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EEG correlates (event-related desynchronization) of emotional face elaboration: A temporal analysis


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An EEG frequency band analysis was conducted, in order to explore the significance of brain oscillations (delta, theta, alpha and beta) for emotional face comprehension during different post-stimulus time intervals (50-150; 150-250; 250-350; and 350-450 ms). The study was conducted on twenty adults who looked at emotional (happy, sad, angry, fearful) or neutral faces. The results showed that motivational significance of the stimulus can modulate the power synchronization (event-related desynchronization (ERD) decrease) within the frequency band of delta and theta. We propose that delta and theta respond to variations in processing stage of emotional face: whereas, delta reflects updating of the stimulus, theta responds to the emotional significance of face. The findings revealed that emotional discrimination by theta is observable mainly within 150-250 time interval and that it is more distributed on anterior regions, whereas delta is maximally synchronized within 250-350 interval and more posteriorly distributed for all the stimulus type. Finally, a right-hemisphere dominance was found for theta during emotional face comprehension.
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Neuroscience Letters 392 (2006) 118–123
EEG correlates (event-related desynchronization) of emotional
face elaboration: A temporal analysis
Michela Balconia,, Claudio Lucchiarib
aLaboratory of Cognitive Psychology, Department of Psychology, Catholic University of Milan, Largo Gemelli 1, 20123 Milan, Italy
bDepartment of Neurology, Neurological National Hospital“C. Besta”, Milan, Italy
Received 31 March 2005; received in revised form 25 August 2005; accepted 2 September 2005
AnEEGfrequencybandanalysiswas conducted,inorderto explorethesignificanceofbrain oscillations(delta, theta,alphaand beta)for emotional
face comprehension during different post-stimulus time intervals (50–150; 150–250; 250–350; and 350–450ms). The study was conducted on
twenty adults who looked at emotional (happy, sad, angry, fearful) or neutral faces. The results showed that motivational significance of the
stimulus can modulate the power synchronization (event-related desynchronization (ERD) decrease) within the frequency band of delta and theta.
We propose that delta and theta respond to variations in processing stage of emotional face: whereas, delta reflects updating of the stimulus, theta
responds to the emotional significance of face. The findings revealed that emotional discrimination by theta is observable mainly within 150–250
time interval and that it is more distributed on anterior regions, whereas delta is maximally synchronized within 250–350 interval and more
posteriorly distributed for all the stimulus type. Finally, a right-hemisphere dominance was found for theta during emotional face comprehension.
© 2005 Elsevier Ireland Ltd. All rights reserved.
Keywords: Emotional face; Event-related desynchronization; Temporal analysis; Hemispheric asymmetry
Facial expressions of emotion have an important role in com-
municating the needs and intentions of people and humans must
be specially prepared by evolution and learning to detect and
identify the meaning of emotional faces [8]. When an individual
perceives a motivationally relevant stimulus, such as an emo-
tional face, a variety of specific emotional processes emerge in
the central and peripheral nervous system. Specifically, motiva-
tionalsignificance and relevanceof the emotional face may have
an effect on attentional mechanism [20,21]. The present study
aimedatstudying the brain mechanisms underlying humanemo-
tional processing by measuring frequency band power (delta,
theta, alpha, and beta) changes in response to emotional faces
presented visually. We attended that emotional content may be
indexed by oscillatory activity of the brain that was directly
related to attentional processes and arousal [15,19].
Correlatesofaffectiveface processing havebeeninvestigated
using a variety of recording techniques. On one hand, some
authors studied ERP correlates associated with face processing.
It has been argued that emotional face processing arises early. A
Corresponding author. Tel.: +39 02 72342960; fax: +39 02 72342280.
E-mail address: (M. Balconi).
positive peak was observed at about 100ms post-stimulus (PI),
related to emotional valence of the facial stimulus [23]. It might
demonstrate that emotional perception of faces can take place
pre-attentively and automatically. More recently, the differences
between ERPs elicited by emotional face and neutral faces were
observable specifically between 250 and 550ms after stimulus
onset[20].An early negativedeflection (N2) of higher amplitude
was revealed for arousing facial stimuli [3,24,26] in comparison
with neutral facial stimuli. A successive positive ERP deflection
(P300) was monitored by some authors after an emotional stim-
ulation, even if it does not seem to be exclusive for faces, since
it was observed even in response to adjectives or objects with
an emotional content [6]. Thus, P3 effect seems to be a compo-
nent representing updating aspect of processing, independently
of the nature of the stimuli, since this effect is viewed as reflect-
ing decision or cognitive closure of the recognition processing
On the other hand, brain oscillations were found a powerful
tool to analyze the cognitive processes related to emotion com-
prehension [5,18]. Recent researches showed the event-related
thetaband power responds specifically to prolonged visualemo-
tional stimulation [19], and a synchronization was revealed in
case of coordinated response indicating alertness, arousal and
0304-3940/$ – see front matter © 2005 Elsevier Ireland Ltd. All rights reserved.
M. Balconi, C. Lucchiari / Neuroscience Letters 392 (2006) 118–123 119
Fig. 1. Event-related desynchronization (ERD) of frequency band power in response to the stimulus type (emotional vs. neutral) for each time interval.
readiness to process information [4]. Thus, theta EEG power
typically increases with increasing attentional demands and/or
task difficulty. Contrarily, the amplitude of the delta response is
considerably increased as a function of the necessity of stim-
ulus evaluation and memory updating [14]. Nevertheless, at
present no specific data exist on modulation of delta band by
emotional significance of the stimulus. Moreover, as regard of
alpha frequency, it was showed a memory-related alpha oscil-
lations, strongly correlated with working memory and probably
with long-term memory. It was suggested that the responses of
alpha band most probably reflect brain processes associated to
phasic alertness, and it was found an anterior asymmetries in
alpha reduction, that was explained as correlates of changes on
individual affective state [1,9] (Fig. 1).
Although brain oscillations have recently been investigated
in various sensory modalities, their role for brain functioning
remains unclear. Secondly, it remains an open question whether
it is possible to assign a single brain operation or psychological
function for emotion decoding to a certain type of oscillatory
activity. Thus, we intend to explore functional correlates of
brain oscillations with regard to emotional face processing and
emphasize the importance of distributed oscillatory networks
in a narrow frequency range (between 1 and 20Hz). Another
critical issue of the present research is the comparison of the fre-
quency band changes within different time intervals, since the
distribution of the band frequency along the time appeared more
informative than the peak frequency of the band. Our intent is to
analyze the variability of frequency bands inside some known
time intervals (that is temporal windows around 200ms and
300 ms of latency) that were found as discriminant in emotional
processing. In addition, one question that has been raised con-
cerns asymmetric organization in the cerebral hemisphere of the
mechanisms mediating emotional facial stimulus [10]. A recent
study on generic emotional stimuli showed a significant valence
by hemisphere interaction of theta band in the anterior temporal
areas,showingrelatively greater righthemisphereERSfornega-
tive and left for positive stimuli, and an overall right hemisphere
dominance in theta ERS for valenced versus neutral stimuli [2].
Thus, we expected a significant difference in the hemispheric
response (left-right and anterior-posterior axes) as a function of
the emotional content (emotional versus neutral stimulus).
Twenty healthy volunteers took part in the study (11 women,
age 19–25, mean=23.47, S.D.=2.13) after giving informed
consent. They were all right-handed and with normal or
corrected-to-normalvisual acuity.Stimulus materialsweretaken
from the set of pictures of Ekman and Friesen [11]. They were
blackandwhite pictures of male andfemale(equallydistributed)
actors, presenting respectively a happy, sad, angry, fearful, or
neutral face (resulting in a total of 100 stimuli, twenty for each
category). Pictures were presented in a randomised order in the
center of a computer monitor, with a horizontal angle of 4and
a vertical angle of 6(STIM 4.2 software). The stimulus was
presented for 500 ms on the monitor with an interstimulus inter-
val parameter (ISI) of 1500ms, and the inter-stimulus fixation
point was projected at the center of the screen (a white point
on a black background). Subjects were seated comfortably in
a moderately lighted room with the monitor screen positioned
approximately 100cm in front of their eyes. During the exami-
nation, they were requested to continuously focus their eyes on
the small fixation point and to minimize blinking. The EEG was
recorded with a 62-channel DC amplifier (SYNAMPS system)
and acquisition software (NEUROSCAN 4.2). An ElectroCap
with Ag/AgCl electrodes were used to record EEG from active
scalp sites referred to earlobe (10/20 system of electrode place-
ment). Additionally two EOG electrodes were sited on the outer
side of the eyes. The data were recorded using sampling rate
of 256 Hz, with a frequency band of 0.1–50 Hz. The impedance
of recording electrodes was monitored for each subject prior
to data collection and it was always below 5k. After EOG
correction and visual inspection only artefact-free trials were
considered. Only 14 electrodes were used for the successive sta-
tistical analysis (4 central, Fz, Cz, Pz, Oz; 10 lateral, F3, F4, C3,
120 M. Balconi, C. Lucchiari / Neuroscience Letters 392 (2006) 118–123
C4, T3, T4, P3, P4, 01, 02) [24,25]. The digital EEG data were
band-pass filtered in the following frequency bands: 0.5–4, 4–8,
8–12, and 14–20 Hz. To obtain a signal proportion to the power
of the EEG frequency band, the filtered signal samples were
squared [22]. Successively, the data were epoched, triggered
each second, using four different time windows of 100ms. An
average absolute power value for each electrode for each con-
dition (emotional versus neutral) was calculated separately for
each frequency band. An average of the pre-experimental abso-
lutepowerwasused todeterminethe individualpowerduring no
stimulation. From this reference power value, individual power
changes during face viewing were determined as the relative
stimulus-related decrease (desynchronization). In fact, accord-
ing to ERD/ERS method, changes in band power were defined
as the percentage of a decrease (ERD) in band power during a
test interval (here 900ms post-stimulus) as compared to a ref-
erence interval (here 1500ms before picture onset). For each
subject, after band-pass filtering ERD was calculated within the
4 frequency bands for the four intervals of 50–150, 150–250,
250–350, and 350–450ms. The average ERD values across the
respective electrode sites were calculated for each time interval.
The data were entered into repeated measures analysis of
variance (ANOVA) with three repeated factors: stimulus type
(neutral versus emotional), frequency band (4 levels) and elec-
trode sites (14 levels). Four ANOVAs were conducted, one for
each time interval. Thereafter, four ANOVAs were calculated
separately for each frequency band, with two within subject fac-
tors, the stimulus type (2) and the time interval (4). Finally,
in order to analyze widely the cortical distribution of band
modulation, the data were averaged over anterior (F3, Fz, F4),
central (C3, Cz, C4), and posterior (P3, Pz, P4) electrode loca-
tion, and secondly over left (F3, C3, T3, P3, 01) and right (F4,
C4, T4, P4, 02) sides. These new values were entered in two
distinctstatisticalanalyses. For all the ANOVAs, degreesoffree-
dom were Greenhouse–Geisser corrected where appropriate. In
the first time interval, ANOVA showed the statistical signifi-
cance for only Band (F(3,19) =8.60, P< 0.001) main effect. As
showed by the contrast analysis, the alpha and beta frequency
bands showed a higher ERD in comparison with delta (respec-
tively for alpha/delta (F(l,19)= 4.88, P= 0.007) and beta/delta
(F(l,19) = 6.91, P= 0.002) and theta (alpha/theta (F(l,19)= 4.12,
P=0.009) and beta/theta (F(l,19)=5.58, P=0.006) bands. On
the contrary, theta and delta were not differentiated each other.
In the 150–250 time window, main effects for Type
(F(l,19) =5.41, P= 0.006) Band (F(3,19)= 7.44, P=0.001) and
Electrodes (F(13,19)=8.02, P<0.001) were found. For the
Band effect, it was showed a greater decrease of alpha and
beta power, whereas delta and theta showed an increased
power. The contrast comparison verified that this was due
to the significant difference for alpha/theta (F(l,19)= 9.40,
P<0.001), alpha/delta (F(l,19)=8.81, P<0.001), as well
as for beta/theta (F(l,19)=10.05, P<0.001) and beta/delta
(F(l,19)=9.40, P<0.001). In addition, an increased syn-
chronization was found for theta band if compared to
delta (F(l,19)=4.26, P=0.005). A higher synchronization of
the oscillations was found in this time interval for theta
band. Moreover Band×Type interaction was also significant
(F(3,19)=5.29, P=0.002). Contrast effects showed a signifi-
cant difference for alpha/theta (F(l,19)= 3.49, P= 0.041) and
alpha/delta (F(l,19)=3.32, P=0.043) comparisons in emo-
tional face processing, as well as for beta/theta (F(l,19)=3.76,
P=0.038) and beta/delta (F(l,19)=4.05, P=0.028) compar-
isons. The synchronization was varied as a function of stim-
ulus type. In particular, theta and delta band synchronization
was due to the emotional content of the stimulus, whereas
desynchronization for alpha and beta was observed for all the
facial stimuli. The significant interaction Band×Electrodes
(F(39,19) =12.86, P< 0.001) was explored more deeply by two
successiveANOVAs, in order to analyze Location (anterior,cen-
tral, posterior) and Side (right, left) contribution to the cortical
distribution of the frequency bands. The first ANOVA revealed
a significant interaction effect for Location×Type×Band
(F(6,19) =6.16, P= 0.001). Specifically, post-hoc analysis indi-
cated that theta frequency band synchronizes mainly in the
frontal regions of the scalp during emotional stimulus elab-
oration, whereas delta band was concentrated in the pos-
terior regions for the entire stimulus. The second ANOVA
showed a significant interaction effect for Side×Type×Band
(F(3,19)=8.53, P<0.001).
A higher right synchronization was observed only for theta
bandduringelaborationofemotionalstimuli in comparison with
neutral stimuli.
The 250–350 time window showed a significant main
effect for Band (F(3,19)= 11.53, P< 0.001), and Electrodes
(F(13,19)=8.81, P<0.001) as well as for the interaction
Type×Band (F(13,19)=8.02, P<0.001) and Type×Band×
Electrodes (F(39,19)=9.12, P<0.001). Specifically, the post-
hoc comparison showed that alpha and beta frequency bands
desynchronize for each type of stimulus, on the contrary that
beta and theta synchronize during this time interval, but whereas
the delta synchronization was found for all the stimulus (emo-
tional and neutral) theta showed a more decreased ERD for
emotional face if compared with neutral faces. In addition,
theta and delta were differentiated each other (F(l,19)= 5.99,
P=0.002),since delta showed the higher increased power (max-
imum of synchronization). Moreover, the successive ANOVAs
revealed a Type×Side ×Band (F(3,19) = 7.12, P= 0.001) and
Type×Location×Band effect (F(6,19)= 8.62, P< 0.001): a
right anterior synchronization was revealed during emotional
face elaboration in comparison with neutral face elaboration
for theta band, whereas delta was preferentially located in the
posterior sites. Finally, in the Time interval 350–450ms, Band
effect was significant (F(3,19)= 4.02, P= 0.008). Specifically,
as showed by post-hoc comparison, delta frequency band syn-
chronizes within 350–450 time window, if compared with alpha
(F(l,19)=9.11, P=0.001), beta (F(l,19)=8.06, P=0.001) and
theta (F(l,19)=3.88, P=0.033) that showed a greater desyn-
chronization. This effect was revealed for all stimulus type (both
emotional and neutral stimuli).
In order to reveal power variation for each frequency band
within the overall 0–450 temporal duration, specific ANOVAs
Type (2)×Time (4)×Electrodes (14) were conducted sepa-
rately for each frequency band. In the alpha band only the
Time main effect was statistically significant (F(3,19)= 6.05,
M. Balconi, C. Lucchiari / Neuroscience Letters 392 (2006) 118–123 121
P= 0.001). Contrast analysis showed a significant increasing of
ERDfor the firstintervalincomparisonwiththe others(1/2inter-
vals (F(l,19)= 4.47, P= 0.006), 1/3 (F(l,19) = 5.12, P= 0.002),
and 1/4 (F(l,19)=5.50, P=0.002). No other effect resulted
statistically significant. In fact, a higher desynchronization of
alpha band was observed during the early latency, whereas
ERD reduces gradually inside the successive intervals for both
the emotional and neutral stimuli. As in the alpha frequency
band, ANOVA applied to beta revealed the significance for only
one of the main effect, Time (F(3,19)= 6.03, P= 0.003). The
post-hoc analysis showed a gradual desynchronization within
the four time intervals. Delta frequency band showed sensi-
tivity to Type (F(l,19)= 6.01, P=0.002), Time (F(3,19)=8.96,
P<0.001) and Electrodes (F(13,19)=8.08, P<0.001) fac-
tors, as well as to Time×Electrodes (F(39,19) = 11.22,
P<0.001), and Type×Time×Electrodes (F(39,19) = 13.05,
P<0.001). Specifically, ERD showed a significant decrease
within 150–450ms. Moreover, a maximum of synchroniza-
tion of the oscillations was revealed during the third time
interval (250–350ms), with a peak of the band power around
320 ms. This synchronization appears due to the emotional con-
tent of the stimulus during 150–250 time interval (significant
differences between emotional versus neutral faces), whereas
it responds to the facial stimulus in general in the succes-
sive time intervals. ANOVAs revealed differences in Loca-
tion (F(2,19)=5.18, P=0.001). Specifically, as revealed by
the contrast analysis, delta band power synchronizes mainly
in the posterior than in the anterior (F(l,19)=4.88, P=0.012)
or central (F(l,19)=4.60, P=0.010) sites. A similar statis-
tical result was observed for theta band (significant effects
for Time (F(3,19)= 9.60, P< 0.001), Type (F(l,19)= 8.14,
P< 0.001) and Electrodes (F(13,19)= 14.08, P< 0.001), as well
as for the interactions Type×Time (F(3,19)= 5.16, P=0.001)
and Type×Time×Electrodes (F(39,19) =11.28, P< 0.001), it
beingassociatedwithaselectiveERD reduction within 150–250
timewindow,and agradualincreasing ofERDduringthe succes-
sive time intervals (350–450 time). An interesting result of the
analysiswasthat the synchronization of theta band was observed
mainly for emotional stimuli compared with neutral stimuli in
thesecondandthirdtime interval. SuccessiveANOVAs revealed
a Side×Type×Time effect (F(3,19)= 7.78, P< 0.001), and
a Type×Time×Location effect (F(9,19) = 9.35, P< 0.001).
Specifically post-hoc comparison verified a higher right ante-
rior synchronization of theta frequency band during the second
and third time interval, and this effect was related to emotional
Three major effects were found in the present research.
First, the results support the view that the responses of differ-
ent EEG frequencies to emotional face differ from each other
systematically as a function of stimulus type. Secondly, band
frequency modulation arises in concomitance with some critical
time intervals that were observed to be discriminant for emotion
in previous analysis based on ERPs. Third, location differences
(right–left hemisphere, frontal–posterior sites) were observed
for some frequency bands in emotional face elaboration.
Firstly, some of the frequency bands were revealed to be sen-
sitive to emotional content of face. Especially theta and delta
EEG frequencies responded specifically to visual emotional
stimulation, whereas alpha and beta frequencies are modulated
by all the stimulus types. Thus, these two sub-categories of fre-
quency band power were differentiated as a function of their
higher (delta/theta) and lower (alpha/beta) sensitivity to emo-
tional significance of face. For the alpha band power an interest-
ing features is the spectral changes in response to the stimulus as
compared to baseline in the first time interval, showing an inter-
action between stimulus elaboration and this frequency band.
Specifically, alpha showed a greater decrease (desynchroniza-
tion) selectively up 150ms for all the stimulus, whereas a more
stableERDis observed duringtheotherstagesof stimulus elabo-
ration(from 150 ms). Previousstudy foundthatalpha power(and
more specifically lower-1 alpha frequency) desynchronizes as a
response to a presented warning stimulus, and it could be linked
to attentional demand and habituation [16,17]. Thus, in the
presentresearch alpha variationmaybea marker of thefirststage
ofstimulus elaboration thatisrelated toalertnessmechanism. On
synchronizeespecially duringemotion-relatedinformation elab-
oration.Weobserved that this effect was most pronounced in the
last part of the post-stimulus interval, that is the second and third
time windows (up to about 350ms), where the increase of theta
and delta power reached a maximum of intensity. Specifically,
delta showed a higher synchronization at about 320ms post-
stimulus. Moreover, the synchronization effect was sustained
from 150 up 350, then it begins a gradual desynchronization of
delta oscillations. In parallel, theta band synchronized mainly
within the second time window (with a peak at about 240ms
of latency). In comparison with delta power, theta showed an
earlier synchronization, an anticipated increased power and it
more quickly desynchronized (at about 250 latency). In addi-
tion a significant difference between delta and theta must be
considered. In fact, whereas during 150–250 time interval both
the frequency bands synchronized in correspondence with the
emotional more than with the neutral stimulus elaboration, the
successive response (250–350 interval) of the two frequency
bands differed, since only for theta band the synchronous oscil-
lations were related to the emotional content of face, whereas
deltarespondedsimilarly (synchronously) to emotional andneu-
tral stimuli.
What mechanisms can we suppose to be underlying these
frequency band variations? We have showed that in the present
experiment the EEG is modulated as a function of time, and it
is assumable that the power changes between different tempo-
ral windows are specifically due to the evolving of stimulus
elaboration. In particular, time course of affective theta and
beta synchronization during facial expression comprehension
showeddiscrimination between early and later processing stages
ofstimulus. Deltabandreached a gradualsynchronizationwithin
the temporal sequences, with a peak at about 300ms. Contrar-
ily, theta was enhanced during the 150–250ms, reaching greater
synchronizationatabout 200 ms post-stimulus. This pattern sug-
gests that band modulation of this early time-locked response
reflects processing of the features of the facial stimuli but in
different manner. In the first case, delta synchronization could
be a marker of novelty of the stimulus, and it can respond to
122 M. Balconi, C. Lucchiari / Neuroscience Letters 392 (2006) 118–123
the exigency of stimulus updating in memory [12]. This cogni-
tive process need a longer time to be concluded and it appears
not to be exclusively sensitive to the emotional content of the
stimulus but generalized to the overall facial stimuli. Never-
theless, it is likely that the higher complexity of the emotional
than the neutral stimuli is signalled in the first time (150–250
post-stimulus interval) of updating process and it is not present
successively (250–350ms) when the subject have familiarized
with the stimulus. In the second case, theta appears to vary in
concomitance with motivational significance of face that is it
synchronizes mainly as a function of the emotional expressions
and not of the neutral ones. More generally, it was found that
theta band was related to the function of orienting and atten-
tion for emotional significance of the stimulus, representing the
first stage of conceptual stimulus processing of a short-term
conceptual memory-system, in which stimuli reach meaningful
representation rapidly [2]. It was also observed that in compari-
son to delta band, there is a general tendency in theta to exhibit
negative ERD values with increasing attentional demand. Thus,
here enhanced synchronization of theta might index selective
attention for arousing stimuli and a concomitant increased moti-
vational significance of the emotional faces.
Moregenerally,an interesting result ofthe present research is
that each oscillation appears to respond to variations in process-
ing stage of emotional face by variations in latency. As we have
stated the latency (different time intervals) and content sensitiv-
ity (emotional versus neutral content) of delta and theta differed
and it appears to be likely that they are related (or contribute to)
the correspondent N2 and P3 ERP correlates. In this view, oscil-
latory neural assemblies effect on event-related potentials were
supposed [14]. Previous study found that N2 have an emotional
significance [3,24,26]. Specifically, it was related to arousing
stimulation and thus differentiated as a function of the moti-
vational value of the stimulus [25]. Contrarily, P3 was more
generally linked to the decisional aspect of processing, indepen-
dently of the nature of the stimuli, since this effect is viewed
as reflecting decision or cognitive closure of the recognition
processing. Taking into consideration our results, whereas theta
could represent a complex set of cognitive processes whereby
selective attention becomes focused on an emotional-relevant
stimulus that is maintained in short-term memory, on the con-
trary delta activity could reflect at least in part P3, and it is
elicited whenever there is a need to update context.
Moreover, the modulation of the narrow frequency bands
was revealed at both the anterior (theta) and posterior (delta)
recording sites. Nevertheless, two different cortical preferen-
tial distributions were supposed for theta and delta: theta was
anterior-distributed in response to emotional face, whereas delta
was more posterior-distributed independently from the stimulus
type. Previously it was showed that attentional aspect of theta
is obtained from the frontal locations, with the probable gen-
erators lying in corticohippocampal and frontolimbic structures
[14]. The topographical distribution of theta band modulation
suggests that emotional content comprehension is related to
alterations in anterior areas. A vigilance mechanism activated in
concomitance of detection and evaluation of facial expression is
likelyto be locatedattheanterior sites thatareanetwork of atten-
tion consisting of the frontal site is argued to maintain a state of
alertness when salient stimuli are encountered. In addition, the
cortical sides (left and right) have an effect in modulating band
distribution on the scalp, being theta most pronounced on the
right hemisphere than the left, and this effect revealed for theta
could be involved in the modulation of emotion-related arousal.
This effect regarding hemisphere differences is in line with pre-
vious study, that underlined the lateralization of emotional face
processing, since aright hemisphere dominance for emotional
face comprehension was pointed out [10,20]. In parallel, corti-
cal asymmetries were reported for some of the ERP variations
related to emotion elaboration that is N2 and P3, with maximal
effects over the right region. Specifically, the N2 amplitude was
increased for negative compared to neutral stimuli at right hemi-
sphere side [3]. Nevertheless our results present some limits due
to the necessity to analyze in a more systematic manner the spe-
cific effect of different emotional content on band variations as a
function of the valence – positive versus negative – and arousal
– high versus low – of each face [2]. Moreover, the it is likely
thatthe emotional valenceof face (negativeversus positive) may
have an effect on cortical distribution of band modulation, as it
was pointed out by Pizzagalli et al. [23]. Indeed, it was found
that recognition of specific emotions would depend on the exis-
tence of partially distinct systems. For example, amygdala is
required for processing fear but not happiness. Thus, the inci-
dence of this variable on the attentional and motivational levels,
and therefore, on the brain oscillations must be tested systemat-
ically in the future.
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... finding indicates that the features extracted from the low-frequency component can significantly account for the linear ERP variations between the two groups. The role of the delta-band in recognising FE had been reported in different studies kinds of(Balconi and Lucchiari, 2006;Balconi and Pozzoli, 2009). In particular,Garcia Dominguez et al. (2013) found that those with ASD had increased coherence in the lowest frequency bands, delta and theta, over occipital channels, including the Fusiform Gyrus region, as viewing emotional faces compared to controls.Different classifiers were trained and tested with various feature vectors constructed from IMF5-IMF7 to investigate their practical capability in ASD classification. ...
Neurodevelopmental disorders (NDDs) are a group of neurological disorders emerging during early development and impacting higher-level brain function. Early identification of NDDs raises the possibility of improving outcomes. However, NDDs are still clinically detected through a subjective evaluation approach that lacks biological evidence and requires an extended period to identify the disorder. This thesis aims to identify biomarkers from the electroencephalogram (EEG) for abnormal brain dynamics and utilise these biomarkers for NDDs prediction. Nonlinear time series analysis methods, mainly complexity (entropies) and synchronisation (node degree of the phase-lag index) features are investigated for this purpose due to their ability to reflect brain dynamics. A machine learning framework that combines advanced nonlinear EEG processing methods for NDDs identification has been developed and evaluated. The proposed framework was first used with a dataset of children with autism spectrum disorder (ASD) and controls to validate its classification efficacy. This exploration resulted in high performance, suggesting complexity features as biomarkers for ASD prediction. The framework was then used to explore at-birth EEG characteristics of infants with Hypoxic-Ischemic Encephalopathy (HIE) who later developed cerebral palsy (CP). High performance has been reached, and the proposed features were reported as potential biomarkers for early CP prediction. A regression model has also been developed to explore the correlation between the EEG characteristics of the HIE infants and their two-year cognitive scores. The results suggest the proposed features as biomarkers for early cognitive function prediction. Finally, the framework was used with a dataset of individuals with a major depressive disorder to validate its ability to predict their depression severity. Compared to the state-of-the-art research, an acceptable regression performance has been reached, and the proposed features have been suggested as biomarkers for depression severity prediction. This work lays the foundation for evidence-based decision-making applications for early prediction of CP and cognitive outcomes of infants with HIE, paving the way for establishing tailored intervention programs at an appropriate point during development to improve the outcomes.
... The oscillations activity of EEG rhythms has a vital role in processing emotional stimuli and is susceptible to emotional intensity and potency (Lewis, 2005;Knyazev, 2007;Bekkedal et al., 2011). The activity of theta rhythms is more sensitive to emotional stimuli, and negative pictures with higher arousal enhance the activity of theta rhythms (Aftanas et al., 2001;Balconi and Lucchiari, 2006;Balconi and Pozzoli, 2009). Oscillations of Beta are associated with topdown control of behavior (Stoll et al., 2016), while studies have also confirmed the relevance of emotion regulation to cognitive control (Moser et al., 2010;Ochsner et al., 2012). ...
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Depression increases the risk of progression from mild cognitive impairment (MCI) to dementia, where impaired emotion regulation is a core symptom of depression. However, the neural mechanisms underlying the decreased emotion regulation in individuals with MCI combined with depressive symptoms are not precise. We assessed the behavioral performance by emotion regulation tasks and recorded event-related electroencephalography (EEG) signals related to emotion regulation tasks simultaneously. EEG analysis, including event-related potential (ERP), event-related spectral perturbation (ERSP), functional connectivity and graph theory, was used to compare the difference between MCI individuals and MCI depressed individuals in behavioral performance, the late positive potential (LPP) amplitudes, neural oscillations and brain networks during the processing of emotional stimuli. We found that MCI depressed individuals have negative preferences and are prone to allocate more attentional resources to negative stimuli. Results suggested that theta and alpha oscillations activity is increased, and gamma oscillations activity is decreased during negative stimulus processing in MCI depressed individuals, thus indicating that the decreased emotion regulation in MCI depressed individuals may be associated with enhanced low-frequency and decreased high-frequency oscillations activity. Functional connectivity analysis revealed a decrease in functional connectivity in the left cerebral hemisphere of the alpha band and an increase in functional connectivity in the right cerebral hemisphere of the alpha band in MCI depressed individuals. Graph theory analysis suggested that global network metrics, including clustering coefficients and disassortative, decreased, while nodal and modular network metrics regarding local nodal efficiency, degree centrality, and betweenness centrality were significantly increased in the frontal lobe and decreased in the parieto-occipital lobe, which was observed in the alpha band, further suggesting that abnormal alpha band network connectivity may be a potential marker of depressive symptoms. Correlational analyses showed that depressive symptoms were closely related to emotion regulation, power oscillations and functional connectivity. In conclusion, the dominant processing of negative stimuli, the increased low-frequency oscillations activity and decreased high-frequency activity, so as the decrease in top-down information processing in the frontal parieto-occipital lobe, results in the abnormality of alpha-band network connectivity. It is suggested that these factors, in turn, contribute to the declined ability of MCI depressed individuals in emotion regulation.
... This is suggestive of a greater level of attentional engagement with the stress imagery in the PLACEBO treatment. However, the proposed relationship between alpha inhibition and attentional engagement is largely reflective of the operation of non-affective attentional processes; the relationship between alpha activity and affective attentional processes is inconsistent and at times contradictory (46), including evidence of no modulation of alpha power (47,48), increased alpha power (49,50) and decreased alpha power (51,52) during the processing of affective stimuli. Therefore, the lack of significant ROI treatment differences and the inconsistent pattern of relationship between affective attentional processing and alpha activity limits further interpretation of the findings. ...
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BackgroundA combination of green tea, rhodiola and magnesium with B vitamins has previously been reported to significantly increase EEG resting state theta, attenuate subjective stress, anxiety and mood disturbance, and heighten subjective and autonomic arousal under acute psychosocial laboratory stress. Here we examine the capacity of green tea and rhodiola extract administered in combination or in isolation with magnesium and B vitamins to moderate spectral brain activity during attentional task performance under stress.Materials and Methods One-hundred moderately stressed adults received oral supplementation of (i) Mg + B vitamins + green tea + rhodiola; (ii) Mg + B vitamins + rhodiola; (iii) Mg + B vitamins + green tea; or (iv) placebo, in a double-blind, randomised, placebo-controlled, parallel-group design ( NCT03262376; 25/0817). Participants completed an attention switching and emotionally threatening attentional bias task after stress induction (Trier Social Stress Test). Spectral alpha and theta brain activity and event related potentials (ERPs) were recorded during cognitive task performance by electroencephalogram (EEG; BioSemi ActiveTwo 64 channel).ResultsThe combined treatment of Mg + B vitamins + green tea + rhodiola significantly increased frontal midline theta vs. placebo and rhodiola in isolation during the attention switching task, specifically in anticipation of a change in task performance parameter. The combined treatment also significantly increased contralateral theta activation in relation to viewing emotionally threatening images in the left (vs. placebo and rhodiola in isolation) and right parietal (vs. placebo) regions. Further, this treatment demonstrated significantly heightened ipsilateral left parietal theta activation in relation to viewing emotionally threatening images. The combined treatment attenuated a decrease in alpha power during the attentional bias task evident in comparator treatments, but this did not reach significance. No significant effects of treatments on behavioural performance or ERP were found.Conclusion The combination of Mg + B vitamins + green tea + rhodiola increased spectral theta brain activity during the execution of two attentional tasks suggestive of a potential to increase attentional capacity under conditions of stress. Further examination of these ingredients in relation to attentional performance under stress is warranted to ascertain if functional benefits suggested by theta activation can be shown behaviourally.
... For instance, some authors reported increased Alpha power for emotional compared with neutral stimuli both in anterior and posterior regions (Aftanas et al., 2002(Aftanas et al., , 2004, while others found Alpha decreasing during emotional conditions, both in anterior and posterior sites (Everhart and Demaree, 2003;Sarlo et al., 2005;de Cesarei and Codispoti, 2011;Schubring and Schupp, 2019). Notably, some studies did not find any relation between Alpha rhythm and emotional processing (Müller et al., 1999;Balconi and Lucchiari, 2006). A possible explanation for these heterogenous results could be related to the different emotional elicitation methods adopted in these studies, including affective word lists, pictures from various databases and clips. ...
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Films, compared with emotional static pictures, represent true-to-life dynamic stimuli that are both ecological and effective in inducing an emotional response given the involvement of multimodal stimulation (i.e., visual and auditory systems). We hypothesized that a direct comparison between the two methods would have shown greater efficacy of movies, compared to standardized slides, in eliciting emotions at both subjective and neurophysiological levels. To this end, we compared these two methods of emotional stimulation in a group of 40 young adults (20 females). Electroencephalographic (EEG) Alpha rhythm (8–12 Hz) was recorded from 64 scalp sites while participants watched (in counterbalanced order across participants) two separate blocks of 45 slides and 45 clips. Each block included three groups of 15 validated stimuli classified as Erotic, Neutral and Fear content. Greater self-perceived arousal was found after the presentation of Fear and Erotic video clips compared with the same slide categories. sLORETA analysis showed a different lateralization pattern: slides induced decreased Alpha power (greater activation) in the left secondary visual area (Brodmann Area, BA, 18) to Erotic and Fear compared with the Neutral stimuli. Instead, video clips elicited reduced Alpha in the homologous right secondary visual area (BA 18) again to both Erotic and Fear contents compared with Neutral ones. Comparison of emotional stimuli showed smaller Alpha power to Erotic than to Fear stimuli in the left precuneus/posterior cingulate cortex (BA 7/31) for the slide condition, and in the left superior parietal lobule (BA 7) for the clip condition. This result matched the parallel analysis of the overlapped Mu rhythm (corresponding to the upper Alpha band) and can be interpreted as Mu/Alpha EEG suppression elicited by greater motor action tendency to Erotic (approach motivation) compared to Fear (withdrawal motivation) stimuli. Correlation analysis found lower Alpha in the left middle temporal gyrus (BA 21) associated with greater pleasantness to Erotic slides ( r 38 = –0.62, p = 0.009), whereas lower Alpha in the right supramarginal/angular gyrus (BA 40/39) was associated with greater pleasantness to Neutral clips ( r 38 = –0.69, p = 0.012). Results point to stronger emotion elicitation of movies vs. slides, but also to a specific involvement of the two hemispheres during emotional processing of slides vs. video clips, with a shift from the left to the right associative visual areas.
... Furthermore, theta frequency has been mostly associated to emotional information processing (Balconi & Lucchiari, 2006;Sammler et al., 2007), together with internal attention and memory-related processes (Cona et al., 2020;Sauseng et al., 2010). At a general level, introductory and technical phases seem to be the more challenging from an emotional perspective in candidates and interviewers. ...
In the last decades, improving remote communications in companies has been a compelling issue. With the outspread of SARS-CoV-2 pandemic, this phenomenon has undergone an acceleration. Despite this, little to no research, considering neurocognitive and emotional systems, was conducted on job interview, a critical organizational phase which significantly contributes to a company long-term success.In this study, we aimed at exploring the emotional and cognitive processes related to different phases of a job interview (introductory, attitudinal, technical and conclusion), when considering two conditions: face-to-face and remote, by simultaneously gathering EEG (frequency bands: alpha, beta, delta, and theta) and autonomic data (skin-conductance-level, SCL, skin-conductance-response, SCR, and heart rate, HR) in both candidates and recruiters. Data highlighted a generalized alpha desynchronization during the job interview interaction. Recruiters showed increased frontal theta activity, which is connected to socio-emotional situations and emotional processing. In addition, results showed how face-to-face condition is related to increased SCL and theta power in the central-brain area, associated with learning processes, via the mid-brain dopamine system and the anterior cingulate cortex. Furthermore, we found higher HR in the candidates. Present results call to re-examine the impact of information-technology in the organization, opening to translational opportunities.
... When considering effects other than ERP effects, in the time window when the regulation takes place, theta and beta frequencies decrease (Sulpizio et al., 2020;Tortella-Feliu et al., 2014). Thus, lower activity in such bands may represent diminished salience and reduced attentional demand for the incoming emotional stimuli (Balconi & Lucchiari, 2006) as an effect of the application of the strategy to the emotions elicited by such stimuli Guntekin & Basar, 2007;Woodruff et al., 2011). Nevertheless, Tolegenova and colleagues (2014) reported no effect in the beta band for participants asked to regulate their emotions while seeing negative movies. ...
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Over the past years, EEG studies focused on task-related activity to characterize cortical responses associated with emotion regulation, without exploring the possibility that regulating emotions can leave a trace in the brain by affecting its oscillatory activity. Demonstrating whether the effect of regulation alters the brain activity after the session and whether this reflects an increased cognitive regulatory ability has great relevance. To address this issue, five minutes of electrical brain activity at rest were recorded before and after 1) one session in which participants perceived and regulated (through distancing) their emotions (Regulation Session, ReS), and 2) another session in which they only perceived emotions (Attend Session, AtS). One hundred and sixty visual stimuli were presented and subjective ratings of valence and arousal of stimuli were recorded. Behavioral results showed the efficacy of the regulation strategy in modulating both arousal and valence. A cluster-based permutation test on EEG data at rest revealed a significant increase in theta and delta activity after the ReS compared to the AtS, suggesting that regulating emotions can alter brain activity after the session. We then outlined a comprehensive view of the neurophysiological mechanisms associated with emotion regulation.
... With the development of the brain-computer interface (BCI) and the advancement of artificial intelligence, the recognition of emotions based on EEG signals has become an active research topic of emotion recognition. EEG signals contain a large amount of information related to emotions and have the characteristics of high time resolution, and are not effortless to disguise (4)(5)(6), which shows tremendous advantages in the field of real-time emotion recognition. Accurate and real-time judgment of human emotional state through some technical means has great application value in many areas, for example, driving fatigue detection (7), depression monitoring (8), and real-time monitoring of critically ill patients (9). ...
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The main characteristic of depression is emotional dysfunction, manifested by increased levels of negative emotions and decreased levels of positive emotions. Therefore, accurate emotion recognition is an effective way to assess depression. Among the various signals used for emotion recognition, electroencephalogram (EEG) signal has attracted widespread attention due to its multiple advantages, such as rich spatiotemporal information in multi-channel EEG signals. First, we use filtering and Euclidean alignment for data preprocessing. In the feature extraction, we use short-time Fourier transform and Hilbert–Huang transform to extract time-frequency features, and convolutional neural networks to extract spatial features. Finally, bi-directional long short-term memory explored the timing relationship. Before performing the convolution operation, according to the unique topology of the EEG channel, the EEG features are converted into 3D tensors. This study has achieved good results on two emotion databases: SEED and Emotional BCI of 2020 WORLD ROBOT COMPETITION. We applied this method to the recognition of depression based on EEG and achieved a recognition rate of more than 70% under the five-fold cross-validation. In addition, the subject-independent protocol on SEED data has achieved a state-of-the-art recognition rate, which exceeds the existing research methods. We propose a novel EEG emotion recognition framework for depression detection, which provides a robust algorithm for real-time clinical depression detection based on EEG.
... In the current study, during the time window of 800-1200 ms, the main effect of three conditions was significant, with theta increases of funny conditions being significantly larger than unfunny and unrelated conditions in frontal areas (funny and unfunny conditions presented marginally significant difference) (see Fig. 3a), in that theta power was enhanced by affective content (Aftanas & Colochekine, 2001;Balconi & Lucchiari, 2006). ERO power changes in theta frequency range showed a marked reactivity, suggesting a functional role of theta band activity in mediating verbal-humor processing by intelligence levels. ...
Intelligence (measured by IQ) varies across individuals. An individual's IQ has been evidenced to be positively associated with verbal-humor production. However, to our knowledge, no study to date has examined how intelligence affects verbal-humor processing. The objective of this current electroencephalogram (EEG) study is to explore the dynamic impact of intelligence on processing patterns in three stages of verbal-humor processing from both temporal and oscillatory perspectives. Twenty-six subjects were recruited and required to read setup-punchline type statements in three conditions (funny, unfunny and unrelated). Event-related Potentials (ERPs) analysis found the earliest differences between relatively higher IQ (RHI) group and relatively lower IQ (RLI) group in dealing with unfunny conditions in the P200 component due to its role as a neural marker mediated by intelligence in language processing; more importantly, the processing patterns in two stages, incongruity detection and mirth, were found to be modulated by intelligence levels: the analysis of the N400 effect presented typical characteristics of incongruity detection for RHI group, while nontypical characteristics close to N300-like effect were found for RLI group; in the stage of mirth, RHI group presented a sustained P600 effect, while RLI group presented proper features of emotion processing. At the global level, these results indicate that people with different intelligence levels may employ dual-pattern model in processing two stages among three stages of verbal-humor appreciation. Event-related Oscillations (EROs) analysis revealed the functional role of the theta band and disclosed the impact of intelligence levels on the early stage of verbal-humor processing from the perspective of ERO. In the future research, further methodological considerations should be included to clarify the innate brain mechanisms aiming at examining intelligence differences regarding verbal-humor processing or indeed on any other issues.
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To date, affective and cognitive processing of emotional information in individuals with depressive symptoms have been examined through peripheral psychophysiological measures, event-related potentials, and time–frequency analysis of oscillatory activity. However, electrocortical correlates of emotional and cognitive processing of affective content in depression have not been fully understood. Time–frequency analysis of electroencephalographic activity allows disentangling the brain's parallel processing of information. The present study employed a time–frequency approach to simultaneously examine affective disposition and cognitive processing during the viewing of emotional stimuli in dysphoria. Time–frequency event-related changes were examined during the viewing of pleasant, neutral and unpleasant pictures in 24 individuals with dysphoria and 24 controls. Affective disposition was indexed by delta and alpha power, while theta power was employed as a correlate of cognitive elaboration of the stimuli. Cluster-based statistics revealed a centro-parietal reduction in delta power for pleasant stimuli in individuals with dysphoria relative to controls. Also, dysphoria was characterized by an early fronto-central increase in theta power for unpleasant stimuli relative to neutral and pleasant ones. Comparatively, controls were characterized by a late fronto-central and occipital reduction in theta power for unpleasant stimuli relative to neutral and pleasant. The present study granted novel insights on the interrelated facets of affective elaboration in dysphoria, mainly characterized by a hypoactivation of the approach-related motivational system and a sustained facilitated cognitive processing of unpleasant stimuli.
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The waking brain efficiently detects emotional signals to promote survival. However, emotion detection during sleep is poorly understood, and may be influenced by individual sleep characteristics or neural reactivity. Notably, dream recall frequency has been associated with stimulus reactivity during sleep, with enhanced stimulus-driven responses in high versus low recallers. Using electroencephalography (EEG), we characterized the neural responses of healthy individuals to emotional, neutral voices and control stimuli, both during wakefulness and NREM sleep. Then, we tested how these responses varied with individual dream recall frequency. Event-related potentials (ERPs) differed for emotional versus neutral voices, both in wakefulness and NREM. Likewise, EEG arousals (sleep perturbations) increased selectively after the emotional voices, indicating emotion reactivity. Interestingly, sleep ERP amplitude and arousals after emotional voices increased linearly with participants’ dream recall frequency. Similar correlations with dream recall were observed for beta and sigma responses, but not for theta. In contrast, dream recall correlations were absent for neutral or control stimuli. Our results reveal that brain reactivity to affective salience is preserved during NREM, and is selectively associated to individual memory for dreams. Our findings also suggest that emotion-specific reactivity during sleep, and not generalized alertness, may contribute to the encoding/retrieval of dreams.
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Recently, numerous novel methods have flourished in brain research and cognitive sciences, increasing our knowledge of the ways in which the human brain processes information. Experimental studies utilizing modern neurophysiological and neuroimaging techniques (EEG; electroencephalogram, MEG; magnetoencephalogram; fMRI; functional magnetic resonance imaging, PET; positron emission tomography) in association with cognitive processing have provided an opportunity to approach subtle brain-behavior relationships in a more direct and empirical manner than ever before. Although being one of the oldest psychophysiological methods to study brain activity, the electroencephalogram (EEG) can successfully be utilized in modern brain research in order to assess brain activity during cognitive functioning. In this chapter, the role of brain electric oscillations in revealing the neural basis of human cognitive and memory processes will be discussed.
This book establishes a brain theory based on neural oscillations with a temporal relation to a well-defined event. New findings about oscillations at the cellular level show striking parallels with EEG and MEG measurements. The authors embrace both the level of single neurons and that of the brain as a whole, showing how this approach advances our knowledge about the functional significance of the brain's electrical activity. They are related to sensory and cognitive tasks, leading towards an "integrative neurophysiology". The book will appeal to scientists and graduate students. This two-volume treatise has the special features that: - powerful mathematical algorithms are used; - concepts of synergetics, synchronization of cell assemblies provide a new theory of evoked potentials; - the EEG frequencies are considered as a type of alphabet of brain function; - based on the results described, brain oscillations are correlated with multiple functions, including sensory registration, perception, movement and cognitive processes related to attention,learning and memory; - the superposition principle of event-related oscillations and brain Feynmann diagrams are introduced as metaphors from quantum theory.
Roche Holding AG signed a $230 million deal with Maxygen Inc. to license its next-generation interferons to treat hepatitis. The deal boosted Rocke's stake in the interferon alpha drug market, which is poised for rapid expansion. Total payment to Maxygen over the next two years, including research and development funding and option fees, is $30 million.
Individual differences in emotional reactivity or affective style can be decomposed into more elementary constituents. Several separable of affective style are identified such as the threshold for reactivity, peak amplitude of response, the rise time to peak and the recovery time. latter two characteristics constitute components of affective chronometry The circuitry that underlies two fundamental forms of motivation and and withdrawal-related processes-is described. Data on differences in functional activity in certain components of these are next reviewed, with an emphasis on the nomological network of surrounding individual differences in asymmetric prefrontal The relevance of such differences for understanding the nature affective dysfunction in affective disorders is then considered. The ends by considering what the prefrontal cortex “does” in certain of affective style and highlights some of the important questions for future research.
This article reviews the modern literature on two key aspects of the central circuitry of emotion - the prefrontal cortex (PFC) and the amygdala. There are several different functional divisions of the PFC including the dorsolateral, ventromedial and orbitofrontal sectors. Each of these regions plays some role in affective processing that shares the feature of representing affect in the absence of immediate rewards and punishments as well as in different aspects of emotional regulation. The amygdala appears to be crucial for the learning of new stimulus-threat contingencies and also appears to be important in the expression of cue-specific fear. Individual differences in both tonic activation and phasic reactivity in this circuit play an important role in governing affective style. Emphasis is placed upon affective chronometry, or the time course of emotional responding, as a key attribute of emotion that varies across individuals and is regulated by this circuitry.
Auditory event-related potentials (ERPs) were recorded from 71 healthy individuals between 18 and 82 years of age during performance of a disjunctive reaction time task in an auditory oddball paradigm. The effects of aging on reaction times and on the latencies, amplitudes, and distributions of each of the main ERP components were examined. No significant slowing of the reaction times of the elderly subjects was observed in relation to the younger ones. The peak latencies of both the N1 and P2 components elicited by standard tones were slightly but significantly slowed with age. In the ERPs of target tones, the later, endogenous components (N2, P3, and SW) showed linear increases in latency as a function of age; the later the component, the longer the age-related delay. In general, aging was associated with less negativity (both N2 and SW) and more positivity (P3) over the anterior scalp, together with a smaller P3 and a more pronounced N2 over posterior scalp areas. Most of the effects observed in target ERPs were also evident in the difference waves derived from subtraction of the standard from the target ERPs, although the slope of the age-related latency increase of N2 was shallower and that of the P3 was steeper in the difference ERPs. These findings are discussed in relation to previous accounts of ERP changes with aging.