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Go–no-go performance in pathological gamblers
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Psychiatry Research 161 (2008) 1 – 10 www.elsevier.com/locate/psychres
Go–no-go performance in pathological gamblers Semion Kertzman a,b , Katherine Lowengrub a,b , Anat Aizer b , Michael Vainder b , Moshe Kotler a,b , Pinhas N. Dannon a,b,⁎ a
The Rehovot Community Mental Health & Rehabilitation Clinic affiliated to Beer-Ya'akov-Ness Ziona Medical Complex, Israel b Sackler Faculty of Medicine, Tel Aviv University, Israel Received 24 August 2006; received in revised form 5 March 2007; accepted 30 June 2007
Abstract Previous neuropsychological studies demonstrated various deficits of impulse control in pathological gamblers (PGs). However, there are limited data available on response-inhibition impairment among PGs. The present study attempted to assess response inhibition in untreated PGs (N = 83), in comparison with normal subjects (N = 84). Go/no-go and target-detection conditions of a computerized task were used as a measure of response-inhibition ability. A repeated measures analysis of covariance (ANCOVARM) was used with response time, variability of response time, and number of false alarms and misses as dependent measures; group (PG and controls) as the between-subjects measure; condition (target detection or go/no-go) and time slice (first and second in each condition) as repeated measures within-subject factors; and educational level as a covariate. Our results showed that PGs were significantly more impaired in both target detection and go/no-go task performance than controls. The PGs had significantly more false alarms and misses than controls, and they were slower and less consistent in their responses. © 2007 Elsevier Ireland Ltd. All rights reserved. Keywords: Pathological gamblers; Attention; Continuous performance task; Target detection; Speed–accuracy tradeoff
1. Introduction Gambling is defined as placing something of value at risk with the hope of gaining something of greater value in return. While different forms of gambling have existed throughout history, modern forms of gambling include casino bets, lotteries, horse racing, scratch tickets, bingo, and internet gambling (Potenza et al., 2001). Up to 86% of the general adult population has been estimated to have gambled at some point in their lives; it has been ⁎ Corresponding author. The Rehovot Community Mental Health & Rehabilitation Center, Remez Street 80, Rehovot, 76449, Israel. Tel.: +972 8 9461893; fax: +972 8 9468962. E-mail address: [email protected] (P.N. Dannon).
estimated that nearly 10% of adult gamblers meet criteria for the diagnosis of problematic gambling (Shaffer et al., 1999) and 2.5–3.4% meet criteria for pathological gambling (PG). Pathological gambling is characterized by gambling behavior that significantly impairs occupational, interpersonal, and financial functioning (National Opinion Research Center, 1999). Pathological gambling is classified in DSM-IV (American Psychiatric Association, 1994) as a disorder of impulse control. Recent neurobehavioral research has shown that there appears to be a connection between impulsivity and pathological gambling (Petry, 2001). According to the current psychiatric literature, impulsivity implies a tendency to react to stimuli in a rapid, unplanned fashion without allowing time for complete
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processing of information. Impulsive behavior has also been shown to be associated with a decreased sensitivity to negative consequences of behavior, and a lack of regard for long-term consequences (Moeller et al., 2001). The importance of further defining the neurocognitive and neuropsychological aspects of impulsivity has been recognized, for there has been little consensus with respect to specific neurobehavioral correlates of impulsive behavior (Evenden, 1999; Nigg, 2003). In an attempt to further delineate psychiatric aspects of impulsivity, Moeller et al. (2001) demonstrated that targeted laboratory tasks can be used to examine and define different inhibitory mechanisms. These inhibitory mechanisms include 1) the ability to delay appropriate responses before checking all alternatives (“response inhibition”), 2) the ability to stop an inappropriate response after the context has changed (“interruptive inhibition”), and 3) the ability to protect the period of delay (a certain amount of time, in which no decision is taken) despite distraction from competing information (“interference inhibition”) (Kertzman et al., 2006a). Both the Continuous Performance Test (CPT, Rodriguez-Jimenez et al., 2006) and the go/no-go task (Goudriaan et al., 2005; Fuentes et al., 2006) have been used for the assessment of “response inhibition” ability in PG. Interestingly, these tasks have shown differing results with regard to impaired response inhibition in PG. In a study using the CPT to examine response inhibition, no impairment was found in a group of pathological gamblers (Rodriguez-Jimenez et al., 2006). In contrast to these findings, however, go/no-go performance was impaired in pathological gamblers (Goudriaan et al., 2005; Fuentes et al., 2006). This discordance of results may be partially related to the differential frequency of the go and no-go stimuli between the CPT and the go/no-go task, which may, in turn, have created a difference in salience between the event types that confounds an examination of differences in response inhibition (Braver et al., 2001). The CPT task generally requires ability to detect and respond to go stimuli, whereas the go/no-go tasks require ability to withhold a response to no-go stimuli. In the go/ no-go task, the relatively decreased frequency of no-go events enhances an expectation that the next stimulus will be a go stimulus, thereby promoting a tendency toward making a rapid response in favor of responding to go stimuli. Typically in go/no-go task variants, authors used only 6–25% no-go stimuli (de Zubicaray et al., 2000; Durston et al., 2002; Ford et al., 2004; Garavan et al., 2002; Mathalon et al., 2003; Mostofsky et al., 2003). Therefore, this design provides a useful test for evaluation of inhibitory control and action monitoring (Menon et al., 2001) in which inaccurate response to the no-go event is
assumed to reflect impaired inhibition ability (Rubia et al., 2001; Berwid et al., 2005). Berwid et al. (2005) studied response inhibition in children with attention deficit disorder and presented the following hypotheses regarding impulsive behavior: (a) the time required to respond to a stimulus should be shorter for impulsive subjects than non-impulsive controls; (b) commission errors (producing a response to a no-go stimulus) should be more frequent among impulsive subjects and such errors can be interpreted as either the impulsive subjects do not take enough time to respond accurately or they fail to properly integrate information; and (c) response time and number of commission errors would hold a significant negative relationship. They note that if omission errors during CPT tasks are usually taken to reflect failures of sustained attention, errors of commission on CPTs are more difficult to interpret (Halperin et al., 1991). Conversely, during go/no-go tasks, errors of commission would be interpreted as failures of inhibitory control, whereas errors of omission would be difficult to interpret. Despite growing evidence of the association between impaired response inhibition and PG, the neurocognitive basis for impaired response inhibition has yet to be delineated. The present study was designed to compare performance on the CPT and the go/no-go task on a cohort of pathological gamblers versus healthy controls. We used an inverse contrast model of the go/no-go task, in which frequent no-go and rare go stimuli were presented (Nieuwenhuis et al., 2003; Berwid et al., 2005). 2. Methods 2.1. Subjects Eighty-three consecutive outpatients suffering from pathological gambling (PG) were included in our study. All patients were recruited from ambulatory services throughout Israel. Patients receiving any ongoing psychiatric treatment were excluded. Other exclusion criteria were neurological disorders, mental retardation, alcohol and substance abuse/dependence, major psychiatric disorders, and treatment with any psychiatric medication in the month prior to the screening interview. Senior psychiatrists (PND and KL) administered a semistructured diagnostic interview, which was performed according to the guidelines of DSM-IV and the South Oaks Gambling Scale (SOGS) (Lesieur and Blume, 1987). Patients that did not meet the SOG score of 5 were excluded. The control group included 84 healthy volunteers who were recruited among staff members and medical students. Exclusion criteria for the control group
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included any current psychiatric disorder and any lifetime diagnosis of a DSM-IV axis I psychiatric disorder such as schizophrenia, bipolar disorders, ADD, obsessive–compulsive disorder, and substance-related disorders. Our study was approved by the local Institutional Review Board, and approved by the Ministry of Health. All subjects provided a written informed consent, and the nature of the neurocognitive tests was fully explained to them. Potential participants completed an additional screening questionnaire and a screening interview that covered the following areas: medical history, illicit drug use, family psychiatric history, personal psychiatric history, color blindness, visual and hearing impairment, smoking, literacy, and native language. All of the subjects were free of any psychopharmacologic treatment for at least 4 weeks before the study. 2.2. Neuropsychological assessment For this study, a computerized special task that included both the CPT and the go/no-go was developed (AnimaScan Ltd, Ashdod, Israel, 2000). Reliability of the task was calculated for a normal adult sample and was controlled for age and gender. The subtests are described below, along with their monthly test-retest reliability coefficients (Pearson product-moment coefficients), which were r = 0.80 and r = 0.88 for the mean response time of the CPT and the go/no-go, respectively; r = 0.77 and r = 0.85 for the mean of the standard deviation of response time of the CPT and the go/no-go, respectively; r = 0.91 and r = 0.64 for the number of commission errors of the CPT and the go/no-go, respectively; r = 0.75 and r = 0.81 for the number of omission errors in the CPT and the go/no-go, respectively (Kertzman et al., 2000; unpublished data, 109 healthy subjects). 2.2.1. Experimental task The computerized version of experimental task was administered to all subjects in the morning at 8–11 AM. Stimuli were displayed on the monitor (frame rate, 100 Hz) of an IBM-compatible personal computer using the experimental software (Anima-Scan LTD) and the operating system Windows 2000. The viewing distance was 60 cm from the screen. It has been previously reported that go/no-go performance is multidimensional, reflecting various inter-related cognitive and emotional functions (Erickson et al., 2005). Therefore, in order to investigate pure response-inhibition deficits, we used a simple situation and controlled for confounding factors. To this end, a computerized version of tasks was designed in a way that minimally involved working
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memory (Kalenscher et al., 2005). In addition, stimuli were neutral because the emotional value of stimuli may bias performance (Shafritz et al., 2006). Subjects were requested to respond to red squares (go event) by immediate button press, but to withhold responses to black squares (no-go event). All stimuli were briefly displayed centrally on the screen, 100 ms each, because the results of previous investigations have suggested that the speed of stimulus presentation is crucial for establishing inhibitory control on the go/no-go task (Konishi et al., 1999; Simpson and Riggs, 2006). The stimuli were presented in random order, as red or black squares against a white background on a computer screen at a rate of one stimulus per 2000 ms. In the go/ no-go discrimination task, a speeded reaction was required, since participants had to respond during the 2000-ms interval in which the stimulus was presented (Riccio et al., 2002). In addition, a constant interstimulus interval was also chosen to minimize any orienting response due to unpredictability of stimulus occurrence. The whole experimental task lasts for 10 min, and each condition (either CPT or go/no-go) continues for 5 min without a pause between them. A total of 300 stimuli were divided into two successive conditions, each of which contained 150 stimuli. The CPT is a condition with frequent (80%) no-go events and the subjects were instructed to detect and generate a response to rare go stimuli (20% frequency). The go/no-go is a condition with frequent go (80%) events, and the subjects were instructed to withhold responding to rare no-go stimuli (20%). The performance of each patient is measured during two blocks in each condition [the CPT condition includes both block 1 (75 stimuli) and block 2 (76–150 stimuli); the go/no-go condition includes both block 3 (151–225 stimuli) and block 4 (226–300 stimuli)]. The order of task conditions was constant for each examinee. It was found that this specific construction of the task might help to investigate the inhibition ability in situations involving performance shifting (Koch and Philipp, 2005; Milan et al., 2006) from rare go stimuli (as in the CPT) to frequent go events (in the go/no-go). The participants were instructed to press a response button “as quickly as possible” on go trials. The subject was asked to react each time a red square was displayed, by pressing a red key. Participants responded with a dominant index-finger button press to the go stimuli using a computer keyboard. Participants were instructed to keep their fingers over the key in order to be ready to respond. Errors of commission occur when the subject incorrectly responds to black squares; such a response is considered to be a measure of impulsivity. Errors of omission occur when the subject omits pressing the button
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when a red square appears; such a response is considered to be a measure of inattention. Reaction times to go events were computed for trials in which the participants responded within 2100 ms of stimulus onset. Failures to respond to a go event within a period of more than 2100 ms of stimulus onset or implausibly early, i.e. less than 250 ms after red stimuli onset, were considered errors of omission. Errors of commission were defined as responses that occurred within 2100 ms of a no-go stimulus onset. Given that reaction times were neither obtained during no-go events nor during omission errors, we did not use reaction times as an outcome variable in our analysis. To ensure comprehension of the task instructions, participants carried out a practice with 30 stimuli that familiarized them with the task. Also, they were given feedback at the end of the practice session, showing their accuracy of performance. Therefore, in practice sessions, accuracy of decision was stressed, and subjects were trained until they achieved a 100% correct performance level. 2.3. Data analysis Data were analyzed using the SAS (v. 9.01) software for windows. All analyses used two-tailed levels of significance. Descriptive statistics were calculated with Age, Education Level (years) and Gender. Parametric (t-test) and non-parametric (χ2 and Mann–Whitney U tests) analyses were performed to compare differences between groups in demographic characteristics. To evaluate differences between groups in trial-to-trial performance, repeated measures analyses of covariance (ANCOVAs) with performance variables (response time, variability of response time, numbers of commission and omission errors) as dependent measures, Group (PG and Controls) as between-subject measures, Blocks (1, 2, 3 and 4) and Condition (“CPT” and “go/no-go”) as within-subject measures were performed. Two conditions of the performance were examined: (i) CPT as the ‘target detection’ condition, (ii) ‘go/no-go’ as the ‘inhibition ability’ condition. A separate analysis was performed for the ‘switch’ from block 2 to block 3 as a measure of remapping the strategy of responses (from ability to detect the go event to ability to withhold a response to the no-go event). Task switching especially involves ‘task management’ processes, i.e. scheduling processes which require switching of focused attention between tasks, and ‘attention and inhibition’ processes (Smith and Jonides, 1999). Pearson's correlation test between response time and numbers of errors was used as appropriate. Pearson's correlation test between response time and numbers of errors was performed to compare differences between groups in speed-accuracy tradeoff characteristics.
3. Results 3.1. Study population PG patients were significantly less educated than controls: mean schooling was 13.4± 2.4 years versus 15.2 ± 2.9 years (Mann–Whitney U test = 4791; P b 0.001). No significant between-group differences were found for age: 39.5 ± 13.4 versus 36.8 ± 12.1 years (t(165) = 1.39; P = 0.1673) or for gender: 56 men and 27 women versus 56 men and 28 women (Χ2 = 0.122; df = 1, P = 0.9121). Since group differences in education level were present, education was entered as a covariate in all analyses. 3.2. Response time We found that PG patients were significantly slower than controls (Table 1 and Fig. 1A). Three-way ANCOVA revealed a significant main effect of ‘Group’ [F(1,164) = 25.15, P b 0.001]. There was no significant main effect of ‘Conditions’ [F(1,164) = 0.28, P = 0.5961] or of ‘Block’ [F(1,164) = 0.002, P = 0.8876]. There was also neither a significant interaction between ‘Group’ and ‘Condition’ [F(1, 164) = 2.32, P = 0.1295] nor a significant interaction between ‘Condition’ and ‘Block’ [F(1,164) = 0.69, P = 0.4062]. A separate repeated measures ANCOVA was carried out to evaluate the switch between ‘CPT’ and ‘go/no-go’ conditions. The between-subject variable was ‘Group’ (PG and Control) and the within-subject variable was ‘Switch’ with two levels: block 2 (the CPT or ‘target detection’) to block 3 (the go/no-go task or ‘inhibition Table 1 Adjusted means (and standard deviations) of performance on the CPT and the go/no-go in PG and Control group Variable
CPT Block 1
Go/no-go Block 2
Block 3
Block 4
448 (116.5) 366 (116.4)
396 (94.6) 330 (94.4)
390 (88.8) 326 (88.7)
Reaction time variability PG 111.7 (72.15) 93.3 (64.32) Control 64.4 (72.09) 57.3 (64.21)
91.1(44.00) 68.9 (43.97)
98.7 (49.28) 68.4 (49.28)
Commission PG 0.44 (0.796) Control 0.22 (0.791)
0.20 (0.492) 0.11 (0.491)
1.17 (1.312) 0.89 (1.312)
1.44 (1.476) 1.06 (1.475)
Omission PG Control
0.75 (1.534) 0.10 (1.532)
2.28 (5.360) 0.25 (5.355)
2.23 (5.426) 0.33 (5.422)
Reaction time PG 458 (107.5) Control 374 (107.4)
0.74 (1.044) 0.08 (1.043)
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Fig. 1. The response time, standard deviation of response time, number of commission and omission errors in the Continuous Performance Test and the go/nogo task in the pathological gamblers (PG) compared with the healthy controls. (a) The PG group shows a significantly longer response time to go stimuli than the control group. All subjects showed a speeding up of the response time after an increased frequency of go events; (b) the PG group showed less consistent performance during both tasks than the control group, as well as in the CPTand go/no-go conditions separately and within blocks; (c) the PG patients showed a higher number of commission errors than the control group. There were significant differences between PG and controls in decreased numbers of commission errors in the second block and increased number of commission errors in the fourth block. There was a clear main effect of frequency of go events on increasing numbers of errors of commission in both groups when the condition was changed from rare go stimulation (CPT) to frequent go events (go/no-go task); (d) PG patients showed greater inattention than the control group. The data indicate that patients with PG are inefficient in retaining an adequate level of performance during the switch from the condition of dealing with rare go events (CPT) to the condition in which they are presented with frequent go events (go/no-go task).
ability’). There was a significant main effect of ‘Group’ [F(1,164) = 21.69, P b 0.0001], but there was no significant effect of ‘Switch’ [F(1,164) = 0.37, P = 0.5412]. There was also no significant interaction between ‘Group’ and ‘Switch’ [F(1,164) = 1.93, P = 0.1664]. 3.3. Variability of response time in PG versus controls The PG patients were more variable in their response time than controls (Table 1 and Fig. 1B). This could be seen in the significantly higher standard deviation of the response time [ANCOVA-RM F(1,164) = 22.34, P b 0.001]. There were no main effects of ‘Condition’ [F(1,164) = 0.63, P = 0.4301] or ‘Block’ [F(1,164) = 0.03, P = 0.8524]. A significant interaction between Group and Condition [F(1,164) = 4.04, P = 0.0462] and between Condition and Block [F(1,164) = 4.35, P = 0.0385] was found. A two-way repeated measures ANCOVA was used to assess the switch effect between CPT and go/no-go conditions. The between-subject variable was ‘Group’ (PG and Controls) and the within-subject variable was ‘Switch’ with two levels: block 2 (‘target detection’) and block 3 (‘inhibition ability’). The ANCOVA revealed a
significant main effect of Group [F(1,164) = 13.98, P = 0.0003]. There was no significant main effect of Switch [F(1,164) = 0.81, P = 0.3680] showing that there were no differences in variability of response time during switch between the CPT to the go/no-go condition. No significant interaction between Group and Condition was found [F(1,164) = 2.99, P = 0.0859]. 3.4. Errors Table 1 gives the incidences of the different errors. 3.4.1. Commission A three-way repeated measures ANCOVA revealed a significant main effect for Group [F(1, 164) = 4.17, P b 0.042]: The PG group showed more commission errors than controls (Table 1 and Fig. 1C). The mean number of errors of commission was significantly less in the CPT than in the go/no-go condition [ANCOVA-RM F(1, 164) = 26.5, P b 0.001]. There was no significant main effect of ‘Block’ [F(1,164) = 0.17, P = 0.6800] but a significant interaction of Block with Condition [ANCOVA-RM F(1,164) = 8.05, P = 0.005] showing a decrease in errors of commission for the second time on
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CPT performance and an increase in errors of commission for the second time on go/no-go performance. A two-way repeated measures ANCOVA was used to assess the switch effect between CPT and go/no-go conditions. The between-subject variable was ‘Group’ (PG and Controls) and the within-subject variable was ‘Switch’ with two levels: block 2 (‘target detection’) and block 3 (‘inhibition ability’). In concordance with our hypothesis, PG subjects did not show a significantly higher increase in commission errors following the switch from the CPT to the go/no-go condition than the controls [F(1,164) = 2.20, P = 0.1403]. However, there was a significant main effect of Condition [F(1,164) = 19.82, P b 0.0001], showing significant increase in number of errors of commission in both groups when the condition was changed from the CPT to the go/no-go task. No significant interaction effect was found [F(1,164) = 0.83, P = 0.3625]. 3.4.2. Omission This three-way ANCOVA revealed a significant main effect for Group [F(1, 164) = 7.04, P = 0.009]. The PG group showed a much higher incidence of errors of omissions than the controls (Table 1 and Fig. 1D). There was no significant main effect for Condition [F(1,164) = 0.20, P = 0.6554] or for Block [F(1,164) = 0.68, P = 0.4119]. There were also no significant interaction effects between Group and Condition [F(1, 164) = 3.33, P =0.069], between Condition and Block [F(1, 164) = 2.40, P = 0.1236] or between Group and Time [F(1, 164) = 0.20, P = 0.6536]. A two-way repeated measures ANCOVA was used to assess the switch effect between CPT and go/no-go conditions. The between-subject variable was ‘Group’ (PG and Controls) and the within-subject variable was ‘Switch’ with two levels: block 2 (‘target detection’) and block 3 (‘inhibition ability’). These data suggest that patients with PG are inefficient in maintaining an adequate level of performance during the switch from the condition of dealing with rare go events to the situation in which rare no-go events occur [F(1, 164) = 6.37, P = 0.0125]. In addition, there was a significant group by condition interaction with the group. During Table 2 Pearson correlation between response time and number of commission errors in PG subjects vs. controls
CPT Go/no-go
Block 1 Block 2 Block 3 Block 4
PG group
Control group
0.2515 (0.0218) 0.3266 (0.0026) − 0.0835 (0.4528) − 0.1879 (0.0890)
−0.3747 (0.0004)⁎ −0.0748 (0.4988) −0.2697 (0.0131) −0.2510 (0.0213)
Table 3 Correlation between response time and number of omission errors in PG subjects vs. controls
CPT go/go-no
Block 1 Block 2 Block 1 Block 2
PG group
Control group
0.2563 (0.0194) − 0.0397 (0.7218) − 0.1867 (0.091) − 0.2042 (0.0641)
−0.1720 (0.1177) −0.2153 (0.0492) −0.0209 (0.8504) −0.0281 (0.7995)
the switch from CPT to go/no-go conditions, the PG group showed an increased number of errors of omissions (they were less attentive) [F(1,164) = 4.29, P = 0.0398]. There was no significant main effect for Condition [F(1,164) = 0.89, P = 0.3462]. 3.5. Time–accuracy tradeoff The correlation between the number of errors and response time in the CPT was different in PG versus healthy subjects. As seen in Table 2, the number of commissions was negatively correlated with response time for the CPT and the go/no-go task only in the control group. In the PG group, a positive correlation was found between the number of commission errors and response time for the CPT condition. There was nearly a zero correlation between the number of commissions and response time, however, for go/no-go condition in the PG group. As seen in Table 3, the number of omission errors was negatively correlated with response time for the CPT and go/no-go conditions in the control group only. In the PG group, a positive correlation or a zero correlation was found between numbers of omission errors and response time for the CPT and slightly negative correlation in the go/no-go task. 4. Discussion Our study investigated neuropsychological correlates of inhibition ability in PG patients using the go frequency manipulation. In both the CPT and the go/ no-go conditions, the examinee chooses one correct response from a set of multiple alternative responses, and therefore, these tasks examine basic inhibitory mechanisms (Iversen and Mishkin, 1970). The number of commission errors is considered to be a direct measure of the ability to delay automatic responses. The major finding of our study was that, as compared to the control group, that performance in the PG cohort was characterized by significantly slower and less accurate responses in both the CPT and go/no-go conditions than in the control group.
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4.1. Response time measure The slow rate of performance seen in our PG patients is consistent with previous data (Exposito and AndresPueyo, 1997; Keilp et al., 2005; Kertzman et al., 2006b). It has been proposed that the paradox of response slowness in an impulsive subject might result from a deficit in the organization of stimulus-response schemata (Alexander et al., 2005; Stuss et al., 2005). We propose that situations which present a conflict between automatic and voluntary behavior may tend to cause response slowness in impulsive subjects. For example, in impulsive subjects, slowness may tend to occur in situations in which the same stimulus simultaneously elicits an automatic response but requires a voluntary response as seen in both the CPT and the go/no-go tasks. Thus, these incompatible and therefore competing automatic and voluntary tendencies may cause a response conflict (Botvinick et al., 2001), and longer reaction times and higher error rates are the results (Nakamura et al., 2005). The variability of response time was significantly higher in the PG group than in the control group. Slow or variable response time may be a consequence of distraction by external or internal stimuli resulting in fluctuations in processing speed throughout the task. Previously, the high variability of response time has been described for groups with traumatic brain injury or attention-deficit/hyperactivity disorder (ADHD) (Arcia and Gualtieri, 1994; Collins and Long, 1996; Lezak, 1995). 4.2. Commission and omission errors Our PG group had more commission errors on the go/ no-go task suggesting an inability to suppress an automatic response when a conflicting response is presented (Spreen and Strauss, 1998). The speed-accuracy tradeoff may help to elucidate the impairment of inhibitory function during task performance (Glickman et al., 2005). Theoretically, impulsive persons preferred a quick, automatic selection of stimuli for responses without monitoring (Tzelgov et al., 1997). The commission error is ignored, and the speed of performance is stressed at the expense of accuracy. Therefore, if commissions are an expression of impulsive reactions, a negative correlation should be found between number of commission errors and response time. This type of reaction has been found in psychopaths (Newman et al., 1990), juvenile delinquents (LeMarquand et al., 1998), adults with disorders of impulse control, patients with borderline personality disorder (Leyton et al., 2001) and children with ADHD (Riccio et al., 2002). In other words, impulsive behavior would be associated with the tradeoff of greater speed at the cost of lower accuracy. Conversely,
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however, we found a positive correlation between the number of commission errors and response time in PG subjects, and this finding suggests an alternate explanation for the errors of commission in the go/no-go task. Our results demonstrate that PG subjects make a higher number of errors of omissions than controls. The number of omission errors is usually considered to be a measure of inattention (Halperin et al., 1991). Inattention is defined as the inability to register information in working memory for further processing. Inattentive individuals spend more time on task performance, and as a result, the processing of information is delayed (Van Zomeren and Brouwer, 1990). Comparison of performance the CPT and the go/no-go task can help to distinguish attentional problems from inhibition ability impairments. In our study the PG subjects were impaired on both attention (the CPT) and inhibition (the go/no-go task) functioning. The presence of ADHD during childhood has been proposed as a possible risk factor for the development of PG in adulthood (Carlton and Manowitz, 1992; Rugle and Melamed, 1993; Specker et al., 1995). Yet, the PG patients with retrospective childhood diagnoses of ADHD did not exhibit significantly more impaired CPT (Rodriguez-Jimenez et al., 2006) or go/no-go (Fuentes et al., 2006) performance than the PG patients without ADHD. Thus, despite the fact that our PG patients had significantly poorer performance on the CPT and go/no-go tasks than controls, it would be highly speculative to conclude that this impairment was influenced by the existence of childhood ADHD. 4.3. Analysis of performance Our working hypothesis at the start of our study was that the PG group had a primary deficit in inhibitory control and therefore would make more commission errors during the condition with higher go frequency (as on the go/no-go task) because less inhibition is needed to prevent the execution of the rare go response in the context of frequent no-go events (as on the CPT) (Berwid et al., 2005). However, contrary to our expectations, the PG patients showed impaired performance irrespective to the frequency of go events (in both the CPT and the go/no-go task). Thus, our results are more consistent with the “response conflict monitoring” hypothesis (Botvinick et al., 2001; Carter et al., 1998; Ridderinkhof et al., 2004). Response conflict is thought to arise when two competing response pathways are simultaneously activated: the go reaction (responding with a button press) and the no-go reaction (withholding a response). In other
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words, when several stimuli are presented, some meeting the response criteria, others not, the subject must discriminate the go stimulus and provide an adequate response, while refraining from responding to no-go stimuli. Efficient executive control of behavior requires us to monitor our performance for errors (e.g., conflict between competing responses) and then to adjust our behavior accordingly (Botvinick et al., 2001; Funahashi, 2001). ‘Switch ability’ in our PG subjects was impaired when they needed to change performance from target detection to response inhibition (from block 2 to block 3). Our finding of impaired switch ability in our PG group is consistent with previous studies that found poor performance on tasks involving executive functions among PG subjects (Cavedini et al., 2002; Petry, 2001; Rugle and Melamed, 1993). Our results demonstrate that controls had fewer commission errors than the PG patients. We propose that the good performance in the control group was due to stronger inhibition of the incorrect response. Given the correlational nature of commission errors, interpretations consistent with the inhibition hypothesis do not seem to be plausible. The number of uninhibited responses in PG patients was positively correlated with response time, and this speed-accuracy tradeoff provides further support for the response-conflict hypothesis (Van Veen and Carter, 2002; Yeung et al., 2004). It is possible that the PG subjects have adopted a nonoptimal strategy to perform the task that is manifested in the less differentiated responses to go and no-go stimuli (Goudriaan et al., 2005; Fuentes et al., 2006). A previous study suggests that PG patients possibly employ more distributed networks, as compared with controls, in order to accomplish the same task (Potenza et al., 2003). The impaired performance on both the CPT and the go/no-go task observed in PG subjects may be a result of impaired functioning of the fronto-parietal circuits, which contributes to a lowered efficiency of neural processing (Huang et al., 2005) and impaired information processing in PG patients (Stojanov et al., 2003). In summary, neuropsychological studies consistently show that PG patients perform poorly on tests of response inhibition and response selection. In PG, dysfunction of cognitive regulatory processes may impair ability to appropriately inhibit self-defeating urges or desires. This failure to resist repetitive and maladaptive behaviours is a key clinical feature of PG. With provocation, the inhibitory system in PG is overwhelmed by intense motivational drives, resulting in the disinhibition of behaviour that is unduly dominated by ‘stimulus-driven’ tendencies. This leads to impulsivity (experienced as a loss of control) without consideration of adverse future
consequences, as seen in recurrent compulsive drugtaking. We note that our study has been carried out in PG patients free of comorbid substance abuse (i.e. no substance use in at least the previous 12 months with the exception of nicotine and caffeine), so as to avoid the possible damage to brain structures and secondary influence on the execution of the CPT and go/no-go task that substance abuse might cause. Although our study was limited to a cross-sectional study of neurocognitive functions, our findings give indirect evidence that diminished CPT and go/no-go performance may be a risk factor for developing PG. Future neuropsychological studies combined with neuroimaging techniques may help to clarify the particular brain mechanisms underlying impaired CPT and go/no-go performance in pathological gamblers. 4.4. The limitations of the present study Personality disorders, which may have an impact on neuropsychological performance (Posner et al., 2002), were not assessed in our sample of PG patients. Another limitation of this study is the absence of parallel audio versions of tasks for assessment of cognitive mechanisms of inhibition ability among PG patients as reported in previous studies. Declaration of interests: Neither financial nor material support was received from any external resource for this work. References Alexander, M.P., Stuss, D.T., Shallice, T., Picton, T.W., Gillingham, S., 2005. Impaired concentration due to frontal lobe damage from two distinct lesion sites. Neurology 65, 572–579. American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, 4th ed. APA, Washington, DC. Arcia, E., Gualtieri, C.T., 1994. Neurobehavioural performance of adults with closed-head injury, adults with attention deficit, and controls. Brain Injury 8, 395–404. Berwid, O.G., Curko Kera, E.A., Marks, D.J., Santra, A., Bender, H.A., Halperin, J.M., 2005. Sustained attention and response inhibition in young children at risk for attention deficit/hyperactivity disorder. Journal of Child Psychology and Psychiatry 46, 1219–1229. Botvinick, M.M., Braver, T.S., Barch, D.M., Carter, C.S., Cohen, J.D., 2001. Conflict monitoring and cognitive control. Psychological Review 108, 624–652. Braver, T.S., Barch, D.M., Gray, J.R., Molfese, D.L., Snyder, A., 2001. Anterior cingulate cortex and response conflict: effects of frequency, inhibition and errors. Cerebral Cortex 11, 825–836. Carlton, P.L., Manowitz, P., 1992. Behavioral restraint and symptoms of attention deficit disorder in alcoholics and pathological gamblers. Neuropsychobiology 25, 44–48.
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Psychiatry Research 161 (2008) 1 – 10 www.elsevier.com/locate/psychres
Go–no-go performance in pathological gamblers Semion Kertzman a,b , Katherine Lowengrub a,b , Anat Aizer b , Michael Vainder b , Moshe Kotler a,b , Pinhas N. Dannon a,b,⁎ a
The Rehovot Community Mental Health & Rehabilitation Clinic affiliated to Beer-Ya'akov-Ness Ziona Medical Complex, Israel b Sackler Faculty of Medicine, Tel Aviv University, Israel Received 24 August 2006; received in revised form 5 March 2007; accepted 30 June 2007
Abstract Previous neuropsychological studies demonstrated various deficits of impulse control in pathological gamblers (PGs). However, there are limited data available on response-inhibition impairment among PGs. The present study attempted to assess response inhibition in untreated PGs (N = 83), in comparison with normal subjects (N = 84). Go/no-go and target-detection conditions of a computerized task were used as a measure of response-inhibition ability. A repeated measures analysis of covariance (ANCOVARM) was used with response time, variability of response time, and number of false alarms and misses as dependent measures; group (PG and controls) as the between-subjects measure; condition (target detection or go/no-go) and time slice (first and second in each condition) as repeated measures within-subject factors; and educational level as a covariate. Our results showed that PGs were significantly more impaired in both target detection and go/no-go task performance than controls. The PGs had significantly more false alarms and misses than controls, and they were slower and less consistent in their responses. © 2007 Elsevier Ireland Ltd. All rights reserved. Keywords: Pathological gamblers; Attention; Continuous performance task; Target detection; Speed–accuracy tradeoff
1. Introduction Gambling is defined as placing something of value at risk with the hope of gaining something of greater value in return. While different forms of gambling have existed throughout history, modern forms of gambling include casino bets, lotteries, horse racing, scratch tickets, bingo, and internet gambling (Potenza et al., 2001). Up to 86% of the general adult population has been estimated to have gambled at some point in their lives; it has been ⁎ Corresponding author. The Rehovot Community Mental Health & Rehabilitation Center, Remez Street 80, Rehovot, 76449, Israel. Tel.: +972 8 9461893; fax: +972 8 9468962. E-mail address: [email protected] (P.N. Dannon).
estimated that nearly 10% of adult gamblers meet criteria for the diagnosis of problematic gambling (Shaffer et al., 1999) and 2.5–3.4% meet criteria for pathological gambling (PG). Pathological gambling is characterized by gambling behavior that significantly impairs occupational, interpersonal, and financial functioning (National Opinion Research Center, 1999). Pathological gambling is classified in DSM-IV (American Psychiatric Association, 1994) as a disorder of impulse control. Recent neurobehavioral research has shown that there appears to be a connection between impulsivity and pathological gambling (Petry, 2001). According to the current psychiatric literature, impulsivity implies a tendency to react to stimuli in a rapid, unplanned fashion without allowing time for complete
0165-1781/$ - see front matter © 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.psychres.2007.06.026
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processing of information. Impulsive behavior has also been shown to be associated with a decreased sensitivity to negative consequences of behavior, and a lack of regard for long-term consequences (Moeller et al., 2001). The importance of further defining the neurocognitive and neuropsychological aspects of impulsivity has been recognized, for there has been little consensus with respect to specific neurobehavioral correlates of impulsive behavior (Evenden, 1999; Nigg, 2003). In an attempt to further delineate psychiatric aspects of impulsivity, Moeller et al. (2001) demonstrated that targeted laboratory tasks can be used to examine and define different inhibitory mechanisms. These inhibitory mechanisms include 1) the ability to delay appropriate responses before checking all alternatives (“response inhibition”), 2) the ability to stop an inappropriate response after the context has changed (“interruptive inhibition”), and 3) the ability to protect the period of delay (a certain amount of time, in which no decision is taken) despite distraction from competing information (“interference inhibition”) (Kertzman et al., 2006a). Both the Continuous Performance Test (CPT, Rodriguez-Jimenez et al., 2006) and the go/no-go task (Goudriaan et al., 2005; Fuentes et al., 2006) have been used for the assessment of “response inhibition” ability in PG. Interestingly, these tasks have shown differing results with regard to impaired response inhibition in PG. In a study using the CPT to examine response inhibition, no impairment was found in a group of pathological gamblers (Rodriguez-Jimenez et al., 2006). In contrast to these findings, however, go/no-go performance was impaired in pathological gamblers (Goudriaan et al., 2005; Fuentes et al., 2006). This discordance of results may be partially related to the differential frequency of the go and no-go stimuli between the CPT and the go/no-go task, which may, in turn, have created a difference in salience between the event types that confounds an examination of differences in response inhibition (Braver et al., 2001). The CPT task generally requires ability to detect and respond to go stimuli, whereas the go/no-go tasks require ability to withhold a response to no-go stimuli. In the go/ no-go task, the relatively decreased frequency of no-go events enhances an expectation that the next stimulus will be a go stimulus, thereby promoting a tendency toward making a rapid response in favor of responding to go stimuli. Typically in go/no-go task variants, authors used only 6–25% no-go stimuli (de Zubicaray et al., 2000; Durston et al., 2002; Ford et al., 2004; Garavan et al., 2002; Mathalon et al., 2003; Mostofsky et al., 2003). Therefore, this design provides a useful test for evaluation of inhibitory control and action monitoring (Menon et al., 2001) in which inaccurate response to the no-go event is
assumed to reflect impaired inhibition ability (Rubia et al., 2001; Berwid et al., 2005). Berwid et al. (2005) studied response inhibition in children with attention deficit disorder and presented the following hypotheses regarding impulsive behavior: (a) the time required to respond to a stimulus should be shorter for impulsive subjects than non-impulsive controls; (b) commission errors (producing a response to a no-go stimulus) should be more frequent among impulsive subjects and such errors can be interpreted as either the impulsive subjects do not take enough time to respond accurately or they fail to properly integrate information; and (c) response time and number of commission errors would hold a significant negative relationship. They note that if omission errors during CPT tasks are usually taken to reflect failures of sustained attention, errors of commission on CPTs are more difficult to interpret (Halperin et al., 1991). Conversely, during go/no-go tasks, errors of commission would be interpreted as failures of inhibitory control, whereas errors of omission would be difficult to interpret. Despite growing evidence of the association between impaired response inhibition and PG, the neurocognitive basis for impaired response inhibition has yet to be delineated. The present study was designed to compare performance on the CPT and the go/no-go task on a cohort of pathological gamblers versus healthy controls. We used an inverse contrast model of the go/no-go task, in which frequent no-go and rare go stimuli were presented (Nieuwenhuis et al., 2003; Berwid et al., 2005). 2. Methods 2.1. Subjects Eighty-three consecutive outpatients suffering from pathological gambling (PG) were included in our study. All patients were recruited from ambulatory services throughout Israel. Patients receiving any ongoing psychiatric treatment were excluded. Other exclusion criteria were neurological disorders, mental retardation, alcohol and substance abuse/dependence, major psychiatric disorders, and treatment with any psychiatric medication in the month prior to the screening interview. Senior psychiatrists (PND and KL) administered a semistructured diagnostic interview, which was performed according to the guidelines of DSM-IV and the South Oaks Gambling Scale (SOGS) (Lesieur and Blume, 1987). Patients that did not meet the SOG score of 5 were excluded. The control group included 84 healthy volunteers who were recruited among staff members and medical students. Exclusion criteria for the control group
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included any current psychiatric disorder and any lifetime diagnosis of a DSM-IV axis I psychiatric disorder such as schizophrenia, bipolar disorders, ADD, obsessive–compulsive disorder, and substance-related disorders. Our study was approved by the local Institutional Review Board, and approved by the Ministry of Health. All subjects provided a written informed consent, and the nature of the neurocognitive tests was fully explained to them. Potential participants completed an additional screening questionnaire and a screening interview that covered the following areas: medical history, illicit drug use, family psychiatric history, personal psychiatric history, color blindness, visual and hearing impairment, smoking, literacy, and native language. All of the subjects were free of any psychopharmacologic treatment for at least 4 weeks before the study. 2.2. Neuropsychological assessment For this study, a computerized special task that included both the CPT and the go/no-go was developed (AnimaScan Ltd, Ashdod, Israel, 2000). Reliability of the task was calculated for a normal adult sample and was controlled for age and gender. The subtests are described below, along with their monthly test-retest reliability coefficients (Pearson product-moment coefficients), which were r = 0.80 and r = 0.88 for the mean response time of the CPT and the go/no-go, respectively; r = 0.77 and r = 0.85 for the mean of the standard deviation of response time of the CPT and the go/no-go, respectively; r = 0.91 and r = 0.64 for the number of commission errors of the CPT and the go/no-go, respectively; r = 0.75 and r = 0.81 for the number of omission errors in the CPT and the go/no-go, respectively (Kertzman et al., 2000; unpublished data, 109 healthy subjects). 2.2.1. Experimental task The computerized version of experimental task was administered to all subjects in the morning at 8–11 AM. Stimuli were displayed on the monitor (frame rate, 100 Hz) of an IBM-compatible personal computer using the experimental software (Anima-Scan LTD) and the operating system Windows 2000. The viewing distance was 60 cm from the screen. It has been previously reported that go/no-go performance is multidimensional, reflecting various inter-related cognitive and emotional functions (Erickson et al., 2005). Therefore, in order to investigate pure response-inhibition deficits, we used a simple situation and controlled for confounding factors. To this end, a computerized version of tasks was designed in a way that minimally involved working
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memory (Kalenscher et al., 2005). In addition, stimuli were neutral because the emotional value of stimuli may bias performance (Shafritz et al., 2006). Subjects were requested to respond to red squares (go event) by immediate button press, but to withhold responses to black squares (no-go event). All stimuli were briefly displayed centrally on the screen, 100 ms each, because the results of previous investigations have suggested that the speed of stimulus presentation is crucial for establishing inhibitory control on the go/no-go task (Konishi et al., 1999; Simpson and Riggs, 2006). The stimuli were presented in random order, as red or black squares against a white background on a computer screen at a rate of one stimulus per 2000 ms. In the go/ no-go discrimination task, a speeded reaction was required, since participants had to respond during the 2000-ms interval in which the stimulus was presented (Riccio et al., 2002). In addition, a constant interstimulus interval was also chosen to minimize any orienting response due to unpredictability of stimulus occurrence. The whole experimental task lasts for 10 min, and each condition (either CPT or go/no-go) continues for 5 min without a pause between them. A total of 300 stimuli were divided into two successive conditions, each of which contained 150 stimuli. The CPT is a condition with frequent (80%) no-go events and the subjects were instructed to detect and generate a response to rare go stimuli (20% frequency). The go/no-go is a condition with frequent go (80%) events, and the subjects were instructed to withhold responding to rare no-go stimuli (20%). The performance of each patient is measured during two blocks in each condition [the CPT condition includes both block 1 (75 stimuli) and block 2 (76–150 stimuli); the go/no-go condition includes both block 3 (151–225 stimuli) and block 4 (226–300 stimuli)]. The order of task conditions was constant for each examinee. It was found that this specific construction of the task might help to investigate the inhibition ability in situations involving performance shifting (Koch and Philipp, 2005; Milan et al., 2006) from rare go stimuli (as in the CPT) to frequent go events (in the go/no-go). The participants were instructed to press a response button “as quickly as possible” on go trials. The subject was asked to react each time a red square was displayed, by pressing a red key. Participants responded with a dominant index-finger button press to the go stimuli using a computer keyboard. Participants were instructed to keep their fingers over the key in order to be ready to respond. Errors of commission occur when the subject incorrectly responds to black squares; such a response is considered to be a measure of impulsivity. Errors of omission occur when the subject omits pressing the button
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when a red square appears; such a response is considered to be a measure of inattention. Reaction times to go events were computed for trials in which the participants responded within 2100 ms of stimulus onset. Failures to respond to a go event within a period of more than 2100 ms of stimulus onset or implausibly early, i.e. less than 250 ms after red stimuli onset, were considered errors of omission. Errors of commission were defined as responses that occurred within 2100 ms of a no-go stimulus onset. Given that reaction times were neither obtained during no-go events nor during omission errors, we did not use reaction times as an outcome variable in our analysis. To ensure comprehension of the task instructions, participants carried out a practice with 30 stimuli that familiarized them with the task. Also, they were given feedback at the end of the practice session, showing their accuracy of performance. Therefore, in practice sessions, accuracy of decision was stressed, and subjects were trained until they achieved a 100% correct performance level. 2.3. Data analysis Data were analyzed using the SAS (v. 9.01) software for windows. All analyses used two-tailed levels of significance. Descriptive statistics were calculated with Age, Education Level (years) and Gender. Parametric (t-test) and non-parametric (χ2 and Mann–Whitney U tests) analyses were performed to compare differences between groups in demographic characteristics. To evaluate differences between groups in trial-to-trial performance, repeated measures analyses of covariance (ANCOVAs) with performance variables (response time, variability of response time, numbers of commission and omission errors) as dependent measures, Group (PG and Controls) as between-subject measures, Blocks (1, 2, 3 and 4) and Condition (“CPT” and “go/no-go”) as within-subject measures were performed. Two conditions of the performance were examined: (i) CPT as the ‘target detection’ condition, (ii) ‘go/no-go’ as the ‘inhibition ability’ condition. A separate analysis was performed for the ‘switch’ from block 2 to block 3 as a measure of remapping the strategy of responses (from ability to detect the go event to ability to withhold a response to the no-go event). Task switching especially involves ‘task management’ processes, i.e. scheduling processes which require switching of focused attention between tasks, and ‘attention and inhibition’ processes (Smith and Jonides, 1999). Pearson's correlation test between response time and numbers of errors was used as appropriate. Pearson's correlation test between response time and numbers of errors was performed to compare differences between groups in speed-accuracy tradeoff characteristics.
3. Results 3.1. Study population PG patients were significantly less educated than controls: mean schooling was 13.4± 2.4 years versus 15.2 ± 2.9 years (Mann–Whitney U test = 4791; P b 0.001). No significant between-group differences were found for age: 39.5 ± 13.4 versus 36.8 ± 12.1 years (t(165) = 1.39; P = 0.1673) or for gender: 56 men and 27 women versus 56 men and 28 women (Χ2 = 0.122; df = 1, P = 0.9121). Since group differences in education level were present, education was entered as a covariate in all analyses. 3.2. Response time We found that PG patients were significantly slower than controls (Table 1 and Fig. 1A). Three-way ANCOVA revealed a significant main effect of ‘Group’ [F(1,164) = 25.15, P b 0.001]. There was no significant main effect of ‘Conditions’ [F(1,164) = 0.28, P = 0.5961] or of ‘Block’ [F(1,164) = 0.002, P = 0.8876]. There was also neither a significant interaction between ‘Group’ and ‘Condition’ [F(1, 164) = 2.32, P = 0.1295] nor a significant interaction between ‘Condition’ and ‘Block’ [F(1,164) = 0.69, P = 0.4062]. A separate repeated measures ANCOVA was carried out to evaluate the switch between ‘CPT’ and ‘go/no-go’ conditions. The between-subject variable was ‘Group’ (PG and Control) and the within-subject variable was ‘Switch’ with two levels: block 2 (the CPT or ‘target detection’) to block 3 (the go/no-go task or ‘inhibition Table 1 Adjusted means (and standard deviations) of performance on the CPT and the go/no-go in PG and Control group Variable
CPT Block 1
Go/no-go Block 2
Block 3
Block 4
448 (116.5) 366 (116.4)
396 (94.6) 330 (94.4)
390 (88.8) 326 (88.7)
Reaction time variability PG 111.7 (72.15) 93.3 (64.32) Control 64.4 (72.09) 57.3 (64.21)
91.1(44.00) 68.9 (43.97)
98.7 (49.28) 68.4 (49.28)
Commission PG 0.44 (0.796) Control 0.22 (0.791)
0.20 (0.492) 0.11 (0.491)
1.17 (1.312) 0.89 (1.312)
1.44 (1.476) 1.06 (1.475)
Omission PG Control
0.75 (1.534) 0.10 (1.532)
2.28 (5.360) 0.25 (5.355)
2.23 (5.426) 0.33 (5.422)
Reaction time PG 458 (107.5) Control 374 (107.4)
0.74 (1.044) 0.08 (1.043)
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Fig. 1. The response time, standard deviation of response time, number of commission and omission errors in the Continuous Performance Test and the go/nogo task in the pathological gamblers (PG) compared with the healthy controls. (a) The PG group shows a significantly longer response time to go stimuli than the control group. All subjects showed a speeding up of the response time after an increased frequency of go events; (b) the PG group showed less consistent performance during both tasks than the control group, as well as in the CPTand go/no-go conditions separately and within blocks; (c) the PG patients showed a higher number of commission errors than the control group. There were significant differences between PG and controls in decreased numbers of commission errors in the second block and increased number of commission errors in the fourth block. There was a clear main effect of frequency of go events on increasing numbers of errors of commission in both groups when the condition was changed from rare go stimulation (CPT) to frequent go events (go/no-go task); (d) PG patients showed greater inattention than the control group. The data indicate that patients with PG are inefficient in retaining an adequate level of performance during the switch from the condition of dealing with rare go events (CPT) to the condition in which they are presented with frequent go events (go/no-go task).
ability’). There was a significant main effect of ‘Group’ [F(1,164) = 21.69, P b 0.0001], but there was no significant effect of ‘Switch’ [F(1,164) = 0.37, P = 0.5412]. There was also no significant interaction between ‘Group’ and ‘Switch’ [F(1,164) = 1.93, P = 0.1664]. 3.3. Variability of response time in PG versus controls The PG patients were more variable in their response time than controls (Table 1 and Fig. 1B). This could be seen in the significantly higher standard deviation of the response time [ANCOVA-RM F(1,164) = 22.34, P b 0.001]. There were no main effects of ‘Condition’ [F(1,164) = 0.63, P = 0.4301] or ‘Block’ [F(1,164) = 0.03, P = 0.8524]. A significant interaction between Group and Condition [F(1,164) = 4.04, P = 0.0462] and between Condition and Block [F(1,164) = 4.35, P = 0.0385] was found. A two-way repeated measures ANCOVA was used to assess the switch effect between CPT and go/no-go conditions. The between-subject variable was ‘Group’ (PG and Controls) and the within-subject variable was ‘Switch’ with two levels: block 2 (‘target detection’) and block 3 (‘inhibition ability’). The ANCOVA revealed a
significant main effect of Group [F(1,164) = 13.98, P = 0.0003]. There was no significant main effect of Switch [F(1,164) = 0.81, P = 0.3680] showing that there were no differences in variability of response time during switch between the CPT to the go/no-go condition. No significant interaction between Group and Condition was found [F(1,164) = 2.99, P = 0.0859]. 3.4. Errors Table 1 gives the incidences of the different errors. 3.4.1. Commission A three-way repeated measures ANCOVA revealed a significant main effect for Group [F(1, 164) = 4.17, P b 0.042]: The PG group showed more commission errors than controls (Table 1 and Fig. 1C). The mean number of errors of commission was significantly less in the CPT than in the go/no-go condition [ANCOVA-RM F(1, 164) = 26.5, P b 0.001]. There was no significant main effect of ‘Block’ [F(1,164) = 0.17, P = 0.6800] but a significant interaction of Block with Condition [ANCOVA-RM F(1,164) = 8.05, P = 0.005] showing a decrease in errors of commission for the second time on
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CPT performance and an increase in errors of commission for the second time on go/no-go performance. A two-way repeated measures ANCOVA was used to assess the switch effect between CPT and go/no-go conditions. The between-subject variable was ‘Group’ (PG and Controls) and the within-subject variable was ‘Switch’ with two levels: block 2 (‘target detection’) and block 3 (‘inhibition ability’). In concordance with our hypothesis, PG subjects did not show a significantly higher increase in commission errors following the switch from the CPT to the go/no-go condition than the controls [F(1,164) = 2.20, P = 0.1403]. However, there was a significant main effect of Condition [F(1,164) = 19.82, P b 0.0001], showing significant increase in number of errors of commission in both groups when the condition was changed from the CPT to the go/no-go task. No significant interaction effect was found [F(1,164) = 0.83, P = 0.3625]. 3.4.2. Omission This three-way ANCOVA revealed a significant main effect for Group [F(1, 164) = 7.04, P = 0.009]. The PG group showed a much higher incidence of errors of omissions than the controls (Table 1 and Fig. 1D). There was no significant main effect for Condition [F(1,164) = 0.20, P = 0.6554] or for Block [F(1,164) = 0.68, P = 0.4119]. There were also no significant interaction effects between Group and Condition [F(1, 164) = 3.33, P =0.069], between Condition and Block [F(1, 164) = 2.40, P = 0.1236] or between Group and Time [F(1, 164) = 0.20, P = 0.6536]. A two-way repeated measures ANCOVA was used to assess the switch effect between CPT and go/no-go conditions. The between-subject variable was ‘Group’ (PG and Controls) and the within-subject variable was ‘Switch’ with two levels: block 2 (‘target detection’) and block 3 (‘inhibition ability’). These data suggest that patients with PG are inefficient in maintaining an adequate level of performance during the switch from the condition of dealing with rare go events to the situation in which rare no-go events occur [F(1, 164) = 6.37, P = 0.0125]. In addition, there was a significant group by condition interaction with the group. During Table 2 Pearson correlation between response time and number of commission errors in PG subjects vs. controls
CPT Go/no-go
Block 1 Block 2 Block 3 Block 4
PG group
Control group
0.2515 (0.0218) 0.3266 (0.0026) − 0.0835 (0.4528) − 0.1879 (0.0890)
−0.3747 (0.0004)⁎ −0.0748 (0.4988) −0.2697 (0.0131) −0.2510 (0.0213)
Table 3 Correlation between response time and number of omission errors in PG subjects vs. controls
CPT go/go-no
Block 1 Block 2 Block 1 Block 2
PG group
Control group
0.2563 (0.0194) − 0.0397 (0.7218) − 0.1867 (0.091) − 0.2042 (0.0641)
−0.1720 (0.1177) −0.2153 (0.0492) −0.0209 (0.8504) −0.0281 (0.7995)
the switch from CPT to go/no-go conditions, the PG group showed an increased number of errors of omissions (they were less attentive) [F(1,164) = 4.29, P = 0.0398]. There was no significant main effect for Condition [F(1,164) = 0.89, P = 0.3462]. 3.5. Time–accuracy tradeoff The correlation between the number of errors and response time in the CPT was different in PG versus healthy subjects. As seen in Table 2, the number of commissions was negatively correlated with response time for the CPT and the go/no-go task only in the control group. In the PG group, a positive correlation was found between the number of commission errors and response time for the CPT condition. There was nearly a zero correlation between the number of commissions and response time, however, for go/no-go condition in the PG group. As seen in Table 3, the number of omission errors was negatively correlated with response time for the CPT and go/no-go conditions in the control group only. In the PG group, a positive correlation or a zero correlation was found between numbers of omission errors and response time for the CPT and slightly negative correlation in the go/no-go task. 4. Discussion Our study investigated neuropsychological correlates of inhibition ability in PG patients using the go frequency manipulation. In both the CPT and the go/ no-go conditions, the examinee chooses one correct response from a set of multiple alternative responses, and therefore, these tasks examine basic inhibitory mechanisms (Iversen and Mishkin, 1970). The number of commission errors is considered to be a direct measure of the ability to delay automatic responses. The major finding of our study was that, as compared to the control group, that performance in the PG cohort was characterized by significantly slower and less accurate responses in both the CPT and go/no-go conditions than in the control group.
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4.1. Response time measure The slow rate of performance seen in our PG patients is consistent with previous data (Exposito and AndresPueyo, 1997; Keilp et al., 2005; Kertzman et al., 2006b). It has been proposed that the paradox of response slowness in an impulsive subject might result from a deficit in the organization of stimulus-response schemata (Alexander et al., 2005; Stuss et al., 2005). We propose that situations which present a conflict between automatic and voluntary behavior may tend to cause response slowness in impulsive subjects. For example, in impulsive subjects, slowness may tend to occur in situations in which the same stimulus simultaneously elicits an automatic response but requires a voluntary response as seen in both the CPT and the go/no-go tasks. Thus, these incompatible and therefore competing automatic and voluntary tendencies may cause a response conflict (Botvinick et al., 2001), and longer reaction times and higher error rates are the results (Nakamura et al., 2005). The variability of response time was significantly higher in the PG group than in the control group. Slow or variable response time may be a consequence of distraction by external or internal stimuli resulting in fluctuations in processing speed throughout the task. Previously, the high variability of response time has been described for groups with traumatic brain injury or attention-deficit/hyperactivity disorder (ADHD) (Arcia and Gualtieri, 1994; Collins and Long, 1996; Lezak, 1995). 4.2. Commission and omission errors Our PG group had more commission errors on the go/ no-go task suggesting an inability to suppress an automatic response when a conflicting response is presented (Spreen and Strauss, 1998). The speed-accuracy tradeoff may help to elucidate the impairment of inhibitory function during task performance (Glickman et al., 2005). Theoretically, impulsive persons preferred a quick, automatic selection of stimuli for responses without monitoring (Tzelgov et al., 1997). The commission error is ignored, and the speed of performance is stressed at the expense of accuracy. Therefore, if commissions are an expression of impulsive reactions, a negative correlation should be found between number of commission errors and response time. This type of reaction has been found in psychopaths (Newman et al., 1990), juvenile delinquents (LeMarquand et al., 1998), adults with disorders of impulse control, patients with borderline personality disorder (Leyton et al., 2001) and children with ADHD (Riccio et al., 2002). In other words, impulsive behavior would be associated with the tradeoff of greater speed at the cost of lower accuracy. Conversely,
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however, we found a positive correlation between the number of commission errors and response time in PG subjects, and this finding suggests an alternate explanation for the errors of commission in the go/no-go task. Our results demonstrate that PG subjects make a higher number of errors of omissions than controls. The number of omission errors is usually considered to be a measure of inattention (Halperin et al., 1991). Inattention is defined as the inability to register information in working memory for further processing. Inattentive individuals spend more time on task performance, and as a result, the processing of information is delayed (Van Zomeren and Brouwer, 1990). Comparison of performance the CPT and the go/no-go task can help to distinguish attentional problems from inhibition ability impairments. In our study the PG subjects were impaired on both attention (the CPT) and inhibition (the go/no-go task) functioning. The presence of ADHD during childhood has been proposed as a possible risk factor for the development of PG in adulthood (Carlton and Manowitz, 1992; Rugle and Melamed, 1993; Specker et al., 1995). Yet, the PG patients with retrospective childhood diagnoses of ADHD did not exhibit significantly more impaired CPT (Rodriguez-Jimenez et al., 2006) or go/no-go (Fuentes et al., 2006) performance than the PG patients without ADHD. Thus, despite the fact that our PG patients had significantly poorer performance on the CPT and go/no-go tasks than controls, it would be highly speculative to conclude that this impairment was influenced by the existence of childhood ADHD. 4.3. Analysis of performance Our working hypothesis at the start of our study was that the PG group had a primary deficit in inhibitory control and therefore would make more commission errors during the condition with higher go frequency (as on the go/no-go task) because less inhibition is needed to prevent the execution of the rare go response in the context of frequent no-go events (as on the CPT) (Berwid et al., 2005). However, contrary to our expectations, the PG patients showed impaired performance irrespective to the frequency of go events (in both the CPT and the go/no-go task). Thus, our results are more consistent with the “response conflict monitoring” hypothesis (Botvinick et al., 2001; Carter et al., 1998; Ridderinkhof et al., 2004). Response conflict is thought to arise when two competing response pathways are simultaneously activated: the go reaction (responding with a button press) and the no-go reaction (withholding a response). In other
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words, when several stimuli are presented, some meeting the response criteria, others not, the subject must discriminate the go stimulus and provide an adequate response, while refraining from responding to no-go stimuli. Efficient executive control of behavior requires us to monitor our performance for errors (e.g., conflict between competing responses) and then to adjust our behavior accordingly (Botvinick et al., 2001; Funahashi, 2001). ‘Switch ability’ in our PG subjects was impaired when they needed to change performance from target detection to response inhibition (from block 2 to block 3). Our finding of impaired switch ability in our PG group is consistent with previous studies that found poor performance on tasks involving executive functions among PG subjects (Cavedini et al., 2002; Petry, 2001; Rugle and Melamed, 1993). Our results demonstrate that controls had fewer commission errors than the PG patients. We propose that the good performance in the control group was due to stronger inhibition of the incorrect response. Given the correlational nature of commission errors, interpretations consistent with the inhibition hypothesis do not seem to be plausible. The number of uninhibited responses in PG patients was positively correlated with response time, and this speed-accuracy tradeoff provides further support for the response-conflict hypothesis (Van Veen and Carter, 2002; Yeung et al., 2004). It is possible that the PG subjects have adopted a nonoptimal strategy to perform the task that is manifested in the less differentiated responses to go and no-go stimuli (Goudriaan et al., 2005; Fuentes et al., 2006). A previous study suggests that PG patients possibly employ more distributed networks, as compared with controls, in order to accomplish the same task (Potenza et al., 2003). The impaired performance on both the CPT and the go/no-go task observed in PG subjects may be a result of impaired functioning of the fronto-parietal circuits, which contributes to a lowered efficiency of neural processing (Huang et al., 2005) and impaired information processing in PG patients (Stojanov et al., 2003). In summary, neuropsychological studies consistently show that PG patients perform poorly on tests of response inhibition and response selection. In PG, dysfunction of cognitive regulatory processes may impair ability to appropriately inhibit self-defeating urges or desires. This failure to resist repetitive and maladaptive behaviours is a key clinical feature of PG. With provocation, the inhibitory system in PG is overwhelmed by intense motivational drives, resulting in the disinhibition of behaviour that is unduly dominated by ‘stimulus-driven’ tendencies. This leads to impulsivity (experienced as a loss of control) without consideration of adverse future
consequences, as seen in recurrent compulsive drugtaking. We note that our study has been carried out in PG patients free of comorbid substance abuse (i.e. no substance use in at least the previous 12 months with the exception of nicotine and caffeine), so as to avoid the possible damage to brain structures and secondary influence on the execution of the CPT and go/no-go task that substance abuse might cause. Although our study was limited to a cross-sectional study of neurocognitive functions, our findings give indirect evidence that diminished CPT and go/no-go performance may be a risk factor for developing PG. Future neuropsychological studies combined with neuroimaging techniques may help to clarify the particular brain mechanisms underlying impaired CPT and go/no-go performance in pathological gamblers. 4.4. The limitations of the present study Personality disorders, which may have an impact on neuropsychological performance (Posner et al., 2002), were not assessed in our sample of PG patients. Another limitation of this study is the absence of parallel audio versions of tasks for assessment of cognitive mechanisms of inhibition ability among PG patients as reported in previous studies. Declaration of interests: Neither financial nor material support was received from any external resource for this work. References Alexander, M.P., Stuss, D.T., Shallice, T., Picton, T.W., Gillingham, S., 2005. Impaired concentration due to frontal lobe damage from two distinct lesion sites. Neurology 65, 572–579. American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, 4th ed. APA, Washington, DC. Arcia, E., Gualtieri, C.T., 1994. Neurobehavioural performance of adults with closed-head injury, adults with attention deficit, and controls. Brain Injury 8, 395–404. Berwid, O.G., Curko Kera, E.A., Marks, D.J., Santra, A., Bender, H.A., Halperin, J.M., 2005. Sustained attention and response inhibition in young children at risk for attention deficit/hyperactivity disorder. Journal of Child Psychology and Psychiatry 46, 1219–1229. Botvinick, M.M., Braver, T.S., Barch, D.M., Carter, C.S., Cohen, J.D., 2001. Conflict monitoring and cognitive control. Psychological Review 108, 624–652. Braver, T.S., Barch, D.M., Gray, J.R., Molfese, D.L., Snyder, A., 2001. Anterior cingulate cortex and response conflict: effects of frequency, inhibition and errors. Cerebral Cortex 11, 825–836. Carlton, P.L., Manowitz, P., 1992. Behavioral restraint and symptoms of attention deficit disorder in alcoholics and pathological gamblers. Neuropsychobiology 25, 44–48.
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