphere Injured Ss:
Eyes-Closed Absolute Power
Absolute Power
(uV2)
40.00
30.00
20.00
10.00
Pre
Post
Front/Delta
Centr/Delta
Post/Delta
Front/Delta
Centr/Theta
Post/Theta
Front/Alpha
Centr/Alpha
Post/Alpha
Front/Beta
Centr/Beta
Post/Beta
Area/Band
FIGURE 7. Right hemisphere cases: Eyes-closed absolute power.
REFERENCES
Adamovich, B., Henderson, J., & Auerbach, S. (1985). Cognitive rehabilitation of closed
head injured patients: A dynamic approach. San Diego, CA: College Hill Press.
Alhambra, M. A., Fowler, T. P., & Alhambra, A. A. (1995). EEG biofeedback: A new
treatment option for ADD/ADHD. Journal of Neurotherapy,1(2), 83-99.
Ashley, M. J., & Krych, D. K. (1995). Traumatic brain injury rehabilitation. Boca
Raton, Florida: CRC Press.
Baribeau, J., Ethier, M., & Braun, C. (1989). A neurophysiological assessment of se-
lective attention before and after cognitive remediation in patients with severe
closed head injury. Journal of Neurological Rehabilitation,3(2), 71-92.
Carlson, R. N. (2001). Physiology of behavior. Amherst, MA: Pearson Education
Company.
Chabot, R. J., Orgill, A. A., Crawford, G., Harris, M. J., & Serfontein, G. (1999). Be-
havioral and electrophysiological predictors of therapy response to stimulants in
children with attention deficit disorders. Journal of Child Neurology,14 (6),
343-351.
Chabot, R. J., & Serfontein, G. (1996). Quantitative electroencephalographic profiles
of children with attention deficit disorder. Biological Psychiatry,40 (10), 961-963.
Corbetta, M., Miezin, F. M., Dobmeyer, S., Shulman, G. L., & Petersen, S. E. (1990).
Attentional modulation of neural processing of shape, color, and velocity in hu-
mans. Science,248 (4962), 1556-1559.
Coull, J. T., Frackowiak, R. S., & Frith, C. D. (1998). Monitoring for target objects:
Activation of right frontal and parietal cortices with increasing time on task.
Neuropsychologia,36 (12), 1325-1334.
Enomoto, T., Ono, Y., Nose, T., Maki, Y., & Tsukada, K. (1986). Electroencephalog-
raphy in minor head injury in children. Children’s Nervous System,2(2), 72-79.
Finlayson, M. A., & Garner, S. H. (1994). Brain injury rehabilitation: Clinical consid-
erations. Baltimore: Williams & Wilkins.
Goldstein, G., & Ruthven, L. (1983). Rehabilitation of the brain damaged adult. New
York: Plenum.
Gronwall, D. (1977). Paced auditory serial addition task: A measure of recovery from
concussion. Perceptual Motor Skills,44, 367-373.
Haxby, J. V., Horwitz, B., Ungerleider, L. G., Maisog, J. M., Pietrini, P., & Grady, C.
L. (1994). The functional organization of human extrastriate cortex: A PET-rCBF
study of selective attention to faces and locations. Journal of Neuroscience,11 (1),
6336-6353.
Hudspeth, W. J., & Pribram, K. H. (1992). Psychophysiological indices of cerebral
maturation. International Journal of Psychophysiology,12, 19-29.
Jackson, G. M., & Eberly, D. A. (1982). Facilitation of performance on an arithmetic
task as a result of the application of a biofeedback procedure to suppress alpha wave
activity. Biofeedback Self-Regulation,7(2), 211-221.
Klingberg, T. (1998). Concurrent performance of two working memory tasks: Poten-
tial mechanisms of interference. Cerebral Cortex,8(7), 593-601.
Koski, L., & Petrides, M. (2001). Time-related changes in task performance after le-
sions restricted to the frontal cortex. Neuropsychologia,39 (3), 268-281.
48 JOURNAL OF NEUROTHERAPY
Kuhlman, W. N., & Kaplan, B. J. (1979). Clinical applications of EEG feedback train-
ing. In R. J. Gatchel & K. P. Price (Eds.), Clinical applications of biofeedback: Ap-
praisal and status (pp. 65-96). New York: Pergamon Press.
Langfitt, T. W., & Gennarelli, J. A. (1982). Can the outcome from head injury be im-
proved? Journal of Neurosurgery,48, 227-240.
Lantz, D., & Sterman, M. B. (1988). Neuropsychological assessment of subjects with un-
controlled epilepsy: Effects of EEG feedback training. Epilepsia,29 (2), 163-171.
Le, T. H., Pardo, J. H., & Hu, X. (1998). 4 T-fMRI study of nonspatial shifting of selec-
tive attention: Cerebellar and parietal contributions. Journal of Neurophysiology,
79 (3), 1535-1548.
Lewin, J. S., Friedman, L., Wu, D., Miller, D. A., Thompson, L. A., Klein, S. K., et al.,
(1996). Cortical localization of human sustained attention: Detection with func-
tional MRI using a visual vigilance paradigm. Journal of Computer Assisted To-
mography,20 (5), 695-701.
Linden, M., Habib, T., & Radojevic, V. A. (1996). Controlled study of the effects of
EEG biofeedback on cognition and behavior of children with attention deficit disor-
der and learning disabilities. Biofeedback and Self Regulation,21 (1), 35-49.
Lubar, J. F., Swartwood, M. O., Swartwood, J. N., & O’Donnell, P. H. (1995). Evalua-
tion of the effectiveness of EEG neurofeedback training for ADHD in a clinical set-
ting as measured by changes in TOVA scores, behavioral ratings, and WISC–R
performance. Biofeedback and Self Regulation,20 (1), 83-99.
Lubar, J. F. (1989). Electroencephalographic biofeedback and neurological applica-
tions. In J. V. Basmajian, (Ed.), Biofeedback: Principles and practice for clinicians
(p. 3). Baltimore: Williams & Williams.
Lubar, J. O., & Lubar, J. F. (1984). Electroencephalographic biofeedback of SMR and
beta for treatment of attention deficit disorders in a clinical setting. Biofeedback and
Self-Regulation,9(1), 1-23.
Mesulam, M. M. A. (1981). Cortical network for directed attention and unilateral ne-
glect. Annals of Neurology, 10 (4), 309-325.
Montgomery, E. A., Fenton, G. W., McClelland, R. J., & MacFlynn, G. (1991). The
psychobiology of minor head injury. Psychological Medicine,21 (2), 375-384.
Nall, A. (1973). Alpha training and the hyperkinetic child. Is it effective? Academic
Therapy,9(1), 5-19.
National Head Injury Foundation (1985). An educator’s manual: What educators need
to know about students with traumatic head injury. Framingham, MA: The Guilford
Press.
Pardo, J. V., Fox, P. T., & Raichle, M. E., (1991). Localization of a human system for
sustained attention by positron emission tomography. Nature,349 (6304), 61-64.
Patmon, R., & Murphy, P. J. (1978, March). Differential treatment efficacy of EEG and
EMG feedback for hyperactive adolescents. Paper presented at the meeting of the
Biofeedback Society of America, Albuquerque, NM.
Ponsford, J. L., & Kinsella, G. (1988). Evaluation of a remedial program for attentional
deficits following closed-head injury. Journal of Clinical and Experimental Neuro-
psychology,10 (6), 693-708.
Prigatano, G. (1986). Neuropsychological rehabilitation after brain injury. Baltimore:
John Hopkins University Press.
Scientific Articles 49
Pugh, K. R., Offywitz, B. A., Shaywitz, S. E., Fulbright, R. K., Byrd, D., Skudlarski, P.,
et al.(1996). Auditory selective attention: An fMRI investigation. Neuroimage,4
(3), 159-173.
Ramirez, P. M., Desantis, D., & Opler, L. A. (2001). EEG biofeedback treatment of
ADD. A viable alternative to traditional medical intervention? Annals of the New
York Academy of Science,931, 342-358.
Ramos, F. (1998). Frequency band interaction in ADD/ADHD. Journal of Neuro-
therapy,3(1), 26-41.
Randolph, C., & Miller, M. (1988). EEG and cognitive performance following closed
head injury. Neuropsychobiology,20, 43-50.
Ravizza, S. M., & Ivry, R. B. (2001). Comparison of the basal ganglia and cerebellum
in shifting attention. Journal of Cognitive Neuroscience,13 (3), 285-297.
Ravizza, S. M., & Ciranni, M. A. (2002). Contributions of the prefrontal cortex and
basal ganglia to set shifting. Journal of Cognitive Neuroscience.14 (3), 472-483.
Rees, G., & Lavie, N. (2001). What can functional imaging reveal about the role of at-
tention in visual awareness? Neuropsychologia,39 (12), 1343-1353.
Sandford, J. A. (1992). Captain’s Log. Richmond, VA: BrainTrain Inc.
Sandford, J. A., & Turner, A. (1995). Integrative visual and auditory continuous per-
formance test. Richmond, VA: BrainTrain, Inc.
Sevostianov, A., Fromm, S., Nechaev, V., Horwitz, B., & Braun, A. (2002). Effect of
attention on central auditory processing: An fMRI study. International Journal of
Neuroscience,112 (5), 587-606.
Shouse, M. N., & Lubar, J. F. (1979). Operant conditioning of EEG rhythms and
Ritalin in the treatment of hyperkinesis. Biofeedback and Self-Regulation,4(4),
299-312.
Skinner, A. D., & Trachman, L. H. (1985). Brief or new: Use of a computer program
(PC coloring book) in cognitive rehabilitation. American Journal of Occupational
Therapy,39 (7), 470-472.
Sohlberg, M. M., & Mateer, C. A. (1989). Introduction to cognitive rehabilitation.
New York: The Guilford Press.
Sohlberg, M. M., & Mateer, C. A. (1987). Effectiveness of an attention training pro-
gram. Journal of Clinical and Experimental Neuropsychology,9(2), 117-130.
Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Exper-
imental Psychology,18, 643-662.
Tansey, M. A. (1993). Ten-year stability of EEG biofeedback results for a hyperactive
boy who failed fourth grade perceptually impaired class. Biofeedback and Self Reg-
ulation,18 (1), 33-44.
Tansey, M. A., & Bruner, R. I. (1983). EMG and EEG biofeedback training in the treat-
ment of 10-year old hyperactive boy with a developmental reading disorder. Bio-
feedback and Self-Regulation,8(1), 25-37.
Taylor, S.F., Komblum, S., Lauber, E. J., Minoshima, S., & Koeppe, R. A. (1997). Iso-
lation of specific interference processing in the Stroop task: PET activation studies.
Neuroimage, 6 (2), 81-92.
Thatcher, R. W., Cantor, D. S., McAlaster, R., Geisler, F., & Krause, P. (1991). Com-
prehensive predictions of outcome in closed head-injured patients. The develop-
50 JOURNAL OF NEUROTHERAPY
ment of prognostic equations. Annals of the New York Academy of Science,620,
82-101.
Thatcher, R. W., Walker, R. A., Gerson, I., & Geisler, F. H. (1989). EEG discriminant
analyses of mild head trauma. Electroencephalography and Clinical Neuro-
physiology, 73 (2), 94-106.
Tinius, T. P., & Tinius K. A. (2000). Changes after EEG biofeedback and cognitive re-
training in adults with mild traumatic brain injury and attention deficit hyperactivity
disorder. Journal of Neurotherapy,4(2), 27-44.
Vandenberghe, R., Gitelman, D. R., Parrish, T. B., & Mesulam, M. M. (2001). Loca-
tion or feature-based targeting of peripheral attention. Neuroimage,14 (1), 37-47.
Wechsler, D. (1981). Wechsler adult intelligence scale-revised. San Antonio, TX: The
Psychological Corporation.
White, J. N. (2001). Neuropsychological and electrophysiological assessment of adults
with Attention Deficit Hyperactivity Disorder. Unpublished doctoral dissertation,
The University of Tennessee, Knoxville.
Woodruff, P. W., Benson, R. R., Bandettini, P. A., Kwong, K. K., Howard, R. J.,
Talavage, T., et al. (1996). Modulation of auditory and visual cortex by selective at-
tention is modality-dependent. Neuroreport,7(12), 1909-1913.
RECEIVED: 03/20/02
REVISED: 02/26/03
07/30/03
ACCEPTED: 08/27/03
Scientific Articles 51
... Another measure is known as power spectrum density (PSD), which calculates the distribution of energy sampled into the frequencies composing that signal (Canuet et al., 2011). According to Stathopoulou and Lubar (2004), there are indications that people experiencing cognitive dysfunction may exhibit increased power in waves associated with drowsier states (i.e., delta, theta), whereas waves associated with cognitive activity (i.e., beta, gamma) may exhibit decreases in power. ...
... First, group differences in power during resting state were examined. To more cleanly assess power, frequency waves were collapsed into two units: cognitive activity, which consisted of gamma and beta waves, and drowsy state, which included theta, delta, and alpha waves (Stathopoulou & Lubar, 2004). Hypothesis 1 predicted significant group differences. ...
... Hypothesis 1a: Relative to the non-injured comparison group, the mTBI group would exhibit a significant reduction in overall cognitive activity and a significant increase in drowsy state power (Stathopoulou and Lubar, 2004). ...
Article
The topic of mild traumatic brain injury (mTBI) has rapidly gained attention not only in academic science but also in popular media. Unlike severe traumatic brain injury, mTBI is difficult to diagnose. There are no objective diagnostic criteria, and symptoms can vary greatly across individuals. Further, although individuals with mTBI are frequently compared to non-injured individuals, it cannot be concluded with certainty that any differences found between groups can be attributed solely to the head injury and not a more general injury-factor. Identifying a sensitive and specific physiological signal across similar injury groups is critical to establishing a criterion that would facilitate the development of tools which could be rapidly employed. The purpose of the present study was to investigate neurophysiological functioning in individuals who recently sustained a mTBI or orthopedic injury, as well as non-injured individuals, using multiple electrophysiological analysis procedures. Twenty-four participants ages 18-30 were recruited for this study. Individuals were in one of three groups: mTBI (3 males and 3 females; age M: 22.50), mild orthopedic injury (6 males and 2 females; age M:20.76), or non-injured (2 males and 8 females; age M: 21.50). Injured participants took part in the study no longer than ten days post-injury. All participants completed a resting state task, analyzed with quantitative EEG, and two cognitive event-related potential (ERP) tasks: auditory oddball and n-back. Results indicated no significant group differences for resting state or n-back. However, the mTBI group displayed significantly larger P300 amplitudes during the auditory oddball. Although some individuals with mTBI may show reduced activation in brain areas supporting working memory, areas outside this network are recruited and included in order to meet task demands, which could account for the increase in amplitude. The current study lends support for the use of ERP, specifically with an auditory oddball task, in the identification of acute mTBI. Of primary significance is the inclusion of an orthopedic injury group and the finding that P300 amplitude is significantly increased only for those with mTBI. This provides an important basis for future research and strategies for the development of a rapid, objective measure of mTBI. Advisors: Arthur C. Maerlender and Cary Savage
... 1,3,13,18 Similarly, ERPs and oscillatory activity from the human EEG give relevant information about the severity of injury and its impact on neuronal pathways, including their efficiency in conducting signals from the peripheral to the central nervous system (CNS), the ability of CNS structures to process sensory input, and the ability of specific sensory systems to perceive and integrate stimuli. 25 However, even if many studies discussed all the possible applications of neuroimaging and neurophysiological instruments for diagnostic and prognostic purpose, [25][26][27][28][29][30][31][32][33] as far as we know there are no review studies focusing on the neuroplastic changes induced by cognitive training in TBI individuals. The main purpose of this work was to broadly examine the literature on the structural, functional, and neurophysiological modifications of cognitive treatments in chronic TBI subjects. ...
... 60 Finally, 2 studies were excluded because they did not use posttraining neuroimaging examinations. 30,31 In light of such analysis, 11 studies were found to meet the inclusion criteria: 7 fMRI studies (2 single-case studies 1,61 and 5 group studies 11,19,[62][63][64] ), 3 articles with evoked readiness potentials (2 single-case studies, 65,66 and 1 group study 67 ), and one EEG study 28 (see Table 1 and Figure 1). ...
... Mild to severe disturbances of attention are frequently reported after TBI and constitute one of the main barriers to social and vocational reintegration. 28 In a first fMRI study, Laatsch and colleagues 1 analyzed the neural and cognitive sequelae of a training on visual search and reading abilities in a subject with severe TBI. In spite of the absence of significant behavioral changes, the authors found a qualitative improvement in most of the trained abilities. ...
Article
Background: Cognitive deficits are among the most disabling consequences of traumatic brain injury (TBI), leading to long-term outcomes and interfering with the individual's recovery. One of the most effective ways to reduce the impact of cognitive disturbance in everyday life is cognitive rehabilitation, which is based on the principles of brain neuroplasticity and restoration. Although there are many studies in the literature focusing on the effectiveness of cognitive interventions in reducing cognitive deficits following TBI, only a few of them focus on neural modifications induced by cognitive treatment. The use of neuroimaging or neurophysiological measures to evaluate brain changes induced by cognitive rehabilitation may have relevant clinical implications, since they could add individualized elements to cognitive assessment. Nevertheless, there are no review studies in the literature investigating neuroplastic changes induced by cognitive training in TBI individuals. Objective: Due to lack of data, the goal of this article is to review what is currently known on the cerebral modifications following rehabilitation programs in chronic TBI. Methods: Studies investigating both the functional and structural neural modifications induced by cognitive training in TBI subjects were identified from the results of database searches. Forty-five published articles were initially selected. Of these, 34 were excluded because they did not meet the inclusion criteria. Results: Eleven studies were found that focused solely on the functional and neurophysiological changes induced by cognitive rehabilitation. Conclusions: Outcomes showed that cerebral activation may be significantly modified by cognitive rehabilitation, in spite of the severity of the injury.
... Like seeing letters with shift or in reverse. 3,9,10 As it is clear, all of these problems are essential factors in the learning process at school years. Dyslexic child suffers these consequences despite having a right IQ level and health in hearing and vision. ...
Article
Full-text available
Background: The brain has four lobes consist of frontal, parietal, occipital, and temporal. Most researchers have reported that the left occipitotemporal region of the brain, which is the combined region of the occipital and temporal lobes, is less active in children with dyslexia like Sklar, Glaburda, Ashkenazi and Leisman. Methods: There are different methods and tools to investigate how the brain works, such as magnetic resonance imaging (MRI), positron emission tomography (PET), magneto-encephalography (MEG) and electroencephalography (EEG). Among these, EEG determines the electrical activity of the brain with the electrodes placed on the special areas on the scalp. In this research, we processed the EEG signals of dyslexic children and healthy ones to determine what the areas of the brain are most likely to cause the disease. Results: For this purpose, we extracted 43 features, including relative spectral power (RSP) features, mean, standard deviation, skewness, kurtosis, Hjorth, and AR parameters. Then an SVM classifier is used to separate two classes. Finally, we show the particular brain activation pattern by calculating the correlation coefficients and co-occurrence matrices, which suggests the activation of the working memory region as an active area. Conclusion: By identifying the brain areas involved in reading activity, it has expected that psychologists and physicians will be able to design the therapeutic exercises to activate this part of the brain.
... utive function.Methodology of frontal and executive function, 1-38.Sohlberg, M. M., & Mateer, C. A. (2001). Cognitive rehabilitation: An integrative neuropsychological approach: Guilford Press. Strauss, E.,Sherman, E. M., & Spreen, O. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary: American Chemical Society.Stathopoulou, S., & Lubar, J. F. (2004). EEG changes in traumatic brain injured patients after cognitive rehabilitation. Journal of Neurotherapy, 8(2), 21-51.Stuss, D. T., & Benson, D. F. (1986). The frontal lobes:Raven Pr Trombly CA, Trombly Latham CA,Radomski MV.Occupational therapy for physical dysfunction.Downloaded from shenakht.muk.ac.ir at 5:42 +0430 on Tuesday April 1 ...
... Additionally, one study used functional magnetic brain imaging techniques (De Luca et al., 2014), but only at preintervention assessment and not as an outcome measure. The use of these methods in order to assess the efficacy of NRP provides information about the neural correlates, and increased accuracy regarding the identification of the type of neuropathologies or location of brain lesions (Chaytor & Schmitter-Edgecombe, 2003;Cho et al, 2016;Stathopoulou & Lubar, 2004;Thornton & Carmody, 2005). The data provided could be used to modify and improve NRP accordingly to the patients' brain functioning, enhancing the probability of success of the rehabilitation programs. ...
Article
Full-text available
This systematic review aims to analyze the methods used in the assessment of the efficacy of Neurocognitive Rehabilitation Programs (NRP) based on Information and Communication Technologies in patients with Acquired Brain Injury, namely platforms and online rehabilitation programs. Studies with the main purpose of evaluating the efficacy of those programs were retrieved from multiple literature databases, accordingly to inclusion and exclusion criteria. The inclusion and analysis of the studies followed preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) and Cochrane Collaboration Guidelines. Thirty-one studies were included in this review. Results showed that most studies used a pre-post methodological design, with few studies performing assessment moments during intervention or follow-up. Attention, memory, and executive functions were the cognitive variables considered by a larger number of studies at the assessment of NRP efficacy. Despite that, there is a growing evidence on the inclusion of variables related to everyday functioning in this process, increasing its ecological validity. Concerning the instruments used, the studies presented a large heterogeneity of the instruments and methods used, even for the same assessment purpose, highlighting a lack of consensus regarding assessment protocol. Psychophysiological and neuroimaging techniques are seldom used on this field. This review identifies the main characteristics of the methodology used at the assessment of NRP and potential limitations, providing useful information to guide the practice of the health care professionals in rehabilitation of Acquired Brain Injury. It also suggests new directions for future studies.
... A higher delta-alpha initial value was associated with poorer recovery. Stathopoulou & Lubar (2004) reported that the most systemic change on the EEG data (eyes closed, eyes open conditions) in the TBI patients following 22 sessions of a cognitive rehabilitation program. (Captain's Log) was a decrease in alpha, contrary to the expectation of decreased delta, theta, and alpha (microvolts and relative power) and increases in beta. ...
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.
... CCT was based on the commercially available cognitive training software "Captain's Log" (BrainTrain Inc, Richmond, VA). Captain's Log has a history of use in clinical populations such as adults diagnosed with traumatic brain injury (Tinius and Tinius, 2000;Stathopoulou and Lubar, 2004), schizophrenia (Bellucci et al., 2003), and chronic psychiatric disorders (Burda et al., 1994) as well as children with attention difficulties (Rabiner et al., 2010) and older adults (Eckroth-Bucher and Siberski, 2009). An adaptive and personalized training program was set using the software's Personal Trainer Wizard, which adjusts training difficulty and content according to predefined settings as well as individual performance. ...
Article
Full-text available
Cognitive skills are important predictors of job performance, but the extent to which computerized cognitive training (CCT) can improve job performance in healthy adults is unclear. We report, for the first time, that a CCT program aimed at attention, memory, reasoning and visuo-spatial abilities can enhance productivity in healthy younger adults on bookkeeping tasks with high relevance to real-world job performance. 44 business students (77.3% female, mean age 21.4 ± 2.6 years) were assigned to either (a) 20 h of CCT, or (b) 20 h of computerized arithmetic training (active control) by a matched sampling procedure. Both interventions were conducted over a period of 6 weeks, 3-4 1-h sessions per week. Transfer of skills to performance on a 60-min paper-based bookkeeping task was measured at three time points-baseline, after 10 h and after 20 h of training. Repeated measures ANOVA found a significant Group X Time effect on productivity (F = 7.033, df = 1.745; 73.273, p = 0.003) with a significant interaction at both the 10-h (Relative Cohen's effect size = 0.38, p = 0.014) and 20-h time points (Relative Cohen's effect size = 0.40, p = 0.003). No significant effects were found on accuracy or on Conners' Continuous Performance Test, a measure of sustained attention. The results are discussed in reference to previous findings on the relationship between brain plasticity and job performance. Generalization of results requires further study.
Article
The aim of this study is to assess the ability of EEG-based indices in providing relevant information about cognitive engagement level during the execution of a clinical sustained attention (SA) test in healthy volunteers and DAI (diffused axonal injury)-affected patients. We computed three continuous power-based engagement indices (Pβ/Pα, 1/Pα, and Pβ / (Pα + Pθ)) from EEG recordings in a control group (n = 7) and seven DAI-affected patients executing a 10-min Conners’ “not-X” continuous performance test (CPT). A correlation analysis was performed in order to investigate the existence of relations between the EEG metrics and behavioral parameters in both the populations. Pβ/Pα and 1/Pα indices were found to be correlated with reaction times in both groups while Pβ / (Pα + Pθ) and Pβ/Pα also correlated with the errors rate for DAI patients. In line with previous studies, time course fluctuations revealed a first strong decrease of attention after 2 min from the beginning of the test and a final fading at the end. Our results provide evidence that EEG-derived indices extraction and evaluation during SA tasks are helpful in the assessment of attention level in healthy subjects and DAI patients, offering motivations for including EEG monitoring in cognitive rehabilitation practice. Open image in new windowGraphical abstractThree EEG-derived indices were computed from four electrodes montages in a population of seven healthy volunteers and a group of seven DAI-affected patients. Results show a significant correlation between the time course of the indices and behavioral parameters, thus demonstrating their usefulness in monitoring mental engagement level during a sustained attention task.
Chapter
In this chapter, we shall provide a rationale for the use of behaviortherapeutic methods in the assessment and treatment of brain-damaged patients and present some data gathered by ourselves and others to illustrate how various methods derived from behavior therapy can be used effectively in treatment. We will begin with a brief introduction to behavior therapy, go on to provide a rationale for building an interrelationship between behavior therapy and neuropsychology centered around treatment of brain-damaged patients, and conclude with a number of illustrations of how this relationship can work in actual practice.
Chapter
In two recent publications, empirical observations on the efficacy of neuropsychologically oriented rehabilitation and its theoretical and clinical nature have been presented (Prigatano et al., 1984; Prigatano et al, 1986). The recently published work by Ben-Yishay et al., 1985 and a review chapter by Cotman and Nieto-Sampedro (1985) on mechanisms of CNS recovery provide an additional opportunity to further reflect on the nature and efficacy of this work.
Article
A comprehensive diagnostic evaluation was administered to 162 closed head-injured patients within 1 to 21 days (mean, 7.5 days) after injury. Each evaluation consisted of (1) power spectral analyses of electroencephalogram (EEG) recorded from 19 scalp locations referenced to age-matched norms, (2) brainstem auditory evoked potentials, (3) computed tomography (CT)-scan, and (4) Glasgow Coma Score (GCS) at time of admission (GCS-A) and at time of EEG test (GCS-T). Functional outcome at one year following injury was assessed using the Rappaport Disability Rating Scale (DRS), which measures the level of disability in the six diagnostic categories of (1) eye opening, (2) best verbal response, (3) best motor response, (4) self-care ability for feeding, grooming, and toileting, (5) level of cognitive functioning, and (6) employability. The ability of the different diagnostic measures to predict outcome at one year following injury was assessed using stepwise discriminant analyses to identify patients in the extreme outcome categories of complete recovery versus death and multivariate regression analyses to predict patients with intermediate outcome scores. The best combination of predictor variables was EEG and GCS-T, which accounted for 74.6% of the variance in the multivariate regression analysis of intermediate outcome scores and 95.8% discriminant accuracy between good outcome and death. The best single predictors of outcome in both the discriminant analyses and the regression analyses were EEG coherence and phase. A gradient of prognostic strength of diagnostic measures was EEG phase greater than EEG coherence greater than GCS-T greater than CT-scan greater than EEG relative power. The value of EEG coherence and phase in the assessment of diffuse axonal injury was discussed.