International Journal of Psychophysiology 90 (2013) 334–340

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International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho

Event-related synchronization of delta and beta oscillations reflects developmental changes in the processing of affective pictures during adolescence Wenhai Zhang a,b, Jiamei Lu b, Xia Liu c,⁎, Hailin Fang a, Hong Li d, Dahua Wang c, Jiliang Shen c a b c d

Mental Health Center, Yancheng Institute of Technology, Yancheng City, China Department of Psychology, Shanghai Normal University, Shanghai City, China School of Psychology, Beijing Normal University, Beijing City 100875, China College of Psychology, Liaoning Normal University, Dalian City 116029, China

a r t i c l e

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Article history: Received 30 December 2012 Received in revised form 7 October 2013 Accepted 11 October 2013 Available online 18 October 2013 Keywords: Adolescence Event-related synchronization Delta Beta Late positive potential Affective picture

a b s t r a c t Recent research has determined that affective pictures modulate event-related delta and beta oscillations in adults. However, it is unclear whether these brain oscillations reflect developmental changes in the processing of affective information during adolescence. EEG data were collected from 51 adolescents and 18 undergraduates as they viewed a total of 90 pictures. In the range of fast wave activities, event-related synchronization (ERS) in the beta band varied with emotional valence, indicating that beta ERS is indicative of early bottom-up processing of visual emotional stimuli. Adolescents at the age of 12 years exhibited more positive beta ERS amplitudes over posterior brain regions for positive versus neutral pictures compared to adolescents at the ages 14 years, 16 years and in young adults; however, no age-related differences were found for negative versus neutral pictures. In the range of slow wave activities, delta ERSs and late positive potential (LPP) amplitudes exhibited affective modulation and decreased over anterior brain regions from between the age of 12 years and early adulthood. These slow wave activities (delta and LPPs) reflected top-down attention to the motivational relevance of the emotional stimuli. Taken together, these observations suggest that adolescents exhibit dissociable ERS patterns in the delta and beta bands during affective processing. Furthermore, adolescents undergo age-dependent changes in oscillatory brain reorganization. Our results should be useful to researchers interested in affective processing during adolescence. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Adolescence is a developmental period that is associated with increased vulnerability to stress, particularly with respect to affective stimuli (Dahl, 2004; Somerville et al., 2010; Spear, 2000). Behaviorally, adolescents display heightened responses to both positive and negative environmental stimuli compared with children and adults (Brenhouse and Andersena, 2011; Somerville et al., 2010). Neuroimaging research has shown that adolescents exhibit greater differences in responses in the amygdala in response to both fearful and happy facial expressions versus neutral facial expressions than do children and adults (Monk et al., 2003; Williams et al., 2006). However, these studies did not assess electrocortical changes in the processing of affective information. In this study, we used event-related potentials (ERPs) and event-related oscillations (EROs) to explore developmental changes in affective processing during adolescence. ⁎ Corresponding author at: Institute of Developmental Psychology, Beijing Normal University, NO.19 Xinjiekou Outer Street, Haidian District, Beijing City 100875, China. Tel.: +86 10 58807700; fax: +86 10 58808230. E-mail address: [email protected] (X. Liu). 0167-8760/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ijpsycho.2013.10.005

Numerous ERP studies of affective processing have determined that the late positive potential (LPP) is a measure of emotional reactivity in adults. The LPP is a positive component with a central-parietal scalp distribution that begins within a few hundred milliseconds after stimulus onset and is sustained for seconds (Cuthbert et al., 2000; Weinberg et al., 2012). Positive and negative pictures elicit larger LPP amplitudes compared to neutral pictures (Foti and Hajcak, 2008; Hajcak and Nieuwenhuis, 2006; Hajcak et al., 2009; Schupp et al., 2004; Yen et al., 2010), indicating that the LPP reflects an increase in attention to visual emotional stimuli (Lang et al., 1997; Schupp et al., 2006). Moreover, the LPP shows age-dependent changes during childhood. For example, children aged 5–8 years and 8–13 years of age exhibit increased LPP activities while viewing emotional pictures relative to neutral pictures from the international affective picture system (IAPS) (Hajcak and Olvet, 2008; Kujawa et al., 2012). Additionally, EROs are a powerful tool for the study of electrocortical changes in emotional processing including bottom-up and top-down processes (Aftanas et al., 2003a, 2003b; Knyazev, 2011). Bottom-up processing rapidly deploys attention to the properties of a sensory stimulus and results in fast wave activities (e.g., beta oscillations) (Baluch and Itti, 2011; Siegel et al., 2000). In contrast, top-down

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processing requires more effort to pay attention to behaviorally relevant events and results in slow wave activities (e.g., delta oscillations) (Mathes et al., 2006; Siegel et al., 2000). Delta oscillations (0.5–3.5 Hz) originate not only from subcortical areas, such as the nucleus accumbens (Leung and Yim, 1993), the ventral tegmental area (Grace, 1995), and the ventral pallidum (Lavin and Grace, 1996), but also from cortical regions, such as the medial prefrontal, anterior cingulate, and orbit frontal cortices (Dang-Vu et al., 2008). Moreover, cortical sources of delta activity show extensive reciprocal connectivity with various cortical, midbrain, and limbic structures (Alper et al., 2006) that are implicated in motivational brain circuits (Knyazev, 2012). Enhanced delta activity in the P300 paradigm is related to the motivational relevance of the task and the salience of the target stimulus (Knyazev, 2007). Additionally, IAPS pictures elicit synchronized delta power after stimulus onset (Klados et al., 2009). Increased delta power is observed in response to highly arousing, but not minimally arousing, IAPS pictures (Balconi et al., 2009). Delta synchronization intensifies upon the presentation of emotional stimuli during explicit and implicit emotional processing (Knyazev et al., 2009). Within the range of fast wave activities, beta oscillations (15–30 Hz) have been proposed to represent a cortico-cortical process that indexes local information processing (Jensen et al., 2005) and are associated with emotional and cognitive processes (Ray and Cole, 1985). Several studies have revealed significant roles of early beta responses in face recognition and the differentiation of known and unknown faces (ÖzgÖren et al., 2005; Başar et al., 2006, 2007). A growing number of studies have shown that affective stimuli elicit eventrelated beta responses (Güntekin et al., 2010); however, previous studies have produced contradictory results. Some studies have stressed the negativity bias of beta responses toward negative stimuli. For example, a reliable early beta oscillation in the visual cortex rapidly discriminates aversive IAPS images (Keil et al., 2007). Negative pictures elicit greater beta response amplitudes in parietal and occipital electrodes when compared with neutral pictures (Güntekin et al., 2010). Beta responses to angry faces are greater amplitude compared to those elicited by happy faces (Güntekin and Başar, 2007). Other studies have suggested that both negative and positive images from the IAPS elicit greater beta synchronization than neutral images (Cohen et al., 2012; Hummel and Gerloff, 2006; Miskovic and Schmidt, 2010). Another study suggested that beta frequencies are not modulated by facial expressions (Balconi and Pozzoli, 2007). However, the exact functional significance of eventrelated beta oscillations in affective processing has yet to be determined. To date, few studies have used event-related delta and beta oscillations to study affective information processing during adolescence. The adolescent brain undergoes structural and functional reorganization via through increased synaptic pruning and continued intra-cortical myelination (Brenhouse and Andersena, 2011; Thompson et al., 2000; Yurgelun-Todd, 2007). During adolescence, the normal pattern of EEG maturation involves a redistribution of relative EEG power as a function of age because posterior regions mature earlier than anterior regions (Segalowitz et al., 2010). Developmental reductions in the amplitudes of oscillations over a wide frequency range (e.g., delta and beta) continue until early adulthood (Uhlhaas and Singer, 2011). Moreover, developmental decreases in EEG power are accompanied by reductions in BOLD power and gray matter volume (Lüchinger et al., 2011, 2012; Whitford et al., 2007), all of which increase cortical efficiency later in development (Rypma, 2007). Thus, adolescents progressively improve their selective attention capacities for affective processing (Durston et al., 2006; Monk et al., 2003). Adolescents also exhibit heightened sensitivity to environmental cues (Segalowitz et al., 2010; Somerville et al., 2010). These age-related changes clearly point to the need to understand the profile of oscillatory brain responses to affective stimuli during adolescence. Our present study examined whether event-related delta and beta oscillations and LPPs, reflect age-related changes in affective processing during adolescence. EEGs were collected from 51 adolescents and 18

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undergraduates while they viewed 90 images from the Chinese affective picture system (Bai et al., 2005). The emotional intensity of each picture was then rated. Based on recent LPP investigations in adults and children (Foti and Hajcak, 2008; Hajcak and Nieuwenhuis, 2006; Hajcak and Olvet, 2008; Hajcak et al., 2009; Kujawa et al., 2012), we predicted that the LPP amplitudes elicited by positive and negative images in adolescents would be enhanced relative to neutral pictures. If delta oscillations reflect top-down attention to the motivational relevance of emotional stimuli (Balconi et al., 2009; Klados et al., 2009; Knyazev, 2007, 2012; Knyazev et al., 2009), we predicted that positive and negative pictures would increase delta synchronization compared to neutral pictures. Consistent with previous findings using IAPS pictures (Keil et al., 2007; Güntekin et al., 2010), we predicted that negative pictures would increase beta synchronization compared to positive and neutral pictures. Based on the hypothesis of increasing cortical efficiency (Casey et al., 2000; Rypma, 2007), we predicted that event-related delta and beta synchronization and LPP amplitudes would decrease with age. 2. Methods 2.1. Participants Sixty-nine right-handed adolescent students and undergraduates were recruited from Shanghai Normal University and four nearby schools in China. All of the participants selected had normal or corrected-to-normal visual acuity and were free of histories of unstable medical illness, head injury, or neurological illness. The participants were classified into four age groups as follows: 12 male and 5 female 12-year-old adolescents in grade 5 from one elementary school (11.78– 13.17 years of age), 13 male and 5 female 14-year-old adolescents in grade 8 from two junior high schools (13.75–14.83 years of age), 10 male and 6 female 16-year-old adolescents in grade 11 from one senior high school (15.33–16.67 years), and 10 male and 8 female young adults from undergraduate institutions (18.58–22.08 years of age). All participants, or their guardians if the participants were under 18 years of age, provided written informed consent and were paid approximately $10 for their participation. The relevant institutional ethical committee approved this research. 2.2. Stimulus materials Participants viewed 90 pictures from the Chinese Affective Picture System (Bai et al., 2005), which is a collection of standardized photographic materials that were obtained from the International Affective Picture System (Lang et al., 1997). Of these images, 30 depicted positive events (e.g., attractive infants, smiling face, and hugging), 30 depicted neutral events (e.g., vegetation, household objects, and buildings), and 30 depicted negative events (e.g., wreckage, a snake, and a horrible face) (Zhang et al., 2013). All image groups differed significantly in the valence dimension [F (2, 87) = 98.32, p b 0.001; M ± SD: Positive = 7.42 ± 0.16; Neutral = 4.87 ± 0.08; Negative = 2.23 ± 0.13]. In the arousal dimension, the positive and negative pictures differed from the neutral ones [F (1, 84) = 53.27, 69.57, p b 0.001] but did not significantly differ from each other [F (1, 84) = 1.21, p N 0.05; M ±SD: Positive = 5.78 ± 00.41; Neutral = 4.69 ± 0.43; Negative = 5.89 ± 0.35]. All images were displayed on a color PentiumIV computer using E-prime 2.0 (Psychology Software Tools, Inc.) to control stimulus timing. Each image was presented in the center of the monitor and encompassed a visual angle of approximately 23 degrees and a viewing distance of approximately 70 cm. 2.3. Procedure Upon arrival at the laboratory, the participants completed an informed consent form and several questionnaires. Participants then

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sat in a sound-attenuated, dimly lit room that was approximately 12 square meters in size. After the EEG sensors were attached, the participants were told to view a series of pictures. Three pictures, one per picture type, were randomly selected for each experimental block (30 randomized blocks total). Following a fixation mark (+) that was visible for 1000 ms, the word “View” appeared for 1500 ms and then a picture was presented for 1500 ms. Next, the picture disappeared and the word “assessment” appeared in the center of screen to cue participants to rate the strength of their emotional responses (how strongly they feel that the picture influenced their own emotional state) after viewing the picture. Using a Likert scale ranging from 1 (extremely weak) to 9 (extremely strong), the rating was indicated by pressing a button. After participants completed the rating in approximately 3000 ms, a blank screen appeared for 1000–1500 ms (random duration) before the next trial started. A 15 s resting baseline was inserted between every three blocks. The first three blocks served as practice and were discarded during data analysis.

2.4. Data collection and analysis According to the International 10-20 System, raw EEG data were recorded using a Quick-cap with 64 Ag/AgCl electrodes (NeuroScan Inc., USA) referenced to the left mastoid. Vertical electrooculogram activity was monitored from electrodes located above and below the left eye, and horizontal electrooculogram activity was monitored from electrodes located at the outer canthus of each eye. Electrode gel was applied to produce an impedance of less than 5 kΩ. Signals were sampled at 1000 Hz and filtered on-line from 0.01 to 100 Hz. The continuous EEG signals were corrected offline for blink artifacts using an ocular artifact reduction procedure (Semlitsch et al., 1986) and then converted to the average mastoid reference. The EEGs for each trial were segmented into 1500-ms epochs beginning 2500 ms before the onset of each picture. Subject averages and grand averages were calculated for each electrode site and picture type. Fig. 1 illustrates the LPP amplitudes, which reached their maximums approximately 300 ms after the stimuli (Olofsson et al., 2008). Thus, the LPP amplitude was defined as the average activity between 300 and 700 ms after the stimuli over the following nine electrodes: C1, Cz, C2, CP1, CPz, CP2, P1, Pz, and P2 (Chen et al., 2010; Hajcak and Dennis, 2009). According to the ERD/ERS method (Pfurtscheller and Aranibar, 1977), changes in band power were defined as percentage decreases (ERD, positive) or increases (ERS, negative) in each band power during each test interval (e.g., 1500 ms after picture onset) compared with a reference interval (e.g., − 2500 ms to − 1500 ms before picture onset). For each subject, the ERD/ERS was calculated in the delta (0.5–3.5 Hz) and beta (15–30 Hz) bands using a zero-phase finite impulse response (FIR) bandpass filter with a 48 dB/octave roll off, a warm-up filter left and right to 100 ms, and trim left and right of 100 ms. Data were then averaged for each emotional category (Knyazev, 2012; Başar et al., 2006, 2007). The following 12 electrode sites were selected for statistical analysis: frontal (F3, Fz, F4), central (C3, Cz, C4), parietal (P3, Pz, P4), and occipital (O1, Oz, O2) (Güntekin et al., 2010). SPSS version 16.0 was used for the statistical analysis. Behavioral and LPP data were subjected to two-way repeated measures ANOVAs with 3 valence levels (positive, neutral, and negative) × 4 age levels (12-, 14-, and 16-year-old adolescents, and young adults). Threeway repeated measures ANOVAs with 3 valence levels (positive, neutral, and negative) × 4 regions (frontal, central, parietal, and occipital) × 4 age levels (between-subject factor: 12-, 14-, and 16year-old adolescents, and young adults) were separately performed on the delta and beta ERS data. The Greenhouse–Geisser correction was applied when the variance sphericity assumption was not satisfied. The Bonferroni method was used for all post-hoc analyses. Significant effects of p b 0.05 are reported.

Fig. 1. The group-averaged event-related potential waveforms of the 12-, 14-, and 16-yearold adolescent and the young adults that were elicited by positive (green dashed line), neutral (red solid line), and negative (blue dotted line) pictures. The late positive potentials were defined as the potentials between 300 and 700 ms after picture onset.

3. Results 3.1. Emotional intensity Fig. 2 illustrates the mean emotional intensity ratings for positive, neutral, and negative pictures among the four age groups. A two-way mixed ANOVA yielded a significant effect of valence on emotional intensity [F (2, 65) = 19.46, p b 0.001, partial η2 = 0.36]. Post-hoc tests revealed that positive and negative pictures induced greater emotional intensities than the neutral pictures [F (1, 65) = 8.68, p b 0.01, partial η2 = 0.20; F (1, 65) = 9. 76, p b 0.01, partial η2 = 0.24, respectively]; however, no significant difference was found between the positive and negative pictures [F (1, 65) = 2.61, p N 0.05, partial η2 = 0.06]. Moreover, emotional intensity ratings varied as a function of age [F (2, 65) = 6.26, p b 0.01, partial η2 = 0.27]. Post-hoc tests revealed

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Fig. 2. The mean emotional intensity ratings for positive, neutral, and negative pictures as scored by the 12- (n = 17), 14- (n = 18), and 16-year-old adolescents (n = 16) and young adults (n = 18). The error bars indicate the standard errors.

that 12-year-old adolescents rated each picture type as more intense than 14-year-old adolescents [F (1, 65) = 5.38, p b 0.05, partial η2 = 0.15]. The 14-year-old adolescents rated each picture type as more intense than did the 16-year-old adolescents and young adults [F (1, 65) = 5.45, p b 0.05, partial η2 =0.16; [F (1, 65)=6.92, pb 0.05, partial η2 =0.19, respectively]. 3.2. LPP amplitudes A two-way repeated measures ANOVA revealed a significant main effect of valence on the LPP amplitudes [F (2, 65) = 16.58, p b 0.001, partial η2 = 0.39, Fig. 1]. Post-hoc tests indicated that the positive and negative pictures elicited greater LPP amplitudes than the neutral pictures [F (1, 65) = 5.81, p b 0.05, partial η2 = 0.17; F (1, 65) = 5.62, p b 0.01, partial η2 = 0.16, respectively]; however, there was no significant difference between the negative and positive pictures [F (1, 65) = 1.48, p N 0.05, partial η2 = 0.04]. Moreover, we detected a significant main effect of age [F (3, 65) = 12.62, p b 0.001, partial η2 = 0.31]. Post-hoc tests indicated that the LPP amplitudes of the 12-yearold adolescents were more pronounced than those of the 14-year-old adolescents [F (1, 65) = 5.64, p b 0.05, partial η2 = 0.16]. The LPP amplitudes of the 14-year-old adolescents were more pronounced than those of 16-year-old adolescents [F (1, 65) = 8.67, p b 0.01, partial η2 = 0.20], and the LPP amplitudes of the 16-year-olds were more pronounced than those of the young adults [F (1, 65) = 8.92, p b 0.01, partial η2 = 0.22]. 3.3. ERO 3.3.1. Delta ERS A three-way repeated measures mixed ANOVA revealed a significant main effect of valence [F (2, 65) = 12.47, p b 0.001, partial η2 = 0.34], indicating that positive and negative pictures elicited greater delta ERS responses than did the neutral pictures; however, there was no significant difference between the positive and negative pictures. Moreover, we observed a significant main effect of brain region [F (3, 65) = 9.71, p b 0.01, partial η2 = 0.27], indicating that delta ERS amplitudes at the frontal and central sites were greater than those of the parietal and occipital sites. There was a significant region × age interaction [F (9, 65) = 3.47, p b 0.01, partial η2 = 0.28; see Fig. 3]. Post-hoc tests indicated that delta ERS amplitudes at the frontal and central sites of the 12-year-old adolescents were larger than those of the 14-year-old adolescents [F (1, 65) = 8.52, 8.15, p b 0.01, partial η2 = 0.20, 0.19, respectively]. The delta ERS amplitudes of the 14-year-old adolescents were larger than those of the 16-year-old adolescents [F (1, 65) = 8.46, 7.41, p b 0.01, partial η2 = 0.22, 0.17, respectively], which, in turn, were larger than

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Fig. 3. A region × age interaction in event-related delta synchronization was observed. The error bars indicate the standard errors. ** p b 0.01.

those of the young adults [F (1, 65) = 7.35, 7.94, p b 0.01, partial η2 = 0.16, 0.19, respectively]. At the parietal and occipital sites, the delta ERS amplitudes of 12- through 16-year-old adolescents were larger than those of the young adults [all F (1, 65) N 7.25, all p b 0.01, all partial η2 N 0.15]. 3.3.2. Beta ERS A three-way repeated measures ANOVA revealed a significant main effect of valence [F (2, 65) =15.47, p b 0.001, partial η2 =0.36]. Post-hoc tests indicated that the negative pictures elicited larger beta ERS amplitudes than did the positive and neutral pictures [F (1, 65) = 8.48, p b 0.01, partial η2 = 0.20; F (1, 65) = 9.92, p b 0.01, partial η2 = 0.26, respectively]. The positive pictures elicited greater beta ERS than did the neutral pictures [F (1, 65) = 8.23, p b 0.01, partial η2 = 0.19]. There was also a significant main effect of brain region [F (3, 65) = 10.85, p b 0.001, partial η2 = 0.41], indicating that the beta ERS amplitudes elicited at the frontal and central sites were smaller than those elicited at the parietal and occipital sites. Moreover, we detected a significant valence × region × age interaction [F (18, 65) = 13.85, p b 0.001, partial η2 = 0.44, Fig. 4]. Posthoc tests indicated that beta ERS amplitudes elicited by positive and negative versus neutral pictures in 12- to 14-year-old adolescents were larger at the frontal and central sites than those of the 16-year-old adolescents and the young adults [all F (1, 65)N 7.27, all pb 0.01, all partial η2 N0.16]. At the parietal and occipital sites, the differences in the beta ERS amplitudes elicited by positive and neutral pictures in the 12-year-old adolescents were larger than those of the other three age groups [all F (1, 65) N 7.31, all p b 0.01, all partial η2 N 0.17]; however, the differences in the beta ERS amplitudes elicited by the negative and neutral pictures did not differ across the four age groups [all Fs (1, 45) b 2.62, all p N 0.05, all partial η2 b 0.06]. 4. Discussion The present study investigated whether LPP and delta and beta ERS exhibited age-dependent changes in affective processing during adolescence. In the range of slow wave activities, we observed affective modulation of delta ERS that were largely confined to the anterior sites. These data are consistent with previous results using IAPS pictures (Balconi et al., 2009; Klados et al., 2009; Knyazev et al., 2009). The LPP amplitudes elicited by the positive and negative pictures exhibited affective modulations that were similar to those of the delta ERS (Foti and Hajcak, 2008; Hajcak and Nieuwenhuis, 2006; Hajcak and Olvet, 2008; Hajcak et al., 2009; Kujawa et al., 2012). These results suggest that slow wave responses reflect a top-down attention to the motivational relevance of affective stimuli. This may be due to two reasons as follows. First, the delta ERS and LPP share neural sources such as the medial prefrontal cortex and the anterior cingulate cortex.

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Fig. 4. A valence × region × age interaction in event-related beta synchronization was observed. The error bars indicate the standard errors.

These cortical sources involved in top-down attention are reciprocally linked to motivational brain circuits (Knyazev, 2012; Phillips et al., 2008; Scharmüller et al., 2011; Zhang and Lu, 2012). Second, in our study, the participants were instructed to provide online behavioral ratings; therefore, the affective pictures were processed in a top-down manner from the initiation of sensory processing. The behavioral ratings of the participants support the notion that delta ERS occurs in parallel with the LPP. Taken together, our results indicate that slow wave activities (delta ERS and LPP) play a significant role in monitoring the motivational relevance of affective pictures. In the range of fast wave activities, beta ERS decreased with affective valence. The largest effect was observed for negative pictures at the posterior sites, which is consistent with a study of facial expressions in adults (Başar and Güntekin, 2010). Thus, beta frequencies discriminate known and unknown faces (Başar et al., 2006, 2007) and the emotional valences of affective pictures during visual processing. Moreover, the effect of valence on beta ERS parallels the finding that early ERP components (e.g., P1) are modulated by valence (Olofsson et al., 2008). Bottom-up processing results in high frequency (e.g., beta band) synchronization (Siegel et al., 2000); therefore, the valence-induced beta ERS might reflect bottom-up visual processing of affective information. Early components that are sensitive to low-level physical features, such as contrast and luminance (Rousselet et al., 2008), could potentially influence the results of our study; however, this has yet to be determined. Future studies should strictly control for these low-level physical factors to clarify this hypothesis. Additionally, event-related delta and beta oscillations in adolescents exhibited dissociable developmental changes in affective processing. Independent of affective valence, adolescents aged 12 to 16 years showed larger delta ERS amplitudes within the range of the delta band in posterior brain regions when compared with young adults. In contrast, delta ERS amplitudes decreased with age in the anterior brain regions. These results are consistent with the idea that the adolescent brain continues to develop its structure and function and reorganizes in a back-to-front manner (Rubia et al., 2000; YurgelunTodd, 2007). During adolescence, the developmental decline of delta

power parallels gray matter reduction (Lüchinger et al., 2011, 2012; Whitford et al., 2007), both of which increase cortical efficiency in affective processing (Rypma, 2007). Briefly, these observations suggest that adolescents improve their top-down attentional capacities for affective information processing. Within the beta band, the beta ERS amplitudes elicited by positive and negative pictures in the 12- and 14-year-old adolescents were more different than those elicited by the neutral pictures at the anterior sites when compared to the differences observed in the 16-year-old adolescents and young adults. During adolescence, age-related changes reflect the development of neurocognitive functions and increases in skull thickness that result in greater attenuation of the EEG signal (Adeloye et al., 1975; Knott et al., 2004). However, the beta ERS reduction observed in our study could not have been caused by increased skull thicknesses because the differences in beta ERS amplitudes elicited by negative and neutral pictures did not vary with age in the posterior brain regions. Specifically, we observed that 12-year-old adolescents exhibited larger differences in the beta ERS amplitudes elicited by positive versus negative pictures in the posterior regions compared to the other age groups. These data may imply that the capacity for positive emotions matures later than that for negative emotions. Taken together, these results suggest that beta ERS shows distinct developmental trajectories in the bottom-up processing of positive and negative stimuli. There are some limitations of this study. First, it should be explicitly acknowledged that the observed between-group differences were, strictly speaking, only cohort differences. Future longitudinal studies should determine the true presence of age-related effects. Second, although brain oscillations measured at a scalp site may be indicative of neural activation directly below that site, they can also reflect activity generated elsewhere in the brain that is subsequently conducted to that site through the layers of cortical folding or the scalp. Our region-related inferences remain speculative and require additional investigations using source analysis techniques (e.g., sLORETA; Pascual-Marqui, 2002) or functional magnetic resonance imaging to confirm our results. In summary, we extended the existing ERP and ERO results regarding affective processing in adults to adolescent subjects. In the

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range of slow wave activities, the delta ERS and LPPs of adolescents displayed affective modulation that was similar to that of adults and reflected top-down attention to the motivational relevance of affective pictures. Furthermore, the values of these measures decreased with age in anterior brain regions. In the range of fast wave activities, beta ERS discriminated emotional valences and reflected visual bottom-up processing, and positive emotions maturated later than negative emotions. These results increase our understanding of the development of oscillatory brain mechanisms during affective information processing. Acknowledgments This study was supported by the Chinese Ministry of Education, Humanities and Social Sciences Planning Fund (11YJA190024) the National Natural Science Foundation of China (81171289). References Adeloye, A., Kattan, K.R., Silverman, F.N., 1975. Thickness of the normal skull in the American blacks and whites. Am. J. Phys. Anthropol. 43, 23–30. Aftanas, L.I., Pavlov, S.V., Reva, N.V., Varlamov, A.A., 2003a. Trait anxiety impact on the EEG theta band power changes during appraisal of threatening and pleasant visual stimuli. Int. J. Psychophysiol. 50, 205–212. Aftanas, L.I., Varlamov, A.A., Reva, N.V., Pavlov, S.V., 2003b. Disruption of early eventrelated theta synchronization of human EEG in alexithymics viewing affective pictures. Neurosci. Lett. 340, 57–60. Alper, K.R., John, E.R., Brodie, J., Güther, W., Daruwala, R., Prichep, L.S., 2006. Correlation of PET and qEEG in normal subjects. Psychiatry Res. Neuroimaging 146, 2712–2782. Bai, L., Ma, H., Huang, Y.X., Luo, Y.J., 2005. The development of native Chinese affective picture system—a pretest in 46 college students. Chin. Ment. Health J. 19, 719–722. Balconi, M., Pozzoli, U., 2007. Event-related oscillations (EROs) and event-related potentials (ERPs) comparison in facial expression recognition. J. Neuropsychol. 1, 283–294. Balconi, M., Brambilla, E., Falbo, L., 2009. BIS/BAS, cortical oscillations and coherence in response to emotional cues. Brain Res. Bull. 80, 151–157. Baluch, F., Itti, L., 2011. Mechanisms of top-down attention. Trends Neurosci. 34 (4), 210–224. Başar, E., Güntekin, B., 2010. Event-related beta oscillations are affected by emotional eliciting stimuli. Neurosci. Lett. 483, 173–178. Başar, E., Güntekin, B., Öniz, A., 2006. Principles of oscillatory brain dynamics and a treatise of recognition of faces and facial expressions. Prog. Brain Res. 159, 43–62. Başar, E., Özgören, M., Öniz, A., Schmiedt, C., Başar-Eroğlu, C., 2007. Brain oscillations differentiate the picture of one’s own grandmother. Int. J. Psychophysiol. 64, 81–90. Brenhouse, H.C., Andersena, S.L., 2011. Developmental trajectories during adolescence in males and females: a cross-species understanding of underlying brain changes. Neurosci. Biobehav. Rev. 35, 1687–1703. Casey, B.J., Giedd, J.N., Thomas, K.M., 2000. Structural and functional brain development and its relation to cognitive development. Biol. Psychol. 54, 241–257. Chen, M.L., Ma, Q.G., Li, M.L., Dai, S.Y., Wang, X.Y., Shu, L.C., 2010. The neural and psychological basis of herding in purchasing books online: an event-related potential study. Cyberpsychol. Behav. Soc. Netw. 13 (3), 321–328. Cohen, J.E., Shalev, H., Admon, R., Hefetz, S., Gasho, C.J., Shachar, L.J., Shelef, I., Hendler, T., Friedman, A., 2012. Emotional brain rhythms and their impairment in post-traumatic patients. Hum. Brain Mapp. http://dx.doi.org/10.1002/hbm.21516. Cuthbert, B.N., Schupp, H.T., Bradley, M.M., Birbaumer, N., Lang, P.J., 2000. Brain potentials in affective picture processing: covariation with autonomic arousal and affective report. Biol. Psychol. 52 (2), 95–111. Dahl, R.E., 2004. Adolescent brain development: a period of vulnerabilities and opportunities, Keynote address. Ann. N. Y. Acad. Sci. 1021, 1–22. Dang-Vu, T.T., Schabus, M., Desseilles, M., Albouy, G., Boly, M., Darsaud, A., Gais, S., Rauchs, G., Sterpenich, V., Vandewalle, G., Carrier, J., Moonen, G., Balteau, E., Degueldre, C., Luxen, A., Phillips, C., Maquet, P., 2008. Spontaneous neural activity during human slow wave sleep. Proc. Natl. Acad. Sci. U. S. A. 105, 15160–15165. Durston, S., Davidson, M.C., Tottenham, N., Galvan, A., Spicer, J., Fossella, J.A., Casey, B.J., 2006. A shift from diffuse to focal cortical activity with development. Dev. Sci. 9, 1–8. Foti, D., Hajcak, G., 2008. Deconstructing reappraisal: descriptions preceding arousing pictures modulate the subsequent neural response. J. Cogn. Neurosci. 20, 977–988. Grace, A.A., 1995. The tonic/phasic model of dopamine system regulation: its relevance for understanding how stimulant abuse can alter basal ganglia function. Drug Alcohol Depend. 37, 111–129. Güntekin, B., Başar, E., 2007. Emotional face expressions are differentiated with brain oscillations. Int. J. Psychophysiol. 64, 91–100. Güntekin, B., Tulay, E., Turp, B., Başar, E., 2010. Brain's beta response is strongly enhanced upon negative emotion eliciting stimuli. Int. J. Psychophysiol. 77, 266. Hajcak, G., Dennis, T.A., 2009. Brain potentials during affective picture processing in children. Biol. Psychol. 80, 333–338. Hajcak, G., Nieuwenhuis, S., 2006. Reappraisal modulates the electrocortical response to negative pictures. Cogn. Affect. Behav. Neurosci. 6, 291–297. Hajcak, G., Olvet, D.M., 2008. The persistence of attention to emotion: brain potentials during and after picture presentation. Emotion 8, 250–255.

339

Hajcak, G., Dunning, J.P., Foti, D., 2009. Automatic and controlled attention to emotion: time-course of the late positive potential. Clin. Neurophysiol. 120, 505–510. Hummel, F.C., Gerloff, C., 2006. Interregional long-range and short-range synchrony: a basis for complex sensorimotor processing. Prog. Brain Res. 159, 223–236. Jensen, O., Goel, P., Kopell, N., Pohja, M., Hari, R., Ermentrout, B., 2005. On the human sensorimotor-cortex beta rhythm: sources and modeling. NeuroImage 26, 347–355. Keil, A., Stolarova, M., Moratti, S., Ray, W.J., 2007. Adaptation in human visual cortex as a mechanism for rapid discrimination of aversive stimuli. NeuroImage 36, 472–479. Klados, M.A., Frantzidis, C., Vivas, A.B., Papadelis, C., Lithari, C., Pappas, C., Bamidis, P.D., 2009. A frame work combining delta event-related oscillations (EROs) and synchronization effects (ERD/ERS) to study emotional processing. Comput. Intell. Neurosci. http:// dx.doi.org/10.1155/2009/549419. Knott, D.P., Hazony, D., Karafa, M., Koltai, P.J., 2004. High-frequency ultra sound in the measurement of pediatric craniofacial integrity. Otolaryngol. Head Neck Surg. 131, 851–855. Knyazev, G.G., 2007. Motivation, emotion, and their inhibitory control mirrored in brain oscillations. Neurosci. Biobehav. Rev. 31, 377–395. Knyazev, G.G., 2011. Cross-frequency coupling of brain oscillations: an impact of state anxiety. Int. J. Psychophysiol. 80, 236–245. Knyazev, G.G., 2012. EEG delta oscillations as a correlate of basic homeostatic and motivational processes. Neurosci. Biobehav. Rev. 36, 677–695. Knyazev, G.G., Slobodskoj-Plusnin, J.Y., Bocharov, A.V., 2009. Event-related delta and theta synchronization during explicit and implicit emotion processing. Neuroscience 164, 1588–1600. Kujawa, A., Klein, D.N., Hajcak, G., 2012. Electrocortical reactivity to emotional images and faces in middle childhood to early adolescence. Dev. Cogn. Neurosci. 2, 458–467. Lang, P.J., Bradley, M.M., Cuthbert, B., 1997. In: Lang, P.J., Simons, R.F., Balaban, M. (Eds.), Motivated Attention: Affect, Activation, and Action. Erlbaum, Mahwah, NJ, pp. 97–135. Lavin, A., Grace, A.A., 1996. Physiological properties of rat ventral pallidal neurons recorded intracellularly in vivo. J. Neurophysiol. 75, 1432–1443. Leung, L.S., Yim, C.Y., 1993. Rhythmic delta-frequency activities in the nucleus accumbens of anesthetized and freely moving rats. Can. J. Physiol. Pharmacol. 71, 311–320. Lüchinger, R., Michels, L., Martin, E., Brandeis, D., 2011. EEG–BOLD correlations during (post-) adolescent brain maturation. NeuroImage 56, 1493–1505. Lüchinger, R., Michels, L., Martin, E., Brandeis, D., 2012. Brain state regulation during normal development: intrinsic activity fluctuations in simultaneous EEG-fMRI. NeuroImage 60, 1426–1439. Mathes, B., Strüber, D., Stadler, M.A., Basar-Eroglu, C., 2006. Voluntary control of Necker cube reversals modulates the EEG delta-and gamma-band response. Neurosci. Lett. 402, 145–149. Miskovic, V., Schmidt, L.A., 2010. Cross-regional cortical synchronization during affective image viewing. Brain Res. 1362, 102–111. Monk, C.S., McClure, E.B., Nelson, E.E., Zarahn, E., Bilder, R.M., Leibenluft, E., Charney, D.S., Ernst, M., Pine, D.S., 2003. Adolescent immaturity in attention-related brain engagement to emotional facial expressions. NeuroImage 20, 420–428. Olofsson, J.K., Nordin, S., Sequeira, H., Polich, J., 2008. Affective picture processing: an integrative review of ERP findings. Biol. Psychol. 77, 247–265. ÖzgÖren, M., BaŞar-Eroğlu, C., BaŞar, E., 2005. Beta oscillations in face recognition. Int. J. Psychophysiol. 55, 51–59. Pascual-Marqui, R.D., 2002. Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find. Exp. Clin. Pharmacol. 24, 5–12. Pfurtscheller, G., Aranibar, A., 1977. Event-related cortical desynchronization detected by power measurement of scalp EEG, EEG. Clin. Neurophysiol. 42, 817–826. Phillips, M.L., Ladouceur, C.D., Drevets, W.C., 2008. A neural model of voluntary and automatic emotion regulation: implications for understanding the pathophysiology and neurodevelopment of bipolar disorder. Mol. Psychiatry 13, 833–857. Ray, W.J., Cole, H.W., 1985. EEG alpha activity reflects attentional demands and beta activity reflects emotional and cognitive processes. Science 228, 750–752. Rousselet, G.A., Husk, J.S., Bennett, P.J., Sekuler, A.B., 2008. Time course and robustness of ERP object and face differences. J. Vis. 8 (12), 1–18. Rubia, K., Overmeyer, S., Taylor, E., Brammer, M., Williams, S.C., Simmons, A., Andrew, C., Bullmore, E.T., 2000. Functional frontalisation with age: mapping neurodevelopmental trajectories with fMRI. Neurosci. Biobehav. Rev. 24, 13–19. Rypma, B., 2007. A neural efficiency hypothesis of age-related changes in human working memory performance. In: Osaka, N., Logie, R.H., D'Esposito, M. (Eds.), The cognitive neuroscience of working memory. Oxford Scholarship Online, p. 281. http:// dx.doi.org/10.1093/acprof:oso/9780198570394.003.0017. Scharmüller, W., Leutge, V., Schäfer, A., Köchel, A., Schienle, A., 2011. Source localization of late electrocortical positivity during symptom provocation in spider phobia: an sLORETA study. Brain Res. 1397, 10–18. Schupp, H.T., Junghofer, M., Weike, A.I., Hamm, A.O., 2004. The selective processing of briefly presented affective pictures: an ERP analysis. Psychophysiology 41, 441–449. Schupp, H.T., Flaisch, T., Stockburger, J., Junghofer, M., 2006. Emotion and attention: event-related brain potential studies. Prog. Brain Res. 156, 123–143. Segalowitz, S.J., Santesso, D.L., Jetha, M.K., 2010. Electrophysiological changes during adolescence: a review. Brain Cogn. 72, 86–100. Semlitsch, P.A., Schuster, P., Presslisch, O., 1986. A solution for reliable and valid reduction of ocular artifacts applied to the P300 ERP. Psychophysiology 23, 695–703. Siegel, M., Kording, K.P., Konig, P., 2000. Integrating top-down and bottom-up sensory processing by somato-dendritic interactions. J. Comput. Neurosci. 8, 161–173. Somerville, L.H., Jones, R.M., Casey, B.J., 2010. A time of change: behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues. Brain Cogn. 72, 124–133. Spear, L.P., 2000. The adolescent brain and age-related behavioral manifestations. Neurosci. Biobehav. Rev. 24 (4), 417–463.

340

W. Zhang et al. / International Journal of Psychophysiology 90 (2013) 334–340

Thompson, P.M., Giedd, J.N., Woods, R.P., MacDonald, D., Evans, A.C., Toga, A.W., 2000. Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature 404, 190–193. Uhlhaas, P.J., Singer, W., 2011. The development of neural synchronization and large-scale cortical networks during adolescence: relevance for the pathophysiology of schizophrenia and neurodevelopmemtal hypothesis. Schizophr. Bull. 37, 514–523. Weinberg, A., Hilgard, J., Bartholow, B.D., Hajcak, G., 2012. Emotional targets: evaluative categorization as a function of context and content. Int. J. Psychophysiol. 84, 149–154. Whitford, T.J., Rennie, C.J., Grieve, S.M., Clark, C.R., Gordon, E., Wiliams, L.M., 2007. Brain maturation in adolescence: concurrent changes in neuroanatomy and neurophysiology. Hum. Brain Mapp. 28, 228–237.

Williams, L.M., Brown, K.J., Palmer, D., Liddell, B.J., Kemp, A.H., Olivieri, G., Peduto, A., Gordon, E., 2006. The mellow years? Neural basis of improving emotional stability with age. J. Neurosci. 26, 6422–6430. Yen, N.S., Chen, K.H., Liu, E.H., 2010. Emotional modulation of the late positive potential (LPP) generalizes to Chinese individuals. Int. J. Psychophysiol. 75, 319–325. Yurgelun-Todd, D., 2007. Emotional and cognitive changes during adolescence. Curr. Opin. Neurobiol. 17, 251–257. Zhang, W., Lu, J., 2012. Time course of automatic emotion regulation during a facial Go/Nogo task. Biol. Psychol. 89, 444–449. Zhang, W., Lu, J., Liu, X., Wang, D., Shen, J., 2013. Harm avoidance in adolescents modulates late positive potentials during affective picture processing. Int. J. Dev. Neurosci. 31 (15), 297–302.