The influence of stimulus material on attention and performance in the visual expectation paradigm

Abstract

This longitudinal study examined the influence of stimulus material on attention and expectation learning in the visual expectation paradigm. Female faces were used as attention-attracting stimuli, and non-meaningful visual stimuli of comparable complexity (Greebles) were used as low attention-attracting stimuli. Expectation learning performance was operationalized using the average reaction time and number of anticipations. For the measurement of attention, the percentage of trials with on-task attention behavior was calculated. To analyze attention and differences in performance, a total of 108 German infants (3–6 months of age) were assessed. Significant differences were found between the two types of stimuli concerning the infants’ rate of attention and anticipations. The results indicate learning material to influence attentional processes and expectation learning.

Keywords

attention expectation learning faces Greebles infancy stimulus material visual expectation paradigm

Expectation learning is understood as the ability to anticipate environmental contingencies based on the ability to develop expectancies for future events. Thus expectation learning is an important component of future-oriented thinking. The ability to learn expectations in infancy has important implications for later intellectual functioning. As previous studies have shown, expectation learning abilities of infants are significantly related to processing speed during childhood and intelligence quotient (IQ) at 4 years of age (cf. Benson, Cherny, Haith, & Fulker, 1993; Cardon & Fulker, 1991; DiLalla et al., 1990; Domsch, Lohaus, & Thomas, 2009; Dougherty & Haith, 1997). Therefore expectation learning as an indicator of processing speed may be a central intellectual ability and a key element for reasoning and memory (e.g., Fagan, 2000; Kail, 2000).

However, additional cognitive components seem to have an influence on the mental performance of infants. Colombo (2001) suggests that attention also plays an important role, besides processing speed (cf. Rose, Feldman, & Jankowski, 2004). Learning material in particular might play an important role for the attention attraction process, whilst also influencing the child’s mental performance. However, the influence of the learning material on attention and the benefits it harbours for expectation learning in infancy has been scarcely explored in the past. This study, therefore, focuses on the impact of learning material on attention processes and performance in an expectation learning task.

Infants’ expectation learning

Expectation learning is usually assessed with the visual expectation paradigm (VExP). This is a dynamic action perception task, developed by Haith and colleagues (Haith, Hazan, & Goodman, 1988; Haith, Wentworth, & Canfield, 1993). In the VExP, a series of stimuli is presented in a sequence following an inherent rule. The easiest version would be to present a stimulus alternately on the left and on the right side of a screen. Infants are expected to learn that the left stimulus follows the right and that the right stimulus follows the left. Once this rule is learned, infants’ perception speed regarding stimulus presentation generally increases. The latency of the infant’s eye movements also decreases across the presentation of the learning trials (reduced reaction time across stimulus presentations). Ideally the infant looks in an anticipatory manner to the side of the screen where the next stimulus will appear, even before the stimulus appears (cf. Canfield, Smith, Brezsnyak, & Snow, 1997). Following traditional conventions, an eye movement is classified as anticipatory once the reaction time (RT) is 200 milliseconds (ms) and less, after the appearance of the new target stimulus (Rose, Feldman, Jankowski, & Caro, 2002). The typical indicators for information processing in the VExP are: (a) the average RT; and (b) the amount of anticipatory eye movements across the learning trials (cf. Canfield et al., 1997).

Past research has shown that expectation learning in the VExP starts at approximately 2–3 months of age, and continuously improves up to 9 months of age (Canfield et al., 1997; Haith et al., 1988; Reznick, Chawarska, & Betts, 2000). However, this developmental pattern has only been shown for average RT. The results concerning the percentage of anticipatory eye movements are somewhat more ambiguous. Whilst Rose et al. (2002) found an increase in anticipatory performance, other studies indicate contradictory results (e.g., Canfield et al., 1997). The differences might be explained through the use of different cut-off points for the definition of an anticipatory eye movement, or through the use of presentation rules with different complexities (cf. Canfield et al., 1997; Rose et al., 2002).

The influence of the learning material in the VExP

The use of different kinds of stimuli might influence the outcomes of experimental studies used in infancy (e.g., Rose, 1989). For example, Fassbender et al. (2011) used a sample of German infants and Caucasian faces as familiar ethnic stimuli, whilst African faces were used for the unfamiliar ethnic category. The results from this study showed a significant decrease in RT for the Caucasian faces condition for the 6-month-old infants, but not in the African faces condition, thus indicating that the kind of stimuli (familiar vs. unfamiliar faces) impacts the performance in the VExP. Additionally, irregularities of the stimulus material used in the VExP can lead to a decrease in anticipatory performance (cf. Adler & Haith, 2003). This supports the assumption that the stimulus material is in fact an important influence on the learning process of visuo-spatial contingencies in the VExP. It can, therefore, be assumed that the kind of stimulus material modulates the infants’ attention. Results of previous studies showed, for example, that the properties of stimuli (like stimulus complexity or stimulus movements) influence the attention of infants (Slater & Lewis, 2007). The sensory information held by a stimulus may be better encoded if attention is directed towards the stimulus (Goldstein, 2008). Therefore the attributes of a stimulus might be important for the attention attraction process, which consequently might lead to an improved performance.

Faces are considered to be highly salient and biologically significant visual stimuli. During infancy faces are especially prioritized, which can be attributed to the helplessness of infants. To survive, infants need to interact with other people to communicate their needs (Keller, 2000). Even newborns are able to distinguish faces and face-like patterns from other stimuli, despite their incomplete developed visual perception skills (e.g., Goren, Sarty, & Wu, 1975; Macchi Cassia, Turati, & Simion, 2004), For example, Valenza, Simion, Macchi Cassia, and Umilta (1996) found that newborns preferred schematic faces in comparison to other stimuli of identical complexity (cf. Goren et al., 1975; Johnson & Morton, 1991). The prominent role of human faces as stimuli might be a result of a high biological significance of these stimuli for the child. Therefore it can be assumed that human faces lead to an attention increase in the VExP.

Measurement of attention in the VExP

For the measurement of attention, it is important to note that infants are free to choose in the VExP whether to look at the stimulus or not. An important factor indicating inattentiveness is non-task-related behavior, which is termed off-task behavior. The off-task behavior is defined through looking away from the presented stimuli, closing eyes and other behaviors that prevent the infant from looking towards the stimuli (Canfield et al., 1997; Rose et al., 2002). To determine the attention level, Canfield and colleagues (1997) proposed the use of the number of off-task trials in relation to the number of total trials. In most studies, off-task behavior is used to identify and to exclude inattentive infants from the analysis. However, measures of the amount of on- and off-task behavior may be used to analyze the influence of the stimulus material on attention and on the performance in the VExP.

Current study

This study focuses on the meaning of stimulus material and the influence it has on attention (the amount of on-task-behavior) and performance in the VExP. To replicate previous findings, we expected attention and performance to increase continuously with age (hypothesis 1) and performance to increase across trials (hypothesis 2). More importantly, it is hypothesized that meaningful stimulus material (facial stimuli) increases attention and also performance across trials in the VExP, in comparison to non-meaningful visual stimuli of comparable complexity (hypothesis 3). The age (3 months vs. 6 months) was also included as an additional independent variable, thus allowing the testing of possible age effects. For the analysis of these hypotheses in the VExP task, female faces were used as high attention-attracting stimuli and Greebles as low attention-attracting stimuli. Greebles were chosen as they were designed as control stimuli for faces. Greebles were constructed with an equal number of parts and similar properties as faces. However, the human visual system does not treat Greebles as faces (see Gauthier, Behrmann, & Tarr, 2004; Gauthier & Tarr, 1997).

Method

Participants

One hundred and eight Caucasian infants (55 boys and 53 girls) were assessed at 3 months, and reassessed at 6 months of age. Seven additional infants had to be excluded due to fussiness, technical or experimenter errors. Infants were recruited from middle and upper middle-class families in a German urban area via newspaper advertisements or letters of invitation sent to the parents of newborn children. By offering the parents a small financial incentive they were motivated to participate in the repeated assessments. The infants included in the data analysis were born at term and, except for minor illnesses, had been healthy since birth. The mean age (in days) at the first point of measurement was 95.5 days (SD = 4.6) and 187.3 days (SD = 5.1) at the second point. Written consent was obtained from all parents prior to participation.

Procedure

Parents first brought their infants to the laboratory where they were given instructions and received detailed information about the procedure. The parents were also asked to answer questions concerning demographic information and medical preventive checkups. If the infants had been classed as quiet and alert, they were seated on their parent’s lap, inside an enclosure measuring 94.5cm × 96.5cm × 164cm and which was opened on one side. The ceiling and the three walls were covered using a dim grey sound-absorbing rubber material. The open front of the enclosure was constructed in a way which made it comfortable for the parent to seat their child on their lap. The infant’s head was positioned about 60cm away from the presentation screen. The screen measured 40cm × 70cm. The VExP was presented using the Apple Keynote program. The ceiling of the enclosure contained a block, which prevented the parent from seeing the screen; small mirrors were positioned in the enclosure so that the stimulus position could be recorded simultaneously with the infant’s looking behavior by a camcorder, hidden above the screen. During assessment the room light was dimmed to achieve a light intensity of about 26 luces. Parents were asked to refrain from talking and moving their head or body during the presentation to prevent influencing the looking behavior of the infants. Parents received the instruction to hold their child securely and in an ideal position for viewing the presentation and filming.

Stimuli and VExP sequence types

The VExP was created based on the studies from Canfield and colleagues (1997) as well as Domsch and colleagues (2009). The stimuli were presented in a simple left–right sequence (left–right–left–right, etc.). Stimuli were presented for 1 second consecutively, with the interstimulus interval (ISI) set at 1.5 seconds. The task consisted of 18 trials.

Two kinds of stimuli were used in the VExP: (a) photographs of culturally familiar smiling female faces; and (b) pictures of Greebles, based on Gauthier and Tarr (1997). Greebles are photo-realistically rendered 3D objects. Each stimulus was 24.7cm × 18.7cm in size. A total of six faces and Greebles were used in the sequences presented to the infants. Each infant was presented a sequence of either faces or Greebles, whilst each stimulus set contained either two faces or two Greebles. Additionally, the faces or the Greebles were presented in three different poses: a full frontal orientation; a left three-quarter turned; and a right three-quarter turned profile orientation. An example for a sequence is: left picture with stimulus A (frontal), right picture with stimulus B (left three-quarter turned pose), left picture with stimulus A (right three-quarter turned pose), right picture with stimulus B (frontal) and so forth. Examples of the stimuli are depicted in Figure 1. In the reassessment at 6 months, the infants saw a sequence of the same kind of stimuli (either faces or Greebles), but with two other stimuli from the set of six faces or Greebles.

Figure 1.

Example stimuli of each condition in all three poses

Data scoring

The average RT and the number of anticipatory eye movements, as indicators for expectation learning, were generated by video analysis. The same procedure was used for the assessments at 3 and 6 months. The scoring was based on a frame-by-frame video analysis for each learning trial. Frames were transformed into milliseconds (1 frame = 33 ms). The RT per trial results from the difference between the appearance of a target stimulus (onset) and the start of the major fixation shift. The major fixation shift is defined as an eye movement starting from the position of the previous stimulus (reference stimulus) and leading to the fixation of the following target stimulus (cf. Canfield et al., 1997). For example, if an infant had started a major fixation shift to a target stimulus 990 ms after the onset of the target stimulus, a latency of 990 ms was coded. If an infant started the major fixation shift 165 ms before the onset of the target stimulus, a latency of −165 ms was encoded. All major fixation shifts of the whole presentation were coded. Other eye movements, which were unrelated to the stimulus series—for example, the infant cried or turned around—were not included in the RT coding. For the reduction of measurement errors the RTs of the major fixation shifts were averaged across trials 1–6, 7–12, and 13–18, resulting in three blocks. Furthermore, a total score across all trials was calculated. Trials with RTs ≤ 200 ms (critical value) after the stimulus onset were considered as anticipatory (cf. Canfield et al., 1997; Rose et al., 2002). The number of trials with anticipatory responses was included as an additional learning criterion in the VExP (again for trials 1–6, 7–12, and 13–18 separately and as a total score across all trials).

The attention rate was calculated for each six-trial block and across all trials. The attention rate can be defined as the percentage of trials in which the infant shows task-oriented shifts of attention. This coding includes trials with major fixation shifts and trials without major fixation shifts, in which infants focus on the screen without interruptions of seven (231 ms) and more frames. For example, the infant only looked to the side of the screen where the stimulus appeared without showing off-task behavior. If the infant showed this behavior in four of six trials of a trial block, the attention rate of this trial block was 66.7%.

In total there were three measures (blocks of six trials) related to attention, to RT, and to the number of anticipations for each of the two time points (at 3 and 6 months). In addition, there were total scores for attention, RT, and the number of anticipations across the three blocks.

To estimate the reliability of the codings, the videos were analyzed by two independent coders. For the 3-month-old infants, 44.9% (44 films, 792 trials in total) and for the 6-month-old infants 45.3% of the videos (43 films, 774 trials in total) were analyzed by two coders. The reliability of the coding of the RT in frames was computed by using the intraclass correlation (ICC) for all coded films across all trials. The results of pi = .98 at 3 months and of pi = .99 at 6 months indicate a very good reliability of the RT measurements (see Shrout & Fleiss, 1979). To estimate the reliability of the attention value, Cohen’s kappa was calculated which led to κ = 1 at 3 months and κ = .98 at 6 months, indicating very good reliabilities (Landis & Koch, 1977).

Statistical analysis

The intercorrelations between the VExP outcome variables were calculated using Pearson correlations. Hypotheses 1 and 2 were tested using multivariate analysis of variance with repeated measures. The attention behavior and expectation learning performance (average RT and number of anticipations) were used as the dependent variables. The age (3 vs. 6 months) and trial blocks (one to three) were used as within-subjects factors, while the meaning of stimulus material (faces vs. Greebles) was used as between-subjects factor.

Results

Intercorrelations between the variables

The intercorrelations between the outcome variables, across all trials, are displayed separately for both age groups in Table 1. As can be seen from Table 1, there are large negative correlations between the expectation learning measures (average RT and the number of anticipations). Increased numbers of anticipations are associated to decreases in average RT. This association may be due to an inherent relation between average RT and the number of anticipations, because anticipations are defined as reaction times ≤ 200 ms. Moreover, substantial correlations between attention and the measures of expectation learning were found (see Table 1). The RT decreases and the number of anticipations increases once infants show an increase in their attention levels. These relations are similar in both age groups. However, there are no longitudinal relations between the measures at 3 and 6 months.

Table 1.

Pearson correlations between attention, average RT and the number of anticipatory eye movements within and across age levels

Age	Variable	2.	3.	4.	5.	6.
3 Months	1. Attention (%)	−.28^**	.68^**	.22^*	.02	.06
	2. Average RT (ms)	—	−.61^**	−.01	.02	−.06
	3. Number of anticipations	—	—	.09	.02	.01
6 Months	4. Attention (%)	—	—	—	−.17	.52^**
	5. Average RT (ms)	—	—	—	—	−.75^**
	6. Number of anticipations	—	—	—	—	—

Note. N= 108; ^* = p < .05; ^** = p< .01 (two-tailed).

Effects of age and trial blocks on attention and expectation learning

Before the effects of the stimulus material are analyzed, the focus lies on attention and expectation learning across age and trial blocks (hypotheses 1 and 2). Therefore a multivariate analysis of variance, with repeated measures, was calculated using age (3 vs. 6 months) and the three blocks of learning trials as independent variables. Both variables represent within-subjects factors. Attention, average RT, and the number of anticipations served as dependent variables. The results show a multivariate effect for age, F(3, 105) = 22.21, p < .001, η² = .39, for the blocks of learning trials, F(6, 102) = 11.27, p < .001, η² = .40, and additionally an interaction between both within-subjects factors, F(6, 102) = 4.92, p< .001, η² = .22.

The subsequent univariate analyses show a significant age effect for attention, F(1, 107) = 19.72, p < .001, η² = .16. As the means in Table 2 indicate, attention increases across age. However, no significant main effect regarding attention shifts across the trial blocks can be found. However, there is a significant interaction effect between age and trial blocks for attention, F(2, 214) = 9.49, p < .001, η² = .08. As Table 2 shows, attention increases across trial blocks for the 3-month-olds, whereas it is decreased for the 6-month-old infants. Regarding the average RT, a main effect for age is present, F(1, 107) = 51.41, p < .001, η² = .33. The average RT is considerably lower for the 6-month-olds in comparison to the 3-month-old infants. Additionally, the average RT decreases across trial blocks, F(2, 214) = 31.12, p < .001, η² = .23. The results also show an interaction between age and trial blocks for the average RT, F(2, 214) = 5.11, p = .007, η² = .05 indicating a greater decrease across trial blocks in 3-month-old infants in comparison to the older age group. With regard to the number of anticipations, the results show a significant age effect, F(1, 107) = 17.49, p < .001, η² = .14, indicating an increased number of anticipations for older infants. Moreover, the number of anticipations increases across blocks, F(2, 214) = 21.23, p < .001, η² = .17. There is no significant interaction with age, indicating that the increase is comparable for both age groups. With few exceptions, the univariate analyses of variance for the three dependent variables support hypotheses 1 and 2. Generally age effects on attention and learning performance are present, as well as improvements across blocks of learning trials. Regarding attention, however, an improvement can only be found for the 3-month-old, but not for 6-month-old infants.

Table 2.

Attention, average RT and the number of anticipatory eye movements across trial blocks at 3 and 6 months

		Attention (%)		Average RT (ms)		Number of anticipations
Age	Trial block	Mean	SD	Mean	SD	Mean	SD
3 months	1. Block	72.69	27.00	437.55	190.35	1.03	1.25
	2. Block	76.85	26.09	336.07	216.38	1.63	1.64
	3. Block	79.24	25.06	253.54	259.05	1.81	1.56
6 months	1. Block	89.81	14.12	225.50	153.56	1.96	1.46
	2. Block	85.75	20.24	173.59	197.35	2.27	1.58
	3. Block	82.76	20.66	147.96	267.24	2.42	1.71

Note. N= 108. Possible range of number of anticipations per block 1–6.

Effects of the stimulus material (faces vs. Greebles)

To analyze the effects of the stimulus material on attention and expectation learning performance, the meaning of stimulus material (faces vs. Greebles) was added as an additional independent variable (between-subjects factor) to the previous analysis. It was hypothesized that the meaning of the stimulus material would have an effect on attention and expectation learning (hypothesis 3). In line with the hypothesis, the multivariate analysis of variance shows a multivariate effect for the kind of stimulus material, F(3, 104) = 3.29, p = .024, η² = .09. The univariate analysis indicates a significant main effect for attention, F(1, 106) = 6.56, p = .012, η² = .06, thus supporting hypothesis 3. As a comparison of the means shows (see Figure 2), attention is increased in the case of meaningful stimulus material (faces). In addition, there is a univariate effect for the number of anticipations, F(1, 106) = 8.78, p = .004, η² = .08. As Figure 2 shows, the number of anticipations is increased for meaningful stimulus material (faces in comparison to Greebles). However, no effect regarding average RT or interactions were found.

Figure 2.

Effects of the meaning of stimulus material (faces vs. Greebles) on infants’ attention and number of anticipations in the VExP Note. Attention rate is the percentage of all trials where infants attended to the screen. Error bars represent SD. Possible range for number of anticipations: 0–18.

To analyze if expectation learning is enhanced by faces independent of attention, because it may be easier to learn faces than Greebles, a hierarchical regression analysis was computed partialling out the effects of attention on anticipation. Attention was included in the first step of the hierarchical regression analysis and the meaningfulness of the stimulus material was added in the second step. At the first measurement point, attention significantly predicted the number of anticipations (β = .68, p < .001). The attention variable explained 47% of the variance (R ² = .47, p < .001). When entering the stimulus material into the regression analysis, the relationship between attention and the number of anticipations did not change. Moreover, stimulus material does not significantly predict the number of anticipations (β = .00, p = .975). The same analysis was also conducted for the second point of measurement. This analysis revealed that attention significantly predicts the number of anticipations (β = .52, p < .001) and explains 27% of the variance (R ² = .27, p < .001). The relationship between attention and the number of anticipations slightly decreased once stimulus material was entered into the regression analysis (β = .49, p < .001). Also, the stimulus material significantly predicts the number of anticipations (β = .17, p = .047). The stimulus material explains 3% of variance of the number of anticipations (ΔR ² = .03, p = .047). In sum, 30% of variance is explained through attention and the stimulus material (R ² = .30, p < .001).

Discussion

The aim of the present study was to replicate earlier findings, which found an increase of expectation leaning with age, and to examine the influence of the stimulus material on attention and expectation learning performance (average RT and number of anticipations) in 3- and 6-month-old infants. In line with previous research (Rose et al., 2002), our results showed that attention and expectation learning performance increased with age (hypothesis 1; e.g., Canfield et al., 1997; Reznick et al., 2000; Rose et al., 2002). This effect may be explained by neuronal maturation processes, because the ability to form expectations and also attentional outcomes are dependent on the neuronal maturation during infancy (Canfield et al., 1997; Colombo, 2001).

The attention increased in 3-month-olds across trial blocks, whereas it decreased in 6-month-old infants. The attention decrease in 6-month-old infants might be due to the simplicity of the alternating left–right sequence, which may have become increasingly boring across the trials. With regard to reaction times there was—in line with hypothesis 2—a decrease across trials. It may be suggested that the slight decrease of the reaction time across trials in 6-month-old, in comparison to 3-month-old infants may be the result of a ceiling effect. Due to the better performances in the first block of six trials, the 6-month-old infants had lesser chances for major improvements. Again, in line with hypothesis 2, the number of anticipations increased across trial blocks in both the 3- and 6-month-old infants.

In hypothesis 3 we assumed that meaningful stimulus material increases the attention and performance in the VExP. Given that human faces are the most preferred stimuli for infants, female faces were used as high attention-attracting stimuli. Greebles were implemented as low attention-attracting stimuli. As expected, the infants’ attention was higher when confronted with human faces in comparison to the Greebles. Additionally, the number of anticipations was also higher for faces than for Greebles. However, with respect to the average RT, no stimulus effect was found. A subsequently conducted regression analysis shows that attention is the main variable, which explains the learning effects. Only in the 6-month-old infants is additional variance explained by the kind of stimulus (faces vs. Greebles). This is, however, a rather small effect, which may indicate that faces are easier to learn for reasons not directly connected to attention. As a consequence, the stimulus conditions lead to differential effects on attention, but there are only small additional effects which cannot be explained by attention.

The results support the unique role of human faces for the infants’ learning behavior. Additionally, these results can be seen as evidence for a relation between expectation learning and attention. It can be assumed that, due to the high attention attraction of faces, the encoding of the sensory information—which includes spatiotemporal information like the sequence of the presented stimuli—is more successful. This interpretation supports models which differentiate between factors such as processing speed and attention (cf. Rose et al., 2004).

Rose and colleagues (2004) and Rose, Feldman, and Jankowski (2005) found that anticipatory eye movements were associated with processing speed but not with attention. Tamis-Lemonda and McClure (1995) showed that the amount of anticipatory eye movements across the learning trials was associated with the cognitive components of processing speed as well as attention. In line with the results of Tamis-Lemonda and McClure (1995), the results of this study suggest that the number of anticipatory eye movements is related to both processing speed and attention regulation. Moreover, attention is influenced by the stimulus material, which may lead to an additional increase in the number of anticipations. High correlations between attention and the number of anticipations support this assumption. However, the higher attention induced by the stimulus material did not influence average RT. The correlation between average RT and attention at 3 months of age is significant but small. At 6 months of age, no significant correlation between average RT and attention was disclosed. This may indicate that the additional effect produced by the stimulus material may not be strong enough to influence all indicators of expectation learning performance.

A possible explanation for low assessment stabilities in early infancy may be that infants have large physiologic variations and attention fluctuations (Belsky, Gilstrap, & Rovine, 1984; Canfield et al., 1997). As a consequence, a high within-individual variation in state over time may lead to changes in performance. A second possible explanation is related to the inclusion of inattentive infants. In most studies, the off-task behavior is used to exclude data from inattentive children from the final analysis. As Lewis and Johnson (1971) state, removing inattentive infants from the data set may lead to a distortion effect. The reason is that infants who were removed from the data set do not show the same performance and intraindividual stability compared to infants who were attentive during the entire experiment.

A possible limitation of this study can be seen in the restricted age range. Cognitive abilities of infants show a strong development during this period. As a consequence, further studies should examine the effect of different types of stimuli for broader age ranges. It should also be noted that the influence of the learning material depends on different components of attention, such as attention to object features or endogenous factors that may influence attention (cf. Colombo, 2001). In the VExP it is not feasible to capture these different components of attention. Thus the shift of attention to stimulus features could have been influenced by different object features (like color, novelty, etc.) or initiated by the infants themselves as endogenous control of visual attention.

To conclude, our results show an influence of the type of stimuli on attention and expectation learning. Attention seems to be a necessary precondition for expectation learning in addition to processing speed. It may be interesting to compare additional kinds of stimulus material, to allow a more detailed analysis of the attentional effects. Therefore more attention should be focused on the type of stimulus used in studies of cognitive performance.

Footnotes

Funding

This study was supported by a grant from the German Research Foundation (Deutsche Forschungsgemeinschaft) for Heidi Keller, Monika Knopf, Arnold Lohaus and Gudrun Schwarzer (KE 263/53-1, KN 275/6-1, LO 337/20-1 and SCHW 665/9-1).

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