Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer-journals/moment-to-moment-dynamics-of-adhd-behaviour-dPy8NVKYOs
- Publisher
- Springer Journals
- Copyright
- Copyright © 2005 by Aase and Sagvolden; licensee BioMed Central Ltd.
- Subject
- Biomedicine; Neurosciences; Neurology; Behavioral Therapy; Psychiatry
- eISSN
- 1744-9081
- DOI
- 10.1186/1744-9081-1-12
- pmid
- 16060963
- Publisher site
- See Article on Publisher Site
Abstract
Background: The behaviour of children with Attention-Deficit / Hyperactivity Disorder is often described as highly variable, in addition to being hyperactive, impulsive and inattentive. One reason might be that they do not acquire complete and functional sequences of behaviour. The dynamic developmental theory of ADHD proposes that reinforcement and extinction processes are inefficient because of hypofunctioning dopamine systems, resulting in a narrower time window for associating antecedent stimuli and behaviour with its consequences. One effect of this may be that the learning of behavioural sequences is delayed, and that only short behavioural sequences are acquired in ADHD. The present study investigated acquisition of response sequences in the behaviour of children with ADHD. Methods: Fifteen boys with ADHD and thirteen boys without, all aged between 6–9 yr, completed a computerized task presented as a game with two squares on the screen. One square was associated with reinforcement. The task required responses by the computer mouse under reinforcement contingencies of variable interval schedules. Reinforcers were cartoon pictures and small trinkets. Measures related to response location (spatial dimension) and to response timing (temporal dimension) were analyzed by autocorrelations of consecutive responses across five lags. Acquired response sequences were defined as predictable responding shown by high explained variance. Results: Children with ADHD acquired shorter response sequences than comparison children on the measures related to response location. None of the groups showed any predictability in response timing. Response sequencing on the measure related to the discriminative stimulus was highly related to parent scores on a rating scale for ADHD symptoms. Conclusion: The findings suggest that children with ADHD have problems with learning long sequences of behaviour, particularly related to response location. Problems with learning long behavioural sequences may ultimately lead to deficient development of verbally governed behaviour and self control. The study represents a new approach to analyzing the moment-to-moment dynamics of behaviour, and provides support for the theory that reinforcement processes are altered in ADHD. Page 1 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 Reinforcement and behavioural sequences Background Attention-Deficit/Hyperactivity Disorder (ADHD) [1] is a The DDT suggests that dysfunctioning reinforcement and behavioural disorder characterized by developmentally extinction processes can explain why symptomatic ADHD inappropriate levels of hyperactive, inattentive, impulsive, behaviour is acquired through dynamic interaction and variable behaviour. Impulsiveness is increasingly between the child and the environment throughout devel- considered as a major behavioural symptom. A recent opment [2,3]. Reinforcement and extinction are the main comprehensive theory of ADHD, the dynamic develop- selection mechanisms of behaviour, and they are associ- mental theory (DDT), suggests two processes, altered rein- ated with dopaminergic activity [9]. According to the forcement processes and inefficient extinction, as being DDT, these mechanisms may operate constantly to repro- causative of several of the behavioural symptoms in gram neuronal connections by strengthening (reinforcing ADHD [2,3]. Specifically, the DDT suggests that delayed or potentiating) connections associated with reinforced learning of complete and functional behavioural behaviour, and at the same time weakening (extinguish- sequences may be causing the frequent shifts between ing or depressing) other neuronal connections associated activities, non-completion of tasks, lack of long-term with nonreinforced behaviour [2]. planning, and deficient self-control that often are described as outcomes of impulsivity. On a behavioural level, reinforcers select responses by increasing the probability of repeating responses that pro- There is some support for the notion that ADHD behav- duce reinforcers. Reinforcement as a process operates iour may be characterized by hampered acquisition of within a limited time window from the occurrence of the complete and functional sequences of behaviour. First, behaviour to the perception of the consequences of this children with ADHD did not perform sequences of arm behaviour. Altered reinforcement processes in ADHD may movements as one functional unit, but were slower, be described as a narrower time window than normal for showed greater variability in movement timing, and dem- associating behaviour with its consequences. A narrow onstrated longer inter-segment intervals than children time window may theoretically be depicted as a shorter without ADHD, who appeared to program the entire arm and steeper delay-of-reinforcement gradient (called delay movements and executed the sequence as one functional gradient from here onwards) (Figure 1). The delay gradi- unit that was temporally coordinated [4]. The children ent describes that the effect of a reinforcer is largest when without ADHD in this study showed age adequate it is delivered immediately after the response has been planned movement, while the children with ADHD emitted, and wanes as a function of the delay in reinforcer resembled the performance of younger children using delivery. The delay gradient thus depicts the relation "on-line" or immediate-feedback monitoring [5]. Second, between reinforcers and responses as an effect of time. in a serial choice button-press task where advance infor- mation about the next steps in the sequence was gradually There may be many behavioural consequences of a reduced, children with ADHD (and children with shorter delay gradient in ADHD (see [2,3] for details); one Tourette syndrome) showed increasing movement of them being that it will only allow for short behavioural sequencing deficits compared to healthy controls as the sequences to be associated with reinforcement. Thus, level of advance information was reduced [6]. Third, on a when there is a short time interval passing from the occur- task requiring high-level controlled processing (follow a rence of a particular response to the presentation of a rein- target that randomly moves across the computer screen), forcer, or a short sequence of responses is quickly and preschool children at risk for ADHD were disproportion- contingently followed by a reinforcer, this sequence will ately more inaccurate and variable compared to healthy be strengthened by reinforcement with equal probability controls, children with borderline ADHD, and children in ADHD behaviour and in normal behaviour (given that with other psychopathology [7]. On a task requiring low- the delay gradients are at the same height at the time of level processing (trace the mouse cursor within the limits reinforcement, see Figure 1). However, when reinforcers of two lines), though, the difference between the groups are delayed or follow after a long behavioural sequence, was not significant. The authors concluded that deficits in only the behaviour occurring within the restricted time self-control and self-regulation seemed to be present very window will be associated with the reinforcement and early in the development of ADHD [7]. Finally, in a study thus be strengthened. This may affect the establishment of investigating multitasking in ADHD and community con- serial ordering of behavioural units, which is fundamental trols, children with ADHD appeared to have a specific def- to all forms of skilled action, from speech to typing to icit in monitoring their ongoing behaviours and reaching and grasping [10,11]. generating useful strategies for task completion [8]. Skilled performance involves hierarchically organized units of behaviour, where the higher levels are controlled by longer-term consequences, and lower levels are Page 2 of 14 (page number not for citation purposes) Effect of Reinforcer Rft Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 ADHD ---- Normal R Response Rft Reinforcer Time→ Th Figure 1 eoretical delay-of-reinforcement gradients Theoretical delay-of-reinforcement gradients. The shorter and steeper delay gradient for ADHD (solid red line) implies that the relation between the response R and R will not be reinforced, while this relation will be reinforced with a normal delay gradient (broken blue line). The relation between R and R is close enough to be reinforced both when the delay gradient is short and when it is normal. A reinforcer will have almost the same effect on responses occurring immediately before rein- forcer delivery with both a short and a long delay gradient, increasing the probability of repeating R with almost the same amount irrespective of the shape of the gradient. controlled by short-term consequences of individual control will be slowed, resulting in impulsivity and movements [12]. The hierarchical organization of behav- increased behavioural variability [2]. This style of learning ioural units seems to combine autonomous functions at may ultimately impede the development of verbally gov- low levels with the possibility of learning new operations erned behaviour and "self control", and will have conse- at higher control levels: "If the 'vital' centers of the lowest quences for how the child with ADHD understands and levels were not strongly organized at birth, life would not behaves within his or her environment. be possible; if the centers on the highest levels ('mental centers') were not little organized and therefore very mod- Purpose of the present study ifiable we could only with difficulty and imperfectly The aims of the present study is to investigate the hypoth- adjust ourselves to the circumstances and should make esis that a short and steep delay gradient in ADHD will few acquirements" (Taylor, 1932 [13], p 437, cited in result in shorter and less predictable sequences in the [12], p. 701). Hypothetically, a narrow time window for behaviour of children with ADHD compared to controls, associating actions with its consequences may, through- and to explore an untraditional way of investigating out ontogenesis, detain the natural evolution of hierarchi- details in behavioural change. Traditional ways of analyz- cally controlled behavioural units of increasing ing behaviour in terms of means and standard deviations complexity. Further, with a short delay gradient, a dis- are too crude to identify moment-to-moment changes in criminative stimulus will not systematically be associated behaviour, and may not reveal the behavioural dynamics with reinforcement and the establishment of stimulus underlying more global concepts like impulsivity and Page 3 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 Table 1: Means, Standard Deviations, and t-Tests for Age, IQ, and Questionnaire Scores Groups Measure ADHD group Normal controls Group Comparison N = 15 N = 13 Mean SD Mean SD Age yr:mo (SD in mo) 7:6 9,5 7:10 9,4 p > .282, n.s. - range yr : mo 6:2 – 8:9 6:4 – 9:0 10.5 114.5 12.5 p < .04 IQ Full scale WISC-R 104.5 DBRS Teacher - inattention items 16.1 6.5 3.0 2.5 p < .001 - hyperactive/impulsive 18.4 8.0 2.0 2.5 p < .001 DBRS Parents - inattention items 16.7 6.0 4.1 2.1 p < .001 - hyperactive/impulsive 17.4 4.4 3.0 2.7 p < .001 CBCL - externalised T-score 68.2 8.9 38.9 7.5 p < .001 - internalised T-score 57.2 9.5 40.0 5.7 p < .001 - attention factor T-score 63.8 9.9 51.1 2.1 p < .001 TRF - externalised T-score 69.5 10.9 46.1 6.8 p < .001 - internalised T-score 57.5 9.5 45.0 7.2 p < .001 - attention factor T-score 60.5 6.5 50.4 1.0 p < .001 One case missing Two cases missing Disruptive Behaviour Rating Scale [16] Child Behaviour Checklist – parent form [30]. Teacher Report Form [30]. Two-tailed t-test for equality of means. Bonferroni adjustment of the p-level is set to p = .039. Results are highlighted after Bonferroni adjustment variability. The present study of behavioural sequences Methods applies autocorrelations of consecutive responses as a Participants means of studying moment-to-moment dynamics in The present study analyzed response data from 28 boys in responding. The data set was obtained from a study pre- the age range of 6:2–9:0 (yr:mo), 15 of whom had an sented previously [14] and is presently analyzed in a dif- ADHD diagnosis and 13 were healthy controls. These ferent way. boys represented the young age group from the previous study. The older children (aged 9.5–12 yr) from that study The task was a computerized game where mouse clicks on were not included, as the comparison group showed to be one of two squares on the screen resulted in the presenta- inadequate (see [14], for discussion). The details of the tion of a reinforcer. Reinforcers were delivered according recruitment and assessment procedures are presented to variable interval (VI) schedules, where responses result elsewhere [14]; only an outline of group characteristics is in a reinforcer after varying time intervals. With VI sched- provided here. ules a possible confusion of reinforcement effects with timing problems is avoided, as reinforcers are presented at Participants in the ADHD group were referred from differ- unpredictable times [15]. All mouse clicks were recorded ent clinical sources (school psychologists, child and ado- both in terms of where on the screen responses were lescent psychiatric units, habilitation services, and a placed (response location; spatial dimension) and private specialist centre) and were included if they met the response timing (temporal dimension). Thus, the present following criteria: 1) DSM-IV diagnosis of ADHD, of task allowed for analysis of both spatial and temporal either three subcategories; 2) Full Scale IQ of at least 80; aspects of behaviour. 3) no evidence of neurological disorder, psychosis, or per- vasive developmental disorder; and 4) not taking any medication within the last 48 hours prior to testing. A Page 4 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 diagnosis was confirmed after thorough clinical evalua- in cartoon presentations. Following reinforcer delivery, tion. Eight of the children had ADHD combined type, six the squares switched sides at random, keeping the total had ADHD hyperactive / impulsive type, and one child number of presentations on each side the same. had ADHD inattentive type. In addition, inclusion in the th ADHD group warranted a score at or above the 95 per- Variable interval (VI) schedules of reinforcement, where centile on the Disruptive Behaviour Rating Scale (DBRS) responses may produce reinforcers after the passage of [16] home or school version. varying time intervals [15], were used. Two VI schedules alternated, each signalled by a separate screen background Comparison children were recruited from schools in colour. The background colour functioned as the condi- urban and suburban areas of Oslo, the capital of Norway. tioned discriminative stimulus for the specific condition Inclusion criteria were the same as for the ADHD group, in operation, while the dark grey colour of the correct except that no DSM-IV diagnosis should be present. In square was the discriminative stimulus for the reinforcer. addition, they had to score below the sub-clinical range The two schedules were a short VI (VI 2s) signalled by a on the DBRS. navy blue background and a long VI (VI 20s) signalled by a bright yellow background. Intellectual ability was assessed by screening all children with four subtests (information, similarities, block design, There were two sessions, each of five segments. Each seg- and picture completion) of the WISC-R [17] (demo- ment consisted of four short and four long intervals, and graphic variables outlined in Table 1). was terminated by a response and the delivery of a rein- forcer. In the first session, the child would see a total of 40 Procedure reinforcers (cartoons). In the second session, the child The study was approved of by the Regional Medical Com- received a small tangible reinforcer (trinket, coin or sweet) mittee of Research Ethics. The parents of all the partici- in addition to the cartoon picture. This was done in order pants received written information about the study and to maintain reinforcer value. The entire task, including gave written consent for their child to take part. All chil- instruction, break between sessions, and a final, short dren were tested in quiet rooms, using the same tasks, interview with the child, took less than 30 min to apparatus, and test procedures (see [14] for details). complete. Reinforcement Task Data recording and statistics The task was designed as a computer game, and was pre- Data were recorded by the laptop. Response side (left or sented to the child with the following instruction (trans- right), response coordinates (i.e. the horizontal and verti- lated from Norwegian): "This is a game you may play now. It cal pixel that the tip of the arrow-shaped cursor touched is a little strange, because I will not tell you how to play the when the child clicked a mouse button), and interre- game. Your task is to find out how the game works. You may sponse times (IRTs) were the recorded dependent meas- use this mouse and move the arrow across the screen like this ures. The individual IRT distributions were highly skewed (experimenter demonstrates how to move the mouse). If you with a long tail towards long IRTs. IRTs were therefore want to point, you can click with one of these buttons (experi- normalized by log transformations prior to analysis menter points to the mouse buttons). You may talk while you (logIRT = log10 (IRT/1000 + 0.001)). are playing, but I will not answer any questions about the game. I will sit back here and write a little while you play. Do you Behavioural measures understand your task? You may start now." Data from the VI 20s condition was used to study response sequences, as the short schedule only allowed The task was run on a Toshiba Pentium 300 CDT laptop for one or a few responses before a reinforcer was deliv- connected to a colour monitor (see [14] for details). In ered. Predictability of responses over long sequences brief, response squares were two same-sized, aligned could theoretically be found according to different aspects squares on the screen, one in a light and the other in a of the behaviour, and in order to explore the different pos- dark shade of grey. The computer mouse was the response sibilities we computed three measures related to the spa- device. Clicks with either right or left button on one of the tial dimension and one measure related to timing. The squares induced a brief change in the grey shade as feed- first measure was a general side response pattern, i.e., back. Responses outside the squares were recorded, but whether consecutive responses were on the left or right did not result in any feedback. The dark grey square was side of the screen. Highly predictable responding would the "correct" target. Clicks within this square would, with probably be related to the side where the correct target was varying time intervals, result in a cartoon picture (rein- positioned, and would thus be a complementary measure forcer) appearing on the screen for 1.5 s together with a of stimulus control. Likewise, low predictability implies sound. Responses on the light grey square never resulted that responses are equally distributed on the two sides and Page 5 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 Table 2: Results from repeated measures ANOVA and multivariate tests for repeated measures, of explained variance (squared autocorrelations) Measure Variable ANOVA Multivariate Df F Df F Side Response Pattern Group (G) 1, 26 14,700*** Session (Ses) 1, 26 1,136 1, 26 1,136 Segment (Seg) 4, 104 11,684*** 4, 23 5,317** Lag 4, 104 143,735*** 4, 23 42,369*** G * Seg 4, 104 4,756*** 4, 23 2,824* G * Seg * Lag 16, 416 1,810* 16, 11 1,675 Square Response Pattern G 1, 26 10,981** Ses 1, 26 2,505 1, 26 2,505 Seg 4, 104 1,290 4, 23 0,721 Lag 4, 104 91,581*** 4, 23 28,576*** G * Lag 4, 104 8,779*** 4, 23 5,097** G * Ses * Lag 4, 104 2,812* 4,023 1,681 Target Response Pattern G 1, 26 3,083 Ses 1, 26 1,061 1, 26 1,061 Seg 4, 104 4,127** 4, 23 3,131* Lag 4, 104 201,232*** 4, 23 60,921*** G * Lag 4, 104 1,232 4, 23 3,172* Timing Response Pattern G 1, 26 0,155 Ses 1, 26 6,793** 1, 26 6,793** Seg 4, 104 2,125 4, 23 1,253 Lag 4, 104 41,613*** 4, 23 13,364*** G * Ses 1, 26 5,116* 1, 26 5,116* G * Ses * Lag 4, 104 4,326** 4, 23 2,499 * : p < .05; **: p < .01; ***: p < .001 Due to a very large number of possible interactions, only main effects and significant interactions involving the group variable are reported. All non-published results may be obtained from the first author. is thus also a measure of low stimulus control. Next, due second lag, and so on up to correlations between n and to the fact that reinforcers affect more responses than the n+5 response being the fifth lag). The autocorrelations one that produces it (Figure 1), predictable patterns in were computed for each individual over sessions and seg- other aspects of response locations were explored. The ments. We predicted that the behaviour of children with square response pattern measure was based on the distance ADHD would be characterized by lower autocorrelations from the centre of the selected square, whether correct or and that their autocorrelation curves across lags would be not, to the spot where the response was placed. The target steeper compared to the behaviour of healthy comparison response pattern measure was based on the distance from children. the centre of the correct response target to where the response was placed. Both distance scores were in terms of Statistics pixels, with the centre of the square defined as 0,0. Finally, Data were analyzed by means of SPSS 11.0 for Windows response sequences might be predicted by patterns in tim- (SPSS) and Statistica 6.1 [18] program packages. The dis- ing. Thus, timing response patterns were analyzed based on tance scores were computed as the square root of the sum consecutive interresponse times (IRTs). of squared horizontal and vertical distances. Explained variance (autocorrelations squared) was analyzed using The ordering of responses spatially and temporally was repeated measures ANOVA over sessions, segments, and assessed by autocorrelations. Autocorrelations (serial cor- lags. The ANOVA was supplemented with MANOVA. A relations) of each measure were correlations of consecu- multivariate approach to repeated measures of more than tive values over five lags (correlations between n and n+1 two levels is recommended because it bypasses the response is the first lag, between n and n+2 response is the assumption of compound symmetry and sphericity [18]. Page 6 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 Clinical group (2) was the between-group variable; and parison group there was a general within-session upward session (2), segment (5), and lag (5) were within-group trend from segment 1 to 4, indicating a learning effect, but variables. this trend did not continue into the last segment of each session (see Figure 2). The ADHD group did not show a Demographic data similar pattern; explained variance did not improve dur- Demographic and diagnostic measures of the ADHD and ing the task. This group difference was supported by a sig- the comparison group were tested with two-tailed t-tests nificant three-way ANOVA interaction between Group, for equality of means and are displayed in Table 1. There Segment, and Lag. However, this interaction was not con- were significant differences between groups on all meas- firmed by the MANOVA. ures including IQ, but not age. Whether to control for IQ Square response pattern difference has been debated (e.g., [19]) as undue weight may be put on the impact of IQ and remove variance that This measure assessed to what degree the children tended is a result of ADHD itself. Running the analyses with IQ as to respond in any predictable pattern in terms of the dis- a covariate and without gave a similar overall picture of tance between responses, anchored to the centre of the results. Thus, IQ was not included as a covariate in the square that responses were placed within (whether it was reported analyses. (All non-published results may be the correct response target or not). Highly predictable obtained from the first author upon request.) responding would imply that behaviour was ordered in sequences of similar distances between responses. Again, Results the explained variance for the ADHD group was lower In general, acquisition of predictable response sequences than for the comparison group (Figure 3). Explained vari- was found in the spatial measures and not in the temporal ance in the first lag for the ADHD group were in the low 2 2 measure. The ADHD group had significantly lower auto- range (0.25 > mean R > 0.13; median R = 0.18), indicat- correlations than the comparison group on two of the ing that there was rather low predictability from one three spatial measures. Both groups had very low autocor- response to the next. For the comparison group, explained relations related to response timing. There was no Session variance in the first lag was higher (0.51 > mean R > 0.22; effect on the three spatial measures, but the main effect of median R = 0.42). Lag was significant for all four measures. Results of the planned analyses with ANOVA and MANOVA are shown There were significant main effects of Group and Lag, but in Table 2. not of Session and Segment (Table 2). A significant ANOVA interaction between Group and Lag was con- Side response pattern firmed by the multivariate analysis, while the significant This measure assessed whether responding predictably interaction between Group, Session, and Lag was not con- would continue on the same side or vary unpredictably firmed by the MANOVA. between sides, irrespective of on which side the correct Target response pattern response target was displayed (see Behavioural measures in Methods for a detailed description of the variables). This measure assessed patterns of response placements in Highly predictable responding over lags would imply that terms of distance from the centre of the correct square. behaviour was ordered in sequences related to side. Less Highly predictable responding would imply that behav- variance was accounted for in the ADHD group than in iour was ordered in sequences of similar distances the comparison group. For the ADHD group, explained between responses, specifically related to the centre of the variance in the first lag across segments was low (range correct square. Again, low explained variance indicated 2 2 0.33 > mean R > 0.22, median R = 0.26), while it was in high variability in responding. Explained variance in the the upper range for the comparison group (0.62 > mean first lag across segments of the ADHD group was in the 2 2 2 2 R > 0.35; median R = 0.50) (Figure 2). Actually, in some middle range (0.46 > mean R > 0.27; median R = 0.40), segments, explained variance over all five lags was higher and slightly higher for the comparison group (0.60 > 2 2 for the comparison group than in the first lag for the mean R > 0.36; median R = 0.41) (Figure 4). ADHD group. In addition, explained variance in these segments did not descend much from the first to the fifth The main effects of Segment and Lag were statistically sig- lag (not shown), indicating highly predictable response nificant, but not the main effects of Group or of Session sequences for up to six responses for the comparison (Table 2). The MANOVA, but not the ANOVA, showed a group. two-way interaction between Group and Lag. There were no other significant interactions. As can be seen in Figure There were significant main effects of Group, Segment, 4, the curves are quite similar for the two groups, but and Lag (Table 2). In addition, there was a significant two- explained variance tends to be lower in lags 2–5 in the way interaction between Group and Segment. In the com- ADHD group compared to the comparison group. Page 7 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 0.6 ADHD Comparison 0.5 0.4 0.3 0.2 0.1 0.0 1 2345 12 345 12 345 12 345 12 345 Segm. 1 2 3 4 5 Response pattern according t Figure 2 o side of the screen Response pattern according to side of the screen. Predictability of which side of the screen consecutive responses were placed, depicted as mean explained variance (autocorrelations squared), by segments (1–5) and lags (1–5 per segment), for ADHD and comparison groups. Graphs show means of session 1 and session 2. Timing response pattern than the comparison group in the first session, the com- The development of patterns in response timing was parison group had lower explained variance than the investigated by means of consecutive interresponse times ADHD group in the second session. The significant inter- (IRTs). Explained variance of the first lag was generally action between Group, Session, and Lag in the ANOVA very low and not significantly different between the was not confirmed by the MANOVA. 2 2 groups (0.06 > mean R > 0.12; median R = 0.06 for 2 2 ADHD, and 0.16 > mean R > 0.02; median R = 0.1 for Relation to clinical scores comparisons). The significant main effect of Session The dynamic developmental theory (DDT) argues that a showed that explained variance was lower in the second shortened delay gradient probably relates more to the session than in the first, particularly for the comparison hyperactive / impulsive and the combined subtypes of group. The main effect of Lag was significant, while the ADHD than to the inattentive subtype [2]. The present main effect of Segment was not. There was a significant sample did not allow for a differential analysis of clinical interaction effect between Group and Session, showing subtypes. However, the relation between the individual that while the ADHD group had lower explained variance scores on the sub-dimensions of ADHD and explained Page 8 of 14 (page number not for citation purposes) Side Response Pattern Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 0.6 ADHD Comparison 0.5 0.4 0.3 0.2 0.1 0.0 1 2345 1 2345 12 3 4 5 12 3 4 5 1 2 345 Segm. 1 2 3 4 5 Response pattern according t Figure 3 o distance from the centre of a square Response pattern according to distance from the centre of a square. Predictability of distance from the centre of the chosen square, whether correct or not, to where on the screen consecutive responses were placed. Curves show mean explained variance (autocorrelations squared) by segments (1–5) and lags (1–5 per segment), for ADHD and comparison groups. Graphs show means of session 1 and session 2. variance on the spatial measures could be computed and 1 as a predictor of scores on the DBRS. The explained var- would indicate if either the hyperactive / impulsive iance of the side response pattern was the best predictor of dimension or the inattentive dimension were better pre- scores on the DBRS, with increasing correlation over lags dictors of the explained variance. Thus, mean explained (Figure 5, solid line). variance across lags for each spatial measure was correlated with sum scores of the inattentive and the Discussion hyperactive / impulsive dimensions on the DBRS parent The present study investigated the predictability of behav- form [16]. The correlations showed an inverse relation- ioural sequences in ADHD and in comparisons. The aims ship between scores on the rating scale and predictability of the study was both to investigate the hypothesis that a of responses, indicated by negative values (Figure 5). Cor- shortened delay gradient in ADHD would result in short relations between the explained variance and the two sub- and less predictable response sequences in the behaviour dimensions on the DBRS were not very different, but of children with ADHD [2], and to explore the use of explained variance from session 2 was better than session autocorrelations as a way of analyzing details in Page 9 of 14 (page number not for citation purposes) Square Response Pattern Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 0.6 ADHD Comparison 0.5 0.4 0.3 0.2 0.1 0.0 1 2345 1 2345 12 3 4 5 12 3 4 5 1 2 345 Segm. 1 2 3 4 5 Response pattern according t Figure 4 o distance from the centre of the correct target Response pattern according to distance from the centre of the correct target. Predictability of distance from the centre of the correct target to where on the screen consecutive responses were placed. Curves show mean explained vari- ance (autocorrelations squared) by segments (1–5) and lags (1–5 per segment), for ADHD and comparison groups. Graphs show means of session 1 and session 2. behavioural dynamics. Consecutive responding was stud- tern, but not according to target response pattern or timing ied in terms of three spatial and one temporal response response pattern. This was supported by the high correla- dimensions. The results showed that predictable response tions between variance accounted for in consecutive sequences did develop according to the spatial response response lags of these two spatial measures and the scores dimensions, but not according to the temporal dimen- on both hyperactive/impulsive and inattentive clinical sion. Importantly, on the spatial dimensions, predictabil- dimensions (Figure 5). Thus, the disorganized behaviour ity of response sequences was considerably lower for the observed in the ADHD group may be a general behav- ADHD group than for the comparison group, as shown by ioural feature captured by the clinical scoring by teachers significant interactions involving group and lag (number and parents. of consecutive responses). In addition, the overall explained variance of the ADHD group responding was The side response pattern assessed whether responding significantly lower than that of the comparison group could be predicted according to side (left or right) of the according to side response pattern and square response pat- screen, irrespective of on which side the correct target was Page 10 of 14 (page number not for citation purposes) Target Response Pattern Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 However, there was a drop in explained variance in the comparison group at the end of each session (Figure 2, -0,60 segment 5). This may have been an effect of the schedule, as the VI schedule was made up of predefined interval lengths, with more of the short intervals in the beginning -0,50 of the session and more of the longer intervals towards the end. Hence, the disappearance of regular, predictable responding seen in the comparison group may have been the result of inter-reinforcement intervals being very long. -0,40 This effect was not seen in the ADHD group. The square response pattern and the target response pattern -0,30 were both computed in order to explore possible patterns related to the spatial distance between responses, anchored to the centre of the squares. Organizing -0,20 responding within the squares was not differentially rein- forced. However, a shortened time window available for Side Response Pattern strengthening connections between events, as suggested Square Response Pattern by the DDT [2], predicts less systematic response patterns -0,10 Target Response Pattern in ADHD compared to normal, which was found. The square response pattern measured distances from the centre of the chosen square to where the response was placed. -0,00 The comparison group showed significantly more predict- able responding than the ADHD group, both overall and 12 3 4 5 across lags, indicated by the significant interaction Lag between group and lag. The target response pattern meas- ured the distance from the centre of the correct square to Relation b an Figure 5 d clinicae l scor tween es explained variance of responding over lags where the response was placed. The similar magnitude of Relation between explained variance of responding explained variance (about 40–50%) in the first lag of the over lags and clinical scores. A correlogram showing the two groups indicates high predictability from response n relation between mean explained variance (autocorrelations to n+1 when in the correct square, while the ADHD group squared) by lags and scores on the hyperactive / impulsive varied more on consecutive responses as indicated by the items of the Parent form of the Disruptive Behaviour Rating significant interaction between group and lag. Scale (DBRS) for the three spatial measures in session 2. The relation was negative; i.e. high scores on the DBRS predicted Increased variability is a consequence of reduced stimulus low scores on the autocorrelations. control. This is seen in the ADHD group in terms of the side response pattern. Therefore, it might be argued that the reduced predictability found in both square response pat- tern and target response pattern is a consequence of larger arm movements in the ADHD group because of more var- displayed. The significant group difference implied a ied responding from side to side, rather than an effect of highly predictable pattern in the comparison group, indi- inefficient reinforcement of response placement within a cating that these children varied their responding between square. The present analysis did not allow identifying pre- sides almost only to the extent that the correct target dictability of response placements when consecutive square switched sides on the screen. This was supported responding was within the same square, which involves by their mean percent correct responding at 87% during smaller movements. However, disentangling the variabil- stable state [14], demonstrating good discriminative con- ity related to larger arm movements and the variability trol. The ADHD group, however, varied their responding related to decreased stimulus control (revealed as more between sides even though the correct target square was varied responding) may not be feasible. Further, it may be still on the same side, and they never exceeded 61% cor- speculated that, since the striatum, which is involved in rect responses [14]. The comparison group showed pre- the planning and execution of motor actions, and the dictable sequences of up to six responses where variance nucleus accumbens, which is involved in learning and accounted for was larger for the n+5 response than for n+1 reinforcement, both receive important dopaminergic response in the ADHD group (e.g. Segments 2 and 3 in afferents, these functional processes may both be Figure 2). impaired in an individual with ADHD [2]. Page 11 of 14 (page number not for citation purposes) Pearson Correlation (r) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 Acquisition of functional behavioural sequences may be results indicate a different style of learning in ADHD, related to processes involved in habit learning. Habit probably brought about by inefficient dopaminergic learning is characterized by a transition from response- processes, which might be regarded as a separate endo- consequence associations that are flexible and sensitive to phenotype of ADHD [3,23] that forms the development reinforcement devaluation, to stimulus-response associa- of behavioural characteristics of variability, impulsive- tions that are less flexible and sensitive (e.g. [20]). Thus, ness, lack of goal-directed behaviour, and hampered the initial part of habit learning may mainly involve activ- development of self-control. Such a learning style may ity in the mesolimbic dopaminergic branch, while the explain the heterogeneity in symptom presentations established habit and the skilled execution of the motor among individuals with ADHD, because the behaviour of sequence may mainly involve the nigrostriatal dopamin- different individuals will be the result of interactions with ergic branch. It may be argued that the present study is different environmental contingencies. mainly concerned with acquisition, since the task was new and relatively short. On the other hand, animal model Other interpretations are possible, however. It has been studies have indicated that operant learning rapidly suggested that the length of delay gradients may be become habitual when the contingency between the dependent on working memory (WM) capacity because response and reinforcer is weakened by using interval the ability to relate sensory information to responses and schedules [20], as used in the present study. Hence, it reinforcing stimuli seems to correlate with ongoing neu- might be speculated that the control group rapidly ronal activity in prefrontal cortex [24]. Behavioural developed a habit, while this process was hampered in the sequences or serial movement has been related to WM ADHD group. Whether the present findings are due to capacity, as it has been argued that serial sensory informa- impairments in habit formation or motor control related tion is stored in WM and converted into a movement pro- to the striatum, or to learning deficits related to nucleus gram with the help of visual stimuli [25]. There is accumbens cannot be settled, but the DDT predicts dys- obviously some kind of memory process involved in rein- function of both processes [2]. forcement, and the delay gradient may as well be described as the result of pairing the reinforcer with the Explained variance of first lag (and following lags) was fading of precursors, e.g., the fading of memory traces of too low to conclude that there was any predictability in the behaviour [3,26]. For the present analysis, it is not crit- IRTs. Thus, there was no timing response pattern. Specula- ical if a shorter delay gradient in ADHD is caused by tively, this lack of a predictable timing pattern could be reduced WM capacity or if both are expressions of under- related to the visuo-spatial nature of the task, both in lying dysfunctioning dopamine systems. Further, WM terms of response alternatives (where, not when) and in capacity is not necessarily a fixed entity and may also be terms of the reinforcer. There is some evidence that striatal modified by learning: a recent study reports that WM was neurons involved in sequential habit learning may encode improved in ADHD children by computerized training visuo-spatial information rather than temporal [21]. [27]. The present findings indicate that the delayed learn- ing of a new task is related to reduced predictability in The present findings suggest that the learning of coherent consecutive responding of ADHD individuals and not, for and predictable behavioural sequences will be difficult in instance, to increased activity in general [14] or to children with ADHD, probably because the time window increased perseveration, which would be the opposite of available for reinforcers to work is narrower in ADHD low predictability. compared to normal. Skilled performance is characterized by responses emitted with brief interresponse intervals, There might be alternative motivational explanations smooth transitions between responses, and efficient coor- (than a shorter delay gradient) for the behaviour observed dination of consecutive movements so that a whole in the ADHD group. Rather than a reduced effect of posi- sequence is conducted in a predictable manner (e.g. [22]). tive reinforcement (i.e., the delivery of a reinforcer), the Reinforcers are actively involved in the selection and behaviour may be a result of reduced negative control shaping of responses, in chunking discrete responses into (i.e., reduced compliance). However, non-compliance larger behavioural units, and in establishing relations would have involved refusal to complete the task, which between antecedent stimuli and behavioural units into none of the children did, and most of them even reported sequences that together constitute a complete action (e.g. that the task was fun. In addition, the instruction was non- sequences of behavioural units comprising the entire directive, excluding the possibility of non-compliance to action of typing a word, writing your signature, or playing any instructed response pattern. A group of children aged an arpeggio on the piano). With a shorter delay gradient, 9–12 yr also participated in the original study, but the the whole process of organizing hierarchical structures of results of the comparison group indicated that their actions comprised of functional units of behaviour may responding was mainly compliant and not controlled by be hampered in ADHD. Although speculative, the present reinforcers, as shown by lack of schedule control [14]. The Page 12 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 behaviour of the younger children that participated in the approach the time-scale of brain processes and we may get present analysis did show schedule control, but the closer to directly measure brain-behavioural interactions. response patterns were different. In this perspective, concepts like working memory, inhibi- tion, and even timing problems may be too wide concepts The present study provides new insights into the recently to identify the underlying learning style, because a learn- started discussion of intra-individual ADHD-related vari- ing style characterized by inefficient chunking or develop- ability (ARV; [28]). Castellanos et al [28] calls for system- ment of entire behavioural sequences may be manifest in atic studies of moment-to-moment changes in ongoing different domains in different individuals. One might behaviour and to integrate such studies into causal mod- speculate that sequencing of motor action and sequencing els. The present study shows that ARV is found in other of speech and thought may be of the same functional ori- domains than reaction times, that it may be influenced by gin (cf., [29]). Thus, sequencing deficits in ADHD may reinforcement contingencies, and that it might be cause problems with rule-governed behaviour and self- explained by a short and steep delay gradient. Although control typical in ADHD behaviour. the present study is purely behavioural, it might provide a framework within which to analyze several parallel proc- Competing interests esses, including cardiovascular and neurophysiologic, as The author(s) declare that they have no competing suggested by Castellanos et al [28]. interests. Some limitations of the present study could be improved Authors' contributions in future studies. First, the findings need to be replicated HA participated in the development of the study design, in a larger sample of children. New samples, including development of the reinforcement task used, carried out girls and children of other ages, need to be analyzed in the data collection, prepared the data, performed the sta- order to verify if this behavioural style is general to tistical analyses, and wrote the manuscript. TS partici- ADHD, whether it may be identified at an earlier age, and pated in the development of the study design, whether it continues to constitute an important factor in development of the reinforcement task, wrote the pro- the behaviour of older children. Children with other psy- grams for statistical analyses, participated in data analyses, chopathologies should be added in order to establish the read the manuscript and approved the final draft. specificity of this learning style. Second, the present task may be criticized for its lack of ecological validity. On the Acknowledgements The present study was supported by grants from The National Council for other hand, the present task may have been optimal for Mental Health – Norway (Heidi Aase) and from The University of Oslo. We studying ordering and sequencing of responses, as no ear- thank Professor Edmund Sonuga-Barke, University of Southampton, for val- lier experience or learning history would interfere. In the uable discussions during the development of the reinforcement task, and future, a wide range of serial or sequential tasks should be Mr. Martin Hall, University of Southampton, for programming it. Professor investigated because the dynamic developmental theory Peter Killeen contributed with valuable insights during data analyses. of ADHD predicts that the presently-observed learning style should be found in the behaviour of people with References ADHD across tasks and activities. Finally, various serial 1. American Psychiatric Association: Diagnostic and statistical manual of mental disorders: DSM-IV 4th edition. Washington, D.C.: Author; 1994. tasks could be conducted during brain imaging in order to 2. Sagvolden T, Johansen EB, Aase H, Russell VA: A dynamic develop- investigate the brain areas involved. mental theory of Attention-Deficit /Hyperactivity Disorder (ADHD) predominantly hyperactive/impulsive and com- bined subtypes. Behav Brain Sci 2005, 28:397-419. Conclusion 3. Johansen EB, Sagvolden T, Aase H, Russell VA: The dynamic devel- The present findings provide support for the dynamic opmental theory of attention-deficit/hyperactivity disorder (ADHD): Present status and future perspectives. Behav Brain developmental theory of ADHD predicting that a short Sci 2005, 28:451-454. and steep delay-of-reinforcement gradient will result in 4. Yan JH, Thomas JR: Arm movement control: differences fewer responses in a predictable sequence than when the between children with and without attention deficit hyperac- tivity disorder. Res Q Exerc Sport 2002, 73:10-18. delay gradient is normal [2]. The hypothesized difference 5. Yan JH, Thomas KT, Stelmach GE, Thomas JR: Developmental dif- in timing patterns did not appear in the present study, as ferences in children's ballistic aiming movements of the arm. none of the groups showed any predictability in timing Percept Mot Skills 2003, 96:589-598. 6. Sheppard DM, Bradshaw JL, Georgiou N, Bradshaw JA, Lee P: Move- patterns. ment sequencing in children with Tourette's syndrome and attention deficit hyperactivity disorder. Mov Disord 2000, 15:1184-1193. The present study represents a new approach to analyzing 7. Kalff AC, de Sonneville LM, Hurks PP, Hendriksen JG, Kroes M, Feron the micro-dynamics of consecutive responses in a FJ, et al.: Low- and high-level controlled processing in execu- moment-to-moment manner. A majority of the responses tive motor control tasks in 5-6-year-old children at risk of ADHD. J Child Psychol Psychiatry 2003, 44:1049-1057. were emitted with IRT < 1s. The study of behavioural proc- esses and their environmental correlates may thus Page 13 of 14 (page number not for citation purposes) Behavioral and Brain Functions 2005, 1:12 http://www.behavioralandbrainfunctions.com/content/1/1/12 8. Siklos S, Kerns KA: Assessing multitasking in children with ADHD using a modified Six Elements Test. Arch Clin Neuropsychol 2004, 19:347-361. 9. Schultz W, Dayan P, Montague PR: A neural substrate of predic- tion and reward. Science 1997, 275:1593-1599. 10. Lashley KS: The problem of serial order in behavior. In Cerebral mechanisms in behavior Edited by: Jeffress LA. New York: Wiley; 1951:112-136. (Reprinted in The neuropsychology of Lashley. Edited by Beach FA, Hebb DO, Morgan CT, & Nissen HW. New York: McGraw-Hill 1960:506–528) 11. Averbeck BB, Chafee MV, Crowe DA, Georgopoulos AP: Parallel processing of serial movements in prefrontal cortex. Proc Natl Acad Sci U S A 2002, 99:13172-13177. 12. Rhodes BJ, Bullock D, Verwey WB, Averbeck BB, Page MP: Learning and production of movement sequences: behavioral, neuro- physiological, and modeling perspectives. Hum Mov Sci 2004, 23:699-746. 13. Taylor J, Ed: Selected writings of John Hughlings Jackson London: Hodder and Stoughton; 1932. 14. Aase H, Sagvolden T: Infrequent, but not frequent, reinforcers produce more variable responding and deficient sustained attention in young children with Attention-Deficit/Hyperac- tivity Disorder (ADHD). J Child Psychol Psychiatry in press. 15. Catania AC: Learning 4th edition. N.J. Englewoods Cliffs: Prentice Hall, Upper Saddle River; 1998. 16. Barkley RA, Murphy KR: Attention-Deficit Hyperactivity Disorder: A Clini- cal Workbook 2nd edition. New York: Guilford Press; 1998. 17. Wechsler D: Wechsler Intelligence Scale for Children – Revised. Trondheim, Norwegian Psychology Association; 1974. 18. StatSoft Inc: STATISTICA for Windows [Computer software]. Tulsa, OK: StatSoft Inc; 1974. 19. Seidman LJ, Biederman J, Faraone SV, Weber W, Ouellette C: Toward defining a neuropsychology of attention deficit- hyperactivity disorder: performance of children and adoles- cents from a large clinically referred sample. J Consult Clin Psychol 1997, 65:150-160. 20. Yin HH, Knowlton BJ, Balleine BW: Lesions of dorsolateral stria- tum preserve outcome expectancy but disrupt habit forma- tion in instrumental learning. Eur J Neurosci 2004, 19:181-189. 21. Schmitzer-Torbert N, Redish AD: Neuronal activity in the rodent dorsal striatum in sequential navigation: separation of spatial and reward responses on the multiple T task. J Neurophysiol 2004, 91:2259-2272. 22. Matsumoto N, Hanakawa T, Maki S, Graybiel AM, Kimura M: Role of [corrected] nigrostriatal dopamine system in learning to perform sequential motor tasks in a predictive manner. J Neurophysiol 1999, 82:978-998. 23. Coghill D, Nigg J, Rothenberger A, Sonuga-Barke E, Tannock R: Whither causal models in the neuroscience of ADHD? Dev Sci 2005, 8:105-114. 24. Tannock R: Hypodopaminergic function influences learning and memory as well as delay gradients. Behav Brain Sci 2005, 28:419-451. 25. Ohbayashi M, Ohki K, Miyashita Y: Conversion of working mem- ory to motor sequence in the monkey premotor cortex. Sci- ence 2003, 301:233-236. 26. Killeen P: Gradus ad Parnassum. Behav Brain Sci 2005, 28:419-451. 27. Klingberg T, Fernell E, Olesen PJ, Johnson M, Gustafsson P, Dahlstrom K, et al.: Computerized training of working memory in chil- dren with ADHD – a randomized, controlled trial. J Am Acad Child Adolesc Psychiatry 2005, 44:177-186. Publish with Bio Med Central and every 28. Castellanos FX, Sonuga-Barke EJ, Scheres A, Di Martino A, Hyde C, scientist can read your work free of charge Walters JR: Varieties of attention-deficit/hyperactivity disor- der-related intra-individual variability. Biol Psychiatry 2005, "BioMed Central will be the most significant development for 57:1416-1423. disseminating the results of biomedical researc h in our lifetime." 29. Aldridge JW, Berridge KC: Coding of serial order by neostriatal Sir Paul Nurse, Cancer Research UK neurons: a "natural action" approach to movement sequence. J Neurosci 1998, 18:2777-2787. Your research papers will be: 30. Achenbach TM, Howell CT, Quay HC, Conners CK: National sur- available free of charge to the entire biomedical community vey of problems and competencies among four- to sixteen- year-olds: parents' reports for normative and clinical peer reviewed and published immediately upon acceptance samples. Monogr Soc Res Child Dev 1991, 56:1-131. cited in PubMed and archived on PubMed Central yours — you keep the copyright BioMedcentral Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp Page 14 of 14 (page number not for citation purposes)
Journal
Behavioral and Brain Functions – Springer Journals
Published: Aug 1, 2005