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EEG correlates (event-related desynchronization) of emotional face elaboration: A temporal analysis
Neuroscience Letters 392 (2006) 118–123
EEG correlates (event-related desynchronization) of emotional face elaboration: A temporal analysis Michela Balconi a,∗ , Claudio Lucchiari b a
Laboratory of Cognitive Psychology, Department of Psychology, Catholic University of Milan, Largo Gemelli 1, 20123 Milan, Italy b Department of Neurology, Neurological National Hospital“C. Besta”, Milan, Italy Received 31 March 2005; received in revised form 25 August 2005; accepted 2 September 2005
Abstract 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. © 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 communicating 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 emotional face, a variety of specific emotional processes emerge in the central and peripheral nervous system. Specifically, motivational significance and relevance of the emotional face may have an effect on attentional mechanism [20,21]. The present study aimed at studying the brain mechanisms underlying human emotional 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]. Correlates of affective face processing have been investigated 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: [email protected] (M. Balconi).
0304-3940/$ – see front matter © 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2005.09.004
positive peak was observed at about 100 ms 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 550 ms after stimulus onset [20]. An early negative deflection (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 stimulation, 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 component representing updating aspect of processing, independently of the nature of the stimuli, since this effect is viewed as reflecting decision or cognitive closure of the recognition processing [7,13]. On the other hand, brain oscillations were found a powerful tool to analyze the cognitive processes related to emotion comprehension [5,18]. Recent researches showed the event-related theta band power responds specifically to prolonged visual emotional stimulation [19], and a synchronization was revealed in case of coordinated response indicating alertness, arousal and
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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 stimulus 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 oscillations, 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 20 Hz). Another critical issue of the present research is the comparison of the frequency 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 200 ms and 300 ms of latency) that were found as discriminant in emotional processing. In addition, one question that has been raised concerns 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, showing relatively greater right hemisphere ERS for nega-
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-normal visual acuity. Stimulus materials were taken from the set of pictures of Ekman and Friesen [11]. They were black and white pictures of male and female (equally distributed) 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 4◦ and a vertical angle of 6◦ (STIM 4.2 software). The stimulus was presented for 500 ms on the monitor with an interstimulus interval parameter (ISI) of 1500 ms, 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 100 cm in front of their eyes. During the examination, 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 placement). 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 5 k. After EOG correction and visual inspection only artefact-free trials were considered. Only 14 electrodes were used for the successive statistical analysis (4 central, Fz, Cz, Pz, Oz; 10 lateral, F3, F4, C3,
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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 100 ms. An average absolute power value for each electrode for each condition (emotional versus neutral) was calculated separately for each frequency band. An average of the pre-experimental absolute power was used to determine the individual power during no stimulation. From this reference power value, individual power changes during face viewing were determined as the relative stimulus-related decrease (desynchronization). In fact, according 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 900 ms post-stimulus) as compared to a reference interval (here 1500 ms 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 350–450 ms. 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 electrode 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 factors, 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 location, and secondly over left (F3, C3, T3, P3, 01) and right (F4, C4, T4, P4, 02) sides. These new values were entered in two distinct statistical analyses. For all the ANOVAs, degrees of freedom were Greenhouse–Geisser corrected where appropriate. In the first time interval, ANOVA showed the statistical significance 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 (respectively 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 synchronization 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 significant 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 emotional 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) comparisons. The synchronization was varied as a function of stimulus 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 successive ANOVAs, in order to analyze Location (anterior, central, 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 indicated that theta frequency band synchronizes mainly in the frontal regions of the scalp during emotional stimulus elaboration, whereas delta band was concentrated in the posterior 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 band during elaboration of emotional stimuli 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 posthoc 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 (emotional 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 (maximum 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 350–450 ms, Band effect was significant (F(3,19) = 4.02, P = 0.008). Specifically, as showed by post-hoc comparison, delta frequency band synchronizes 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 desynchronization. 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 separately for each frequency band. In the alpha band only the Time main effect was statistically significant (F(3,19) = 6.05,
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P = 0.001). Contrast analysis showed a significant increasing of ERD for the first interval in comparison with the others (1/2 intervals (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 sensitivity 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) factors, 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 150–450 ms. Moreover, a maximum of synchronization of the oscillations was revealed during the third time interval (250–350 ms), with a peak of the band power around 320 ms. This synchronization appears due to the emotional content 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 successive time intervals. ANOVAs revealed differences in Location (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 statistical 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 being associated with a selective ERD reduction within 150–250 time window, and a gradual increasing of ERD during the successive time intervals (350–450 time). An interesting result of the analysis was that the synchronization of theta band was observed mainly for emotional stimuli compared with neutral stimuli in the second and third time interval. Successive ANOVAs 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 anterior synchronization of theta frequency band during the second and third time interval, and this effect was related to emotional stimuli. Three major effects were found in the present research. First, the results support the view that the responses of different 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 sensitive to emotional content of face. Especially theta and delta
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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 frequency band power were differentiated as a function of their higher (delta/theta) and lower (alpha/beta) sensitivity to emotional significance of face. For the alpha band power an interesting features is the spectral changes in response to the stimulus as compared to baseline in the first time interval, showing an interaction between stimulus elaboration and this frequency band. Specifically, alpha showed a greater decrease (desynchronization) selectively up 150 ms for all the stimulus, whereas a more stable ERD is observed during the other stages of stimulus elaboration (from 150 ms). Previous study found that alpha 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 present research alpha variation may be a marker of the first stage of stimulus elaboration that is related to alertness mechanism. On the contrary, narrow frequency bands (delta and theta) showed to synchronize especially during emotion-related information elaboration. We observed 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 350 ms), where the increase of theta and delta power reached a maximum of intensity. Specifically, delta showed a higher synchronization at about 320 ms poststimulus. 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 240 ms 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 addition 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 oscillations were related to the emotional content of face, whereas delta responded similarly (synchronously) to emotional and neutral 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 temporal windows are specifically due to the evolving of stimulus elaboration. In particular, time course of affective theta and beta synchronization during facial expression comprehension showed discrimination between early and later processing stages of stimulus. Delta band reached a gradual synchronization within the temporal sequences, with a peak at about 300 ms. Contrarily, theta was enhanced during the 150–250 ms, reaching greater synchronization at about 200 ms post-stimulus. This pattern suggests 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
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the exigency of stimulus updating in memory [12]. This cognitive 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. Nevertheless, 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 (250–350 ms) 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 attention 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 comparison 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 motivational significance of the emotional faces. More generally, an interesting result of the present research is that each oscillation appears to respond to variations in processing stage of emotional face by variations in latency. As we have stated the latency (different time intervals) and content sensitivity (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, oscillatory 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 motivational value of the stimulus [25]. Contrarily, P3 was more generally linked to the decisional aspect of processing, independently 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 contrary 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 preferential 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 generators 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 likely to be located at the anterior sites that are a network 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 previous study, that underlined the lateralization of emotional face processing, since aright hemisphere dominance for emotional face comprehension was pointed out [10,20]. In parallel, cortical 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 hemisphere side [3]. Nevertheless our results present some limits due to the necessity to analyze in a more systematic manner the specific 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 that the emotional valence of face (negative versus 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 existence of partially distinct systems. For example, amygdala is required for processing fear but not happiness. Thus, the incidence of this variable on the attentional and motivational levels, and therefore, on the brain oscillations must be tested systematically in the future. References [1] L.I. Aftanas, V.I. Koshkarov, V.L. Pokrovskaja, N.V. Lotova, Y.N. Mordvintsev, Event-related desynchronization (ERD) patterns to emotionrelated feedback stimuli, Int. J. Neurosci. 87 (1996) 151–173. [2] L.I. Aftanas, A.A. Varlamon, S.V. Pavlov, V.P. Makhnev, N.V. Reva, Affective picture processing: event-related synchronization within individually defined human theta band is modulated by valence dimension, Neurosci. Lett. 303 (2001) 115–118. [3] M. Balconi, U. Pozzoli, Face-selective processing and the effect of pleasant and unpleasant emotional expressions on ERP correlates, Int. J. Psychophysiol. 49 (2003) 67–74. [4] E. Bas¸ar, Brain Function and Oscillations II. Integrative Brain Function. Neurophysiology and Cognitive Processes, Springer, Heidelberg, 1999. [5] E. Bas¸ar, C. Bas¸ar-Eroglu, S. Karakas, M. Schiirman, Are cognitive processes manifested in event-related gamma, alpha, theta and delta oscillations in the EEG? Neurosci. Lett. 259 (1999) 165–168. [6] E. Bernat, S. Bunce, H. Shevrin, Event-related brain potentials differentiate positive and negative mood adjectives during both supraliminal and subliminal visual processing, Int. J. Psychophysiol. 42 (2001) 11–34. [7] M. Brazdil, I. Rektor, P. Daniel, M. Dufek, P. Jurak, Intracerebral eventrelated potentials to subthreshold target stimuli, Clin. Neurophysiol. 112 (2001) 650–661. [8] C. Darwin, The Expression of Emotions in Man and Animals, John Murray, London, 1872. [9] R.J. Davidson, Affective style and affective disorders: perspectives from affective neuroscience, Cog. Emot. 12 (1998) 307–330. [10] R.J. Davidson, The neural circuitry of emotion and affective style: prefrontal cortex and amygdala contribution, Soc. Sci. Inform. 40 (2001) 11–39. [11] P. Ekman, W.V. Friesen, Pictures of Facial Affect Consulting, Psychologist Press, Palo Alto, 1976.
M. Balconi, C. Lucchiari / Neuroscience Letters 392 (2006) 118–123 [12] T. Fernandez, T. Harmony, J. Silva, L. Galan, L. Diaz-Comas, J. Bosch, M. Rodriguez, A. Fernandez-Bouzaas, G. Yafiez, G. Otero, E. Marosi, Relationship of specific EEG frequencies at specific brain areas with performances, NeuroReport 9 (1998) 3681–3687. [13] V.J. Iragui, M. Kutas, M.R. Mtchiner, S.A. Hillyard, Effect of aging on event-related brain potentials and reaction times in an auditory oddball task, Psychophysiology 30 (1993) 10–22. [14] S. Karakas, O.U. Erzengin, E. Bas¸ar, The genesis of human event-related responses explained through the theory of oscillatory neural assemblies, Neurosci. Lett. 285 (2000) 45–48. [15] A. Keil, M.M. Miiller, T. Gruber, C. Wienbruch, M. Stolarova, T. Elbert, Effects of emotional arousal in the cerebral hemispheres: a study of oscillatory brain activity and event-related potentials, Clin. Neuropsychol. 112 (2001) 2057–2068. [16] W. Klimesch, EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis, Brain Res. Rev. 29 (1997) 169–195. [17] W. Klimesch, M. Doppelmayr, J. Schwaiger, P. Auinmger, T. Winkler, Paradoxical’ alpha syncronization in a memory task, Cog, Brain Res. 7 (1999) 493–501. [18] C.M. Krause, Brain electric oscillations and cognitive processes, in: K. Hugdahl (Ed.), Experimental Methods in Neuropsychology, Kluwer, New York, 2003, pp. 11–130. [19] C.M. Krause, V. Viemero, A. Rosenqvist, L. Sillanmaki, T. Astrom, Relative electroencephalographic desyncronization and syncronization in
[20]
[21]
[22]
[23]
[24]
[25]
[26]
123
humans to emotional film content: an analysis of the 4–6, 6–8, 8–10 and 10–12 Hz frequency bands, Neurosci. Lett. 286 (2000) 9–12. P. Krolak-Salmon, C. Fischer, A. Vighetto, F. Mauguiere, Processing of facial emotional expression: spatio-temporal data as assessed by scalp event-related potentials, Eur. J. Neurosci. 13 (2001) 987– 994. P.J. Lang, M.M. Bradley, J. Fitzsimmons, R. Cuthbert, B.N. Scott, J.D. Moulder, B. Nangia, Emotional arousal and activation of the visual cortex: an fMRI analysis, Psychophysiology 35 (1998) 199–210. G. Pfurtscheller, Event-related synchronization (ERS): an electrophysiological correlate of cortical areas at rest, Electroenceph. Clin. Neurophysiol 83 (1992) 62–69. P. Pizzagalli, M. Regars, P. Lehmann, Rapid emotional face processing in the human right and left brain hemispheres, Neuroreport 10 (1999) 2691–2698. W. Sato, K. Takanori, Y. Sakiko, M. Michikazu, Emotional expression boosts early visual processing of the face: ERP recording and its decomposition by independent component analysis, NeuroReport 12 (2000) 709–714. J.L.G. Schutter, E.H.F. de Haan, J. van Honk, Functionally dissociated aspects in anterior and posterior electrocortical processing of facial threat, Int. J. Psychophysiol. 53 (2004) 29–36. M. Streit, W. Wolwer, J. Brinkmeyer, R. Ihl, W. Gaebel, Electrophysiological correlates of emotional and structural face processing in humans, Neurosci. Lett. 278 (2000) 13–16.
EEG correlates (event-related desynchronization) of emotional face elaboration: A temporal analysis Michela Balconi a,∗ , Claudio Lucchiari b a
Laboratory of Cognitive Psychology, Department of Psychology, Catholic University of Milan, Largo Gemelli 1, 20123 Milan, Italy b Department of Neurology, Neurological National Hospital“C. Besta”, Milan, Italy Received 31 March 2005; received in revised form 25 August 2005; accepted 2 September 2005
Abstract 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. © 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 communicating 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 emotional face, a variety of specific emotional processes emerge in the central and peripheral nervous system. Specifically, motivational significance and relevance of the emotional face may have an effect on attentional mechanism [20,21]. The present study aimed at studying the brain mechanisms underlying human emotional 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]. Correlates of affective face processing have been investigated 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
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0304-3940/$ – see front matter © 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2005.09.004
positive peak was observed at about 100 ms 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 550 ms after stimulus onset [20]. An early negative deflection (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 stimulation, 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 component representing updating aspect of processing, independently of the nature of the stimuli, since this effect is viewed as reflecting decision or cognitive closure of the recognition processing [7,13]. On the other hand, brain oscillations were found a powerful tool to analyze the cognitive processes related to emotion comprehension [5,18]. Recent researches showed the event-related theta band power responds specifically to prolonged visual emotional stimulation [19], and a synchronization was revealed in case of coordinated response indicating alertness, arousal and
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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 stimulus 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 oscillations, 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 20 Hz). Another critical issue of the present research is the comparison of the frequency 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 200 ms and 300 ms of latency) that were found as discriminant in emotional processing. In addition, one question that has been raised concerns 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, showing relatively greater right hemisphere ERS for nega-
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-normal visual acuity. Stimulus materials were taken from the set of pictures of Ekman and Friesen [11]. They were black and white pictures of male and female (equally distributed) 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 4◦ and a vertical angle of 6◦ (STIM 4.2 software). The stimulus was presented for 500 ms on the monitor with an interstimulus interval parameter (ISI) of 1500 ms, 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 100 cm in front of their eyes. During the examination, 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 placement). 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 5 k. After EOG correction and visual inspection only artefact-free trials were considered. Only 14 electrodes were used for the successive statistical analysis (4 central, Fz, Cz, Pz, Oz; 10 lateral, F3, F4, C3,
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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 100 ms. An average absolute power value for each electrode for each condition (emotional versus neutral) was calculated separately for each frequency band. An average of the pre-experimental absolute power was used to determine the individual power during no stimulation. From this reference power value, individual power changes during face viewing were determined as the relative stimulus-related decrease (desynchronization). In fact, according 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 900 ms post-stimulus) as compared to a reference interval (here 1500 ms 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 350–450 ms. 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 electrode 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 factors, 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 location, and secondly over left (F3, C3, T3, P3, 01) and right (F4, C4, T4, P4, 02) sides. These new values were entered in two distinct statistical analyses. For all the ANOVAs, degrees of freedom were Greenhouse–Geisser corrected where appropriate. In the first time interval, ANOVA showed the statistical significance 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 (respectively 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 synchronization 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 significant 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 emotional 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) comparisons. The synchronization was varied as a function of stimulus 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 successive ANOVAs, in order to analyze Location (anterior, central, 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 indicated that theta frequency band synchronizes mainly in the frontal regions of the scalp during emotional stimulus elaboration, whereas delta band was concentrated in the posterior 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 band during elaboration of emotional stimuli 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 posthoc 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 (emotional 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 (maximum 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 350–450 ms, Band effect was significant (F(3,19) = 4.02, P = 0.008). Specifically, as showed by post-hoc comparison, delta frequency band synchronizes 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 desynchronization. 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 separately for each frequency band. In the alpha band only the Time main effect was statistically significant (F(3,19) = 6.05,
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P = 0.001). Contrast analysis showed a significant increasing of ERD for the first interval in comparison with the others (1/2 intervals (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 sensitivity 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) factors, 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 150–450 ms. Moreover, a maximum of synchronization of the oscillations was revealed during the third time interval (250–350 ms), with a peak of the band power around 320 ms. This synchronization appears due to the emotional content 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 successive time intervals. ANOVAs revealed differences in Location (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 statistical 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 being associated with a selective ERD reduction within 150–250 time window, and a gradual increasing of ERD during the successive time intervals (350–450 time). An interesting result of the analysis was that the synchronization of theta band was observed mainly for emotional stimuli compared with neutral stimuli in the second and third time interval. Successive ANOVAs 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 anterior synchronization of theta frequency band during the second and third time interval, and this effect was related to emotional stimuli. Three major effects were found in the present research. First, the results support the view that the responses of different 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 sensitive to emotional content of face. Especially theta and delta
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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 frequency band power were differentiated as a function of their higher (delta/theta) and lower (alpha/beta) sensitivity to emotional significance of face. For the alpha band power an interesting features is the spectral changes in response to the stimulus as compared to baseline in the first time interval, showing an interaction between stimulus elaboration and this frequency band. Specifically, alpha showed a greater decrease (desynchronization) selectively up 150 ms for all the stimulus, whereas a more stable ERD is observed during the other stages of stimulus elaboration (from 150 ms). Previous study found that alpha 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 present research alpha variation may be a marker of the first stage of stimulus elaboration that is related to alertness mechanism. On the contrary, narrow frequency bands (delta and theta) showed to synchronize especially during emotion-related information elaboration. We observed 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 350 ms), where the increase of theta and delta power reached a maximum of intensity. Specifically, delta showed a higher synchronization at about 320 ms poststimulus. 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 240 ms 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 addition 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 oscillations were related to the emotional content of face, whereas delta responded similarly (synchronously) to emotional and neutral 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 temporal windows are specifically due to the evolving of stimulus elaboration. In particular, time course of affective theta and beta synchronization during facial expression comprehension showed discrimination between early and later processing stages of stimulus. Delta band reached a gradual synchronization within the temporal sequences, with a peak at about 300 ms. Contrarily, theta was enhanced during the 150–250 ms, reaching greater synchronization at about 200 ms post-stimulus. This pattern suggests 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
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the exigency of stimulus updating in memory [12]. This cognitive 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. Nevertheless, 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 (250–350 ms) 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 attention 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 comparison 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 motivational significance of the emotional faces. More generally, an interesting result of the present research is that each oscillation appears to respond to variations in processing stage of emotional face by variations in latency. As we have stated the latency (different time intervals) and content sensitivity (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, oscillatory 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 motivational value of the stimulus [25]. Contrarily, P3 was more generally linked to the decisional aspect of processing, independently 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 contrary 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 preferential 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 generators 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 likely to be located at the anterior sites that are a network 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 previous study, that underlined the lateralization of emotional face processing, since aright hemisphere dominance for emotional face comprehension was pointed out [10,20]. In parallel, cortical 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 hemisphere side [3]. Nevertheless our results present some limits due to the necessity to analyze in a more systematic manner the specific 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 that the emotional valence of face (negative versus 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 existence of partially distinct systems. For example, amygdala is required for processing fear but not happiness. Thus, the incidence of this variable on the attentional and motivational levels, and therefore, on the brain oscillations must be tested systematically in the future. References [1] L.I. Aftanas, V.I. Koshkarov, V.L. Pokrovskaja, N.V. Lotova, Y.N. Mordvintsev, Event-related desynchronization (ERD) patterns to emotionrelated feedback stimuli, Int. J. Neurosci. 87 (1996) 151–173. [2] L.I. Aftanas, A.A. Varlamon, S.V. Pavlov, V.P. Makhnev, N.V. Reva, Affective picture processing: event-related synchronization within individually defined human theta band is modulated by valence dimension, Neurosci. Lett. 303 (2001) 115–118. [3] M. Balconi, U. Pozzoli, Face-selective processing and the effect of pleasant and unpleasant emotional expressions on ERP correlates, Int. J. Psychophysiol. 49 (2003) 67–74. [4] E. Bas¸ar, Brain Function and Oscillations II. Integrative Brain Function. Neurophysiology and Cognitive Processes, Springer, Heidelberg, 1999. [5] E. Bas¸ar, C. Bas¸ar-Eroglu, S. Karakas, M. Schiirman, Are cognitive processes manifested in event-related gamma, alpha, theta and delta oscillations in the EEG? Neurosci. Lett. 259 (1999) 165–168. [6] E. Bernat, S. Bunce, H. Shevrin, Event-related brain potentials differentiate positive and negative mood adjectives during both supraliminal and subliminal visual processing, Int. J. Psychophysiol. 42 (2001) 11–34. [7] M. Brazdil, I. Rektor, P. Daniel, M. Dufek, P. Jurak, Intracerebral eventrelated potentials to subthreshold target stimuli, Clin. Neurophysiol. 112 (2001) 650–661. [8] C. Darwin, The Expression of Emotions in Man and Animals, John Murray, London, 1872. [9] R.J. Davidson, Affective style and affective disorders: perspectives from affective neuroscience, Cog. Emot. 12 (1998) 307–330. [10] R.J. Davidson, The neural circuitry of emotion and affective style: prefrontal cortex and amygdala contribution, Soc. Sci. Inform. 40 (2001) 11–39. [11] P. Ekman, W.V. Friesen, Pictures of Facial Affect Consulting, Psychologist Press, Palo Alto, 1976.
M. Balconi, C. Lucchiari / Neuroscience Letters 392 (2006) 118–123 [12] T. Fernandez, T. Harmony, J. Silva, L. Galan, L. Diaz-Comas, J. Bosch, M. Rodriguez, A. Fernandez-Bouzaas, G. Yafiez, G. Otero, E. Marosi, Relationship of specific EEG frequencies at specific brain areas with performances, NeuroReport 9 (1998) 3681–3687. [13] V.J. Iragui, M. Kutas, M.R. Mtchiner, S.A. Hillyard, Effect of aging on event-related brain potentials and reaction times in an auditory oddball task, Psychophysiology 30 (1993) 10–22. [14] S. Karakas, O.U. Erzengin, E. Bas¸ar, The genesis of human event-related responses explained through the theory of oscillatory neural assemblies, Neurosci. Lett. 285 (2000) 45–48. [15] A. Keil, M.M. Miiller, T. Gruber, C. Wienbruch, M. Stolarova, T. Elbert, Effects of emotional arousal in the cerebral hemispheres: a study of oscillatory brain activity and event-related potentials, Clin. Neuropsychol. 112 (2001) 2057–2068. [16] W. Klimesch, EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis, Brain Res. Rev. 29 (1997) 169–195. [17] W. Klimesch, M. Doppelmayr, J. Schwaiger, P. Auinmger, T. Winkler, Paradoxical’ alpha syncronization in a memory task, Cog, Brain Res. 7 (1999) 493–501. [18] C.M. Krause, Brain electric oscillations and cognitive processes, in: K. Hugdahl (Ed.), Experimental Methods in Neuropsychology, Kluwer, New York, 2003, pp. 11–130. [19] C.M. Krause, V. Viemero, A. Rosenqvist, L. Sillanmaki, T. Astrom, Relative electroencephalographic desyncronization and syncronization in
[20]
[21]
[22]
[23]
[24]
[25]
[26]
123
humans to emotional film content: an analysis of the 4–6, 6–8, 8–10 and 10–12 Hz frequency bands, Neurosci. Lett. 286 (2000) 9–12. P. Krolak-Salmon, C. Fischer, A. Vighetto, F. Mauguiere, Processing of facial emotional expression: spatio-temporal data as assessed by scalp event-related potentials, Eur. J. Neurosci. 13 (2001) 987– 994. P.J. Lang, M.M. Bradley, J. Fitzsimmons, R. Cuthbert, B.N. Scott, J.D. Moulder, B. Nangia, Emotional arousal and activation of the visual cortex: an fMRI analysis, Psychophysiology 35 (1998) 199–210. G. Pfurtscheller, Event-related synchronization (ERS): an electrophysiological correlate of cortical areas at rest, Electroenceph. Clin. Neurophysiol 83 (1992) 62–69. P. Pizzagalli, M. Regars, P. Lehmann, Rapid emotional face processing in the human right and left brain hemispheres, Neuroreport 10 (1999) 2691–2698. W. Sato, K. Takanori, Y. Sakiko, M. Michikazu, Emotional expression boosts early visual processing of the face: ERP recording and its decomposition by independent component analysis, NeuroReport 12 (2000) 709–714. J.L.G. Schutter, E.H.F. de Haan, J. van Honk, Functionally dissociated aspects in anterior and posterior electrocortical processing of facial threat, Int. J. Psychophysiol. 53 (2004) 29–36. M. Streit, W. Wolwer, J. Brinkmeyer, R. Ihl, W. Gaebel, Electrophysiological correlates of emotional and structural face processing in humans, Neurosci. Lett. 278 (2000) 13–16.