- Email: [email protected]
The developmental relationship between central dopaminergic level and response inhibition from late childhood to young adulthood
International Journal of Psychophysiology 116 (2017) 53–59
Contents lists available at ScienceDirect
International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho
The developmental relationship between central dopaminergic level and response inhibition from late childhood to young adulthood Ting Zhang a,⁎,1, Qin Zhang b,1, Cuicui Wang c, Antao Chen a,⁎ a b c
School of Psychology, Southwest University, Chongqing, China School of Political Science and Public Administration, University of Electronic Science and Technology of China, China State Key Lab of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
a r t i c l e
i n f o
Article history: Received 20 September 2016 Received in revised form 13 February 2017 Accepted 15 February 2017 Available online 20 February 2017 Keywords: Dopamine Spontaneous eye blink rate Response inhibition Late childhood Young adulthood
a b s t r a c t Dopamine (DA) is known to modulate response inhibition (RI). In contrast to the abundant adult studies, only few developmental studies have focused on this topic. Moreover, the mechanism underlying the modulation of RI by the DA system from childhood to adulthood remains unclear. We aimed to assess whether the relationship between DA and RI during late childhood and young adulthood is similar. Accordingly, DA function was measured using the spontaneous eye blink rate (EBR), whereas RI ability was tested using the Go/Nogo task. Experiment 1 included 149 adults (age range, 18–25 years) who completed the EBR test and the Go/Nogo task; the results showed that higher EBR was associated with lower commission error in the Nogo trials. Experiment 2 included 45 children (age range, 10–12 years) and 37 adults (age range, 18–19 years) who completed the EBR test and Go/Nogo tasks (similar to experiment 1); in both the child and adult groups, higher EBR was related to better RI ability. As EBR is closely related to central DA function, these findings suggest that DA plays a similar role in the processing of RI in late childhood and young adulthood. © 2017 Elsevier B.V. All rights reserved.
1. Introduction Response inhibition (RI) refers to the inhibition of prepotent responses or events (Barkley, 1997), and involves a choice between action and non-action (Rubia et al., 2001). Dopamine (DA) is an important neurotransmitter in the brain that modulates RI processing (Padmanabhan and Luna, 2013). Studies have shown that individuals with higher DA function have better behavioral performance on RI tasks, higher inhibition-related brain activation, and a larger inhibition-related event-related potentials (ERPs) component, all of which reflect better RI ability (Albrecht et al., 2014; Ghahremani et al., 2012; van Bochove et al., 2013; Zhang et al., 2015; Zhang et al., 2016). With regard to the underlying mechanism, some studies have proposed that DA modulates the processing of RI through the frontal-striatal neural circuitry (Acheson et al., 2015; Albrecht et al., 2014; Ghahremani et al., 2012). For example, in the frontal-striatal motor loop involved in the Go/Nogo task,2 the supplementary motor area (SMA) sends excitatory glutamatergic input through the dorsal striatum to the ventrolateral ⁎ Corresponding authors at: School of Psychology, Southwest University, Chongqing 400715, China. E-mail addresses: [email protected] (T. Zhang), [email protected] (A. Chen). 1 Co-first authors: Ting Zhang, Qin Zhang. 2 The Go/Nogo task is a classical RI task that requires a response to be made when a frequently occurring “Go” is presented, but withheld when a less frequent “Nogo” stimulus is presented (Cragg and Nation, 2008).
http://dx.doi.org/10.1016/j.ijpsycho.2017.02.009 0167-8760/© 2017 Elsevier B.V. All rights reserved.
thalamus, which projects back to the SMA. In this loop, the dorsal striatum would have either excitatory (dopamine D1 receptor, DRD1) or inhibitory (dopamine D2 receptor, DRD2) influences on striatal firing, which mediates SMA activity (Acheson et al., 2015). However, in contrast to the amount of adult studies, far fewer studies have focused on the relationship between DA and RI in children and adolescents; moreover, the invasive methods generally used in adult populations (positron emission tomography [PET] or medication) typically cannot be used to study developing populations (Padmanabhan and Luna, 2013). Nevertheless, the fact that the spontaneous eye blink rate (EBR) has been non-invasively confirmed to indirectly reflect the central DA activity (Bodfish et al., 1995; Karson, 1983; Shukla, 1985; Eckstein et al., 2016; Jongkees and Colzato, 2016; Slaghter et al., 2015), which begins during the fetal period, increases rapidly during childhood and adolescence, and then stabilizes during adulthood (Bacher, 2014; Cruz et al., 2011). Previous pharmacological studies showed that EBR could be altered by both DRD1 and DRD2 agonists/antagonists (Blin et al., 1990; Groman et al., 2014; Jutkiewicz and Bergman, 2004; Kleven and Koek, 1996; Lawrence and Redmond, 1991; Taylor et al., 1999); however one recent PET study showed that EBR was more strongly related to the DRD2 system (Groman et al., 2014). Besides, the EBR is also associated with dopamine D4 7-repeat allele (Dreisbach et al., 2005) and behavioral interventions (rewards and acute exercise) could also alter the EBR (Aarts et al., 2012; Cooper, 1973). In contrast to healthy controls, DA
54
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
dysfunction could cause increased or decreased EBR in children with immunodeficiency syndrome, fragile X syndrome, ADHD, and iron deficiency anemia, as well as in adults with schizophrenia and Parkinson disease (Chen et al., 2003; Colzato et al., 2008; Dauer and Przedborski, 2003; Freed, 1980; Gauggel et al., 2004; Howes and Kapur, 2009; Kegeles et al., 2010; Lozoff, 2011; MacLean et al., 1985; Roberts et al., 2005; Volkow et al., 1999; Vreugdenhil et al., 1997). Thus, for the evidence of the association between EBR and DA (maybe, in particular the striatal DRD2 system) abovementioned, it is possible to assess the developmental relationship between DA and RI by testing EBR (Eckstein et al., 2016). Thus far, recent studies have shown that higher EBR is related to better performance on RI tasks in adults and children. In adult studies, Zhang et al. (2015) found that the higher accuracy of the Nogo-trials in the Go/Nogo task was related to higher EBR; van Bochove et al. (2013) showed that the occurrence of spontaneous blinks in one trial predicted the exertion of greater conflict control on the subsequent trial in the flanker task. However, some reports have been inconsistent. Colzato et al. (2009) tested inhibition through a stop-signal task, and found that better inhibition is related to reduced EBR. Moreover, Zhang et al. (2016) showed that EBR was positively correlated with the N2 amplitude of Nogo-trials, instead of the accuracy of the Nogo-trials in the Go/Nogo task in a small sample. In contrast, in child studies, Lozoff and colleagues found that children aged 10 years with iron-deficiency anemia had decreased DA function and lower EBR, as compared to healthy controls (Algarín et al., 2013), and that the accuracy in the Nogo trials in the Go/Nogo task was lower in children with iron-deficiency anemia than in healthy controls (Lozoff, 2011). As the EBR and performance in the Go/Nogo tasks were not simultaneously examined in the 2 abovementioned studies, it could only be inferred that the higher EBR was related to better RI ability in children. Furthermore, Lackner et al. (2010) explored the correlation between the EBR in children aged 3–5 years and their RI ability; this correlation was found to be positive, but marginally significant. In brief, according to the abovementioned studies, it can be inferred that the central DA activity reflected by EBR might have a similar relationship with RI in children and adults. This inference is consistent with the development of the brain. From the late childhood to the adolescent period, the thickness of the cortex in the brain increases, and synaptic pruning—referring to the selective elimination of unnecessary neuronal connections—occurs (particularly in the prefrontal cortex [PFC]); both these actions could increase the efficiency of individuals in RI tasks (i.e. smaller response time and higher accuracy) (Cragg and Nation, 2008; Luna and Sweeney, 2004; Luna et al., 2015). These 2 changes are reportedly closely related to DA. For example, recent studies have shown that cortex thickness is positively related to striatal DA activity (Casey et al., 2013; Choi et al., 2016; Fernández-Jaén et al., 2016; Morales et al., 2015), and that synaptic pruning is partly modulated by DA activity through the GABAergic neurons (Thompson et al., 2004). As DA activity in the PFC and striatum increases from late childhood to adulthood (Padmanabhan and Luna, 2013; Thompson et al., 2004), the increase in DA activity would promote the refinement of the brain structure, along with the improvement of the efficiency in RI task; therefore it would lead to better RI in individuals with higher DA. Hence, the inference that children and adults have similar relationships in terms of the association between higher EBR and better RI, is reasonable. However, due to the limitations of previous studies, this interference should be more directly and strongly verified in a study wherein children and adult participants are simultaneously recruited and the same paradigm of RI tasks is adopted in the 2 groups. Accordingly, in the present study, we aimed to explore the relationships between DA system activity (measured using EBR) and RI (measured using the Go/Nogo task) in children and adults in 2 experiments. In experiment 1, we primarily sought to validate the relationship between EBR and Go/Nogo task performance observed in the study by Zhang et al. (2015) of a large sample
of young adults. Furthermore, in experiment 2, we compared the relationships between EBR and the performance on the Go/Nogo task in children (aged 10–12 years) and young adults (aged 17–19 years). Based on previous findings, we hypothesized that individuals with higher and lower EBR would exhibit a better and poorer RI ability, respectively, in the late childhood group and young adult group. 2. Experiment 1 2.1. Participants In experiment 1, we enrolled 149 healthy Chinese participants (70 men and 79 women) aged between 18 and 25 years from Southwest University (mean age, 22.56 years; standard deviation (SD), 1.27 years). Among these participants, 61 were involved in a previous study (Zhang et al., 2015) and 88 were new recruits. Prior to the experiment, the participants were asked to complete a questionnaire, which indicated that none of the participants smoked, took psychoactive drugs, had mental disease, had flu symptoms, wore contact lenses, and had coffee or tea or alcoholic beverages before the experiment on the experimental day. 2.2. Ethics statement The experiment was approved by the institutional review board of the Faculty of Psychology of Southwest University. All the participants read and signed an informed consent form prior to participation and received financial compensation (20 Yuan, RMB) for their participation after the experiment. 2.3. Procedure The participants underwent an EBR test and thereafter completed the Go/Nogo task. The examinations were administered through a Dell desktop PC with a 14.1-inch monitor and a display resolution of 1920 × 1080 pixels. The background color of all the stimuli was gray. The participants responded using a keyboard. 2.3.1. EBR test Given that the EBR increases with an increase in the arousal and fatigue levels as well as in the evening (Barbato et al., 2000; De Paova et al., 2009), the participants underwent the EBR tests between 9:00 A.M. and 5:30 P.M.; moreover, the participants were asked to rest until they felt energetic or were given the option to participate in the experiment on another day in case they felt tired before the experiment. During the EBR test, the participants were seated in front of a computer screen, located at a distance of approximately 1 m. They were asked to look at a black cross (4 × 4 cm) displayed at the center of the computer screen, while in a relaxed state. The eye blinks were recorded using the Brain Product System and were analyzed through 4-min eye-open segments by using a Brain Vision Analyzer (Brain Products GmbH, Munich, Germany). A total of 4 Ag–AgCl electrodes were used to record eye movement. A vertical electrooculogram (EOG), which recorded the voltage difference between the 2 electrodes placed above and below the left eye, was used to detect the eye blinks. A horizontal EOG, which recorded the voltage difference between the electrodes placed lateral to the external canthi, was used to measure horizontal eye movement (Colzato et al., 2009). An eye blink was defined as a waveform that includes an upward deflection, followed by a downward deflection that crosses the zero baseline. The time duration between the upward and downward deflection is no more than 400 ms; and the voltage change between them is more than 100 μV (Barbato et al., 2000). Individual EBR values were calculated by dividing the number of eye blinks that occurred during the 4-min measurement into 4 intervals (Colzato et al., 2009; Chermahini & Hommel, 2010).
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
2.3.2. Go/Nogo task This task was adapted from the study of Hershey et al. (2004). Participants were asked to press a response button (F) when non-“X” letters (one of the other 25 letters from the alphabet) appeared and to withhold their response when the letter “X” appeared. The letters were randomly presented in the center of the screen. Eighty percent of the stimuli included non-“X” letters. Each stimulus was presented for 250 ms, with an inter-trial interval of 1000 ms. One practice block, comprising 60 trials, was conducted and 3 experimental blocks, comprising 120 trials each, were conducted. The main dependent variable for inhibition was the response time (RT; in the Go trials), omission error (wherein participants did not respond to Go stimuli that required a response), and commission error (false alarms, wherein participants erroneously responded to a Nogo stimulus that did not require a response). 2.4. Results 2.4.1. EBR results and Go/Nogo task performance The EBR of the participants ranged from 3 to 45 blinks/min (mean, 16.77 blinks/min; SD, 11.12 blinks/min). Because EBR was not significantly related to age (r = 0.04, n.s.), gender (r = 0.03, n.s.), and average sleep time (r = 0.09, n.s.), it was not residualized for age and average sleep time, as in the studies by Dreisbach et al. (2005). Instead, the EBR value was used directly in the analyses, similar to the approach adopted by Colzato et al. (2009), Lackner et al. (2010). The response time (RT) of the Go trials ranged from 296.63 ms to 635.62 ms (mean, 425.17 ms; SD, 67.98 ms). The omission error of the Go trials ranged from 0 to 0.05 (mean, 0.005; SD, 0.09), whereas the commission error of the Nogo trials ranged from 0 to 0.39 (mean, 0.12; SD, 0.88). 2.4.2. Relationships between EBR and Go/Nogo task performance In the following analyses, all the variables were transformed to Zscores. To validate our previous finding that higher EBR was correlated with better inhibition (Zhang et al., 2015), we examined the relationships in 3 groups of regression analyses (SPSS curve fitting procedure). In each group of regression analyses, EBR was used to predict the RT/ omission error of the Go-trials and commission error of the Nogo-trials, respectively. It should be noted that the regression analysis in the present study indicated the correlation between EBR and the Go/Nogo task performance, rather than a simple causal relation. Results showed significant linear correlations between EBR and performance of the Go/ Nogo task. In the first regression analysis group, the data were obtained from the participants of our original study in 2015 (Zhang et al., 2015); we found that EBR could only significantly predict the commission error, rather than the RT and omission error of the Go/Nogo task (for commission error: adjusted R2 = 0.12, B = −0.33, F (1, 59) = 8.95, p b 0.01; for RT: adjusted R2 = 0.01, B = 0.12, F (1, 59) = 0.74, n.s.; for omission error: adjusted R2 = 0.05, B = −0.05, F (1, 59) = 0.15, n.s.). In the second regression analysis group, the data were obtained from the newly recruited participants; and in the third group, the data were obtained from all of participants; we found that EBR could only significantly predict the commission error, instead of the RT and omission error of the Go/Nogo task (for commission error: adjusted R2 = 0.08, B = − 0.28, F (1, 86) = 6.38, p = 0.01; for RT: adjusted R2 = 0.01, B = 0.15, F (1, 86) = 1.83, n.s.; for omission error: adjusted R2 = 0.02, B = −0.17, F (1, 86) = 2.15, n.s.). For both analysis of the original data in the first regression analysis group and the new data in the second regression analysis group indicated that the EBR could significantly predict the commission error, the 2 groups of data were combined. The subsequent third regression analysis included the data of all participants, and showed that EBR could still significantly predict the commission error (adjusted R2 = 0.06, B = −0.19,
55
F [1, 147] = 10.95, p = 0.001), but not the RT and omission error of the Go/Nogo task (Table 1 and Fig. 1A). 2.5. Discussion Experiment 1 indicated that higher EBR was significantly related to lower commission error in the Nogo trials, which validated the findings of our previous study (Zhang et al., 2015). We then focused on whether the relationship between EBR and RI was similar in children and adults. 3. Experiment 2 3.1. Participants In experiment 2, we examined 45 children aged 10–12 years from the primary school of Southwest University (mean age, 11.02 years; SD, 0.86 years) and 37 healthy adults aged 18–19 years from Southwest University (mean age, 18.51 years; SD, 0.57 years); half of the participants were male and half were female. The adult participants were newly recruited for experiment 2. Prior to the experiment, the participants were asked to complete a questionnaire (similar to that in experiment 1) to indicate their health status and living habits. 3.2. Ethics statement and procedure The ethics statement was the same as that in experiment 1. The participants underwent an EBR test and then completed the Go/Nogo task. The two tasks were the same as those in experiment 1. 3.3. Results 3.3.1. EBR results and Go/Nogo task performance Independent-sample t-tests (two-tail) indicated that the EBR in the child group (M = 17.26 blinks/min, SD = 9.26 blinks/min) was not significantly different from that in the adult group (M = 14.52 blinks/min, SD = 8.34 blinks/min; t (80) = 1.4, n.s.), and that the RT (for children: M = 420.57 ms, SD = 88.03 ms; for adults: M = 378.86 ms, SD = 65.12 ms), omission error (for children: M = 0.47, SD = 0.21; for adults: M = 0.11, SD = 0.09), and commission error (for children: M = 0.44, SD = 0.06; for adults: M = 0.05, SD = 0.01) in the child group were all significantly poorer than those in the adult group (RT: t [80] = 2.39, p = 0.02; omission error: t [80] = 3.74, p b 0.01; commission error: t [80] = 9.56, p b 0.01). 3.3.2. Correlation between EBR and Go/Nogo task performance in the child and adult groups All the variables were transformed to Z-scores. To assess whether the relationship between EBR and RI was similar in the child and adult groups, we first examined the relationships by using regression analysis (SPSS curve fitting procedure). We found that only the linear correlations between EBR and the commission error were significant in both the adult and child groups. Hence, 3 linear regression analyses were conducted in each group to present more clear correlations between EBR and RI. Nevertheless, these regression analyses did not indicate a causal relationship. In these 3 regression equations, the EBR was the independent variable, whereas RT, omission error, and commission error were dependent variables, respectively, in the adult and child groups. As shown in Table 1 and Fig. 1B, in both the child and adult groups, EBR could significantly predict the commission error (child group: adjusted R2 = 0.1, B = −0.33, F [1, 43] = 5.88, p = 0.02; adult group: adjusted R2 = 0.09, B = −0.3, F [1, 43] = 4.93, p = 0.03). However, EBR could not significantly predict the other dependent variables. Thus, the findings suggest that, in both the child and adult groups, a higher EBR was significantly related to a lower commission error in the Nogo trials.
56
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
Table 1 The regression analyses in experiment 1 and experiment 2. Experiment
Participant
Independent variables
Dependent variables
R
Adjust R2
B
F (df)
p Value
Experiment 1
Adult
Experiment 2
Adult
Commission errors Omission errors RT Commission errors Omission errors RT Commission errors Omission errors RT
EBR EBR EBR EBR EBR EBR EBR EBR EBR
0.26 b0.01 0.07 0.35 0.04 0.24 0.35 0.26 0.14
0.06 b0.01 b0.01 0.10 b0.01 0.03 0.10 0.04 0.01
−0.19 b0.01 0.08 −0.30 −0.02 0.26 −0.33 −0.16 0.12
10.95 (1, 147) b0.01 (1, 147) 0.69 (1, 147) 4.93 (1, 35) 0.06 (1, 35) 2.09 (1, 35) 5.88 (1, 43) 3.04 (1, 43) 0.86 (1, 43)
b0.01 0.98 0.41 0.03 0.82 0.16 0.02 0.09 0.36
Child
Note. EBR = spontaneous eye blink rates; RT = response time.
Thereafter, the student residuals of the 2 regression equations where EBR in both children and adults significantly predict the commission error, were compared. This comparison indicated whether the linear correlations between EBR and commission error in the child and adult groups differed. An independent t-test showed that the residuals were not significantly different (t (80) = 0.013, n.s.). Hence, children and adults had similar correlations between EBR and RI.
3.4. Discussion Experiment 2 confirmed that the relationships between EBR and RI in the child and adult groups were similar, and that a higher EBR was correlated with a lower commission error. As EBR is an indicator of the central DA level, the present experiment provides strong evidence that children and adults have a similar relationship between DA and RI.
4. General discussion In the present study, experiment 1 validated our previous finding that higher EBR was significantly correlated with better RI ability in young adults; moreover, experiment 2 indicated a similar correlation between EBR and RI in older children and young adults. As EBR is closely related to the central DA function, the findings suggest that the relationships between DA and RI are similar in late childhood and young adulthood. Furthermore, we discuss the development of EBR and RI and the possible mechanisms underlying the similar relationships between EBR and RI in late childhood and young adulthood.
4.2. Development of RI In the present study, a significant decrease in the RT and omission error in the Go trials, and a decrease in the commission error in the Nogo trials was observed in the adult group, relative to the child group. These findings suggest a marked improvement in RI ability from late childhood to young adulthood, consistent with previous behavioral reports (Cragg and Nation, 2008; Jonkman, 2006; Jonkman et al., 2003). These behavioral improvements in RI depend on the developmental changes in the brain. One such change is the alteration of the brain structure. From late childhood to adolescence, the cortex thickness increases and synaptic pruning occurs (especially in the PFC), both of which can lead to increased efficiency among individuals in RI tasks (Cragg and Nation, 2008; Luna and Sweeney, 2004; Luna et al., 2015). Another related brain developmental change involves the refinement of brain activity from late childhood to adulthood (Best et al., 2009). For instance, during this period, the brain activation elicited by the RI task (e.g., the Go/No-go task) transitions from a diffused to focalized form (Durston et al., 2006), and the connectivity of the frontal brain regions during the RI tasks increases (Liston et al., 2006). These developmental changes in the brain can lead to decreases in the RT and omission error in the Go trials, and a decrease in the commission error in the Nogo-trials between adults and older children. Moreover some of these changes are modulated by the DA system, which may be responsible for the positive correlation between EBR and RI in childhood and adulthood, as discussed in the next section.
4.3. Relationship between EBR and RI in both late childhood and young adulthood 4.1. Development of EBR In the present study, the EBRs in the child group and adult group were not significantly different. However, in the study of Cruz et al. (2011), EBR was found to increase during childhood and adolescence, and then stabilize in adulthood. For an assessment of the differences in the studies, we believe that further investigation is needed to clarify the developmental trajectory of EBR. To our knowledge, EBR is closely related to the central DA function (especially the striatal DA), and is sensitive to changes in the DRD1 and DRD2 density (Groman et al., 2014); however, the exact mechanism underlying these relationships remains unclear. In humans, the densities of the D1 and D2 receptors in the PFC peak during the preadolescent stage, decline during adolescence, and stabilize during adulthood (Lidow and Rakic, 1992); however, in the striatum, the decline in the D1 and D2 receptor occurs at an earlier stage—i.e., during infancy and middle childhood, respectively (Jucaite et al., 2010; Seeman et al., 1987). Moreover, the DA activity in both the PFC and striatum increased in adolescents (Padmanabhan and Luna, 2013; Thompson et al., 2004). Thus, the manner in which these changes influence the EBR of individuals during development needs to be further explored.
The most important finding of the present study was that, in both the child and adult groups, a higher EBR was correlated with better RI ability. As EBR is closely related to the central DA level, these findings suggest that a higher central DA level was associated with better RI ability in both late childhood and young adulthood. These findings were consistent with those of previous adult studies, wherein individuals with higher DA function had better behavioral performance on RI tasks, higher inhibition-related brain activation, and a larger inhibition-related ERPs component (Albrecht et al., 2014; Ghahremani et al., 2012; van Bochove et al., 2013; Zhang et al., 2015; Zhang et al., 2016). Furthermore, the present results were also consistent with those of other developmental studies. For instance, in the study by Lackner et al. (2010), a higher EBR was found to be related to a better performance in the Grass/Snow task (a conflict inhibition task that involves both working memory and response inhibition components) in children aged 3–5 years. Moreover, in the study by Algarín et al. (2013), children aged 10 years with iron-deficiency anemia who had decreased DA function and lower EBR, as compared to healthy controls (Lozoff, 2011), were found to have a lower accuracy in the Nogo trials in the Go/Nogo task. Although these studies did not simultaneously include child and
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
57
Fig. 1. Scatterplots of the correlations between EBR and Go/Nogo task performance in experiment 1 and experiment 2. A. Experiment 1: correlation between the EBR and RT in the Go trials, omission error in the Go trials, or commission error in the Nogo trials in the child and adult groups, respectively. B. Experiment 2: correlation between the EBR and RT in the Go trials, omission error in the Go trials, or commission error in the Nogo trials in the child and adult groups, respectively. All the values of X and Y axes were Z-scores. The correlations presented in the scatterplots in the dotted square were significant.
adult participants, they still indicated similar relationships between the EBR and RI in individuals during both late childhood and young adulthood, consistent with the present study. With regard to the finding that older children and adults had similar relationships between EBR and RI, a possible explanation could be as follows. The developmental improvement in the RI from late childhood to adulthood is more efficient (i.e. smaller response time and higher accuracy) than acquiring new abilities. This behavioral improvement is supported by the changes in the brain structure (Cragg and Nation, 2008; Luna and Sweeney, 2004; Luna et al., 2015). For example, the cortex
thickness increases and synaptic pruning occurs (especially in the PFC), both of which have been suggested to be modulated by the DA system. In fact, recent studies showed that the cortex thickness is positively related to the striatal DA activity (Casey et al., 2013; Choi et al., 2016; Fernández-Jaén et al., 2016; Morales et al., 2015), whereas synaptic pruning is partly modulated by DA activity through the GABAergic neurons (Thompson et al., 2004). Hence, as the DA activity in the brain increases from late childhood to adulthood (Padmanabhan and Luna, 2013; Thompson et al., 2004), the increasing DA activity would promote the refinement of the brain structure and the improvement
58
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
of efficiency in the RI task, which would consequently lead to better RI among individuals with higher DA activity. As EBR reflects the central DA activity (particularly striatal DA activity), the present study showed that higher EBR is related to better RI ability in both the child and adult groups. The abovementioned relationships were based on the behavioral responses of the Go/Nogo task. Nevertheless, care must be taken when generalizing these results to the relationship between EBR and the neural response. Adult studies have suggested that DA may influence the processing of inhibition through the frontal-striatal neural circuitry (Albrecht et al., 2014; Ghahremani et al., 2012). Higher striatal DA receptor availability and higher frontal-cortical DA release were positively related to the inhibition-related fMRI activation of the frontal-striatal neural circuitry and behavioral performance in the inhibition task, respectively (Albrecht et al., 2014; Ghahremani et al., 2012). Throughout development, from late childhood to adulthood, the frontal-striatal neural circuitry plays an important role in the maturation of RI, and it markedly changes in terms of volume of activation and location of activation (Mehnert et al., 2013). In contrast to adults, children showed greater activation, but reduced recruitment, of the frontal-striatal neural circuitry in inhibition tasks; however, children have less focalized and more bilaterally extended activation of the frontal-striatal neural circuitry, as compared to adults (Mehnert et al., 2013). Hence, the differences in the inhibitioninduced volume and location of the activation in the frontal-striatal neural circuitry between older children and adults may lead to variable relationships between EBR and the inhibition-related brain activation in older children. However, very few studies have focused on this issue thus far, and further investigation is needed. 5. Conclusion and limitations In the present study, we found that higher EBR was related to a lower commission error in the Nogo trials in both child and adult groups. As EBR is closely related to central DA function, it was suggested that both children and adults with higher DA function had better RI ability; in fact, there were similar relationships between RI ability and DA function in late childhood and young adulthood. However, there were still some limitations. The present study involved only one condition of the Go/Nogo task. Hence, it is unclear whether the relationships between EBR and RI in the child and adult groups would change if the task difficulty and stimuli modality were altered. Therefore, care must be taken when generalizing the present results to other conditions of the Go/Nogo task and also to other RI tasks. Moreover, as mentioned in the discussion, the present results were based on the behavioral responses. Hence, it is unclear whether the relationship between EBR and RI in children and adults would be similar, and this topic should be further explored in future studies. Acknowledgements This work was supported by the National Nature Science Foundation of China (31300857), the National Social Science Foundation of China (16CSH050) and The Fundamental Research Funds for the Central Universities (ZYGX2015J167). Reference Aarts, H., Bijleveld, E., Custers, R., Dogge, M., Deelder, M., Schutter, D., van Haren, N.E.M., 2012. Positive priming and intentional binding: eye-blink rate predicts reward information effects on the sense of agency. Soc. Neurosci. 7 (1), 105–112. Acheson, A., Tagamets, M.A., Winkler, A., Rowland, L.M., Mathias, C.W., Wright, S.N., ... Dougherty, D.M., 2015. Striatal activity and reduced white matter increase frontal activity in youths with family histories of alcohol and other substance-use disorders performing a go/no-go task. Brain and Behavior 5 (7). Albrecht, D.S., Kareken, D.A., Christian, B.T., Dzemidzic, M., Yoder, K.K., 2014. Cortical dopamine release during a behavioral response inhibition task. Synapse 68 (6), 266–274.
Algarín, C., Nelson, C.A., Peirano, P., Westerlund, A., Reyes, S., Lozoff, B., 2013. Iron-deficiency anemia in infancy and poorer cognitive inhibitory control at age 10 years. Dev. Med. Child Neurol. 55 (5), 453–458. Bacher, L.F., 2014. Development and manipulation of spontaneous eye blinking in the first year: relationships to context and positive affect. Dev. Psychobiol. 56, 783–796. Barbato, G., Ficca, G., Muscettola, G., Fichele, M., Beatrice, M., Rinaldi, F., 2000. Diurnal variation in spontaneous eye-blink rate. Psychiatry Res. 93 (2), 145–151. Barkley, R.A., 1997. Behavioral inhibition, sustained attention, and executive functions: constructing a unifying theory of ADHD. Psychol. Bull. 121, 65–94. Best, J.R., Miller, P.H., Jones, L.L., 2009. Executive functions after age 5: changes and correlates. Dev. Rev. 29 (3), 180–200. Blin, O., Masson, G., Azulay, J.P., Fondarai, J., Serratrice, G., 1990. Apomorphine-induced blinking and yawning in healthy volunteers. Br. J. Clin. Pharmacol. 30 (5), 769–773. Bodfish, J.W., Powell, S.B., Golden, R.N., Lewis, M.H., 1995. Blink rate as an index of dopamine function in adults with mental retardation and repetitive behavior disorders. Am. J. Ment. Retard. 99 (4), 335–344. Casey, K.F., Cherkasova, M.V., Larcher, K., Evans, A.C., Baker, G.B., Dagher, A., ... Leyton, M., 2013. Individual differences in frontal cortical thickness correlate with the D-amphetamine-induced striatal dopamine response in humans. J. Neurosci. 33 (38), 15285–15294. Chen, W.H., Chiang, M.C., Hsu, M.C., Liu, J.S., 2003. The validity of eye blink rate in Chinese adults for the diagnosis of Parkinson's disease. Clin. Neurol. Neurosurg. 105, 90–92. Chermahini, S.A., Hommel, B., 2010. The (b) link between creativity and dopamine: spontaneous eye blink rates predict and dissociate divergent and convergent thinking. Cognition 115 (3), 458–465. Choi, H., Cheon, G.J., Kim, H.J., Choi, S.H., Kim, Y.I., Kang, K.W., ... Lee, D.S., 2016. Gray matter correlates of dopaminergic degeneration in Parkinson's disease: a hybrid PET/MR study using 18F-FP-CIT. Hum. Brain Mapp. 37, 1710–1721. Colzato, L.S., van den Wildenberg, W.P., Hommel, B., 2008. Reduced spontaneous eye blink rates in recreational cocaine users: evidence for dopaminergic hypoactivity. PLoS One 3 (10), e3461. Colzato, L.S., van den Wildenberg, W.P., van Wouwe, N.C., Pannebakker, M.M., Hommel, B., 2009. Dopamine and inhibitory action control: evidence from spontaneous eye blink rates. Exp. Brain Res. 196 (3), 467–474. Cooper, C.J., 1973. Anatomical and physiological mechanisms of arousal, with special reference to the effects of exercise. Ergonomics 16 (5), 601–609. Cragg, L., Nation, K., 2008. Go or no-go? Developmental improvements in the efficiency of response inhibition in mid-childhood. Dev. Sci. 11, 819–827. Cruz, A.A., Garcia, D.M., Pinto, C.T., Cechetti, S.P., 2011. Spontaneous eyeblink activity. The Ocular Surface 9 (1), 29–41. Dauer, W., Przedborski, S., 2003. Parkinson's disease: mechanisms and models. Neuron 39, 889–909. De Paova, V., Barbato, G., Conte, F., Ficca, G., 2009. Diurnal variation of spontaneous eye blink rate in the elderly and its relationships with sleepiness and arousal. Neurosci. Lett. 463, 40–43. Dreisbach, G., Müller, J., Goschke, T., Strobel, A., Schulze, K., ... Brocke, B., 2005. Dopamine and cognitive control: the influence of spontaneous eyeblink rate and dopamine gene polymorphisms on perseveration and distractibility. Behav. Neurosci. 119 (2), 483. 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), 1–8. Eckstein, M.K., Guerra-Carrillo, B., Singley, A.T.M., Bunge, S.A., 2016. Beyond eye gaze: what else can eyetracking reveal about cognition and cognitive development? Developmental Cognitive Neuroscience 19(C), 190–199. Fernández-Jaén, A., Albert, J., Fernández-Mayoralas, D.M., López-Martín, S., Fernández-Perrone, A.L., de la Peña, M.J., ... Arribas, S.L., 2016. Cingulate cortical thickness and dopamine transporter (DAT1) genotype in children and adolescents with ADHD. J. Atten. Disord. 1087054716647483. Freed, W., 1980. Eye-blink rates and platelet monoamine oxidase activity in chronic schizophrenic patients. Biol. Psychiatry 15, 329–332. Gauggel, S., Rieger, M., Feghoff, T.A., 2004. Inhibition of ongoing responses in patients with Parkinson's disease. J. Neurol. Neurosurg. Psychiatry 75 (4), 539–544. Ghahremani, D.G., Lee, B., Robertson, C.L., Tabibnia, G., Morgan, A.T., De Shetler, N., ... London, E.D., 2012. Striatal dopamine D2/D3 receptors mediate response inhibition and related activity in frontostriatal neural circuitry in humans. J. Neurosci. 32 (21), 7316–7324. Groman, S.M., James, A.S., Seu, E., Tran, S., Clark, T.A., ... Jentsch, J.D., 2014. In the blink of an eye: relating positive-feedback sensitivity to striatal dopamine D2-like receptors through blink rate. J. Neurosci. 34, 14443–14454. Hershey, T., Black, K.J., Hartlein, J., Braver, T.S., Barch, D.M., Carl, J.L., Perlmutter, J.S., 2004. Dopaminergic modulation of response inhibition: an fMRI study. Cogn. Brain Res. 20 (3), 438–448. Howes, O.D., Kapur, S., 2009. The dopamine hypoth-esis of schizophrenia: version III—the final common pathway. Schizophr. Bull. 6, 1–4. Jongkees, B.J., Colzato, L.S., 2016. Spontaneous eye blink rate as predictor of dopamine-related cognitive function-a review. Neurosci. Biobehav. Rev. 71, 58–82. Jonkman, L.M., 2006. The development of preparation, conflict monitoring and inhibition from early childhood to young adulthood: a go/nogo ERP study. Brain Res. 1097, 181–193. Jonkman, L.M., Lansbergen, M., Stauder, J.E.A., 2003. Developmental differences in behavioral and event-related brain responses associated with response preparation and inhibition in a go/nogo task. Psychophysiology 40, 752–761. Jucaite, A., Forssberg, H., Karlsson, P., Halldin, C., Farde, L., 2010. Age-related reduction in dopamine D1 receptors in the human brain: from late childhood to adulthood, a positron emission tomography study. Neuroscience 167 (1), 104–110.
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59 Jutkiewicz, E.M., Bergman, J., 2004. Effects of dopamine D1 ligands on eye blinking in monkeys: efficacy, antagonism, and D1/D2 interactions. J. Pharmacol. Exp. Ther. 311 (3), 1008–1015. Karson, C.N., 1983. Spontaneous eye-blink rates and dopaminergic systems. Brain 106 (3), 643–653. Kegeles, L.S., Abi-Dargham, A., Frankle, G., Gil, R., Cooper, T., et al., 2010. Increased synaptic dopamine function in associative regions of the striatum in schizophrenia. Arch. Gen. Psychiatry 3, 231–239. Kleven, M.S., Koek, W., 1996. Differential effects of direct and indirect dopamine agonists on eye blink rate in cynomolgus monkeys. The Journal of Pharmacology 279 (3), 1211–1219. Lackner, C.L., Bowman, L.C., Sabbagh, M.A., 2010. Dopaminergic functioning and preschoolers' theory of mind. Neuropsychologia 48 (6), 1767–1774. Lawrence, M.S., Redmond, D.E., 1991. MPTP lesions and dopaminergic drugs alter eye blink rate in African green monkeys. Pharmacol. Biochem. Behav. 38 (4), 869–874. Lidow, M.S., Rakic, P., 1992. Scheduling of monoaminergic neurotransmitter receptor expression in the primate neocortex during postnatal development. Cereb. Cortex 2 (5), 401–416. Liston, C., Watts, R., Tottenham, N., Davidson, M.C., Niogi, S., Ulug, A.M., Casey, B.J., 2006. Frontostriatal microstructure modulates efficient recruitment of cognitive control. Cereb. Cortex 16 (4), 553–560. Lozoff, B., 2011. Early iron deficiency has brain and behavior effects consistent with dopaminergic dysfunction. J. Nutr. 141 (4), 740S–746S. Luna, B., Sweeney, J.A., 2004. The emergence of collaborative brain function: FMRI studies of the development of response inhibition. Ann. N. Y. Acad. Sci. 1021 (1), 296–309. Luna, B., Marek, S., Larsen, B., Tervo-Clemmens, B., Chahal, R., 2015. An integrative model of the maturation of cognitive control. Annu. Rev. Neurosci. 38, 151–170. MacLean, W.E., Lewis, M.H., Bryson-Brockmann, W.A., Ellis, D.N., Arendt, R.E., Baumeister, A.A., 1985. Blink rate and stereotyped behavior: evidence for dopamine involvement? Biol. Psychiatry 20, 1321–1325. Mehnert, J., Akhrif, A., Telkemeyer, S., Rossi, S., Schmitz, C.H., Steinbrink, J., ... Neufang, S., 2013. Developmental changes in brain activation and functional connectivity during response inhibition in the early childhood brain. Brain Dev. 35 (10), 894–904. Morales, A.M., Kohno, M., Robertson, C.L., Dean, A.C., Mandelkern, M.A., London, E.D., 2015. Gray-matter volume, midbrain dopamine D2/D3 receptors and drug craving in methamphetamine users. Mol. Psychiatry 20 (6), 764–771.
59
Padmanabhan, A., Luna, B., 2013. Developmental imaging genetics: linking dopamine function to adolescent behavior. Brain Cogn. 89, 27–38. Roberts, J.E., Symons, F.J., Johnson, A.M., Hatton, D.D., Boccia, M.L., 2005. Blink rate in boys with fragile X syndrome: preliminary evidence for altered dopamine function. J. Intellect. Disabil. Res. 49 (9), 647–656. Rubia, K., Russell, T., Overmeyer, S., Brammer, M.J., Bullmore, E.T., Sharma, T., ... Taloy, E., 2001. Mapping motor inhibition: conjunctive brain activations across different versions of go/no-go and stop tasks. NeuroImage 13, 250–261. Seeman, P., Bzowej, N.H., Guan, H.C., Bergeron, C., Becker, L.E., Reynolds, G.P., ... Tourtellotte, W.W., 1987. Human brain dopamine receptors in children and aging adults. Synapse 1 (5), 399–404. Shukla, D., 1985. Blink rate as clinical indicator. Neurology 35 (2), 286. Slaghter, H.A., Georgopoulou, K., Frank, M.J., 2015. Spontaneous eye blink rate predicts learning from negative, but not positive, outcomes. Neuropsychologia 71, 126–132. Taylor, J.R., Elsworth, J.D., Lawrence, M.S., Sladek Jr, J.R., Roth, R.H., Redmond Jr, D.E., 1999. Spontaneous blink rates correlate with dopamine levels in the caudate nucleus of MPTP-treated monkeys. Exp. Neurol. 158 (1), 214–220. Thompson, J.L., Pogue-Geile, M.F., Grace, A.A., 2004. Developmental pathology, dopamine, and stress: a model for the age of onset of schizophrenia symptoms. Schizophr. Bull. 30 (4), 875–900. van Bochove, M.E., Van der Haegen, L., Notebaert, W., Verguts, T., 2013. Blinking predicts enhanced cognitive control. Cognitive, Affective, & Behavioral Neuroscience 13 (2), 346–354. Volkow, N.D., Fowler, J.S., Wang, G.J., 1999. Imaging studies on the role of dopamine in cocaine reinforcement and addiction in humans. J. Psychopharmacol. 13, 337–345. Vreugdenhil, H., Brouwers, P., Wolters, P., Bakker, D., Moss, H., 1997. Spontaneous eye blinking, a measure of dopaminergic function, in children with acquired immunodeficiency syndrome. Arch. Pediatr. Adolesc. Med. 151 (10), 1025–1032. Zhang, T., Di, M., Wang, C., Tan, F., Jiang, Y., Zheng, L., ... Li, H., 2015. Dopamine and executive function: increased spontaneous eye blink rates correlate with better setshifting and inhibition, but poorer updating. Int. J. Psychophysiol. 96 (3), 155–161. Zhang, T., Wang, C., Tan, F., Mu, D., Zheng, L., 2016. Different relationships between central dopamine system and sub-processes of inhibition: spontaneous eye blink rate relates with N2 but not P3 in a go/nogo task. Brain Cogn. 105, 95–103.
Contents lists available at ScienceDirect
International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho
The developmental relationship between central dopaminergic level and response inhibition from late childhood to young adulthood Ting Zhang a,⁎,1, Qin Zhang b,1, Cuicui Wang c, Antao Chen a,⁎ a b c
School of Psychology, Southwest University, Chongqing, China School of Political Science and Public Administration, University of Electronic Science and Technology of China, China State Key Lab of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
a r t i c l e
i n f o
Article history: Received 20 September 2016 Received in revised form 13 February 2017 Accepted 15 February 2017 Available online 20 February 2017 Keywords: Dopamine Spontaneous eye blink rate Response inhibition Late childhood Young adulthood
a b s t r a c t Dopamine (DA) is known to modulate response inhibition (RI). In contrast to the abundant adult studies, only few developmental studies have focused on this topic. Moreover, the mechanism underlying the modulation of RI by the DA system from childhood to adulthood remains unclear. We aimed to assess whether the relationship between DA and RI during late childhood and young adulthood is similar. Accordingly, DA function was measured using the spontaneous eye blink rate (EBR), whereas RI ability was tested using the Go/Nogo task. Experiment 1 included 149 adults (age range, 18–25 years) who completed the EBR test and the Go/Nogo task; the results showed that higher EBR was associated with lower commission error in the Nogo trials. Experiment 2 included 45 children (age range, 10–12 years) and 37 adults (age range, 18–19 years) who completed the EBR test and Go/Nogo tasks (similar to experiment 1); in both the child and adult groups, higher EBR was related to better RI ability. As EBR is closely related to central DA function, these findings suggest that DA plays a similar role in the processing of RI in late childhood and young adulthood. © 2017 Elsevier B.V. All rights reserved.
1. Introduction Response inhibition (RI) refers to the inhibition of prepotent responses or events (Barkley, 1997), and involves a choice between action and non-action (Rubia et al., 2001). Dopamine (DA) is an important neurotransmitter in the brain that modulates RI processing (Padmanabhan and Luna, 2013). Studies have shown that individuals with higher DA function have better behavioral performance on RI tasks, higher inhibition-related brain activation, and a larger inhibition-related event-related potentials (ERPs) component, all of which reflect better RI ability (Albrecht et al., 2014; Ghahremani et al., 2012; van Bochove et al., 2013; Zhang et al., 2015; Zhang et al., 2016). With regard to the underlying mechanism, some studies have proposed that DA modulates the processing of RI through the frontal-striatal neural circuitry (Acheson et al., 2015; Albrecht et al., 2014; Ghahremani et al., 2012). For example, in the frontal-striatal motor loop involved in the Go/Nogo task,2 the supplementary motor area (SMA) sends excitatory glutamatergic input through the dorsal striatum to the ventrolateral ⁎ Corresponding authors at: School of Psychology, Southwest University, Chongqing 400715, China. E-mail addresses: [email protected] (T. Zhang), [email protected] (A. Chen). 1 Co-first authors: Ting Zhang, Qin Zhang. 2 The Go/Nogo task is a classical RI task that requires a response to be made when a frequently occurring “Go” is presented, but withheld when a less frequent “Nogo” stimulus is presented (Cragg and Nation, 2008).
http://dx.doi.org/10.1016/j.ijpsycho.2017.02.009 0167-8760/© 2017 Elsevier B.V. All rights reserved.
thalamus, which projects back to the SMA. In this loop, the dorsal striatum would have either excitatory (dopamine D1 receptor, DRD1) or inhibitory (dopamine D2 receptor, DRD2) influences on striatal firing, which mediates SMA activity (Acheson et al., 2015). However, in contrast to the amount of adult studies, far fewer studies have focused on the relationship between DA and RI in children and adolescents; moreover, the invasive methods generally used in adult populations (positron emission tomography [PET] or medication) typically cannot be used to study developing populations (Padmanabhan and Luna, 2013). Nevertheless, the fact that the spontaneous eye blink rate (EBR) has been non-invasively confirmed to indirectly reflect the central DA activity (Bodfish et al., 1995; Karson, 1983; Shukla, 1985; Eckstein et al., 2016; Jongkees and Colzato, 2016; Slaghter et al., 2015), which begins during the fetal period, increases rapidly during childhood and adolescence, and then stabilizes during adulthood (Bacher, 2014; Cruz et al., 2011). Previous pharmacological studies showed that EBR could be altered by both DRD1 and DRD2 agonists/antagonists (Blin et al., 1990; Groman et al., 2014; Jutkiewicz and Bergman, 2004; Kleven and Koek, 1996; Lawrence and Redmond, 1991; Taylor et al., 1999); however one recent PET study showed that EBR was more strongly related to the DRD2 system (Groman et al., 2014). Besides, the EBR is also associated with dopamine D4 7-repeat allele (Dreisbach et al., 2005) and behavioral interventions (rewards and acute exercise) could also alter the EBR (Aarts et al., 2012; Cooper, 1973). In contrast to healthy controls, DA
54
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
dysfunction could cause increased or decreased EBR in children with immunodeficiency syndrome, fragile X syndrome, ADHD, and iron deficiency anemia, as well as in adults with schizophrenia and Parkinson disease (Chen et al., 2003; Colzato et al., 2008; Dauer and Przedborski, 2003; Freed, 1980; Gauggel et al., 2004; Howes and Kapur, 2009; Kegeles et al., 2010; Lozoff, 2011; MacLean et al., 1985; Roberts et al., 2005; Volkow et al., 1999; Vreugdenhil et al., 1997). Thus, for the evidence of the association between EBR and DA (maybe, in particular the striatal DRD2 system) abovementioned, it is possible to assess the developmental relationship between DA and RI by testing EBR (Eckstein et al., 2016). Thus far, recent studies have shown that higher EBR is related to better performance on RI tasks in adults and children. In adult studies, Zhang et al. (2015) found that the higher accuracy of the Nogo-trials in the Go/Nogo task was related to higher EBR; van Bochove et al. (2013) showed that the occurrence of spontaneous blinks in one trial predicted the exertion of greater conflict control on the subsequent trial in the flanker task. However, some reports have been inconsistent. Colzato et al. (2009) tested inhibition through a stop-signal task, and found that better inhibition is related to reduced EBR. Moreover, Zhang et al. (2016) showed that EBR was positively correlated with the N2 amplitude of Nogo-trials, instead of the accuracy of the Nogo-trials in the Go/Nogo task in a small sample. In contrast, in child studies, Lozoff and colleagues found that children aged 10 years with iron-deficiency anemia had decreased DA function and lower EBR, as compared to healthy controls (Algarín et al., 2013), and that the accuracy in the Nogo trials in the Go/Nogo task was lower in children with iron-deficiency anemia than in healthy controls (Lozoff, 2011). As the EBR and performance in the Go/Nogo tasks were not simultaneously examined in the 2 abovementioned studies, it could only be inferred that the higher EBR was related to better RI ability in children. Furthermore, Lackner et al. (2010) explored the correlation between the EBR in children aged 3–5 years and their RI ability; this correlation was found to be positive, but marginally significant. In brief, according to the abovementioned studies, it can be inferred that the central DA activity reflected by EBR might have a similar relationship with RI in children and adults. This inference is consistent with the development of the brain. From the late childhood to the adolescent period, the thickness of the cortex in the brain increases, and synaptic pruning—referring to the selective elimination of unnecessary neuronal connections—occurs (particularly in the prefrontal cortex [PFC]); both these actions could increase the efficiency of individuals in RI tasks (i.e. smaller response time and higher accuracy) (Cragg and Nation, 2008; Luna and Sweeney, 2004; Luna et al., 2015). These 2 changes are reportedly closely related to DA. For example, recent studies have shown that cortex thickness is positively related to striatal DA activity (Casey et al., 2013; Choi et al., 2016; Fernández-Jaén et al., 2016; Morales et al., 2015), and that synaptic pruning is partly modulated by DA activity through the GABAergic neurons (Thompson et al., 2004). As DA activity in the PFC and striatum increases from late childhood to adulthood (Padmanabhan and Luna, 2013; Thompson et al., 2004), the increase in DA activity would promote the refinement of the brain structure, along with the improvement of the efficiency in RI task; therefore it would lead to better RI in individuals with higher DA. Hence, the inference that children and adults have similar relationships in terms of the association between higher EBR and better RI, is reasonable. However, due to the limitations of previous studies, this interference should be more directly and strongly verified in a study wherein children and adult participants are simultaneously recruited and the same paradigm of RI tasks is adopted in the 2 groups. Accordingly, in the present study, we aimed to explore the relationships between DA system activity (measured using EBR) and RI (measured using the Go/Nogo task) in children and adults in 2 experiments. In experiment 1, we primarily sought to validate the relationship between EBR and Go/Nogo task performance observed in the study by Zhang et al. (2015) of a large sample
of young adults. Furthermore, in experiment 2, we compared the relationships between EBR and the performance on the Go/Nogo task in children (aged 10–12 years) and young adults (aged 17–19 years). Based on previous findings, we hypothesized that individuals with higher and lower EBR would exhibit a better and poorer RI ability, respectively, in the late childhood group and young adult group. 2. Experiment 1 2.1. Participants In experiment 1, we enrolled 149 healthy Chinese participants (70 men and 79 women) aged between 18 and 25 years from Southwest University (mean age, 22.56 years; standard deviation (SD), 1.27 years). Among these participants, 61 were involved in a previous study (Zhang et al., 2015) and 88 were new recruits. Prior to the experiment, the participants were asked to complete a questionnaire, which indicated that none of the participants smoked, took psychoactive drugs, had mental disease, had flu symptoms, wore contact lenses, and had coffee or tea or alcoholic beverages before the experiment on the experimental day. 2.2. Ethics statement The experiment was approved by the institutional review board of the Faculty of Psychology of Southwest University. All the participants read and signed an informed consent form prior to participation and received financial compensation (20 Yuan, RMB) for their participation after the experiment. 2.3. Procedure The participants underwent an EBR test and thereafter completed the Go/Nogo task. The examinations were administered through a Dell desktop PC with a 14.1-inch monitor and a display resolution of 1920 × 1080 pixels. The background color of all the stimuli was gray. The participants responded using a keyboard. 2.3.1. EBR test Given that the EBR increases with an increase in the arousal and fatigue levels as well as in the evening (Barbato et al., 2000; De Paova et al., 2009), the participants underwent the EBR tests between 9:00 A.M. and 5:30 P.M.; moreover, the participants were asked to rest until they felt energetic or were given the option to participate in the experiment on another day in case they felt tired before the experiment. During the EBR test, the participants were seated in front of a computer screen, located at a distance of approximately 1 m. They were asked to look at a black cross (4 × 4 cm) displayed at the center of the computer screen, while in a relaxed state. The eye blinks were recorded using the Brain Product System and were analyzed through 4-min eye-open segments by using a Brain Vision Analyzer (Brain Products GmbH, Munich, Germany). A total of 4 Ag–AgCl electrodes were used to record eye movement. A vertical electrooculogram (EOG), which recorded the voltage difference between the 2 electrodes placed above and below the left eye, was used to detect the eye blinks. A horizontal EOG, which recorded the voltage difference between the electrodes placed lateral to the external canthi, was used to measure horizontal eye movement (Colzato et al., 2009). An eye blink was defined as a waveform that includes an upward deflection, followed by a downward deflection that crosses the zero baseline. The time duration between the upward and downward deflection is no more than 400 ms; and the voltage change between them is more than 100 μV (Barbato et al., 2000). Individual EBR values were calculated by dividing the number of eye blinks that occurred during the 4-min measurement into 4 intervals (Colzato et al., 2009; Chermahini & Hommel, 2010).
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
2.3.2. Go/Nogo task This task was adapted from the study of Hershey et al. (2004). Participants were asked to press a response button (F) when non-“X” letters (one of the other 25 letters from the alphabet) appeared and to withhold their response when the letter “X” appeared. The letters were randomly presented in the center of the screen. Eighty percent of the stimuli included non-“X” letters. Each stimulus was presented for 250 ms, with an inter-trial interval of 1000 ms. One practice block, comprising 60 trials, was conducted and 3 experimental blocks, comprising 120 trials each, were conducted. The main dependent variable for inhibition was the response time (RT; in the Go trials), omission error (wherein participants did not respond to Go stimuli that required a response), and commission error (false alarms, wherein participants erroneously responded to a Nogo stimulus that did not require a response). 2.4. Results 2.4.1. EBR results and Go/Nogo task performance The EBR of the participants ranged from 3 to 45 blinks/min (mean, 16.77 blinks/min; SD, 11.12 blinks/min). Because EBR was not significantly related to age (r = 0.04, n.s.), gender (r = 0.03, n.s.), and average sleep time (r = 0.09, n.s.), it was not residualized for age and average sleep time, as in the studies by Dreisbach et al. (2005). Instead, the EBR value was used directly in the analyses, similar to the approach adopted by Colzato et al. (2009), Lackner et al. (2010). The response time (RT) of the Go trials ranged from 296.63 ms to 635.62 ms (mean, 425.17 ms; SD, 67.98 ms). The omission error of the Go trials ranged from 0 to 0.05 (mean, 0.005; SD, 0.09), whereas the commission error of the Nogo trials ranged from 0 to 0.39 (mean, 0.12; SD, 0.88). 2.4.2. Relationships between EBR and Go/Nogo task performance In the following analyses, all the variables were transformed to Zscores. To validate our previous finding that higher EBR was correlated with better inhibition (Zhang et al., 2015), we examined the relationships in 3 groups of regression analyses (SPSS curve fitting procedure). In each group of regression analyses, EBR was used to predict the RT/ omission error of the Go-trials and commission error of the Nogo-trials, respectively. It should be noted that the regression analysis in the present study indicated the correlation between EBR and the Go/Nogo task performance, rather than a simple causal relation. Results showed significant linear correlations between EBR and performance of the Go/ Nogo task. In the first regression analysis group, the data were obtained from the participants of our original study in 2015 (Zhang et al., 2015); we found that EBR could only significantly predict the commission error, rather than the RT and omission error of the Go/Nogo task (for commission error: adjusted R2 = 0.12, B = −0.33, F (1, 59) = 8.95, p b 0.01; for RT: adjusted R2 = 0.01, B = 0.12, F (1, 59) = 0.74, n.s.; for omission error: adjusted R2 = 0.05, B = −0.05, F (1, 59) = 0.15, n.s.). In the second regression analysis group, the data were obtained from the newly recruited participants; and in the third group, the data were obtained from all of participants; we found that EBR could only significantly predict the commission error, instead of the RT and omission error of the Go/Nogo task (for commission error: adjusted R2 = 0.08, B = − 0.28, F (1, 86) = 6.38, p = 0.01; for RT: adjusted R2 = 0.01, B = 0.15, F (1, 86) = 1.83, n.s.; for omission error: adjusted R2 = 0.02, B = −0.17, F (1, 86) = 2.15, n.s.). For both analysis of the original data in the first regression analysis group and the new data in the second regression analysis group indicated that the EBR could significantly predict the commission error, the 2 groups of data were combined. The subsequent third regression analysis included the data of all participants, and showed that EBR could still significantly predict the commission error (adjusted R2 = 0.06, B = −0.19,
55
F [1, 147] = 10.95, p = 0.001), but not the RT and omission error of the Go/Nogo task (Table 1 and Fig. 1A). 2.5. Discussion Experiment 1 indicated that higher EBR was significantly related to lower commission error in the Nogo trials, which validated the findings of our previous study (Zhang et al., 2015). We then focused on whether the relationship between EBR and RI was similar in children and adults. 3. Experiment 2 3.1. Participants In experiment 2, we examined 45 children aged 10–12 years from the primary school of Southwest University (mean age, 11.02 years; SD, 0.86 years) and 37 healthy adults aged 18–19 years from Southwest University (mean age, 18.51 years; SD, 0.57 years); half of the participants were male and half were female. The adult participants were newly recruited for experiment 2. Prior to the experiment, the participants were asked to complete a questionnaire (similar to that in experiment 1) to indicate their health status and living habits. 3.2. Ethics statement and procedure The ethics statement was the same as that in experiment 1. The participants underwent an EBR test and then completed the Go/Nogo task. The two tasks were the same as those in experiment 1. 3.3. Results 3.3.1. EBR results and Go/Nogo task performance Independent-sample t-tests (two-tail) indicated that the EBR in the child group (M = 17.26 blinks/min, SD = 9.26 blinks/min) was not significantly different from that in the adult group (M = 14.52 blinks/min, SD = 8.34 blinks/min; t (80) = 1.4, n.s.), and that the RT (for children: M = 420.57 ms, SD = 88.03 ms; for adults: M = 378.86 ms, SD = 65.12 ms), omission error (for children: M = 0.47, SD = 0.21; for adults: M = 0.11, SD = 0.09), and commission error (for children: M = 0.44, SD = 0.06; for adults: M = 0.05, SD = 0.01) in the child group were all significantly poorer than those in the adult group (RT: t [80] = 2.39, p = 0.02; omission error: t [80] = 3.74, p b 0.01; commission error: t [80] = 9.56, p b 0.01). 3.3.2. Correlation between EBR and Go/Nogo task performance in the child and adult groups All the variables were transformed to Z-scores. To assess whether the relationship between EBR and RI was similar in the child and adult groups, we first examined the relationships by using regression analysis (SPSS curve fitting procedure). We found that only the linear correlations between EBR and the commission error were significant in both the adult and child groups. Hence, 3 linear regression analyses were conducted in each group to present more clear correlations between EBR and RI. Nevertheless, these regression analyses did not indicate a causal relationship. In these 3 regression equations, the EBR was the independent variable, whereas RT, omission error, and commission error were dependent variables, respectively, in the adult and child groups. As shown in Table 1 and Fig. 1B, in both the child and adult groups, EBR could significantly predict the commission error (child group: adjusted R2 = 0.1, B = −0.33, F [1, 43] = 5.88, p = 0.02; adult group: adjusted R2 = 0.09, B = −0.3, F [1, 43] = 4.93, p = 0.03). However, EBR could not significantly predict the other dependent variables. Thus, the findings suggest that, in both the child and adult groups, a higher EBR was significantly related to a lower commission error in the Nogo trials.
56
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
Table 1 The regression analyses in experiment 1 and experiment 2. Experiment
Participant
Independent variables
Dependent variables
R
Adjust R2
B
F (df)
p Value
Experiment 1
Adult
Experiment 2
Adult
Commission errors Omission errors RT Commission errors Omission errors RT Commission errors Omission errors RT
EBR EBR EBR EBR EBR EBR EBR EBR EBR
0.26 b0.01 0.07 0.35 0.04 0.24 0.35 0.26 0.14
0.06 b0.01 b0.01 0.10 b0.01 0.03 0.10 0.04 0.01
−0.19 b0.01 0.08 −0.30 −0.02 0.26 −0.33 −0.16 0.12
10.95 (1, 147) b0.01 (1, 147) 0.69 (1, 147) 4.93 (1, 35) 0.06 (1, 35) 2.09 (1, 35) 5.88 (1, 43) 3.04 (1, 43) 0.86 (1, 43)
b0.01 0.98 0.41 0.03 0.82 0.16 0.02 0.09 0.36
Child
Note. EBR = spontaneous eye blink rates; RT = response time.
Thereafter, the student residuals of the 2 regression equations where EBR in both children and adults significantly predict the commission error, were compared. This comparison indicated whether the linear correlations between EBR and commission error in the child and adult groups differed. An independent t-test showed that the residuals were not significantly different (t (80) = 0.013, n.s.). Hence, children and adults had similar correlations between EBR and RI.
3.4. Discussion Experiment 2 confirmed that the relationships between EBR and RI in the child and adult groups were similar, and that a higher EBR was correlated with a lower commission error. As EBR is an indicator of the central DA level, the present experiment provides strong evidence that children and adults have a similar relationship between DA and RI.
4. General discussion In the present study, experiment 1 validated our previous finding that higher EBR was significantly correlated with better RI ability in young adults; moreover, experiment 2 indicated a similar correlation between EBR and RI in older children and young adults. As EBR is closely related to the central DA function, the findings suggest that the relationships between DA and RI are similar in late childhood and young adulthood. Furthermore, we discuss the development of EBR and RI and the possible mechanisms underlying the similar relationships between EBR and RI in late childhood and young adulthood.
4.2. Development of RI In the present study, a significant decrease in the RT and omission error in the Go trials, and a decrease in the commission error in the Nogo trials was observed in the adult group, relative to the child group. These findings suggest a marked improvement in RI ability from late childhood to young adulthood, consistent with previous behavioral reports (Cragg and Nation, 2008; Jonkman, 2006; Jonkman et al., 2003). These behavioral improvements in RI depend on the developmental changes in the brain. One such change is the alteration of the brain structure. From late childhood to adolescence, the cortex thickness increases and synaptic pruning occurs (especially in the PFC), both of which can lead to increased efficiency among individuals in RI tasks (Cragg and Nation, 2008; Luna and Sweeney, 2004; Luna et al., 2015). Another related brain developmental change involves the refinement of brain activity from late childhood to adulthood (Best et al., 2009). For instance, during this period, the brain activation elicited by the RI task (e.g., the Go/No-go task) transitions from a diffused to focalized form (Durston et al., 2006), and the connectivity of the frontal brain regions during the RI tasks increases (Liston et al., 2006). These developmental changes in the brain can lead to decreases in the RT and omission error in the Go trials, and a decrease in the commission error in the Nogo-trials between adults and older children. Moreover some of these changes are modulated by the DA system, which may be responsible for the positive correlation between EBR and RI in childhood and adulthood, as discussed in the next section.
4.3. Relationship between EBR and RI in both late childhood and young adulthood 4.1. Development of EBR In the present study, the EBRs in the child group and adult group were not significantly different. However, in the study of Cruz et al. (2011), EBR was found to increase during childhood and adolescence, and then stabilize in adulthood. For an assessment of the differences in the studies, we believe that further investigation is needed to clarify the developmental trajectory of EBR. To our knowledge, EBR is closely related to the central DA function (especially the striatal DA), and is sensitive to changes in the DRD1 and DRD2 density (Groman et al., 2014); however, the exact mechanism underlying these relationships remains unclear. In humans, the densities of the D1 and D2 receptors in the PFC peak during the preadolescent stage, decline during adolescence, and stabilize during adulthood (Lidow and Rakic, 1992); however, in the striatum, the decline in the D1 and D2 receptor occurs at an earlier stage—i.e., during infancy and middle childhood, respectively (Jucaite et al., 2010; Seeman et al., 1987). Moreover, the DA activity in both the PFC and striatum increased in adolescents (Padmanabhan and Luna, 2013; Thompson et al., 2004). Thus, the manner in which these changes influence the EBR of individuals during development needs to be further explored.
The most important finding of the present study was that, in both the child and adult groups, a higher EBR was correlated with better RI ability. As EBR is closely related to the central DA level, these findings suggest that a higher central DA level was associated with better RI ability in both late childhood and young adulthood. These findings were consistent with those of previous adult studies, wherein individuals with higher DA function had better behavioral performance on RI tasks, higher inhibition-related brain activation, and a larger inhibition-related ERPs component (Albrecht et al., 2014; Ghahremani et al., 2012; van Bochove et al., 2013; Zhang et al., 2015; Zhang et al., 2016). Furthermore, the present results were also consistent with those of other developmental studies. For instance, in the study by Lackner et al. (2010), a higher EBR was found to be related to a better performance in the Grass/Snow task (a conflict inhibition task that involves both working memory and response inhibition components) in children aged 3–5 years. Moreover, in the study by Algarín et al. (2013), children aged 10 years with iron-deficiency anemia who had decreased DA function and lower EBR, as compared to healthy controls (Lozoff, 2011), were found to have a lower accuracy in the Nogo trials in the Go/Nogo task. Although these studies did not simultaneously include child and
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
57
Fig. 1. Scatterplots of the correlations between EBR and Go/Nogo task performance in experiment 1 and experiment 2. A. Experiment 1: correlation between the EBR and RT in the Go trials, omission error in the Go trials, or commission error in the Nogo trials in the child and adult groups, respectively. B. Experiment 2: correlation between the EBR and RT in the Go trials, omission error in the Go trials, or commission error in the Nogo trials in the child and adult groups, respectively. All the values of X and Y axes were Z-scores. The correlations presented in the scatterplots in the dotted square were significant.
adult participants, they still indicated similar relationships between the EBR and RI in individuals during both late childhood and young adulthood, consistent with the present study. With regard to the finding that older children and adults had similar relationships between EBR and RI, a possible explanation could be as follows. The developmental improvement in the RI from late childhood to adulthood is more efficient (i.e. smaller response time and higher accuracy) than acquiring new abilities. This behavioral improvement is supported by the changes in the brain structure (Cragg and Nation, 2008; Luna and Sweeney, 2004; Luna et al., 2015). For example, the cortex
thickness increases and synaptic pruning occurs (especially in the PFC), both of which have been suggested to be modulated by the DA system. In fact, recent studies showed that the cortex thickness is positively related to the striatal DA activity (Casey et al., 2013; Choi et al., 2016; Fernández-Jaén et al., 2016; Morales et al., 2015), whereas synaptic pruning is partly modulated by DA activity through the GABAergic neurons (Thompson et al., 2004). Hence, as the DA activity in the brain increases from late childhood to adulthood (Padmanabhan and Luna, 2013; Thompson et al., 2004), the increasing DA activity would promote the refinement of the brain structure and the improvement
58
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59
of efficiency in the RI task, which would consequently lead to better RI among individuals with higher DA activity. As EBR reflects the central DA activity (particularly striatal DA activity), the present study showed that higher EBR is related to better RI ability in both the child and adult groups. The abovementioned relationships were based on the behavioral responses of the Go/Nogo task. Nevertheless, care must be taken when generalizing these results to the relationship between EBR and the neural response. Adult studies have suggested that DA may influence the processing of inhibition through the frontal-striatal neural circuitry (Albrecht et al., 2014; Ghahremani et al., 2012). Higher striatal DA receptor availability and higher frontal-cortical DA release were positively related to the inhibition-related fMRI activation of the frontal-striatal neural circuitry and behavioral performance in the inhibition task, respectively (Albrecht et al., 2014; Ghahremani et al., 2012). Throughout development, from late childhood to adulthood, the frontal-striatal neural circuitry plays an important role in the maturation of RI, and it markedly changes in terms of volume of activation and location of activation (Mehnert et al., 2013). In contrast to adults, children showed greater activation, but reduced recruitment, of the frontal-striatal neural circuitry in inhibition tasks; however, children have less focalized and more bilaterally extended activation of the frontal-striatal neural circuitry, as compared to adults (Mehnert et al., 2013). Hence, the differences in the inhibitioninduced volume and location of the activation in the frontal-striatal neural circuitry between older children and adults may lead to variable relationships between EBR and the inhibition-related brain activation in older children. However, very few studies have focused on this issue thus far, and further investigation is needed. 5. Conclusion and limitations In the present study, we found that higher EBR was related to a lower commission error in the Nogo trials in both child and adult groups. As EBR is closely related to central DA function, it was suggested that both children and adults with higher DA function had better RI ability; in fact, there were similar relationships between RI ability and DA function in late childhood and young adulthood. However, there were still some limitations. The present study involved only one condition of the Go/Nogo task. Hence, it is unclear whether the relationships between EBR and RI in the child and adult groups would change if the task difficulty and stimuli modality were altered. Therefore, care must be taken when generalizing the present results to other conditions of the Go/Nogo task and also to other RI tasks. Moreover, as mentioned in the discussion, the present results were based on the behavioral responses. Hence, it is unclear whether the relationship between EBR and RI in children and adults would be similar, and this topic should be further explored in future studies. Acknowledgements This work was supported by the National Nature Science Foundation of China (31300857), the National Social Science Foundation of China (16CSH050) and The Fundamental Research Funds for the Central Universities (ZYGX2015J167). Reference Aarts, H., Bijleveld, E., Custers, R., Dogge, M., Deelder, M., Schutter, D., van Haren, N.E.M., 2012. Positive priming and intentional binding: eye-blink rate predicts reward information effects on the sense of agency. Soc. Neurosci. 7 (1), 105–112. Acheson, A., Tagamets, M.A., Winkler, A., Rowland, L.M., Mathias, C.W., Wright, S.N., ... Dougherty, D.M., 2015. Striatal activity and reduced white matter increase frontal activity in youths with family histories of alcohol and other substance-use disorders performing a go/no-go task. Brain and Behavior 5 (7). Albrecht, D.S., Kareken, D.A., Christian, B.T., Dzemidzic, M., Yoder, K.K., 2014. Cortical dopamine release during a behavioral response inhibition task. Synapse 68 (6), 266–274.
Algarín, C., Nelson, C.A., Peirano, P., Westerlund, A., Reyes, S., Lozoff, B., 2013. Iron-deficiency anemia in infancy and poorer cognitive inhibitory control at age 10 years. Dev. Med. Child Neurol. 55 (5), 453–458. Bacher, L.F., 2014. Development and manipulation of spontaneous eye blinking in the first year: relationships to context and positive affect. Dev. Psychobiol. 56, 783–796. Barbato, G., Ficca, G., Muscettola, G., Fichele, M., Beatrice, M., Rinaldi, F., 2000. Diurnal variation in spontaneous eye-blink rate. Psychiatry Res. 93 (2), 145–151. Barkley, R.A., 1997. Behavioral inhibition, sustained attention, and executive functions: constructing a unifying theory of ADHD. Psychol. Bull. 121, 65–94. Best, J.R., Miller, P.H., Jones, L.L., 2009. Executive functions after age 5: changes and correlates. Dev. Rev. 29 (3), 180–200. Blin, O., Masson, G., Azulay, J.P., Fondarai, J., Serratrice, G., 1990. Apomorphine-induced blinking and yawning in healthy volunteers. Br. J. Clin. Pharmacol. 30 (5), 769–773. Bodfish, J.W., Powell, S.B., Golden, R.N., Lewis, M.H., 1995. Blink rate as an index of dopamine function in adults with mental retardation and repetitive behavior disorders. Am. J. Ment. Retard. 99 (4), 335–344. Casey, K.F., Cherkasova, M.V., Larcher, K., Evans, A.C., Baker, G.B., Dagher, A., ... Leyton, M., 2013. Individual differences in frontal cortical thickness correlate with the D-amphetamine-induced striatal dopamine response in humans. J. Neurosci. 33 (38), 15285–15294. Chen, W.H., Chiang, M.C., Hsu, M.C., Liu, J.S., 2003. The validity of eye blink rate in Chinese adults for the diagnosis of Parkinson's disease. Clin. Neurol. Neurosurg. 105, 90–92. Chermahini, S.A., Hommel, B., 2010. The (b) link between creativity and dopamine: spontaneous eye blink rates predict and dissociate divergent and convergent thinking. Cognition 115 (3), 458–465. Choi, H., Cheon, G.J., Kim, H.J., Choi, S.H., Kim, Y.I., Kang, K.W., ... Lee, D.S., 2016. Gray matter correlates of dopaminergic degeneration in Parkinson's disease: a hybrid PET/MR study using 18F-FP-CIT. Hum. Brain Mapp. 37, 1710–1721. Colzato, L.S., van den Wildenberg, W.P., Hommel, B., 2008. Reduced spontaneous eye blink rates in recreational cocaine users: evidence for dopaminergic hypoactivity. PLoS One 3 (10), e3461. Colzato, L.S., van den Wildenberg, W.P., van Wouwe, N.C., Pannebakker, M.M., Hommel, B., 2009. Dopamine and inhibitory action control: evidence from spontaneous eye blink rates. Exp. Brain Res. 196 (3), 467–474. Cooper, C.J., 1973. Anatomical and physiological mechanisms of arousal, with special reference to the effects of exercise. Ergonomics 16 (5), 601–609. Cragg, L., Nation, K., 2008. Go or no-go? Developmental improvements in the efficiency of response inhibition in mid-childhood. Dev. Sci. 11, 819–827. Cruz, A.A., Garcia, D.M., Pinto, C.T., Cechetti, S.P., 2011. Spontaneous eyeblink activity. The Ocular Surface 9 (1), 29–41. Dauer, W., Przedborski, S., 2003. Parkinson's disease: mechanisms and models. Neuron 39, 889–909. De Paova, V., Barbato, G., Conte, F., Ficca, G., 2009. Diurnal variation of spontaneous eye blink rate in the elderly and its relationships with sleepiness and arousal. Neurosci. Lett. 463, 40–43. Dreisbach, G., Müller, J., Goschke, T., Strobel, A., Schulze, K., ... Brocke, B., 2005. Dopamine and cognitive control: the influence of spontaneous eyeblink rate and dopamine gene polymorphisms on perseveration and distractibility. Behav. Neurosci. 119 (2), 483. 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), 1–8. Eckstein, M.K., Guerra-Carrillo, B., Singley, A.T.M., Bunge, S.A., 2016. Beyond eye gaze: what else can eyetracking reveal about cognition and cognitive development? Developmental Cognitive Neuroscience 19(C), 190–199. Fernández-Jaén, A., Albert, J., Fernández-Mayoralas, D.M., López-Martín, S., Fernández-Perrone, A.L., de la Peña, M.J., ... Arribas, S.L., 2016. Cingulate cortical thickness and dopamine transporter (DAT1) genotype in children and adolescents with ADHD. J. Atten. Disord. 1087054716647483. Freed, W., 1980. Eye-blink rates and platelet monoamine oxidase activity in chronic schizophrenic patients. Biol. Psychiatry 15, 329–332. Gauggel, S., Rieger, M., Feghoff, T.A., 2004. Inhibition of ongoing responses in patients with Parkinson's disease. J. Neurol. Neurosurg. Psychiatry 75 (4), 539–544. Ghahremani, D.G., Lee, B., Robertson, C.L., Tabibnia, G., Morgan, A.T., De Shetler, N., ... London, E.D., 2012. Striatal dopamine D2/D3 receptors mediate response inhibition and related activity in frontostriatal neural circuitry in humans. J. Neurosci. 32 (21), 7316–7324. Groman, S.M., James, A.S., Seu, E., Tran, S., Clark, T.A., ... Jentsch, J.D., 2014. In the blink of an eye: relating positive-feedback sensitivity to striatal dopamine D2-like receptors through blink rate. J. Neurosci. 34, 14443–14454. Hershey, T., Black, K.J., Hartlein, J., Braver, T.S., Barch, D.M., Carl, J.L., Perlmutter, J.S., 2004. Dopaminergic modulation of response inhibition: an fMRI study. Cogn. Brain Res. 20 (3), 438–448. Howes, O.D., Kapur, S., 2009. The dopamine hypoth-esis of schizophrenia: version III—the final common pathway. Schizophr. Bull. 6, 1–4. Jongkees, B.J., Colzato, L.S., 2016. Spontaneous eye blink rate as predictor of dopamine-related cognitive function-a review. Neurosci. Biobehav. Rev. 71, 58–82. Jonkman, L.M., 2006. The development of preparation, conflict monitoring and inhibition from early childhood to young adulthood: a go/nogo ERP study. Brain Res. 1097, 181–193. Jonkman, L.M., Lansbergen, M., Stauder, J.E.A., 2003. Developmental differences in behavioral and event-related brain responses associated with response preparation and inhibition in a go/nogo task. Psychophysiology 40, 752–761. Jucaite, A., Forssberg, H., Karlsson, P., Halldin, C., Farde, L., 2010. Age-related reduction in dopamine D1 receptors in the human brain: from late childhood to adulthood, a positron emission tomography study. Neuroscience 167 (1), 104–110.
T. Zhang et al. / International Journal of Psychophysiology 116 (2017) 53–59 Jutkiewicz, E.M., Bergman, J., 2004. Effects of dopamine D1 ligands on eye blinking in monkeys: efficacy, antagonism, and D1/D2 interactions. J. Pharmacol. Exp. Ther. 311 (3), 1008–1015. Karson, C.N., 1983. Spontaneous eye-blink rates and dopaminergic systems. Brain 106 (3), 643–653. Kegeles, L.S., Abi-Dargham, A., Frankle, G., Gil, R., Cooper, T., et al., 2010. Increased synaptic dopamine function in associative regions of the striatum in schizophrenia. Arch. Gen. Psychiatry 3, 231–239. Kleven, M.S., Koek, W., 1996. Differential effects of direct and indirect dopamine agonists on eye blink rate in cynomolgus monkeys. The Journal of Pharmacology 279 (3), 1211–1219. Lackner, C.L., Bowman, L.C., Sabbagh, M.A., 2010. Dopaminergic functioning and preschoolers' theory of mind. Neuropsychologia 48 (6), 1767–1774. Lawrence, M.S., Redmond, D.E., 1991. MPTP lesions and dopaminergic drugs alter eye blink rate in African green monkeys. Pharmacol. Biochem. Behav. 38 (4), 869–874. Lidow, M.S., Rakic, P., 1992. Scheduling of monoaminergic neurotransmitter receptor expression in the primate neocortex during postnatal development. Cereb. Cortex 2 (5), 401–416. Liston, C., Watts, R., Tottenham, N., Davidson, M.C., Niogi, S., Ulug, A.M., Casey, B.J., 2006. Frontostriatal microstructure modulates efficient recruitment of cognitive control. Cereb. Cortex 16 (4), 553–560. Lozoff, B., 2011. Early iron deficiency has brain and behavior effects consistent with dopaminergic dysfunction. J. Nutr. 141 (4), 740S–746S. Luna, B., Sweeney, J.A., 2004. The emergence of collaborative brain function: FMRI studies of the development of response inhibition. Ann. N. Y. Acad. Sci. 1021 (1), 296–309. Luna, B., Marek, S., Larsen, B., Tervo-Clemmens, B., Chahal, R., 2015. An integrative model of the maturation of cognitive control. Annu. Rev. Neurosci. 38, 151–170. MacLean, W.E., Lewis, M.H., Bryson-Brockmann, W.A., Ellis, D.N., Arendt, R.E., Baumeister, A.A., 1985. Blink rate and stereotyped behavior: evidence for dopamine involvement? Biol. Psychiatry 20, 1321–1325. Mehnert, J., Akhrif, A., Telkemeyer, S., Rossi, S., Schmitz, C.H., Steinbrink, J., ... Neufang, S., 2013. Developmental changes in brain activation and functional connectivity during response inhibition in the early childhood brain. Brain Dev. 35 (10), 894–904. Morales, A.M., Kohno, M., Robertson, C.L., Dean, A.C., Mandelkern, M.A., London, E.D., 2015. Gray-matter volume, midbrain dopamine D2/D3 receptors and drug craving in methamphetamine users. Mol. Psychiatry 20 (6), 764–771.
59
Padmanabhan, A., Luna, B., 2013. Developmental imaging genetics: linking dopamine function to adolescent behavior. Brain Cogn. 89, 27–38. Roberts, J.E., Symons, F.J., Johnson, A.M., Hatton, D.D., Boccia, M.L., 2005. Blink rate in boys with fragile X syndrome: preliminary evidence for altered dopamine function. J. Intellect. Disabil. Res. 49 (9), 647–656. Rubia, K., Russell, T., Overmeyer, S., Brammer, M.J., Bullmore, E.T., Sharma, T., ... Taloy, E., 2001. Mapping motor inhibition: conjunctive brain activations across different versions of go/no-go and stop tasks. NeuroImage 13, 250–261. Seeman, P., Bzowej, N.H., Guan, H.C., Bergeron, C., Becker, L.E., Reynolds, G.P., ... Tourtellotte, W.W., 1987. Human brain dopamine receptors in children and aging adults. Synapse 1 (5), 399–404. Shukla, D., 1985. Blink rate as clinical indicator. Neurology 35 (2), 286. Slaghter, H.A., Georgopoulou, K., Frank, M.J., 2015. Spontaneous eye blink rate predicts learning from negative, but not positive, outcomes. Neuropsychologia 71, 126–132. Taylor, J.R., Elsworth, J.D., Lawrence, M.S., Sladek Jr, J.R., Roth, R.H., Redmond Jr, D.E., 1999. Spontaneous blink rates correlate with dopamine levels in the caudate nucleus of MPTP-treated monkeys. Exp. Neurol. 158 (1), 214–220. Thompson, J.L., Pogue-Geile, M.F., Grace, A.A., 2004. Developmental pathology, dopamine, and stress: a model for the age of onset of schizophrenia symptoms. Schizophr. Bull. 30 (4), 875–900. van Bochove, M.E., Van der Haegen, L., Notebaert, W., Verguts, T., 2013. Blinking predicts enhanced cognitive control. Cognitive, Affective, & Behavioral Neuroscience 13 (2), 346–354. Volkow, N.D., Fowler, J.S., Wang, G.J., 1999. Imaging studies on the role of dopamine in cocaine reinforcement and addiction in humans. J. Psychopharmacol. 13, 337–345. Vreugdenhil, H., Brouwers, P., Wolters, P., Bakker, D., Moss, H., 1997. Spontaneous eye blinking, a measure of dopaminergic function, in children with acquired immunodeficiency syndrome. Arch. Pediatr. Adolesc. Med. 151 (10), 1025–1032. Zhang, T., Di, M., Wang, C., Tan, F., Jiang, Y., Zheng, L., ... Li, H., 2015. Dopamine and executive function: increased spontaneous eye blink rates correlate with better setshifting and inhibition, but poorer updating. Int. J. Psychophysiol. 96 (3), 155–161. Zhang, T., Wang, C., Tan, F., Mu, D., Zheng, L., 2016. Different relationships between central dopamine system and sub-processes of inhibition: spontaneous eye blink rate relates with N2 but not P3 in a go/nogo task. Brain Cogn. 105, 95–103.