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Effects of sensation seeking on habituation to novelty: An EEG study
Neuropsychologia 129 (2019) 133–140
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Neuropsychologia journal homepage: www.elsevier.com/locate/neuropsychologia
Effects of sensation seeking on habituation to novelty: An EEG study Xintong Jiang, Shuting Mei, Wei Yi, Ya Zheng
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T
Department of Psychology, Dalian Medical University, Dalian, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Sensation seeking Habituation Orienting response Novelty P3 Midfrontal theta
Sensation seeking is characterized by a strong need for novelty and has been associated with various risk-taking behaviors. Using the extreme between-group design, the current study investigated the electrophysiological mechanisms underlying habituation to novelty processing in sensation seeking. Twenty high sensation seekers (HSS) and 20 low sensation seekers (LSS) performed an auditory oddball task while their EEG was recorded. The results revealed that both the novelty P3 and midfrontal theta power decreased from the first to the second half for LSS but not for HSS. Additionally, this reduced vigilance was predicted by the experience-seeking subcomponent of sensation seeking. Together, our findings are supportive of an abnormal habituation to novel events in the sensation-seeking trait.
1. Introduction Sensation seeking is a personality trait characterized by a strong need for varied, novel, complex, and intense stimulation and willingness to take risks for such experience (Zuckerman, 1994). This trait is captured by the Sensation Seeking Scale Form V (Zuckerman et al., 1978), which includes four dimensions: thrill and adventure seeking (a desire to engage in physically risky activities), experience seeking (a preference for novel experiences through a nonconformist style), disinhibition (an interest in socially and sexually disinhibited activities), and boredom susceptibility (an aversion to repetitiveness and monotony). High sensation seekers (HSS) relative to low sensation seekers (LSS) are susceptible to be involved in various risk-taking behaviors, such as extreme sports (Ruedl et al., 2012), reckless driving (Jonah, 1997), risky sex (Hoyle et al., 2000), problem gambling (Harris et al., 2015), and substance abuse (Bardo et al., 2007). According to the optimal arousal theory (Zuckerman, 1969, 1984), the sensation-seeking behaviors are associated with a regulatory mechanism to compensate for affective disturbances due to a chronically underaroused state in sensation seeking (Carton et al., 1995). It should be noted that, however, risk is not the merely focus of people high in sensation seeking. For example, among normal populations, HSS are more inclined to switch TV channels than LSS (Perse, 1996), whereas among individuals with addiction, sensation seeking is the most sensitive variable predicting poly versus single drug use (Andrucci et al., 1989). In this regard, the need for novelty and aversion to repetitiveness (i.e., habituation) seem to be at the root of sensation seeking. Electrophysiological investigations of novelty processing and
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habituation typically employ novel oddball tasks in which novel stimuli are embedded randomly when participants were asked to discriminate infrequent target stimuli from frequent standard stimuli. Novel stimuli typically elicit an event-related potential (ERP) component called the novelty P3 (also referred to as the P3a) peaking approximately 250 ms post stimulus onset with an anterior distribution (Courchesne et al., 1975). The novelty P3 is considered to index immediate attention to novel stimuli (Friedman et al., 2001), which is associated with the wellknown orienting response (Pavlov, 1927; Sokolov, 1963). Orienting response is adaptive for preparing the organism to respond quickly to novel events that call for immediate action. With repetition of the same or similar stimuli, however, a neuronal model is formed, and those stimuli no longer elicit the orienting response of similar magnitude. Hence, one distinctive feature of orienting response is habituation (Sokolov, 1963). Unsurprisingly, the novelty P3 typically habituates rapidly as more and more novel stimuli are experienced or the same novel stimulus is repeated (Friedman et al., 2001; Ranganath and Rainer, 2003). The lack of habituation for the novelty P3 has been linked to dysfunctional cognitive processing among aged people (Friedman et al., 1993), patients with neurological impairment (Knight, 1984), and individuals with borderline and avoidant personality disorder (Koenigsberg et al., 2014). To our knowledge, only two ERP studies examined the habituation of the novelty P3/P3a in sensation seeking. As did in most of the previous studies (e.g., Cservenka et al., 2012; Frenkel et al., 2018; Zheng et al., 2017), both studies recruited HSS and LSS at extreme scores on the sensation-seeking scale using the extreme between-group design, which is more sensitive than the dimensional design (i.e., examining
Corresponding author. Department of Psychology, Dalian Medical University, No. 9 West Section, Lvshun South Road, Dalian 116044, China. E-mail address: [email protected] (Y. Zheng).
https://doi.org/10.1016/j.neuropsychologia.2019.03.011 Received 22 October 2018; Received in revised form 25 February 2019; Accepted 20 March 2019 Available online 25 March 2019 0028-3932/ © 2019 Elsevier Ltd. All rights reserved.
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seeking and boredom susceptibility should be related to the habituation to novelty in sensation seeking, indexed by the novelty P3 and midfrontal theta. If confirmed, the results would be helpful to our understanding of habituation in sensation seeking.
linear relationships of sensation seeking across normal population) in terms of maximizing the likelihood of biological correlates associated with sensation seeking (Joseph et al., 2013). Fjell et al. (2007) addressed this issue firstly among a group with HSS, a group with LSS, and a group with “real-life” HSS who engaged in extreme sports. Participants performed a three-stimulus oddball task during which they were instructed to respond to a blue circle (target) and ignore a little smaller blue circle (standard) and a blue rectangle (distractor). The results revealed that the amplitude of the P3a decreased from the first to the second half of the trials (i.e., the habituation effect), which was present for real-life HSS but not for HSS and LSS. In a following study, Zheng et al. (2010) employed a similar oddball task in which participants were asked to respond to an inverted triangle (target) and ignore an upright triangle (standard) and unique line drawings of pseudo-objects (novelty). The author found that LSS, instead of HSS, exhibited a habituation effect such that the amplitude of the novelty P3 decreased from the first to the second half of the task. Given that novelty processing is modulated by contextual novelty (a top-down process determined by task demands) and stimulus novelty (a bottom-up process determined by stimuli) (Bradley, 2009; Friedman et al., 2001), it is possible that the discrepancy between the two studies may reflect the degree of stimulus novelty. Specifically, the novel stimuli in the Fjell et al. study were repeated and familiar blue rectangles. In contrast, the novel stimuli in the Zheng et al. study were unique and unfamiliar and thus deviant from participants’ long-term memory. Indeed, early autonomic studies have demonstrated a close relationship between sensation seeking and information content and intensity. For example, when facing stimuli with moderate intensity, HSS exhibit an orienting response, whereas LSS display a defensive response (Zuckerman, 1990). Importantly, the novel stimuli employed in both the Fjell et al. study (a repeated and familiar blue rectangle) and the Zheng et al. study (unique and nonexistent pseudoobjects) were not typical in our daily life, resulting in a relatively weak ecological validity. Moreover, since both studies have investigated the habituation effect in the visual modality, it also makes sense to examine it in the auditory modality, although the novelty P3 is modality nonspecific (Friedman et al., 2001). In the present study, we adopted an auditory novel oddball paradigm to examine the habituation of novel stimuli in HSS and LSS. The novel stimuli consisted of unrepeated environmental sounds with moderate intensity, which are more prototypical in ordinary life and thus have a greater ecological validity than the previous studies (Fjell et al., 2007; Zheng et al., 2010). It was hypothesized that HSS should exhibit a higher rate of habituation to auditory novel stimuli than LSS, as reflected by a more decreased novelty P3 as the experiment proceeded. Moreover, the current study also focused on another electrophysiological index associated with novelty processing, that is, the frontal midline theta-band (4–7 Hz) activity recorded from the medial prefrontal cortex (Cavanagh et al., 2012; Demiralp et al., 2001; Harper et al., 2017). Midfrontal theta is reliably observed in various situations during which there is a need for cognitive control or cognitive effort (Cavanagh and Frank, 2014; Mussel et al., 2016; Wascher et al., 2014). It is thus unsurprising that, as the novelty P3, midfrontal theta can also be elicited in novelty processing (Cavanagh et al., 2012; Harper et al., 2017). Given that theta-band signals are found to contribute to P3 responses (Bernat et al., 2007; Karakas et al., 2000; Yordanova and Kolev, 1998), it is possible that the novelty P3 and midfrontal theta constitute two complementary indexes of the orienting response elicited by novel stimuli. To our knowledge, no previous study has examined the role of midfrontal theta in habituation as a function of sensation seeking. Finally, given that sensation seeking is not a single construct, it is highly possible that its subdimensions contribute differently to the habituation in sensation seeking. Thus, the third purpose of the study was to explore the association between the subdimensions of sensation seeking and the rate of habituation to novelty. According to the above definition of each dimension, it was hypothesized that both experience
2. Materials and methods 2.1. Participants Participants consisted of 20 HSS and 20 LSS selected from a large student sample (N = 272; 163 females and 109 males) based on their scores on the Chinese version of Sensation Seeking Scale Form V (SSS-V; Wang et al., 2000; Zuckerman, 1994). The SSS-V is designed to measure four dimensions (10 items each) of sensation seeking. Summing all the 40 items results in an overall sensation-seeking score. Responders in the top and the bottom quartile of distribution of the sample were assigned as HSS and LSS, respectively. The criterion of selection was employed for females and males separately because of the gender imbalance in the sample. Qualified participants were then invited randomly for the experiment. The groups differed significantly on the overall sensation-seeking score and its subscale scores with no differences on age, gender, and educational level (Table 1). All had normal hearing and were free of neurological or psychiatric disorders. Each signed a written informed consent form prior to the experiment and received course credit for the participation. This study was approved by the Dalian Medical University Institutional Review Board in accordance with the Helsinki Declaration as revised 1989. 2.2. Stimuli An auditory novel oddball paradigm was adopted in the current study with three types of stimuli (standard, target, and novel). The standard (80%) and target (10%) stimuli were pure tones of 800 Hz and 1000 Hz, respectively. The novel stimuli (10%) consisted of 48 distinct environmental sounds (animal calls, telephone ringing, car honks, etc.), and each was shown once during the experiment. All stimuli were delivered binaurally to ears through headphones with a sound pressure level of about 75 dB and a duration of 100 ms including 10 ms rise/fall times. Participants also completed another visual oddball task (counterbalanced) reported in a previous study (Zheng et al., 2010). 2.3. Procedure Participants were seated in a dimly lit and sound-attenuating chamber wearing stereo headphones. The task consisted of 480 trials divided into four blocks (120 trials each), and a short break was provided between blocks. Each trial began with a stimulus presented for 100 ms and ended with an interstimulus interval varied randomly from 900 to 1100 ms. Stimuli were delivered in a pseudorandom order with Table 1 Characteristics and behavioral performance for target stimuli (M ± SD).
Gender (M/F) Age (years) Thrill and adventure seeking score Experience seeking score Disinhibition scores Boredom susceptibility score Sensation seeking score Reaction time (ms) Accuracy (%)
134
High sensation seekers (N = 20)
Low sensation seekers (N = 20)
p value
10/10 20.75 ± 0.44 9.45 ± 0.83
10/10 20.90 ± 0.45 5.10 ± 1.55
.294 < .001
7.20 ± 1.28
2.95 ± 1.19
< .001
6.05 ± 1.88 4.25 ± 1.33
2.00 ± 1.65 1.15 ± 0.88
< .001 < .001
26.95 ± 2.09 487.82 ± 59.60 95.2 ± 4.7
11.20 ± 2.71 506.26 ± 76.65 96.3 ± 3.9
< .001 .401 .450
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by conversion to a decibel (dB) scale (10*log10[power(t)/power(baseline)]) from a baseline of 500–300 ms prior to stimulus onset such that power changes reflected the relative power, rather than the absolute power. For statistical analyses (Fig. 2), theta power was scored as the mean activity from 150 to 450 ms over 3–7 Hz at FCz. Data from the time domain and time-frequency domain were analyzed using SPSS v22.0 (IBM, Armonk, NY). All data were analyzed with a repeated measures analysis of variance (ANOVA), with half (the first vs. the second) as a within-subjects factor and group (HSS vs. LSS) as a between-subjects factor. Greenhouse-Geisser epsilon correction was applied when appropriate. The Bonferroni correction was used for pairwise comparisons. Furthermore, Pearson's correlation was applied to evaluate the relationship between subscale scores (i.e., thrill and adventure seeking, experience seeking, disinhibition, and boredom susceptibility) of the SSS-V and electrophysiological data, which was followed by a series of linear hierarchical regressions with the subscale scores as the predictors to identify the unique role of each subscale in predicting the electrophysiological activity.
an additional constraint that no more than two deviant (target and novel) stimuli were presented consecutively. The number of each stimulus type was equal across blocks. Participants were instructed to ignore the standard and the novel stimuli and respond to the target stimuli by pressing a button with their index finger as accurately and quickly as possible. The responding finger (right or left) was counterbalanced across participants in each group. Before the task, participants were presented with a practice block with only standard and target stimuli to ascertain that they could discriminate the target and the standard stimuli. As in previous research (Richardson et al., 2011), participants were not informed about the presence of the environmental sounds (i.e., the novel stimuli). 2.4. Recording and analysis The electroencephalogram (EEG) was continuously recorded from a set of 32 Ag/AgCl electrodes mounted in an elastic cap according to the International 10/20 system. The signals were referenced to the linked earlobes. Horizontal electrooculogram (EOG) was recorded via a pair of electrodes placed on the left and right external canthi to monitor horizontal eye movements. Vertical EOG was recorded from a pair of electrodes placed above and below the left eye to detect blinks and vertical eye movements. The EEG and EOG were amplified and digitalized using a NeuroScan NuAmps amplifier with a band pass of 0.1–100 Hz and a sampling rate at 1000 Hz. Electrode impedances were maintained below 5 KΩ throughout the experiment. The EEG data were preprocessed and analyzed in MATLAB 2014a (MathWorks, Natick, MA) using EEGLAB toolbox (v.13.1.1; Delorme and Makeig, 2004). The EEG signals were epoched from −1500 to 2000 ms with the activity from −200 to 0 ms as the baseline. All epoched data were screened manually for artifacts (e.g., spikes, drifts, and nonbiological signals) and then were subjected to an infomax independent component analysis (runica; Delorme and Makeig, 2004). Individual components were inspected, and blink components were removed. An automatic artifact rejection procedure rejected epochs that contained a voltage difference of more than 50 μV between sample points, a voltage difference exceeding 200 μV within an epoch, or a maximum voltage difference less than 0.5 μV within 100-ms intervals. The cleaned data were then averaged for the first half (i.e. blocks 1–2) and the second half (i.e., blocks 3–4) of the task for each stimulus type. Preliminary analysis on the number of accepted EEG trials of target (19.83 ± 2.88 and 21.62 ± 2.13 for the first half and the second half, respectively) and novelty (19.55 ± 3.16 and 21.10 ± 2.34 for the first half and the second half, respectively) revealed no significant effects involving groups (ps > .05). For the figures, the ERP data were filtered with a low-pass cutoff at 30 Hz, as implemented using ERPLAB toolbox (Lopez-Calderon and Luck, 2014). Based on previous studies and the visual inspection of current ERP waveforms, the novelty P3 was scored as the mean activity from 250 to 320 ms following stimulus onset at FCz, and the target P3 from 275 to 355 ms at Pz. Time-frequency decomposition was performed using customwritten MATLAB routines to isolate theta power. The preprocessing stream was same as the time-domain analyses. After removing artifacts described above, time-frequency decomposition was performed by multiplying the fast Fourier transformed (FFT) power spectrum of single-trial EEG data with the FFT power spectrum of a family of complex Morlet wavelets and then taking the inverse FFT. The result of this process is identical to time-domain signal convolution. The wavelets were defined as a Gaussian-windowed complex sine wave: ei2πtfet2/(2σ2), where the t is time, f is frequency, which increased from 1 to 50 Hz in 50 steps distributed on a logarithmic scale, and σ defines the width of each frequency band, set according to 4/(2πf). After convolution of the wavelets with the EEG data, power was defined as the modulus of the resulting complex signal Z[t] (power time series: p (t) = real[z(t)]2 + imag[z(t)]2). Each epoch was then cut in length (−500 to 1000 ms) to account for edge effects. Power was normalized
3. Results 3.1. Behavioral data As shown in Table 1, both HSS and LSS exhibited a higher level of accuracy rates (> 95%) in response to target stimuli. Although average reaction times were faster for HSS than for LSS, it failed to reach significance. 3.2. Electrophysiological data 3.2.1. Time domain Fig. 1 shows the grand-averaged ERP waveforms in response to target and novel stimuli in the first and the second halves as a function of group. Both HSS and LSS elicited the canonical target P3 and novelty P3. Whereas the target P3 displayed a parietal distribution, the novelty P3 showed a more anterior distribution. Furthermore, the novelty P3 (289 ms) peaked earlier than the target P3 (318 ms). For the novelty P3, its amplitude was larger in the first half than that in the second half, as revealed by a significant main effect of half, F(1, 38) = 14.20, p = .001, ηp2 = 0.27. This half effect was qualified by a significant interaction between half and group, F (1, 38) = 6.03, p = .019, ηp2 = 0.14. Post hoc comparisons revealed that the novelty P3 decreased from the first half to the second half for LSS (16.25 vs. 11.75 μV, p < .001) but was comparable across halves for HSS (11.27 vs. 10.32 μV, p = .359). Furthermore, the novelty P3 tended to be reduced for HSS compared to LSS in the first half (p = .057). This group effect, however, was not significant in the second half (p = .504). The main effect of group was not significant, F(1, 38) = 2.07, p = .158, ηp2 = 0.05. The following trend analyses of block (blocks 1–4) revealed a significant linear trend for LSS, F(1, 19) = 13.95, p = .001, ηp2 = 0.42, but not for HSS, F(1, 19) = 1.58, p = .224, ηp2 = 0.08. For the target P3, the main effects of half, F(1, 38) = 0.19, p = .665, ηp2 = 0.01, and group, F(1, 38) = 0.13, p = .720, ηp2 < 0.01, failed to reach significance. Similarly, the interaction between half and group was not significant, F(1, 38) = 0.13, p = .719, ηp2 < 0.01. 3.2.2. Time-frequency domain As illustrated in Fig. 2, both target and novel stimuli elicited an enhancement in theta power (150–450 ms over 3–7 Hz) over frontocentral regions across groups. For the novel stimuli, the main effect of group was marginally significant, F(1, 38) = 4.00, p = .053, ηp2 = 0.10. The main effect of half was significant, F(1, 38) = 12.52, p = .001, ηp2 = 0.25, which was qualified by a significant interaction between half and group, F(1, 38) = 4.48, p = .041, ηp2 = 0.11. Post hoc comparisons revealed that theta power decreased from the first half to the second half (7.43 vs. 6.07 dB, p < .001) for LSS but was 135
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Fig. 1. Grand-averaged ERP waveforms in response to novel and target stimuli in the first and the second halves as a function of group. Topographic maps of the novelty P3 (250–320 ms) and the target P3 (275–355 ms) are also shown.
For the target stimuli, no significant effects were obtained for the main effects of half, F(1, 38) = 0.82, p = .371, ηp2 = 0.02, and group, F (1, 38) = 2.67, p = .111, ηp2 = 0.07, as well as the interaction between half and group, F(1, 38) = 0.83, p = .369, ηp2 = 0.02.
comparable across halves for HSS (5.68 vs. 5.34 dB, p = .321). Group comparisons revealed that theta power was smaller for HSS than LSS in the first half (p = .012) but not in the second half (p = .277). Similar to the novelty P3, the following trend analyses of block (blocks 1–4) indicated a significant linear trend for LSS, F(1, 19) = 16.55, p = .001, ηp2 = 0.47, but not for HSS, F(1,19) = 2.11, p = .163, ηp2 = 0.10.
Fig. 2. Time-frequency representations of EEG power and topographic maps for theta power (150–450 ms over 3–7 Hz) in response to novel and target stimuli in the first and the second halves as a function of group. 136
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4. Discussion
Table 2 Correlations between sensation-seeking subscales and electrophysiological activity. P3 amplitude
The First Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility The Second Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility ∗
p < .05,
The present study investigated the electrophysiological mechanisms underlying habituation to novelty processing in sensation seeking using an auditory novel oddball task with different environmental sounds of moderate intensity as novel stimuli. As expected, LSS exhibited an obvious habituation to novel stimuli, as indexed by the decreased amplitude of the novelty P3 and the reduced power of midfrontal theta from the first half to the second half. In contrast, HSS showed a lack of habituation in the face of novel stimuli, which was caused by their blunted electrophysiological responses to novel events in the first half. Following regression analyses revealed that the blunted vigilance to novel stimuli was specifically predicted by the experience-seeking dimension of sensation seeking. Consistent with previous research (Friedman et al., 2001; Ranganath and Rainer, 2003), LSS exhibited the habituation to novel stimuli in the time domain such that the novelty P3 was decreased from the first to the second half. However, HSS displayed a comparable novelty P3 across halves, indicating a lack of habituation to novel stimulation. Our novelty P3 findings are at odds with the two previous studies using similar oddball tasks (Fjell et al., 2007; Zheng et al., 2010). In the Fjell et al. study, “real-life” HSS (extreme sporters) exhibited a reduced P3a response from the first half to the second half, which, however, was not observed for both HSS and LSS. In the Zheng et al. study, an absence of habituation to the novelty P3 was found for HSS but not for LSS. The inconsistencies may be attributed to methodological factors across the studies. Specifically, the novel stimuli were a repeated rectangle in the Fjell et al. study, unique and nonexistent pseudoobjects in the Zheng et al. study, and varied environmental sounds with moderate intensity in the current study. Therefore, the inconsistent patterns of habituation across these studies might reflect different orienting responses that are dependent on stimulus novelty and stimulus significance (Bradley, 2009). This possibility was supported by group-comparison results. In both the previous studies (Fjell et al., 2007; Zheng et al., 2010), the habituation effect on the novelty P3/P3a was driven by group differences in the second half, suggesting that the orienting response in the first half was comparable between groups. To go a step further, the comparable orienting responses across
Theta power
Novelty
Target
Novelty
Target
−0.17 −0.32∗ −0.12 −0.35∗
0.04 −0.14 0.04 −0.09
−0.24 −0.43∗∗ −0.13 −0.34∗
−0.27 −0.28 −0.03 −0.30
−0.02 −0.14 0.08 −0.07
−0.01 −0.13 −0.02 −0.08
−0.11 −0.25 0.05 −0.19
−0.21 −0.13 −0.11 −0.12
∗∗
p < .01.
3.3. Relationships between sensation-seeking subscales and electrophysiological activity 3.3.1. Time domain Table 2 shows the correlations between sensation-seeking subscales and P3 amplitudes in the first and the second halves. Both higher experience-seeking and boredom-susceptibility scores were associated with lower novelty P3 amplitudes in the first half but not in the second half. However, the following hierarchical regression analyses revealed that no predictors could significantly predicted the P3 responses (Table 3).
3.3.2. Time-frequency domain As shown in Table 2, both higher experience-seeking and boredomsusceptibility scores were associated with reduced theta power in response to novel stimuli in the first half but not in the second half. However, the following regression analyses revealed that experience seeking was the only significant predictor of theta power in response to novel stimuli (Table 3), which was present only in the first half (Fig. 3).
Table 3 Hierarchical linear regression analysis predicting electrophysiological activity in response to novel and target stimuli from the subcomponents of sensation seeking across two halves. P3 amplitude 2
Novelty The First Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility The Second Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility Target The First Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility The Second Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility ∗
Theta power
R
df
F
0.18
4, 35
1.98
β
R2
df
F
0.24
4, 35
2.80∗
0.29 −0.36 0.15 −0.39 0.08
4, 35
0.76
0.21 −0.61∗ 0.24 −0.19 0.15
4, 35
1.50
0.17 −0.41 0.27 −0.05 0.09
4, 35
0.86
0.15 −0.49 0.34 −0.14 0.15
4, 35
1.60 −0.15 −0.22 0.32 −0.21
0.36 −0.41 0.16 −0.15 0.04
4, 35
0.38
0.05 0.23 −0.30 0.07 −0.07
p < .05. 137
β
4, 35
0.45 −0.29 0.04 0.02 0.05
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Fig. 3. Scatterplot of the correlations between experience-seeking score and theta power in the first and the second halves.
groups might reflect a floor effect caused by the repeated rectangle in the Fjell et al. study and a ceiling effect rendered by unique and nonexistent pseudoobjects in the Zheng et al. study. In contrast, the lack of habituation in the current study was due to a reduced orienting response to novel stimuli with moderate intensity in the first half for HSS relative to LSS. Furthermore, although both the target and novel stimuli are contextually significant events, the blunted orienting response in sensation seeking was limited to novel instead of target stimuli. This finding indicates that the reduced orienting response in sensation seeking is more associated with bottom-up processing than top-down processing. The finding of blunted orienting response in sensation seeking was also supported by midfrontal theta, which has not been examined in previous research. HSS relative to LSS exhibited a reduced midfrontal theta response to novel stimuli, which was present for the first half but not for the second half. Theta power has been suggested to reflect the need of cognitive control or cognitive effort in situations including conflict, error commission, motivational salience, and novelty (Cavanagh et al., 2012; Harper et al., 2017; Mei et al., 2018). Our finding of blunted theta power for HSS compared to LSS in the first half suggests a reduced cognitive control for HSS in the face of novel stimuli. It is necessary to keep alert when an individual is confronted with novel events because these events may incur potential danger. The orienting response is thus adaptive for the organism's survival whereby an individual can switch attention immediately (as indexed by the novelty P3) and realize the need for cognitive control (as indexed by theta power) when encountering significant events (Biriukov, 1965; Donchin et al., 1984). In this regard, the absence of orienting response and habituation effect in sensation seeking may predispose individuals high in
sensation seeking to dangerous behaviors. Our findings may have implications for understanding the mechanisms underlying sensation seeking. On the one hand, according to the optimal arousal theory (Zuckerman, 1969, 1984), the absence of the orienting response among individuals high on sensation seeking can be attributed to their chronically underaroused state. That is, environmental sounds with moderate intensity inserted in an oddball task cannot engage their immediate attention and communicate the need for cognitive control. On the other hand, our findings parallel previous research demonstrating that sensation seeking is associated with diminished brain activation to monetary punishment (Kruschwitz et al., 2012), reduced error-related negativity in response to error commission (Santesso and Segalowitz, 2009; Zheng et al., 2014), and a greater tolerance to losses (Zheng et al., 2019), supporting a hypoactive avoidance system in sensation seeking (Joseph et al., 2009; Lissek et al., 2005). Finally, correlation and regression analyses revealed that the reduced orienting response as indexed by theta power was driven by experience seeking, a sensation-seeking dimension that is associated with the preference for novel experiences through a nonconformist style. Previous studies have demonstrated that experience seeking was positively associated with the structural (Martin et al., 2007) and functional (Samson et al., 2009) properties of hippocampus, an area that plays a role in novelty processing. Furthermore, a recent study reported that experience seeking was positively associated with risky decision-making (Chase et al., 2017). Together with these previous studies, our findings suggest that sensation seeking is not a homogenous construct but can be decomposed into different components at the electrophysiological level. However, as the correlation and regression
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analyses were exploratory in nature, further confirmation is required before any robust conclusions can be drawn. There are several potential limitations to the current study. First, we did not manipulate the degree of novelty and significance of the distracter stimuli, which limits our interpretations of distinct patterns of orienting response and habituation in sensation seeking across the studies. This issue could be addressed by including stimuli with varying degrees of novelty and significance as the distracter in the oddball tasks in a single study. Second, the findings in the studied group may not be easily generalizable to the entire population since it had been drawn from a university student pool using a personality questionnaire, as in most of the existing sensation-seeking studies. Future research should extend our findings to “real-life” sensation seekers randomly selected from the community. Third, given the extreme between-group design (HSS vs. LSS) utilized in the current study, future research should include an additional group consisting of participants from the middle quartile of the SSS-V as controls to replicate our results. Moreover, although using extreme between-group design may increase the chance of finding a significant effect, it may not be the most appropriate design to study individual differences in normative personality given the wealth of empirical work suggesting that metrics of normative personality are better represented as continuous/dimensional measures. In this regard, the two extreme groups likely are not a normative representative sample and thus hinder the generalizability of the current findings. In conclusion, the present study revealed an abnormal habituation to novel events in sensation seeking during a novelty oddball task. The lack of habituation in sensation seeking was driven by a blunted orienting response to the novel stimuli, which was indexed by a diminished novelty P3 and reduced midfrontal theta power. In addition, these findings were associated selectively with the experience-seeking subcomponent of sensation seeking. Together, our findings are supportive of a hypoactive avoidance system in the sensation-seeking trait.
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CRediT authorship contribution statement Xintong Jiang: Writing - original draft. Shuting Mei: Formal analysis. Wei Yi: Data curation. Ya Zheng: Writing - review & editing. Acknowledgements This work was supported by the Fundamental Research Program of Liaoning Higher Education Institution (LQ2017050) and the National Natural Science Foundation of China (31500872). All authors have declared that no competing interests exist. References Andrucci, G.L., Archer, R.P., Pancoast, D.L., Gordon, R.A., 1989. The relationship of MMPI and Sensation Seeking Scales to adolescent drug use. J. Personal. Assess. 53 (2), 253–266. https://doi.org/10.1207/s15327752jpa5302_4. Bardo, M.T., Williams, Y., Dwoskin, L.P., Moynahan, S.E., Perry, I.B., Martin, C.A., 2007. The sensation seeking trait and substance use: research findings and clinical implications. Curr. Psychiatr. Rev. 3 (1), 3–13. https://doi.org/10.2174/ 157340007779815682. Bernat, E.M., Malone, S.M., Williams, W.J., Patrick, C.J., Iacono, W.G., 2007. Decomposing delta, theta, and alpha time-frequency ERP activity from a visual oddball task using PCA. Int. J. Psychophysiol. 64 (1), 62–74. https://doi.org/10. 1016/j.ijpsycho.2006.07.015. Biriukov, D.A., 1965. On the nature of the orienting reaction. In: Voronin, L.G., Leontiev, A.N., Luria, A.R., Sokolov, E.N., Vinogradova, O.S. (Eds.), Orienting Reflex and Exploratory Behavior. American Institute of Biological Sciences, Washington, DC, pp. 17–24. Bradley, M.M., 2009. Natural selective attention: orienting and emotion. Psychophysiology 46 (1), 1–11. https://doi.org/10.1111/j.1469-8986.2008.00702.x. Carton, S., Morand, P., Bungenera, C., Jouvent, R., 1995. Sensation-seeking and emotional disturbances in depression: relationships and evolution. J. Affect. Disord. 34 (3), 219–225. https://doi.org/10.1016/0165-0327(95)00020-N. Cavanagh, J.F., Frank, M.J., 2014. Frontal theta as a mechanism for cognitive control. Trends Cognit. Sci. 18 (8), 414–421. https://doi.org/10.1016/j.tics.2014.04.012. Cavanagh, J.F., Zambrano-Vazquez, L., Allen, J.J., 2012. Theta lingua franca: a common mid-frontal substrate for action monitoring processes. Psychophysiology 49 (2),
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Effects of sensation seeking on habituation to novelty: An EEG study Xintong Jiang, Shuting Mei, Wei Yi, Ya Zheng
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T
Department of Psychology, Dalian Medical University, Dalian, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Sensation seeking Habituation Orienting response Novelty P3 Midfrontal theta
Sensation seeking is characterized by a strong need for novelty and has been associated with various risk-taking behaviors. Using the extreme between-group design, the current study investigated the electrophysiological mechanisms underlying habituation to novelty processing in sensation seeking. Twenty high sensation seekers (HSS) and 20 low sensation seekers (LSS) performed an auditory oddball task while their EEG was recorded. The results revealed that both the novelty P3 and midfrontal theta power decreased from the first to the second half for LSS but not for HSS. Additionally, this reduced vigilance was predicted by the experience-seeking subcomponent of sensation seeking. Together, our findings are supportive of an abnormal habituation to novel events in the sensation-seeking trait.
1. Introduction Sensation seeking is a personality trait characterized by a strong need for varied, novel, complex, and intense stimulation and willingness to take risks for such experience (Zuckerman, 1994). This trait is captured by the Sensation Seeking Scale Form V (Zuckerman et al., 1978), which includes four dimensions: thrill and adventure seeking (a desire to engage in physically risky activities), experience seeking (a preference for novel experiences through a nonconformist style), disinhibition (an interest in socially and sexually disinhibited activities), and boredom susceptibility (an aversion to repetitiveness and monotony). High sensation seekers (HSS) relative to low sensation seekers (LSS) are susceptible to be involved in various risk-taking behaviors, such as extreme sports (Ruedl et al., 2012), reckless driving (Jonah, 1997), risky sex (Hoyle et al., 2000), problem gambling (Harris et al., 2015), and substance abuse (Bardo et al., 2007). According to the optimal arousal theory (Zuckerman, 1969, 1984), the sensation-seeking behaviors are associated with a regulatory mechanism to compensate for affective disturbances due to a chronically underaroused state in sensation seeking (Carton et al., 1995). It should be noted that, however, risk is not the merely focus of people high in sensation seeking. For example, among normal populations, HSS are more inclined to switch TV channels than LSS (Perse, 1996), whereas among individuals with addiction, sensation seeking is the most sensitive variable predicting poly versus single drug use (Andrucci et al., 1989). In this regard, the need for novelty and aversion to repetitiveness (i.e., habituation) seem to be at the root of sensation seeking. Electrophysiological investigations of novelty processing and
∗
habituation typically employ novel oddball tasks in which novel stimuli are embedded randomly when participants were asked to discriminate infrequent target stimuli from frequent standard stimuli. Novel stimuli typically elicit an event-related potential (ERP) component called the novelty P3 (also referred to as the P3a) peaking approximately 250 ms post stimulus onset with an anterior distribution (Courchesne et al., 1975). The novelty P3 is considered to index immediate attention to novel stimuli (Friedman et al., 2001), which is associated with the wellknown orienting response (Pavlov, 1927; Sokolov, 1963). Orienting response is adaptive for preparing the organism to respond quickly to novel events that call for immediate action. With repetition of the same or similar stimuli, however, a neuronal model is formed, and those stimuli no longer elicit the orienting response of similar magnitude. Hence, one distinctive feature of orienting response is habituation (Sokolov, 1963). Unsurprisingly, the novelty P3 typically habituates rapidly as more and more novel stimuli are experienced or the same novel stimulus is repeated (Friedman et al., 2001; Ranganath and Rainer, 2003). The lack of habituation for the novelty P3 has been linked to dysfunctional cognitive processing among aged people (Friedman et al., 1993), patients with neurological impairment (Knight, 1984), and individuals with borderline and avoidant personality disorder (Koenigsberg et al., 2014). To our knowledge, only two ERP studies examined the habituation of the novelty P3/P3a in sensation seeking. As did in most of the previous studies (e.g., Cservenka et al., 2012; Frenkel et al., 2018; Zheng et al., 2017), both studies recruited HSS and LSS at extreme scores on the sensation-seeking scale using the extreme between-group design, which is more sensitive than the dimensional design (i.e., examining
Corresponding author. Department of Psychology, Dalian Medical University, No. 9 West Section, Lvshun South Road, Dalian 116044, China. E-mail address: [email protected] (Y. Zheng).
https://doi.org/10.1016/j.neuropsychologia.2019.03.011 Received 22 October 2018; Received in revised form 25 February 2019; Accepted 20 March 2019 Available online 25 March 2019 0028-3932/ © 2019 Elsevier Ltd. All rights reserved.
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seeking and boredom susceptibility should be related to the habituation to novelty in sensation seeking, indexed by the novelty P3 and midfrontal theta. If confirmed, the results would be helpful to our understanding of habituation in sensation seeking.
linear relationships of sensation seeking across normal population) in terms of maximizing the likelihood of biological correlates associated with sensation seeking (Joseph et al., 2013). Fjell et al. (2007) addressed this issue firstly among a group with HSS, a group with LSS, and a group with “real-life” HSS who engaged in extreme sports. Participants performed a three-stimulus oddball task during which they were instructed to respond to a blue circle (target) and ignore a little smaller blue circle (standard) and a blue rectangle (distractor). The results revealed that the amplitude of the P3a decreased from the first to the second half of the trials (i.e., the habituation effect), which was present for real-life HSS but not for HSS and LSS. In a following study, Zheng et al. (2010) employed a similar oddball task in which participants were asked to respond to an inverted triangle (target) and ignore an upright triangle (standard) and unique line drawings of pseudo-objects (novelty). The author found that LSS, instead of HSS, exhibited a habituation effect such that the amplitude of the novelty P3 decreased from the first to the second half of the task. Given that novelty processing is modulated by contextual novelty (a top-down process determined by task demands) and stimulus novelty (a bottom-up process determined by stimuli) (Bradley, 2009; Friedman et al., 2001), it is possible that the discrepancy between the two studies may reflect the degree of stimulus novelty. Specifically, the novel stimuli in the Fjell et al. study were repeated and familiar blue rectangles. In contrast, the novel stimuli in the Zheng et al. study were unique and unfamiliar and thus deviant from participants’ long-term memory. Indeed, early autonomic studies have demonstrated a close relationship between sensation seeking and information content and intensity. For example, when facing stimuli with moderate intensity, HSS exhibit an orienting response, whereas LSS display a defensive response (Zuckerman, 1990). Importantly, the novel stimuli employed in both the Fjell et al. study (a repeated and familiar blue rectangle) and the Zheng et al. study (unique and nonexistent pseudoobjects) were not typical in our daily life, resulting in a relatively weak ecological validity. Moreover, since both studies have investigated the habituation effect in the visual modality, it also makes sense to examine it in the auditory modality, although the novelty P3 is modality nonspecific (Friedman et al., 2001). In the present study, we adopted an auditory novel oddball paradigm to examine the habituation of novel stimuli in HSS and LSS. The novel stimuli consisted of unrepeated environmental sounds with moderate intensity, which are more prototypical in ordinary life and thus have a greater ecological validity than the previous studies (Fjell et al., 2007; Zheng et al., 2010). It was hypothesized that HSS should exhibit a higher rate of habituation to auditory novel stimuli than LSS, as reflected by a more decreased novelty P3 as the experiment proceeded. Moreover, the current study also focused on another electrophysiological index associated with novelty processing, that is, the frontal midline theta-band (4–7 Hz) activity recorded from the medial prefrontal cortex (Cavanagh et al., 2012; Demiralp et al., 2001; Harper et al., 2017). Midfrontal theta is reliably observed in various situations during which there is a need for cognitive control or cognitive effort (Cavanagh and Frank, 2014; Mussel et al., 2016; Wascher et al., 2014). It is thus unsurprising that, as the novelty P3, midfrontal theta can also be elicited in novelty processing (Cavanagh et al., 2012; Harper et al., 2017). Given that theta-band signals are found to contribute to P3 responses (Bernat et al., 2007; Karakas et al., 2000; Yordanova and Kolev, 1998), it is possible that the novelty P3 and midfrontal theta constitute two complementary indexes of the orienting response elicited by novel stimuli. To our knowledge, no previous study has examined the role of midfrontal theta in habituation as a function of sensation seeking. Finally, given that sensation seeking is not a single construct, it is highly possible that its subdimensions contribute differently to the habituation in sensation seeking. Thus, the third purpose of the study was to explore the association between the subdimensions of sensation seeking and the rate of habituation to novelty. According to the above definition of each dimension, it was hypothesized that both experience
2. Materials and methods 2.1. Participants Participants consisted of 20 HSS and 20 LSS selected from a large student sample (N = 272; 163 females and 109 males) based on their scores on the Chinese version of Sensation Seeking Scale Form V (SSS-V; Wang et al., 2000; Zuckerman, 1994). The SSS-V is designed to measure four dimensions (10 items each) of sensation seeking. Summing all the 40 items results in an overall sensation-seeking score. Responders in the top and the bottom quartile of distribution of the sample were assigned as HSS and LSS, respectively. The criterion of selection was employed for females and males separately because of the gender imbalance in the sample. Qualified participants were then invited randomly for the experiment. The groups differed significantly on the overall sensation-seeking score and its subscale scores with no differences on age, gender, and educational level (Table 1). All had normal hearing and were free of neurological or psychiatric disorders. Each signed a written informed consent form prior to the experiment and received course credit for the participation. This study was approved by the Dalian Medical University Institutional Review Board in accordance with the Helsinki Declaration as revised 1989. 2.2. Stimuli An auditory novel oddball paradigm was adopted in the current study with three types of stimuli (standard, target, and novel). The standard (80%) and target (10%) stimuli were pure tones of 800 Hz and 1000 Hz, respectively. The novel stimuli (10%) consisted of 48 distinct environmental sounds (animal calls, telephone ringing, car honks, etc.), and each was shown once during the experiment. All stimuli were delivered binaurally to ears through headphones with a sound pressure level of about 75 dB and a duration of 100 ms including 10 ms rise/fall times. Participants also completed another visual oddball task (counterbalanced) reported in a previous study (Zheng et al., 2010). 2.3. Procedure Participants were seated in a dimly lit and sound-attenuating chamber wearing stereo headphones. The task consisted of 480 trials divided into four blocks (120 trials each), and a short break was provided between blocks. Each trial began with a stimulus presented for 100 ms and ended with an interstimulus interval varied randomly from 900 to 1100 ms. Stimuli were delivered in a pseudorandom order with Table 1 Characteristics and behavioral performance for target stimuli (M ± SD).
Gender (M/F) Age (years) Thrill and adventure seeking score Experience seeking score Disinhibition scores Boredom susceptibility score Sensation seeking score Reaction time (ms) Accuracy (%)
134
High sensation seekers (N = 20)
Low sensation seekers (N = 20)
p value
10/10 20.75 ± 0.44 9.45 ± 0.83
10/10 20.90 ± 0.45 5.10 ± 1.55
.294 < .001
7.20 ± 1.28
2.95 ± 1.19
< .001
6.05 ± 1.88 4.25 ± 1.33
2.00 ± 1.65 1.15 ± 0.88
< .001 < .001
26.95 ± 2.09 487.82 ± 59.60 95.2 ± 4.7
11.20 ± 2.71 506.26 ± 76.65 96.3 ± 3.9
< .001 .401 .450
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by conversion to a decibel (dB) scale (10*log10[power(t)/power(baseline)]) from a baseline of 500–300 ms prior to stimulus onset such that power changes reflected the relative power, rather than the absolute power. For statistical analyses (Fig. 2), theta power was scored as the mean activity from 150 to 450 ms over 3–7 Hz at FCz. Data from the time domain and time-frequency domain were analyzed using SPSS v22.0 (IBM, Armonk, NY). All data were analyzed with a repeated measures analysis of variance (ANOVA), with half (the first vs. the second) as a within-subjects factor and group (HSS vs. LSS) as a between-subjects factor. Greenhouse-Geisser epsilon correction was applied when appropriate. The Bonferroni correction was used for pairwise comparisons. Furthermore, Pearson's correlation was applied to evaluate the relationship between subscale scores (i.e., thrill and adventure seeking, experience seeking, disinhibition, and boredom susceptibility) of the SSS-V and electrophysiological data, which was followed by a series of linear hierarchical regressions with the subscale scores as the predictors to identify the unique role of each subscale in predicting the electrophysiological activity.
an additional constraint that no more than two deviant (target and novel) stimuli were presented consecutively. The number of each stimulus type was equal across blocks. Participants were instructed to ignore the standard and the novel stimuli and respond to the target stimuli by pressing a button with their index finger as accurately and quickly as possible. The responding finger (right or left) was counterbalanced across participants in each group. Before the task, participants were presented with a practice block with only standard and target stimuli to ascertain that they could discriminate the target and the standard stimuli. As in previous research (Richardson et al., 2011), participants were not informed about the presence of the environmental sounds (i.e., the novel stimuli). 2.4. Recording and analysis The electroencephalogram (EEG) was continuously recorded from a set of 32 Ag/AgCl electrodes mounted in an elastic cap according to the International 10/20 system. The signals were referenced to the linked earlobes. Horizontal electrooculogram (EOG) was recorded via a pair of electrodes placed on the left and right external canthi to monitor horizontal eye movements. Vertical EOG was recorded from a pair of electrodes placed above and below the left eye to detect blinks and vertical eye movements. The EEG and EOG were amplified and digitalized using a NeuroScan NuAmps amplifier with a band pass of 0.1–100 Hz and a sampling rate at 1000 Hz. Electrode impedances were maintained below 5 KΩ throughout the experiment. The EEG data were preprocessed and analyzed in MATLAB 2014a (MathWorks, Natick, MA) using EEGLAB toolbox (v.13.1.1; Delorme and Makeig, 2004). The EEG signals were epoched from −1500 to 2000 ms with the activity from −200 to 0 ms as the baseline. All epoched data were screened manually for artifacts (e.g., spikes, drifts, and nonbiological signals) and then were subjected to an infomax independent component analysis (runica; Delorme and Makeig, 2004). Individual components were inspected, and blink components were removed. An automatic artifact rejection procedure rejected epochs that contained a voltage difference of more than 50 μV between sample points, a voltage difference exceeding 200 μV within an epoch, or a maximum voltage difference less than 0.5 μV within 100-ms intervals. The cleaned data were then averaged for the first half (i.e. blocks 1–2) and the second half (i.e., blocks 3–4) of the task for each stimulus type. Preliminary analysis on the number of accepted EEG trials of target (19.83 ± 2.88 and 21.62 ± 2.13 for the first half and the second half, respectively) and novelty (19.55 ± 3.16 and 21.10 ± 2.34 for the first half and the second half, respectively) revealed no significant effects involving groups (ps > .05). For the figures, the ERP data were filtered with a low-pass cutoff at 30 Hz, as implemented using ERPLAB toolbox (Lopez-Calderon and Luck, 2014). Based on previous studies and the visual inspection of current ERP waveforms, the novelty P3 was scored as the mean activity from 250 to 320 ms following stimulus onset at FCz, and the target P3 from 275 to 355 ms at Pz. Time-frequency decomposition was performed using customwritten MATLAB routines to isolate theta power. The preprocessing stream was same as the time-domain analyses. After removing artifacts described above, time-frequency decomposition was performed by multiplying the fast Fourier transformed (FFT) power spectrum of single-trial EEG data with the FFT power spectrum of a family of complex Morlet wavelets and then taking the inverse FFT. The result of this process is identical to time-domain signal convolution. The wavelets were defined as a Gaussian-windowed complex sine wave: ei2πtfet2/(2σ2), where the t is time, f is frequency, which increased from 1 to 50 Hz in 50 steps distributed on a logarithmic scale, and σ defines the width of each frequency band, set according to 4/(2πf). After convolution of the wavelets with the EEG data, power was defined as the modulus of the resulting complex signal Z[t] (power time series: p (t) = real[z(t)]2 + imag[z(t)]2). Each epoch was then cut in length (−500 to 1000 ms) to account for edge effects. Power was normalized
3. Results 3.1. Behavioral data As shown in Table 1, both HSS and LSS exhibited a higher level of accuracy rates (> 95%) in response to target stimuli. Although average reaction times were faster for HSS than for LSS, it failed to reach significance. 3.2. Electrophysiological data 3.2.1. Time domain Fig. 1 shows the grand-averaged ERP waveforms in response to target and novel stimuli in the first and the second halves as a function of group. Both HSS and LSS elicited the canonical target P3 and novelty P3. Whereas the target P3 displayed a parietal distribution, the novelty P3 showed a more anterior distribution. Furthermore, the novelty P3 (289 ms) peaked earlier than the target P3 (318 ms). For the novelty P3, its amplitude was larger in the first half than that in the second half, as revealed by a significant main effect of half, F(1, 38) = 14.20, p = .001, ηp2 = 0.27. This half effect was qualified by a significant interaction between half and group, F (1, 38) = 6.03, p = .019, ηp2 = 0.14. Post hoc comparisons revealed that the novelty P3 decreased from the first half to the second half for LSS (16.25 vs. 11.75 μV, p < .001) but was comparable across halves for HSS (11.27 vs. 10.32 μV, p = .359). Furthermore, the novelty P3 tended to be reduced for HSS compared to LSS in the first half (p = .057). This group effect, however, was not significant in the second half (p = .504). The main effect of group was not significant, F(1, 38) = 2.07, p = .158, ηp2 = 0.05. The following trend analyses of block (blocks 1–4) revealed a significant linear trend for LSS, F(1, 19) = 13.95, p = .001, ηp2 = 0.42, but not for HSS, F(1, 19) = 1.58, p = .224, ηp2 = 0.08. For the target P3, the main effects of half, F(1, 38) = 0.19, p = .665, ηp2 = 0.01, and group, F(1, 38) = 0.13, p = .720, ηp2 < 0.01, failed to reach significance. Similarly, the interaction between half and group was not significant, F(1, 38) = 0.13, p = .719, ηp2 < 0.01. 3.2.2. Time-frequency domain As illustrated in Fig. 2, both target and novel stimuli elicited an enhancement in theta power (150–450 ms over 3–7 Hz) over frontocentral regions across groups. For the novel stimuli, the main effect of group was marginally significant, F(1, 38) = 4.00, p = .053, ηp2 = 0.10. The main effect of half was significant, F(1, 38) = 12.52, p = .001, ηp2 = 0.25, which was qualified by a significant interaction between half and group, F(1, 38) = 4.48, p = .041, ηp2 = 0.11. Post hoc comparisons revealed that theta power decreased from the first half to the second half (7.43 vs. 6.07 dB, p < .001) for LSS but was 135
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Fig. 1. Grand-averaged ERP waveforms in response to novel and target stimuli in the first and the second halves as a function of group. Topographic maps of the novelty P3 (250–320 ms) and the target P3 (275–355 ms) are also shown.
For the target stimuli, no significant effects were obtained for the main effects of half, F(1, 38) = 0.82, p = .371, ηp2 = 0.02, and group, F (1, 38) = 2.67, p = .111, ηp2 = 0.07, as well as the interaction between half and group, F(1, 38) = 0.83, p = .369, ηp2 = 0.02.
comparable across halves for HSS (5.68 vs. 5.34 dB, p = .321). Group comparisons revealed that theta power was smaller for HSS than LSS in the first half (p = .012) but not in the second half (p = .277). Similar to the novelty P3, the following trend analyses of block (blocks 1–4) indicated a significant linear trend for LSS, F(1, 19) = 16.55, p = .001, ηp2 = 0.47, but not for HSS, F(1,19) = 2.11, p = .163, ηp2 = 0.10.
Fig. 2. Time-frequency representations of EEG power and topographic maps for theta power (150–450 ms over 3–7 Hz) in response to novel and target stimuli in the first and the second halves as a function of group. 136
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4. Discussion
Table 2 Correlations between sensation-seeking subscales and electrophysiological activity. P3 amplitude
The First Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility The Second Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility ∗
p < .05,
The present study investigated the electrophysiological mechanisms underlying habituation to novelty processing in sensation seeking using an auditory novel oddball task with different environmental sounds of moderate intensity as novel stimuli. As expected, LSS exhibited an obvious habituation to novel stimuli, as indexed by the decreased amplitude of the novelty P3 and the reduced power of midfrontal theta from the first half to the second half. In contrast, HSS showed a lack of habituation in the face of novel stimuli, which was caused by their blunted electrophysiological responses to novel events in the first half. Following regression analyses revealed that the blunted vigilance to novel stimuli was specifically predicted by the experience-seeking dimension of sensation seeking. Consistent with previous research (Friedman et al., 2001; Ranganath and Rainer, 2003), LSS exhibited the habituation to novel stimuli in the time domain such that the novelty P3 was decreased from the first to the second half. However, HSS displayed a comparable novelty P3 across halves, indicating a lack of habituation to novel stimulation. Our novelty P3 findings are at odds with the two previous studies using similar oddball tasks (Fjell et al., 2007; Zheng et al., 2010). In the Fjell et al. study, “real-life” HSS (extreme sporters) exhibited a reduced P3a response from the first half to the second half, which, however, was not observed for both HSS and LSS. In the Zheng et al. study, an absence of habituation to the novelty P3 was found for HSS but not for LSS. The inconsistencies may be attributed to methodological factors across the studies. Specifically, the novel stimuli were a repeated rectangle in the Fjell et al. study, unique and nonexistent pseudoobjects in the Zheng et al. study, and varied environmental sounds with moderate intensity in the current study. Therefore, the inconsistent patterns of habituation across these studies might reflect different orienting responses that are dependent on stimulus novelty and stimulus significance (Bradley, 2009). This possibility was supported by group-comparison results. In both the previous studies (Fjell et al., 2007; Zheng et al., 2010), the habituation effect on the novelty P3/P3a was driven by group differences in the second half, suggesting that the orienting response in the first half was comparable between groups. To go a step further, the comparable orienting responses across
Theta power
Novelty
Target
Novelty
Target
−0.17 −0.32∗ −0.12 −0.35∗
0.04 −0.14 0.04 −0.09
−0.24 −0.43∗∗ −0.13 −0.34∗
−0.27 −0.28 −0.03 −0.30
−0.02 −0.14 0.08 −0.07
−0.01 −0.13 −0.02 −0.08
−0.11 −0.25 0.05 −0.19
−0.21 −0.13 −0.11 −0.12
∗∗
p < .01.
3.3. Relationships between sensation-seeking subscales and electrophysiological activity 3.3.1. Time domain Table 2 shows the correlations between sensation-seeking subscales and P3 amplitudes in the first and the second halves. Both higher experience-seeking and boredom-susceptibility scores were associated with lower novelty P3 amplitudes in the first half but not in the second half. However, the following hierarchical regression analyses revealed that no predictors could significantly predicted the P3 responses (Table 3).
3.3.2. Time-frequency domain As shown in Table 2, both higher experience-seeking and boredomsusceptibility scores were associated with reduced theta power in response to novel stimuli in the first half but not in the second half. However, the following regression analyses revealed that experience seeking was the only significant predictor of theta power in response to novel stimuli (Table 3), which was present only in the first half (Fig. 3).
Table 3 Hierarchical linear regression analysis predicting electrophysiological activity in response to novel and target stimuli from the subcomponents of sensation seeking across two halves. P3 amplitude 2
Novelty The First Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility The Second Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility Target The First Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility The Second Half Thrill and adventure seeking Experience seeking Disinhibition Boredom susceptibility ∗
Theta power
R
df
F
0.18
4, 35
1.98
β
R2
df
F
0.24
4, 35
2.80∗
0.29 −0.36 0.15 −0.39 0.08
4, 35
0.76
0.21 −0.61∗ 0.24 −0.19 0.15
4, 35
1.50
0.17 −0.41 0.27 −0.05 0.09
4, 35
0.86
0.15 −0.49 0.34 −0.14 0.15
4, 35
1.60 −0.15 −0.22 0.32 −0.21
0.36 −0.41 0.16 −0.15 0.04
4, 35
0.38
0.05 0.23 −0.30 0.07 −0.07
p < .05. 137
β
4, 35
0.45 −0.29 0.04 0.02 0.05
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Fig. 3. Scatterplot of the correlations between experience-seeking score and theta power in the first and the second halves.
groups might reflect a floor effect caused by the repeated rectangle in the Fjell et al. study and a ceiling effect rendered by unique and nonexistent pseudoobjects in the Zheng et al. study. In contrast, the lack of habituation in the current study was due to a reduced orienting response to novel stimuli with moderate intensity in the first half for HSS relative to LSS. Furthermore, although both the target and novel stimuli are contextually significant events, the blunted orienting response in sensation seeking was limited to novel instead of target stimuli. This finding indicates that the reduced orienting response in sensation seeking is more associated with bottom-up processing than top-down processing. The finding of blunted orienting response in sensation seeking was also supported by midfrontal theta, which has not been examined in previous research. HSS relative to LSS exhibited a reduced midfrontal theta response to novel stimuli, which was present for the first half but not for the second half. Theta power has been suggested to reflect the need of cognitive control or cognitive effort in situations including conflict, error commission, motivational salience, and novelty (Cavanagh et al., 2012; Harper et al., 2017; Mei et al., 2018). Our finding of blunted theta power for HSS compared to LSS in the first half suggests a reduced cognitive control for HSS in the face of novel stimuli. It is necessary to keep alert when an individual is confronted with novel events because these events may incur potential danger. The orienting response is thus adaptive for the organism's survival whereby an individual can switch attention immediately (as indexed by the novelty P3) and realize the need for cognitive control (as indexed by theta power) when encountering significant events (Biriukov, 1965; Donchin et al., 1984). In this regard, the absence of orienting response and habituation effect in sensation seeking may predispose individuals high in
sensation seeking to dangerous behaviors. Our findings may have implications for understanding the mechanisms underlying sensation seeking. On the one hand, according to the optimal arousal theory (Zuckerman, 1969, 1984), the absence of the orienting response among individuals high on sensation seeking can be attributed to their chronically underaroused state. That is, environmental sounds with moderate intensity inserted in an oddball task cannot engage their immediate attention and communicate the need for cognitive control. On the other hand, our findings parallel previous research demonstrating that sensation seeking is associated with diminished brain activation to monetary punishment (Kruschwitz et al., 2012), reduced error-related negativity in response to error commission (Santesso and Segalowitz, 2009; Zheng et al., 2014), and a greater tolerance to losses (Zheng et al., 2019), supporting a hypoactive avoidance system in sensation seeking (Joseph et al., 2009; Lissek et al., 2005). Finally, correlation and regression analyses revealed that the reduced orienting response as indexed by theta power was driven by experience seeking, a sensation-seeking dimension that is associated with the preference for novel experiences through a nonconformist style. Previous studies have demonstrated that experience seeking was positively associated with the structural (Martin et al., 2007) and functional (Samson et al., 2009) properties of hippocampus, an area that plays a role in novelty processing. Furthermore, a recent study reported that experience seeking was positively associated with risky decision-making (Chase et al., 2017). Together with these previous studies, our findings suggest that sensation seeking is not a homogenous construct but can be decomposed into different components at the electrophysiological level. However, as the correlation and regression
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analyses were exploratory in nature, further confirmation is required before any robust conclusions can be drawn. There are several potential limitations to the current study. First, we did not manipulate the degree of novelty and significance of the distracter stimuli, which limits our interpretations of distinct patterns of orienting response and habituation in sensation seeking across the studies. This issue could be addressed by including stimuli with varying degrees of novelty and significance as the distracter in the oddball tasks in a single study. Second, the findings in the studied group may not be easily generalizable to the entire population since it had been drawn from a university student pool using a personality questionnaire, as in most of the existing sensation-seeking studies. Future research should extend our findings to “real-life” sensation seekers randomly selected from the community. Third, given the extreme between-group design (HSS vs. LSS) utilized in the current study, future research should include an additional group consisting of participants from the middle quartile of the SSS-V as controls to replicate our results. Moreover, although using extreme between-group design may increase the chance of finding a significant effect, it may not be the most appropriate design to study individual differences in normative personality given the wealth of empirical work suggesting that metrics of normative personality are better represented as continuous/dimensional measures. In this regard, the two extreme groups likely are not a normative representative sample and thus hinder the generalizability of the current findings. In conclusion, the present study revealed an abnormal habituation to novel events in sensation seeking during a novelty oddball task. The lack of habituation in sensation seeking was driven by a blunted orienting response to the novel stimuli, which was indexed by a diminished novelty P3 and reduced midfrontal theta power. In addition, these findings were associated selectively with the experience-seeking subcomponent of sensation seeking. Together, our findings are supportive of a hypoactive avoidance system in the sensation-seeking trait.
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CRediT authorship contribution statement Xintong Jiang: Writing - original draft. Shuting Mei: Formal analysis. Wei Yi: Data curation. Ya Zheng: Writing - review & editing. Acknowledgements This work was supported by the Fundamental Research Program of Liaoning Higher Education Institution (LQ2017050) and the National Natural Science Foundation of China (31500872). All authors have declared that no competing interests exist. References Andrucci, G.L., Archer, R.P., Pancoast, D.L., Gordon, R.A., 1989. The relationship of MMPI and Sensation Seeking Scales to adolescent drug use. J. Personal. Assess. 53 (2), 253–266. https://doi.org/10.1207/s15327752jpa5302_4. Bardo, M.T., Williams, Y., Dwoskin, L.P., Moynahan, S.E., Perry, I.B., Martin, C.A., 2007. The sensation seeking trait and substance use: research findings and clinical implications. Curr. Psychiatr. Rev. 3 (1), 3–13. https://doi.org/10.2174/ 157340007779815682. Bernat, E.M., Malone, S.M., Williams, W.J., Patrick, C.J., Iacono, W.G., 2007. Decomposing delta, theta, and alpha time-frequency ERP activity from a visual oddball task using PCA. Int. J. Psychophysiol. 64 (1), 62–74. https://doi.org/10. 1016/j.ijpsycho.2006.07.015. Biriukov, D.A., 1965. On the nature of the orienting reaction. In: Voronin, L.G., Leontiev, A.N., Luria, A.R., Sokolov, E.N., Vinogradova, O.S. (Eds.), Orienting Reflex and Exploratory Behavior. American Institute of Biological Sciences, Washington, DC, pp. 17–24. Bradley, M.M., 2009. Natural selective attention: orienting and emotion. Psychophysiology 46 (1), 1–11. https://doi.org/10.1111/j.1469-8986.2008.00702.x. Carton, S., Morand, P., Bungenera, C., Jouvent, R., 1995. Sensation-seeking and emotional disturbances in depression: relationships and evolution. J. Affect. Disord. 34 (3), 219–225. https://doi.org/10.1016/0165-0327(95)00020-N. Cavanagh, J.F., Frank, M.J., 2014. Frontal theta as a mechanism for cognitive control. Trends Cognit. Sci. 18 (8), 414–421. https://doi.org/10.1016/j.tics.2014.04.012. Cavanagh, J.F., Zambrano-Vazquez, L., Allen, J.J., 2012. Theta lingua franca: a common mid-frontal substrate for action monitoring processes. Psychophysiology 49 (2),
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