Journal of Rehabilitation Research & Development
Volume 42, Number 1, Pages 29–34
Event-related potential in facial affect recognition: Potential clinical
utility in patients with traumatic brain injury
Henry L. Lew, MD, PhD;1–2* * John H. Poole, PhD;2 Jerry Y. P. Chiang, MD;3 Eun Ha Lee, MD;1
Elaine S. Date, MD;1 Deborah Warden, MD4
1Physical Medicine and Rehabilitation Service, Department of Veterans Affairs Palo Alto Health Care System, Palo Alto,
CA, 1–2Defense and Veterans Brain Injury Center, Palo Alto, CA; 3Stanford University School of Medicine, Stanford, CA;
4Defense and Veterans Brain Injury Center, Walter Reed Medical Center, Washington, DC
Abstract—Traumatic brain injury (TBI) frequently leads to
deficits in social behavior. Prior research suggests that such
deficits may result from impaired perception of basic social
cues. However, these social-emotional deficits have not been
studied electrophysiologically. We measured the P300 event-
related potential (ERP), which has been shown to be a sensitive
index of cognitive efficiency, in 13 patients with a history of
moderate to severe TBI and in 13 healthy controls. The P300
response was measured during detection of 30 pictures of
angry faces (rare target) randomly distributed among 120 neu-
tral faces (frequent nontarget). Compared to control subjects,
the TBI group’s P300 responses were significantly delayed in
latency (p = 0.002) and lower in amplitude (p = 0.003). TBI
patients also showed slower reaction times and reduced accu-
racy when manually signaling their detection of angry faces.
Coefficients of variation (CVs) for the facial P300 response
compared favorably to those of many standard clinical assays,
suggesting potential clinical utility. For this study, we demon-
strated the feasibility of studying TBI patients’ P300 responses
during the recognition of facial affect. Compared to controls,
TBI patients showed significantly impaired electrophysiologi-
cal and behavioral responses while attempting to detect affec-
tive facial cues. Additional studies are required for clinicians to
determine whether this measure is related to patients’ psycho-
social function in the community.
Key words: affect recognition, brain injury, cognition, electro-
encephalograph, emotional processing, event-related potential,
Impairments in emotional and social behavior are a
frequent consequence of traumatic brain injury (TBI),
including emotional disinhibition, reduced social activity,
and a breakdown in relationships [1–2]. Cognitive studies
in this area have focused on behavioral measures in assess-
ing patients’ capacity to recognize facial and vocal expres-
sions of basic emotions such as anger or happiness. Studies
have found affect recognition is frequently impaired in TBI
patients [3–4], and these patients have greater difficulty
recognizing negative than positive affect . At least one
study suggested the severity of these deficits may account
for differences in TBI patients’ social functioning .
Abbreviations: CV = coefficient of variation, EEG = electro-
encephalograph, ERP = event-related potential, SD = standard
deviation, TBI = traumatic brain injury, VA = Department of
This material was based on work supported by the Depart-
ment of Veterans Affairs (VA), Veterans Health Administra-
tion, Rehabilitation Research and Development Service, and
in part by National Institutes of Health grant 5K12HD01097
and VA Research and Development grant B3262K.
*Address all correspondence to Henry L. Lew, MD, PhD;
VA Palo Alto Health Care System, PM&R Service, MS-B117,
3801 Miranda Avenue, Palo Alto, CA 94304; 650-493-5000,
ext. 65368; fax: 650-849-0129; email: firstname.lastname@example.org
JRRD, Volume 42, Number 1, 2005
We used cognitive event-related potentials (ERPs) to
analyze the temporal processing of facial affect in
healthy individuals [6–7]. The recognition of facial affect
is undoubtedly a complex, multifaceted task, and several
early and late ERP components have been found to be
related to different aspects of this process. A “face-
related” N2 component (150–200 ms) is thought to
reflect mainly nonemotional aspects of face perception,
while a later P300 component (250–550 ms) is more
strongly related to the detection of facial emotions [6–8].
In addition, several studies in healthy individuals have
found that the amplitude of the P300 typically shows a
more robust response to negative facial emotions (e.g.,
anger, fear) than positive facial emotions [9–10]. This
may reflect a general characteristic of the P300 in which
the amplitude of the response is proportional to the mean-
ing and emotional salience of stimuli .
Prior studies in TBI patients have demonstrated ERP
abnormalities that are closely related to patients’ neuropsy-
chological status  and functional outcome . To our
knowledge, however, no study has examined TBI patients’
ERP responses to affect recognition tasks. In a prior study,
we found that TBI patients have significantly lower-
amplitude and longer-latency P300 responses to simple
visual stimuli . The present study extends this line of
research by comparing the P300 response of TBI patients
and healthy controls during facial affect recognition. In
view of the stronger P300 response reported for negative
emotions, as well as the reportedly greater impairment of
TBI patients in recognizing negative emotions behavior-
ally, we focused the present study on the detection of angry
faces. We asked subjects to identify relatively infrequent
angry faces among many faces with a neutral expression.
To assess possible contributions from generalized psycho-
motor slowing, we also analyzed the relationship of sub-
jects’ P300 latencies to the speed of their manual responses
to the same facial stimuli.
This protocol was approved by the Department of Vet-
erans Affairs’ (VA) local institutional review board, and
all subjects provided signed informed consent. From the
brain injury rehabilitation unit of a university-affiliated
VA medical center, we recruited patients who had a his-
tory of moderate to severe TBI (initial Glasgow Coma
Score = 3–12) with good recovery (current Glasgow
Coma Scale = 15 and Glasgow Outcome Scale = 5).
Healthy control subjects were recruited from the patients’
friends and family and from hospital volunteers and staff.
All subjects were fully oriented, able to follow instruc-
tions, and had visual acuity within normal limits and bilat-
eral upper-limb strength of 5/5 on neurological screening.
We excluded subjects taking sedatives, anticholinergic
agents, dopamine agonist, or antagonists within the prior
72 h, so we could avoid the potential influence of these
agents on the morphology of the electroencephalograph
(EEG) waveforms [15–16].
The Neuroscan (El Paso, Texas) STIM system and
version 4.2 software were utilized for stimulus genera-
tion, data acquisition, and analysis of ERP waveforms
and reaction times. We employed gold-cup electrodes,
placed on the scalp at Fpz, Fz, Cz, and Pz (International
10–20 System), with the ground electrode over the ster-
num, and one reference electrode at each mastoid. Elec-
trode impedance was kept at less than 5 kΩ. A bandpass
filter was used, with low and high frequencies set
between 0.15 Hz and 30.0 Hz. Four facial stimuli from
Ekman’s series were used , consisting of 150 pictures
of a man and a woman (equally represented), each show-
ing either an angry or a neutral facial expression. We used
30 (20%) angry faces as rare/target stimuli, which ran-
domly appeared among the remaining 120 (80%) neutral
faces (nontarget, frequent stimuli). The faces measured
5.55 × 7.75 in. and appeared on the monitor for 1.0 s each
at an interstimulus interval of 2.11 s, with a luminance of
0.15 foot-candles at a viewing distance of 2 ft.
We tested all subjects between 3 and 5 p.m. to reduce
variability related to diurnal effects . Subjects were
instructed to focus on the monitor and press a response
button as quickly as possible whenever the target stimuli
appeared. EEG waveforms and manual responses (reac-
tion time and accuracy) were recorded simultaneously
during the process. The entire procedure, including elec-
trode application, instructions to subject, and completion
of the experiment, required approximately 30 min per
LEW et al. Affect recognition and traumatic brain injury
EEG responses to nontarget and target stimuli were
separately time-locked, sorted, and averaged. Since the
expected P300 responses are largest at Pz , we ana-
lyzed the averaged ERP waveform at the Pz electrode for
each subject. Amplitudes and latencies of the P300 wave-
forms were determined and entered into a database for fur-
ther analyses. We measured the amplitude from the
prestimulus baseline to peak, and the latency from stimulus
onset to peak. P300 amplitude and latency were normally
distributed within both subject groups, as well as within
the total sample (Kolmogorov-Smirnov Z < 1; p > 0.5),
allowing the use of parametric statistics (t-tests and Pear-
son correlations). We defined statistical significance as
two-tailed p < 0.05.
To provide initial estimates of the clinical utility of the
P300, in terms of the interindividual variability within nor-
mal samples , we calculated coefficients of variation
(CVs) (CV = between-subject standard deviation ÷ the
group mean) for the P300 amplitude and latency. Lower
CV values are generally considered an important prerequi-
site for clinical measures, without which it can be difficult
to attain suitable levels of sensitivity and specificity. We
performed statistical analyses with the Statistical Package
for Social Sciences (SPSS) 10.1.
We recruited 13 TBI patients and 13 control subjects,
and each group completed the procedure. TBI patients’
initial Glasgow Coma Scores ranged from 3 to 12; three
patients had alcohol-related injuries. The TBI group con-
sisted entirely of males (military veteran sample), while
the control group consisted of seven males and six
Within the control group, gender was unrelated to
P300 amplitude, P300 latency, reaction time, or accuracy
on the manual task (all p values > 0.10 by t-test). The TBI
group was marginally younger than the control group (26
± 9 vs. 32 ± 7 years, p = 0.07 by t-test). Age correlated
significantly with P300 latency (r = –0.59, p = 0.03) and
marginally with reaction time (r = 0.48, p = 0.10) in the
TBI group; no age effects were apparent in the control
group. To rule out possible age artifacts, we controlled
for age in the following analyses.
The Figure shows the grand-average ERP waveforms
of the control and TBI groups. The Table provides each
group’s mean P300 amplitude and latency data, as well as
their reaction times and accuracy on the manual task. As
the Figure and Table show, the P300 wave of the TBI
group had smaller amplitude (11.3 vs. 19.1 µV, t = 3.27,
p = 0.003) and longer latency (486 vs. 416 ms, t = 3.58,
p = 0.002) than that of the control group. In terms of indi-
vidual subjects, 7 of the 13 TBI patients had mean P300s
that were lower in amplitude than the tenth percentile of
controls (versus one control subject in this range). Simi-
larly, for mean latency, 9 of the 13 TBI patients attained
their peak P300 more slowly than the tenth percentile of
controls (versus one control subject). On the manual task,
the TBI group had longer reaction times (653 vs. 443 ms,
t = 3.70, p = 0.002) and slightly lower accuracy than con-
trols (95% vs. 99%, t = 2.30, p = 0.04). Slower subjects
were generally less accurate on the manual task (r = –0.65,
p < 0.001), indicating these group differences were not due
to a simple speed-accuracy trade-off. When the aforemen-
tioned series of analyses were repeated controlling for age,
the results were unchanged.
To assess possible contributions from generalized
psychomotor slowing, we also compared subjects’ P300
latencies to their reaction times on the manual task. Hori-
zontal bars representing the reaction time of both groups
to target faces are shown below each ERP waveform in
the Figure. In the control group, subjects’ average reac-
tion time did not differ significantly from their P300
latency (443 vs. 416 ms, t = 1.13, p = 0.3). In contrast, the
TBI group’s average reaction time lagged 167 ms behind
their P300 responses (653 vs. 486 ms, t = 2.63, p = 0.02).
P300 latency was not significantly correlated with reac-
tion time (r = 0.27, p = 0.2). We estimated the normal
variability of the P300 response in the control group,
with the CV. For P300 amplitude, the CV equaled 32 per-
cent. For P300 latency, the CV equaled 7 percent.
In this study, we were the first to demonstrate that sub-
jects with moderate to severe TBI have altered cognitive
ERPs in response to emotionally charged human faces.
These responses were significantly delayed and lower in
amplitude than those of healthy control subjects. This rep-
licates and extends the finding of prior studies in healthy
subjects [6–10] that classical P300 waveforms can be gen-
erated in response to the relatively complex stimulus of a
human face expressing emotions. The findings are also
JRRD, Volume 42, Number 1, 2005
consistent with a number of prior reports [12–14] showing
that subjects with TBI have delayed, lower amplitude
P300 responses compared to healthy controls.
We also found that TBI subjects differ from control
subjects in the relationship between their P300 and
behavioral responses to target faces. Control subjects’
manual response occurred near the peak of their P300
responses. In contrast, TBI subjects’ manual responses
typically occurred significantly after their peak P300. A
number of possible explanations exist for the difference.
One possibility is control subjects achieved accurate deci-
sions regarding facial stimuli earlier than TBI patients
and therefore initiated their behavioral response earlier.
Furthermore, TBI patients may have a variety of psycho-
motor deficits that can interfere with manual responses.
Undoubtedly, some causes of slower motor response may
reside in functional domains unrelated to the cognitive
P300 response. We found that mean reaction time and
P300 latency were uncorrelated with one another, in
agreement with other studies that also found no necessary
relation between these measures [14,19–20]. This finding
is important because it shows that reaction time and P300
latency are not redundant measures of a single parameter,
such as processing speed.
Finally, to provide initial estimates of the potential
clinical utility of the P300 response to facial stimuli,
we calculated interindividual CV in the normal sample.
Relatively low normative values of the CV are required if
a test is to have practical potential for differentiating nor-
mal from impaired performance . Measures with low
CV values have narrower “normal limits” than those with
larger CVs. This is an important prerequisite for clinical
measures, because low CV measures are more likely to
have suitable sensitivity and specificity for detecting dys-
function. In the present study, we obtained CVs of 7 per-
cent for P300 latency and 32 percent for P300 amplitude.
A previous study  reported this aspect of the P300
response to simple nonfacial visual and auditory stimuli
in 120 normal subjects and obtained CVs of 11 percent
for latency and 41 to 48 percent for amplitude. These val-
ues are comparable to or better than those reported for
many standard clinical measures, which typically range
from 6 to 45 percent, including electroretinograms of reti-
nal sensitivity , a common screening test for cognitive
decline , and widely used blood assays for lipids, glu-
cose, and thyrotropin . Of course, our results from a
limited number of normals may not represent the popula-
tion at large and should be replicated with a larger sam-
ple. Nonetheless, these findings suggest that the P300
Grand-average event-related potential (ERP) waveforms and reaction
times. TBI = traumatic brain injury.
Mean P300 ERP and behavioral responses to target stimuli.
(Mean ± SD)
(Mean ± SD)
Group Difference t-Test
P300 Latency (ms)
P300 Amplitude (µV)
Reaction Time (ms)
ERP = event-related potential
416 ± 30
19.1 ± 6.1
486 ± 64
11.3 ± 6.1
443 ± 64
653 ± 204
SD = standard deviationTBI = traumatic brain injury
LEW et al. Affect recognition and traumatic brain injury
response to emotionally charged faces promises to be a
biomedical assay for cognitive dysfunction.
This study should not be overinterpreted. Although the
target stimuli were angry faces, we cannot conclude that
differences between the TBI and control subjects’ ERP
waveforms reflect differences in emotional processing per
se. The present findings may simply reflect generalized
impairment in our capacity to detect relatively infrequent
target stimuli among distractors. To address this question,
future studies should compare patients’ P300 responses to
emotional stimuli with measures of their cognitive skills
and behaviors. We are currently conducting studies com-
paring subjects’ P300 responses to facial emotions with
neuropsychological measures of their emotion perception
and other cognitive abilities, as well as to behavioral mea-
sures of their interpersonal skills and problems.
We feel the main value of this preliminary study dem-
onstrates the feasibility of the P300 response to probe emo-
tional processing in people with TBI. Specifically, we
found that both control and TBI subjects produce classic
P300 responses to the detection of angry faces. Normal
subjects’ ERP waveforms following these stimuli had CVs
that compare favorably to those of P300 responses to non-
facial visual stimuli as well as many standard clinical tests.
TBI subjects showed impaired P300 responses to these
stimuli, both in terms of latency and amplitude. These find-
ings could not be explained by generalized psychomotor
slowing, as measured by manual reaction time, suggesting
that the P300 reflects aspects of cognition that may not be
easily measured by patients’ motor reactions. Taken
together, we suggest that P300 response may provide a
probe into patients’ altered capacity to process facial cues.
Thus, we are currently preparing another study to deter-
mine whether patients’ P300 responses to the detection of
facial affect have a meaningful relationship to their emo-
tional processing and social functioning in the community.
We gratefully acknowledge the contributions of Dr.
Steven Pan and Dr. James Chen in the initial stages of
1. Kersel DA, Marsh NV, Havill JH, Sleigh JW. Psychosocial
functioning during the year following severe traumatic
brain injury. Brain Inj. 2001;15:683–96.
2. Kubu CS. Emotion recognition and psychosocial behavior in
closed head injury. In: Varney NR, Roberts RJ, editors. The
evaluation and treatment of mild traumatic brain injury. New
Jersey: Lawrence Erlbaum Associates, Inc.; 1999. p. 451–64.
3. Green RE, Turner GR, Thompson WF. Deficits in facial
emotion perception in adults with recent traumatic brain
injury. Neuropsychologia. 2004;42:133–41.
4. Milders M, Fuchs S, Crawford JR. Neuropsychological
impairments and changes in emotional and social behav-
iour following severe traumatic brain injury. J Clin Exp
5. Jackson HF, Moffat NJ. Impaired emotional recognition
following severe head injury. Cortex. 1987;23:293–300.
6. Krolak-Salmon P, Fischer C, Vighetto A, Mauguiere F.
Processing of facial emotional expression: spatio-temporal
data as assessed by scalp event-related potentials. Eur J
7. Eger E, Jedynak A, Iwaki T, Skrandies W. Rapid extraction
of emotional expression: evidence from evoked potential
fields during brief presentation of face stimuli. Neuropsy-
8. Campanella S, Gaspard C, Debatisse D, Bruyer R, Crom-
melinck M, Guerit JM. Discrimination of emotional facial
expressions in a visual oddball task: an ERP study. Biol
9. Morita Y, Morita K, Yamamoto M, Waseda Y, Maeda H.
Effects of facial affect recognition on the auditory P300 in
healthy subjects. Neurosci Res. 2001;41:89–95.
10. Lang SF, Nelson CA, Collins PF. Event-related potentials
to emotional and neutral stimuli. J Clin Exp Neuropsychol.
11. Lew HL, Chen CPC, Chen MJL, Hsu THC, Tang SFT,
Date ES. Comparing the effects of different speech targets
on cognitive event-related potentials: theoretical implica-
tions for evaluating brain injury. Am J Phys Med Rehabil.
12. Viggiano MP. Event-related potentials in brain-injured
patients with neuropsychological disorders: a review. J Clin
Exp Neuropsychol. 1996;18:631–47.
13. Lew HL, Dikmen S, Slimp J, Temkin N, Lee EH, Newell
D, Robinson LR. Use of somatosensory-evoked potentials
and cognitive event-related potentials in predicting out-
comes of patients with severe traumatic brain injury. Am J
Phys Med Rehabil. 2003;82:53–61.
14. Lew HL, Lee EH, Pan SSL, Date ES. Electrophysiological
abnormalities of auditory and visual information processing
JRRD, Volume 42, Number 1, 2005
in patients with traumatic brain injury. Am J Phys Med
15. Fowler B, Mitchell I. Biological determinants of P300: the
effects of a barbiturate on latency and amplitude. Biol Psy-
16. Nishimura N, Ogura C, Ohta I. Effects of the dopamine-
related drug bromocriptine on event-related potentials and its
relation to the law of initial value. Psychiatry Clin Neurosci.
17. Ekman P, Friesen WV. Pictures of facial affect. Palo Alto,
(CA): Consulting Psychologists Press; 1976.
18. Polich J, Herbst KL. P300 as a clinical assay: rationale, eval-
uation, and findings. Int J Psychophysiol. 2003;38:3–19.
19. McCarthy G, Donchin E. A metric for thought: a compari-
son of P300 latency and reaction time. Science. 1981;211
20. Ilan AB, Polich J. P300 and response time from a manual
Stroop task. Clin Neurophysiol. 1999;110:367–73.
21. Polich J. EEG and ERP assessment of normal aging. Elec-
troencephalogr Clin Neurophysiol. 1997;104:228–43.
22. Birch DG, Hood DC, Locke KG, Hoffman DR, Tzekov RT.
Quantitative electroretinogram measures of phototransduc-
tion in cone and rod photoreceptors: normal aging, progres-
sion with disease, and test-retest variability. Arch Oph-
23. Espino DV, Lichtenstein MJ, Palmer RF, Hazuda HP. Eval-
uation of the mini-mental state examination’s internal con-
sistency in a community-based sample of Mexican-
American and European-American elders: results from the
San Antonio Longitudinal Study of Aging. J Am Geriatr
Submitted for publication May 13, 2004. Accepted in
revised form August 4, 2004.