Looking at the Sunny Side of Life
Age-Related Change in an Event-Related Potential Measure
of the Negativity Bias
Michael A. Kisley,1Stacey Wood,2and Christina L. Burrows1
1University of Colorado at Colorado Springs and2Scripps College
ABSTRACT—Studies of the negativity bias have demon-
strated that negative information has a stronger influence
than positive information in a wide range of cognitive
documenting emotional and motivational shifts that result
in a positivity effect in older adults. It remains unclear,
however, whether this age-related positivity effect results
from increases in processing of positive information or
from decreases in processing of negative information. Also
unknown is the specific time course of development from a
negative bias to an apparently positive one. The present
the life span using an event-related potential measure of
responding to emotionally valenced images. The results
suggest that neural reactivity to negative images declines
linearly with age, but responding to positive images is
surprisingly age invariant across most of the adult life
of domains, including perception, decision making, and evalu-
2001; Taylor, 1991). Baumeister, Bratslavsky, Finkenauer, and
Vohs (2001), after reviewing a broad array of research, con-
cluded that this bias is pervasive in psychological function, and
that there are only a very limited number of exceptions (e.g.,
optimism in predicting the future).
Recent research has documented age-related shifts in emo-
tional and attentional function that could affect the strength or
even the presence of the negativity bias (Mather & Carstensen,
2005; Mroczek, 2001). For example, pioneering work by Car-
stensen and her colleagues demonstrated that, despite stereo-
types to the contrary, older adults typically report higher well-
being than younger adults, apparently because of motivational
changes to optimize social and emotional goals (Carstensen,
Pasupathi, Mayr, & Nesselroade, 2000; Charles & Carstensen,
1999). Further, these changes appear to affect cognitive func-
tioning as well as mood, resulting in a generalized increase in
attention to positive stimuli compared with negative stimuli.
This has been described as a positivity effect in information
processing for older adults (Charles, Mather, & Carstensen,
2003; Isaacowitz, Wadlinger, Goren, & Wilson, 2006; Mather &
Carstensen, 2003; Pennebaker & Stone, 2003; Wood, Buse-
meyer, Koling, Cox, & Davis, 2005). Although the positivity
effect has been studied among adults in different age ranges
(e.g., young, middle, and old), the life-span developmental
timeline for this effect has not been empirically characterized
(e.g., Carstensen, 1995). Further, it is unclear whether the bias
reversal arises from an age-related increase in responding to
positive information or an age-related decrease in responding to
negative information (Blanchard-Fields, 2006).
Because event-related potential (ERP)methodology has been
applied to the investigation of emotional processing in general,
and the negativity bias in particular (Bartholow, Pearson,
Gratton, & Fabiani, 2003; Schupp et al., 2000; Smith et al.,
2006), this methodology might prove useful in addressing some
of the unresolved issues concerning age-related changes in the
processing of positive and negative information. For example,
using this method, Ito, Larsen, Smith, and Cacioppo (1998)
determined that the negativity bias is measurable in younger
categorization task. In this paradigm, emotionally valenced
images (positive and negative) occur infrequently against a
background of frequently presented neutral images. A charac-
teristic ERP waveform, the late positive potential (LPP), is
elicited by these positive and negative stimuli, which are eval-
uatively inconsistent with the neutral background. Ito et al.
ChristinaBurrows is now atthe DepartmentofPsychology, University
of Houston. Address correspondence to Michael A. Kisley, Depart-
ment of Psychology, University of Colorado at Colorado Springs, 1420
Austin Bluffs Parkway, PO Box 7150, Colorado Springs, CO 80933-
7150, e-mail: email@example.com.
Volume 18—Number 9Copyright r 2007 Association for Psychological Science
LPP waveforms than positive images, even though the positive
and negative images were equal in subjective emotional impact
and arousal. In short, this ERP-based measurement demon-
strated a negativity bias by showing increased allocation of
neural resources to negative, compared with positive, informa-
A recent investigation has demonstrated that the negativity
bias exhibited by the LPP waveform is eliminated in older
adults. We (Wood & Kisley, 2006) replicated the original ERP
sample of older adults (mean age of 68.5 years). For the latter
group, the LPP waveform elicited by valenced images was sig-
the younger adults), but there was no evidence of differential
response amplitude elicited by positive versus negative images.
However, the particular pattern of results left it unclear whether
the lack of bias in the older group reflected a specific change in
the balance between processing of positive information and
processing of negative information or, perhaps more trivially, a
generalized age-related dampening in the processing of all va-
In the present study, we collected ERP measures of brain
activity elicited by emotionally valenced images from an adult
life-span sample (18–81 years). This study was designed to
provide evidence regarding the adult developmental timeline of
the negativity bias in the LPP waveform and to shed light on the
issue of whether the reduced negativity bias in older adults re-
flects age-related changes in response to positive images, in
previous study (Wood & Kisley, 2006), we predicted that aging
would be related to a decline in the negativity bias exhibited by
change with advancing age.
Statisticalanalyses were performed with the data from 51adults
between 18 and 81 years old (M 5 43.16, SD 5 19.23; 34 fe-
male). A total of 65 individuals originally participated, but 14
were excluded for the following reasons: difficulties performing
the behavioral task (n 5 2), an insufficient number of trials
available for computing ERP average waveforms (n 5 10), and
recording problems (n 5 2). The latter two problems are unique
to electrophysiological methodology, and we implemented cri-
teria for number of trials and recording quality to avoid in-
cluding in the analysis ERP waveforms with degraded signal
strength. Wediscusstherationalefortheseexclusions furtherin
the Procedure and Analysis section.
All included subjects had no self-reported visual problems,
tested 20/40 or better with at least one eye on the Snellen visual
acuity chart, and read textual instructions on a computer screen
atadistance of2.5ftwithnodifficulty.Theyscored 28orhigher
on the Mini-Mental State Examination (Folstein, Folstein, &
McHugh, 1975). Years of education ranged from 12 to 20 (M 5
14.82, SD 5 1.88). Because age was significantly correlated
with years of education, r 5 .34, p < .05, and visual acuity, r 5
?.49, p < .01, the latter two variables were controlled for in the
analyses described here.
Images were presented on a 17-in. LCD color computer monitor
2.5 ft from the subject. E-Prime (Psychological Software Tools,
Inc., Pittsburgh, PA) was used for presenting the images and
recording responses. Electroencephalographic signals were re-
corded on a Neuroscan NuAmps amplifier system under control
of a laptop computer running Scan 4.2 (Compumedics Neuro-
scan, El Paso, TX).
Affectively neutral, positive, and negative images were se-
lected from the International Affective Picture System (IAPS;
Lang, Bradley, & Cuthbert, 2005) on the basis of normative
ratings from younger adults (Lang et al., 2005) and previous
ERP studies (Ito etal., 1998; Wood& Kisley,2006). Of these 30
images, 6 (2 positive, 2 negative, and 2 neutral) were used to
compute ERPs. For these 6 images (the oddball and control
images—see Procedure and Analysis), we collected quantita-
tive ratings of bipolar valence (from 1, most negative, to 9, most
positive) and arousal (from 1, least arousing, to 9, most arousing)
using the Self Assessment Manikin instrument (SAM; Lang et
al., 2005). The mean bipolar valence rating for the neutral im-
computer, respectively) was 5.28 (SD 5 0.89), and the mean
arousal rating was 2.25 (SD 5 1.40). The mean ratings for the
positive images (IAPS Pictures 7340 and 7350: chocolate ice
valence and 5.08 (SD 5 2.74) for arousal. For the negative
images (IAPS Pictures 9140 and 9571: decomposing calf and
dead cat, respectively), the mean ratings were 1.26 (SD 5 0.61)
for bipolar valence and 5.71 (SD 5 2.53) for arousal.
These mean ratings for arousal and valence generally fall
within normative ranges established in previous publications
(e.g., they fall between the values obtained by Ito et al., 1998,
and Lang et al., 2005). However, unlike in the study by Ito et al.
(1998), the mean valence ratings for the stimuli suggest that the
negative and positive images were not experienced as equally
distant in valence from neutral. Specifically,the meanabsolute-
value difference between the negative image’s ratings and the-
oretical neutral was 3.74 (i.e., |1.26 ? 5|), whereas the differ-
ence between the positive image’s ratings and neutral was 2.49
(|7.49 ? 5|), and these distances were significantly different
from each other, F(50) 5 28.53, p < .001. For this reason, we
computed for each subject the difference between the distance
from theoretical neutral for positive images and the distance
from theoretical neutral for negative images (i.e., |negative va-
Volume 18—Number 9
Michael A. Kisley, Stacey Wood, and Christina L. Burrows
lence ? 5| ? |positive valence ? 5|) and included this measure
of behavioral bias as a covariate for all statistical analyses pre-
sented here. Partial correlations (df 5 47) controlling for edu-
cation and visual acuity and zero-order correlations (N 5 51)
revealed no significant effect of age on the ratings of subjective
valence or arousal, or on the index of behavioral bias.
Procedure and Analysis
The procedure and ERP analysis for this study were identical to
those we used in our previous investigations of the LPP nega-
tivity bias (Wood & Kisley, 2006) and are described here very
briefly. During an evaluative categorization task, electrophysi-
ological signals were recorded (1000-Hz sampling, 0.1- to 100-
Hz band pass) from standardized scalp electrode sites (refer-
enced to average signal on left and right mastoids), as well as
sites near the eyes, which were used to monitor movements and
blinks. Subjects for whom adequate electrode contact could not
be maintained (i.e., impedances > 5 kO; n 5 2) were excluded
from further analysis because high impedances lead to de-
creased signal-to-noise ratios in the measurement.
The task required subjects to view each image for 1 s and
subsequently categorize it as positive, negative, or neutral by
pressing one of three buttons on a response pad. A 1.2-s lag
Individuals with an excessive number of nonresponses (5 or
more during the entire task) or very high mean response latency
(1,500 ms or longer) were excluded from the final analysis (n 5
2).Twenty-four differentneutralfiller imageswere presented15
times each, to provide a neutral context. At pseudorandom po-
sitions, 60 oddball images and 30 neutral control images were
presented within this series. The oddball images were evalua-
tively inconsistent with the majority of images because of their
emotional valence; 30 oddball images were positive (2 different
images presented 15 times each), and 30 were negative (2
different images presented 15 times each). The 30 control im-
ages also consisted of 15 presentations each of 2 different im-
ages. Subjects responded as expected(i.e., responded ‘‘neutral’’
toneutralimages,‘‘negative’’ tonegativeimages,and ‘‘positive’’
to positive images) on 81.4% (SD 5 14.0%) of the 90 oddball
and control trials; this variable was not significantly correlated
Average ERP waveforms (spanningfrom 100 ms before image
onset to 900 ms after onset) were computed for the oddball-
image presentations and the control-image presentations using
standard procedures for ERP analysis (Wood & Kisley, 2006).
Any ERP waveform corrupted by movement artifact (i.e., a
waveform with a recording channel exceeding ? 100 mV) was
excluded from further analysis. Valence-specific average
waveforms(neutral, positive, and negative) were computedfrom
the remaining trials and smoothed (low-pass filtered at 9Hz). To
avoid including individuals with potentially unreliable average
waveformsinthe analysis, weexcluded anysubjectforwhoman
insufficient number of single trials was available for computing
an average ERP waveform (i.e., five trials or fewer per valence
category remaining after removal of artifactual trials; n 5 10).
The mean number of trials used to compute average ERP
waveforms in the remaining 51 subjects was 22.0 (SD 5 6.4) for
neutral images, 22.3 (SD 5 5.4) for negative images, and 22.0
(SD 5 6.5) for positive images; the three valence categories did
not differ significantly in the number of trials used to compute
Previous research has shown that LPP amplitude is largest at
et al., 1998; Wood & Kisley, 2006), which is over the parietal
lobe and along the midline of the head. Thus, LPP amplitude for
each waveform was taken from the largest peak voltage on
electrode Pz between 400 and 900 ms after image onset (Coles,
Gratton, & Fabiani, 1990).
For the entire sample, peak LPP amplitude was larger in re-
sponse to negative than in response to positive images (Fig. 1);
this result replicates previous demonstrations of a negativity
examined in an analysis of variance (Wilks’s lambda approxi-
mation) with the factor of valence (three levels: neutral, nega-
A main effect of valence was found, F(2, 48) 5 29.00, p < .001,
Z25 .547; behavioral bias did not have a significant effect, and
the interaction between valence and behavioral bias was not
Fig. 1. Grand-averaged event-related potential waveforms recorded
from site Pz during presentation of neutral, negative, and positive images
embedded in a series of mostly neutral images. Positivity is plotted
downward. The label on the graph indicates the late positive potential
(LPP) elicited by the positive and negative images, which were evalua-
tively inconsistent with the majority of the images.
Volume 18—Number 9
Age-Related Change in the Negativity Bias
amplitude differed significantly between each valence category
and the other two (p < .01); amplitude was smallest for neu-
tral images (M 5 5.40 mV, SD 5 2.89 mV), intermediate for
positive images (M 5 8.87 mV, SD 5 4.91 mV), and largest for
negative images (M 5 11.89 mV, SD 5 5.75 mV).
Peak LPP amplitude varied with age, although differentially
depending on image valence. We computed partial correlation
coefficients between LPP amplitude and age, controlling for
years of education, visual acuity, and behavioral bias. The am-
plitude of the waveform elicited by negative images was sig-
nificantly correlated with age, r(46) 5 ?.32, prep 5 .918,
whereas the amplitudeofthe waveforms elicitedby positive and
neutral images was not. By Hotelling’s t test, the difference
between correlation coefficients for negative (r 5 ?.32) and
positive (r 5 .00) images was significant (negative-to-positive
correlation coefficient 5 .47), t(43) 5 ?2.18, prep5 .936. In
summary, amplitude of the LPP elicited by negative images
decreased with age more rapidly than did amplitude of the LPP
elicited by positive images. This effect can be seen in Figure 2.
The present results are consistent with the hypothesis that the
magnitude of the negativity bias in adults decreases with ad-
vancing age because of a gradual age-related reduction in re-
sponding to negative images. The results do not support two
a general dampening of neural activation in response to all
images and an increase in responding to positive images. In our
previous work (Wood & Kisley, 2006), we could not draw any
conclusions regarding whether or not responses to negative in-
formation and responses to positive information showed the
same age-related changes. In that work, we studied only two
extreme groups: 19- to 22-year-olds and 56- to 81-year-olds.
The latter group exhibited statistically indistinguishable re-
sponse amplitudes for positive and negative images, or an
effective lack of response bias. However, amplitudes of re-
sponses to both negative and positive images were reduced in
the older adults relative to the younger adults, leaving open the
possibility that the observed elimination of the negativity bias
arose simply from global reduction in the amplitude of response
to images in both categories.
The life-span approach employed in the present study, how-
adults did appear to be at least slightly more reactive to both
positive and negative stimuli, relative to older adults. For ex-
ample, Figure 2 shows that the youngest adults tested (those
below age 25) had relatively high mean LPP amplitude in re-
sponse to the positive images (M 5 12.22 mV), especially
compared with the oldest adults (i.e., those over age 55: M 5
8.78 mV). This finding is consistent with the findings of our
previous work (Wood & Kisley, 2006). Nevertheless, unlike the
of the LPP elicited by positive images did not seem to decrease
consistently across the large age range studied. Indeed, a test
using a linear model indicated there was very little change
overall. By contrast, the amplitude of response to the negative
images exhibited a gradual, consistent, and significant linear
decrease beginning in the 20s and continuing until late life. So
although there appears to be some generalized age-related
dampening for the LPP waveform—similar to the dampening of
other late positive ERP components that are elicited by non-
evaluative expectancy violations (e.g., Federmeier, Van Petten,
Schwartz, & Kutas, 2003; Jerger & Martin, 2005), including the
P300 (reviewed by Kok, 2000)—the results of the present study
demonstrate an interaction between age and emotional valence.
Specifically, the LPP responses to positive and negative infor-
mation exhibited differential age-related patterns of change.
the reduction in the negativity bias, does not appear to solely
images. The relation between the LPP waveform and the emo-
tional valence of the images changed with age even though
Fig. 2. Scatter plots showing the relation between amplitude of the late
positive potential (LPP) and age, separately for neutral, negative, and
positive images. Best-fitting regression lines are shown for reference.
Volume 18—Number 9
Michael A. Kisley, Stacey Wood, and Christina L. Burrows
subjective ratings for those very same images did not. This
finding is similar to past findings that autonomic responses
(heart rate, skin conductance, etc.) to emotional films and im-
ages exhibit age-related reductions in magnitude even when the
corresponding subjective ratings are stable (Gavazzeni, Wiens,
& Fischer, 2005; Tsai, Levenson, & Carstensen, 2000). We
nevertheless included a measure of behavioral bias (i.e., the
relative distance from neutral for valence ratings of negative vs.
positive images) as a covariate in order to remove the potential
influence of subjective emotional biases. But the pattern of
stimuli with advancing age, did not change when this covariate
was omitted (results not reported here).
Socioemotional selectivity theory (SST) provides a framework
theory emphasizes that as adults age, their attention shifts to-
ward positive information. This shift is driven by a motivationto
maximize emotional goals as one’s perceived remaining lifetime
becomes shorter (Carstensen et al., 2000). Indeed, it has re-
cently been demonstrated that the amplitude of the LPP evoked
by negative images can be suppressed by intentional efforts to
minimize negative emotional experience (Moser, Hajcak, Bu-
kay, & Simons, 2006). This finding fits nicely with SST’s claim
that motivational factors drive older adults toward a change in
the balance between processing of negative information and
processing ofpositive information.Inthepresentstudy,wehave
shown that,atleastfortheneuralactivity thatunderliestheLPP
waveform, the change appears to take the form of a reduction in
the processing of negative information, rather than an increase
directly tested whether changes in time perception, the mech-
information, could be influential early enough to play a role in
the changes in the ERP-based negativity bias observed in the
present study (e.g., starting around age 25; see also Carstensen,
It remains unclear whether the age-related change in the
negativity bias observed in this study was caused by top-down
(voluntary) processes, bottom-up (involuntary) processes, or
possibly a combination of both. The LPP waveform is elicited
even when individuals are not voluntarily attending to the
affective salience of the images, and in fact an implicit nega-
(Ito & Cacioppo, 2000). But voluntary allocation of attention to
the emotional valence of each image has nevertheless been
shown to modulate LPP amplitude (Hajcak, Moser, & Simons,
2006), a finding consistent with the hypothesis that this ERP
component is affected by top-down processes. These demon-
strated top-down modulation effects fit with the suggestion that
the increased suppression of neural activity associated with
processing of negative information in older adults might origi-
nate from the prefrontal cortex (Mather & Carstensen, 2005), a
brain area known to be important for controlled, voluntary
processes. A recent life-span study of behavioral and neural
responding to faces provides support for this hypothesis. Wil-
liams et al. (2006) demonstrated an age-related dissociation in
prefrontal cortex responses to positive and negative facial ex-
pressions (i.e., increasing response to negative expressions and
decreasing response to positive expressions). As in the present
model of aging. On the basis of their results, Williams et al.
proposed that as people age, they devote more resources to
controlling negative emotional responses, but allow automatic
responses to positive stimuli to proceed without restraint. This
model fits well with the results of the current study, which
specifically demonstrated age-related reductions in responding
to negative information, but relatively little age-related change
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Volume 18—Number 9
Michael A. Kisley, Stacey Wood, and Christina L. Burrows