Behavioural Brain Research 262 (2014) 21–30

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Research report

Interference-free acquisition of overlapping sequences in explicit spatial memory Thomas Eggert ∗ , Johannes Drever, Andreas Straube Department of Neurology, Ludwig-Maximilians-Universität, Germany

h i g h l i g h t s • • • •

We investigate the flexibility in acquisition of explicit spatial memory. Partially overlapping sequences, learned successively, did not interfere. Known positions could be reproduced within a modified sequential context. The temporal structure of the retrieval varied between training and test.

a r t i c l e

i n f o

Article history: Received 11 September 2013 Received in revised form 17 December 2013 Accepted 21 December 2013 Available online 7 January 2014 Keywords: Sequence learning Imitation learning Spatial imagination Explicit memory Pointing movements

a b s t r a c t Some types of human sequential memory, e.g. the acquisition of a new composition by a trained musician, seem to be very efficient in extending the length of a memorized sequence and in flexible reuse of known subsequences in a newly acquired sequential context. This implies that interference between known and newly acquired subsequences can be avoided even when learning a sequence which is a partial mutation of a known sequence. It is known that established motor sequences do not have such flexibility. Using learning of deferred imitation, the current study investigates the flexibility of explicit spatial memory by quantifying the interferences between successively acquired, partially overlapping sequences. After learning a spatial sequence on day 1, this sequence was progressively modified on day 2. On day 3, a retention test was performed with both the initial and the modified sequence. The results show that subjects performed very well on day 1 and day 2. No spatial interference between changed and unchanged targets was observed during the stepwise progressive modification of the reproduced sequence. Surprisingly, subjects performed well on both sequences on day 3. Comparison with a control experiment without intermediate mutation training showed that the initial training on day 1 did not proactively interfere with the retention of the modified sequence on day 3. Vice versa, the mutation training on day 2 did not interfere retroactively with the retention of the original sequence as tested on day 3. The results underline the flexibility in acquiring explicit spatial memory. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Serial motor learning tasks comprise two components related to 1) the learning of individual elementary movements, e.g. a keystroke for typing the pin number of a bank card, and 2) the learning of the order, e.g. the order of the keystrokes in the typing sequence. This simplistic statement illustrates Lashley’s [1] elementary idea that “the mechanism which determines the serial activation of the motor units is relatively independent [. . .] of the motor units [. . .]”. A similar dichotomy between the learning of the spatial accuracy of individual movements and their sequential

∗ Corresponding author at: Department of Neurology, Klinikum Grosshadern, Marchioninistr 23, D-81377 Munich, Germany. Tel.: +49 89 7095 4834; fax: +49 89 7095 4801. E-mail address: [email protected] (T. Eggert). 0166-4328/$ – see front matter © 2014 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.bbr.2013.12.047

order was proposed by previous studies which observed differences in the time course of order and accuracy measures in sequence learning [2,3]. Closely related concepts distinguish between explicit and implicit motor learning [4,5] or between spatial and motor sequence learning [6]. Spatial sequence learning differs from motor sequence learning in that spatial learning is independent of a particular motor effector (e.g. right or left arm) and that the speed and the accuracy of movements generated by spatially learned movements are relatively small. Both spatial and motor learning processes occur in parallel, whereby early learning stages of sequence learning are dominated by spatial learning and late stages are dominated by motor learning [3,6]. In everyday life, spatial sequence learning is faced with a number of characteristic problems. Many sequences have to be reproduced without intermediate feedback, are often too long to be stored completely in working memory, and consist of elements which occur in different sequential contexts. For example, a trained

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Fig. 1. Learning task: subjects learned a spatial sequence by alternating visual observation (top: presentation phase) and manual pointing on a blank screen (bottom: reproduction phase). During the presentation phase the visual target stepped through a sequence of 20 positions. The stimulus was displayed on a graphics screen with integrated writing tablet. During the reproduction phase, subjects pointed without any speed requirement to the positions they remembered, trying to reproduce both position and order of the presented sequence.

piano player who wants to learn a new composition needs to arrange a large number of elements such as tones, scales, harmonies, rhythms, and articulations in a long temporal sequence in which equal elements or even equal subsequences occur many times but in different sequential contexts. The main problem in such tasks is not developing a new motor program for the elementary key presses (which are already highly developed in a trained player), but building up the complete sequence in a most efficient way. Most importantly, a good pianist, after learning of the composition, will be able to play spontaneously variations of the main themes of the composition he has learned, i.e. he can make use of many of the acquired subsequences in other sequential contexts. These requirements can obviously not be fulfilled by typical motor learning, because motor sequences cannot be reordered without restarting the process of motor learning from scratch [7]. In contrast to procedural motor learning, declarative memory is thought to be characterized by so-called compositional flexibility [8]. According to the definition of Cohen et al. [8] a memory representation of a larger structure is called compositional if it “. . . preserves the status of the constituents of the larger structure while still permitting the larger structure to be appreciated.” In the concept of these authors the declarative memory differs essentially from procedural memory in that it does not bind larger complex structures within single “configural items”. In this framework a declarative, compositional memory representation of a spatial sequence should therefore allow its constituents (i.e. the individual positions) to be accessed even in the context of a new, unknown sequence. Compositionality is exactly the feature which would allow declarative sequential memory to solve our musical example task efficiently.

For this task, which requires multiple partially overlapping sequences to be learned in parallel, interference effects of learning new subsequences on the retention of previously learned subsequences are evidently of substantial disadvantage. However, such interference was observed in studies on serial reaction time tasks and sequential finger tapping tasks [5,9,10]. These tasks differ from the above example in that they all require fast movement sequences which were, in contrast to that of the trained piano player, not excessively practiced. As a consequence of this challenge of the motor system induced by speeded response requirements, most sequential movement tasks comprise explicit and implicit components [5]. So far, it is not known how different subsequences interfere without speed requirements, with minimal requirement for implicit motor learning. We developed a learning task, which resembles the task of learning a complex composition, in a previous study [11]. The main features of this task (Fig. 1) are: the sequences had to be reproduced by manual pointing in the absence of feedback, they were long (20 different spatial locations), and they had to be learned in deferred imitation, i.e., in alternating presentation and reproduction phases. Hand movements were performed only during the reproduction and not during the presentation phase. Individual pointing movements did not require motor training since they could be generated from a well trained repertoire (pointing in the near workspace). Pointing movements were self triggered and were not subject to any requirement on reproduction speed. The performance observed with this pointing task showed all characteristics critical for testing the acquisition of sequential spatial memory: the reproduction transferred between motor modalities (eye to hand; dominant to non-dominant hand), learning was specific to individual sequences rather than reflecting general skill learning, and

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motor learning (as indicated by improvements in accuracy) was minimal. The paradigm allowed retention periods of several days after short training (25 trials) to be studied. Moreover, the length of the reproduced pointing sequences extended by about one pointing movement per trial, suggesting that information was accumulated starting from low and proceeding to higher serial numbers. Subjects reported, first, that they attentively selected in each presentation phase the target locations they intended to learn, and second, that they consciously recalled the individual target locations before each pointing movement. Thus, memory was explicit (declarative) since encoding and retrieval modes were typical for episodic memory [12,13]. In the current study we used the same explicit spatial learning task to investigate its efficiency during learning progress. Interferences between known and newly acquired parts of the sequence would strongly impede learning progress. Therefore, the main goal of this study is to quantify such interferences in spatial sequence learning. The following types of interferences are considered: 1) The interference of previously acquired sequences with the retention of newly acquired subsequences (proactive interference), and vice versa 2) the interference of newly acquired subsequences with the retention of previously learned subsequences (retroactive interference). Finally, learning of a new sequence that only partly overlaps with a known sequence should benefit from this knowledge. Therefore, during progressive modification of a trained sequence, the study also quantifies 3) interferences between the reproductions of changed and unchanged targets. Testing this third type of interference is an important extension of the commonly applied test paradigms of proactive and retroactive interferences. These well known test paradigms investigate the effect of training a whole sequence on the retention of another, non-overlapping sequence. They do not allow investigation of how parts of known sequences can be recalled in the changed sequential context of newly acquired sequences, a capability which is crucial for the flexibility of efficient sequence learning as illustrated by our introductory example. Moreover, such interferences are interesting for conclusions on the underlying mechanisms of spatial memory. Strong interference would provide evidence for single positions being associated with the geometrical relations (direction, distance) to its neighbors, whereas the absence of such interferences would suggest that single positions of spatial sequences can be stored and recalled independently of these geometrical relations. In the main experiment subjects performed three sessions on three subsequent days reproducing sequences of pointing movements consisting of 20 positions by manual pointing. In the first training session subjects learned a new sequence that was then progressively modified in the second session until half of the original positions had changed. Each modification during this mutation training concerned only two isolated items of the sequence, leaving their neighbors unchanged. This allowed the interference between the reproductions of changed and unchanged targets to be investigated. In the third session, a retention test was performed on both the sequence trained in the first session and the mutated sequence used at the end of the second session. To evaluate proactive and retroactive interference of spatial sequences, the overall correctness of the reproduced sequence order was compared between the main experiment and a control experiment in which the reproduction of the sequence was tested one day after learning without intermediate training on other sequences. 2. Methods 2.1. Subjects Twelve healthy subjects participated in the experiments (age = 28.7 ± 7.1 years). Six subjects performed the three

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experimental sessions of the main experiment. The control experiment was performed by the six other subjects. All subjects participated in previous experiments with the deferred imitation paradigm [11] but none of them had experience with the mutation training. The mean ages of the two groups did not differ significantly (t-test: T(10) = 0.64; p = 0.54). All subjects were right-handed and performed the pointing task with the right hand. Subjects gave informed consent before participation in the study. The study was performed in accordance with the Declaration of Helsinki and was approved by the local ethics committee. 2.2. Apparatus Subjects were seated in a dark room in front of a liquid-crystal display with an integrated writing tablet (WACOM Cintiq 21UX, width × height = 43.2 cm × 32.4 cm) at a viewing distance of 50 cm. Using this device, stimulus presentation and pointing occurred on the same tablet surface and did not require any additional coordinate transformations between presented and reproduced positions. The tablet surface was tilted out of the frontoparallel plane by 35 degrees. The tablet center was located in the midsagittal plane at the height of the shoulder. Pointing movements were performed with a pen whose position and pressure on the tablet was recorded by a computer. 2.3. Visual stimulus The visual target displayed on the screen was a white cross (bar length: 1 cm, bar width: 0.1 cm) on a homogeneous grey background. The luminous sterance of the background was 20 cd/m2 and that of the target was 130 cd/m2 . The target was initially presented at the start location for 1 s before it started to step through a sequence of 20 target locations with an inter-step interval of 1 s. At any time only a single target was visible. The target disappeared after 1 s presentation at the last target location (which was identical to the start location). The target sequences were generated offline before the start of the experiment. The 20 target locations were chosen randomly from a uniform distribution under the additional constraints that the minimal distance between two target locations was 4 cm and that not more than two target locations occurred within a radius of 6 cm. The average distance between successive targets was 11 cm. Sequences containing any obvious geometric regularities (such as three or more positions arranged along straight lines or regular polygons) were excluded by visual inspection by the experimenter. 2.4. Task To investigate learning and retention of long spatial sequences over a few days we used a sequence reproduction task from our previous study [11]. Each trial of this task consisted of a visual presentation phase followed by a reproduction phase. During the visual presentation of the sequence stimulus described in the last paragraph, subjects held the hand with the pen at a start position next to the writing tablet and did not move the hand. After each presentation, subjects reproduced the memorized sequence by pointing with the pen on the blank screen to as many target positions as they could remember and in the same order as shown during the visual presentation. The pen was lifted from the screen between each pointing movement. Thus, subjects performed a sequence of discrete movements. No error feedback or any intermediate cues were given during the entire reproduction phase. In particular, subjects were instructed not to interrupt the reproduction if they noticed the occurrence of an omission, and to indicate by a button press (with the left hand) when they did not remember any further positions. After pressing the button, subjects placed the hand back in

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Table 1 Modifications of the target positions progressively applied during the mutation training TM. The first column indicates the first trial in which the two targets at the specified serial position (second column) were presented for the first time at their modified positions. The displacement with respect to the corresponding target in the preceding trial is shown in polar coordinates in columns 4 and 5 (0 degree: rightward, counter clockwise >0). Trial 7 13 19 25 31 37

Serial position

Distance (cm)

Direction (degree)

4 15 7 16 6 12 4 13 5 11 7 9

11.1 18.5 18.3 8.1 18.9 19.0 17.8 22.3 29.1 19.1 15.9 26.9

−62.3 42.9 32.5 10.0 −105.8 121.0 −177.0 −64.0 48.9 −88.6 −176.6 99.0

the starting position next to the writing tablet. One second after the button press the next trial restarted with the visual presentation of the same sequence. 2.5. Experimental protocol The main experiment consisted of three sessions performed on three subsequent days. In the first session subjects performed 25 trials during an initial training (TI) with the sequence SI and learned to reproduce this sequence on the blank screen. On average the total duration of the session was 20 ± 2 min. Fig. 2 shows the 20 target locations together with the pointing positions (solid triangles) of one subject in the 25th trial. In the second session subjects trained with a spatial sequence that was, after starting with SI, progressively modified across trials. This mutation training (TM) was composed of 7 blocks, each of which had six trials. During the presentation phases of the first block the previously learned sequence SI was used. In each of the following blocks two of the target positions of the previous block were modified until, during the last block, 10 targets of the mutated sequence (SM) differed from the 20 targets of sequence S1. The targets 1, 2, 3, 8, 10, 14, 17, 18, 19, and 20 were not modified. The 2 × 6 = 12 mutations were characterized by target displacements (see Table 1) with a mean distance of 18.7 ± 5.8 cm. The distribution of the displacement direction was uniform between −180 and +180 degrees (Kolmogorov–Smirnov: p = 0.66). The third session of the main experiment served to test the retention of the previously learned sequences and consisted of two blocks, each of which had six trials. In one test block (RI) the initial sequence SI, and in the other block (RM) the final mutated sequence (SM) shown at the end of the second session was used. The order of the two blocks was counterbalanced across the subjects in order to eliminate potential order effects. Half of the subjects performed RM after RI, the other half performed RI after RM. The control experiment consisted of two sessions on two subsequent days without intermediate mutation training. The first session (TI’) was identical to that of the initial training TI of the main experiment but performed with another sequence (SI’). The second session of the control experiment (RI’) consisted of a single block of six trials with same sequence SI’. 2.6. Data analysis 2.6.1. Pointing position For each movement the pointing time was evaluated as the time when the pen pressure (measured by the writing tablet) reached its

first maximum after each pointing movement. The pointing position was defined as the pen position at pointing time.

2.6.2. Valid reproductions The completeness of the sequence reproduction was assessed by an algorithm we developed especially for long sequences in which targets fall in close spatial vicinity to each other despite far distance in sequence order [14]. In short, this algorithm classifies a pointing position as a “valid” reproduction by assigning it to a target position, whereas “invalid” pointing positions remain unassigned. The algorithm avoids inappropriate assignments by favoring ordered assignments of longer partial sequences over ordered assignments of shorter sequences and over disordered assignments. Pairs of pointing positions and target positions with more than 5.5 cm distance were never assigned to each other. It was shown that the classifications of this algorithm resemble that of human operators [14]. The overall correctness of the reproduced sequence was evaluated by the reproduction probability computed as the number of valid reproductions divided by the number of target positions in the sequence (i.e. 20). The spatial accuracy of the sequence reproduction was assessed by the average Euclidian distance between the pointing positions and the target locations to which they were assigned.

2.6.3. Local reproduction shift A particular challenge of the mutation training is that new target positions have to be reproduced in combination with target positions of a known sequence. This allows investigation of whether the movements towards the new targets interfere spatially with the reproduction of the old targets. To that purpose we computed for each target mutation the local reproduction shift ([x, y]) defined as the spatial difference of valid reproductions of a given target across the mutation. The valid reproductions were averaged across the three trials immediately before the mutation and subtracted from the average across the three trials immediately after the mutation. Thus, the local reproduction shift quantifies the spatial effect of the sequence mutation on the reproduction. For each mutation a triple of local reproduction shifts was computed consisting of the local reproduction shifts of the mutated target and that of their two unchanged neighbors in the sequence. This resulted in total in 12 (=2 × 6) shift triples since 2 targets were modified in each of the 6 mutation trials (see Table 1). The coordinate system of each shift triple was rotated such that x denotes the component of reproduction shift in the direction of the respective direction of the target mutation.

2.6.4. Pointing interval The temporal structure of the reproduction was assessed by the pointing interval. Whenever two successive pointing positions were assigned to two successive targets, the pointing interval of the second target was defined as the interval between the two pointing times. The emergence of chunks was evaluated for each subject for the last 6 reproductions of the training session (TI) and for the 6 retention trials (RI). Similarly to the definition used by previous studies [15] a target was considered as the first of a new chunk if its pointing interval was significantly larger than that of its ancestor in the sequence, whereby the significance was evaluated using the Newman–Keuls post-hoc test, under the prerequisite that the one-way ANOVA showed a significant effect of the factor target number on the pointing interval. Both ANOVA and post hoc tests were performed on the logarithmic pointing interval because it was, in contrast to the raw pointing interval, normally distributed across trials. This method for detecting chunks on the basis of the

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horizontal position [cm] Fig. 2. Solid triangles: end positions of the 20 pointing movements performed by one subject in the last trial of the initial training session (TI) with sequence SI. For the sake of clarity, the whole sequence is split into four graphs. Open circles: target positions of sequence SI. The dashed lines indicate which pointing locations were classified as valid reproductions of a target position. Only the targets 7 and 18 were classified as invalid.

temporal response structure was the same as that used by Sakai et al. [15] in order to keep the results comparable. 2.7. Statistics The interference of the mutation training with the retention of SI during RI was evaluated by estimating the reproduction performances during the last 6 trials of TI, during RI, during the last 6 trials of TI’, and during RI’ using a generalized mixed model for binomial data. The model was fitted by the function lmer provided by the lme4 package [16] in the R environment [17]. This model allows estimation of the log-odds of the probability of a target being assigned to a “valid” reproduction, pooled across targets and trials for each subject and for each condition. The model contained the two fixed factors condition (2 levels: end of training; retention test) and group (2 levels: main experiment with intermediate mutation training; control experiment without intermediate mutation training), and two random factors (one for each parameter of the main effect condition) grouped along the levels of the grouping factor subject. The formula of the lmer-model was (group × condition + (condition | subj)). The multiple random effects of this model take into account that the condition effect differed across subjects. This model structure was justified because it was significantly better than a model with only a single random factor (group*condition + (1 | subj)) as confirmed by likelihood ratio tests (2 (2) > 18; p < 0.0002). The significance level of the fixed effects was evaluated with Type III Wald chisquare tests. These tests require the estimated parameters to be normally distributed, which was confirmed by parametric bootstrapping of 10,000 sample data sets. The “reproduction probability” for all group-condition combinations was computed by applying the inverse logit transformation to the log-odds predicted by the fixed-effects of the model.

The same logistic mixed model was used to evaluate the interference of the initial training with SI with the retention of SM during RM. The reproduction probability during the last 6 trials of TM and during RM (with preceding training TI) were now compared with the reproduction probability during the last 6 trials of TI’ and during RI’ (without preceding training). Again, the two levels of first factor represented the condition (end of training; retention test), and the two levels factor group represented the presence or absence of the training that may interfere with the retention (main experiment with preceding training; control experiment without preceding training). All descriptive group statistics are reported as mean ±standard deviations, pooled across all subjects (N = 6). Effects with ˛-errors smaller than 0.05 are considered significant. 3. Results 3.1. Characteristics of the reproduction and the learning progress during the initial training The number of pointing movements generated during the reproduction phase of the initial training with sequence SI started at 4 ± 2.5 in the first reproduction trial and increased monotonously to 20 ± 0 in the last (i.e., the 25th) trial. The average pointing interval was 1350 ± 246 ms. Fig. 3 shows that all subjects learned during the training TI to reproduce the sequence SI with very little error. Similarly to the total number of movements, the number of movements classified as valid reproductions also rose monotonously from 3.8 ± 2.1 in the first trial to 18.2 ± 1.0 in the last trial (Fig. 3A). On average 93% of all movements were classified as valid, indicating that subjects did not generate many erroneous movements: neither explorative guessing nor corrective movements. Fig. 3B shows that

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# of unchanged targets

20

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# of valid reproductions

# of changed targets

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14 12 10 8 # of targets # of valid reproductions

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trial Fig. 3. Reproduction of sequence SI during the initial training TI. Solid lines: mean performance measures across 6 subjects. Shaded area: 95% confidence interval of the group mean. Solid circles: number of target positions of sequence SI presented in each trial. Top: the number of valid reproductions increased continuously until the end of the training to about 19. Bottom: the spatial accuracy of the valid reproductions did not show systematic improvements during the training.

the accuracy of the valid reproduction was consistent across subjects (2.8 ± 0.2 cm) and did not improve during the entire training session. Consistent with our previous study [11], these characteristics show that learning progress was focused on the prolongation of the memorized sequence with no substantial improvements in the accuracy of the individual reproductions. 3.2. Mutation training In the first 6 trials of the mutation training TM, averaged across trials and subjects, subjects performed pointing sequences consisting of 18.1 ± 3.4 movements, 16.8 ± 3.2 of which were classified as valid. Thus, at the beginning of TM the number of valid reproductions of sequence SI (Fig. 4A, Solid, trials 1–6) was only 1.4 smaller than during the last 6 trials of the initial training on the previous day (Fig. 3A, Solid, trials 20–25), indicating almost complete retention of SI. Whenever the sequence SI was progressively modified (in trials 7, 13,. . ., 37) the number of valid reproductions of the new sequence elements (Fig. 4A, Dashed) increased during the 6 trials after each modification. This shows that most subjects modified their pointing sequence at a speed that was fast enough to keep up with the stepwise modifications of the presented sequence. During the last 6 trials, when the sequence SI had finally mutated into the sequence SM, subjects performed pointing sequences consisting of 17.3 ± 5.2 movements, 16.0 ± 4.8 of which were classified as valid. From these 16.0 valid reproductions, 8.3 ± 2.3 were assigned to targets that stayed unchanged (Fig. 4A, Dashed, trials 37–42) and 7.7 ± 2.5 to targets that were modified from sequence SI to sequence SM. Similarly to the initial training session, the accuracy did not systematically change during the mutation training (Fig. 4B). The

accuracy (cm)

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trial 5

0 0

Fig. 4. Reproduction during the mutation training TM. Solid lines: mean performance measures on unchanged targets. Dashed lines: mean performance measures on changed targets. Solid circles: number of target positions which remained unchanged from the previously learned sequence SI. Open circles: number of changed target positions. Every 6 trials, two elements of the sequence were modified. All presented sequences had 20 target positions. Top: the mutation of the valid reproductions followed the stepwise mutation of the target sequence. Bottom: the accuracy of the reproductions of changed and unchanged target positions did not differ. Shaded areas: 95% confidence interval of the group mean (N = 6).

accuracy did not differ between the reproduction of unchanged targets (2.47 ± 0.25 cm) and that of the changed targets (2.54 ± 0.24 cm; paired t-test: T(5) = 0.82; p = 0.45). Fig. 5 shows a typical example of a pointing sequence in the last trial of the mutation training. Comparison with Fig. 2 shows that the sequences SI and SM resembled each other in the beginning and the end (Fig. 2A/DA/D; Fig. 5A/D) but differed very much for the ten central elements (Fig. 2B/CB/C; Fig. 5B/C). Similar to the subject whose pointing sequence is shown in Figs. 2 and 5, four of the six subjects generated, at the end of the mutation training, pointing sequences with 18 or more valid reproductions. 3.3. Spatial interference between the reproductions of changed and unchanged targets The local reproduction shifts induced by the modifications of the target sequence during TM were strictly limited to the reproductions of the mutated targets and did not interfere with the reproduction of their immediate neighbors in the sequence. An example of this lack of interference is shown in Fig. 6, depicting the shift triples of one of the 12 mutations. For the mutated target the local reproduction shift (Fig. 6B) was very similar to the target shift (arrows in Fig. 6B). On the neighbored, unchanged targets (Fig. 6A/C, without target shift), the local reproduction shifts were close to zero. The means of the three distributions did not differ significantly from the corresponding target shifts (Hotelling’s T2 -test: p > 0.13), indicating that the changes in the pointing sequence were identical to the required changes.

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horizontal position [cm] Fig. 5. Reproduction of sequence SM in the last trial of the mutation training (TM) performed by the same subject whose data are shown in Fig. 2. Symbols and lines as in Fig. 2.

Analyzing all 36 (=3 × 12) distributions of local reproduction shifts showed that the local mutation of the pointing did not differ systematically from that required by the local mutation of the target sequence. The distance between the group mean of local reproduction shift and the corresponding target shifts was on average 1.19 ± 0.87 cm (N = 36) which was much smaller (T(70) = 4.13; p < 0.001) than the mean distance between the individual reproduction shifts and their group means (2.01 ± 0.81 cm). Hotelling’s T2 -test revealed that the group mean of the local reproduction shift differed significantly from the corresponding target shifts in only 3 out of the 36 cases. These 3 cases are not meaningful since the probability of occurrence of 3 or more significant (p < 0.05) results in 36 tests in the absence of any true effects is larger than 0.268. This indicates that the reproductions of the changed and the unchanged targets did not spatially interfere with each other.

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3.4. Retroactive interference The retroactive interference of the mutation training with the retention of the sequence SI was tested by analysis of the reproduction probability of the sequences SI and SI’ during the last 6 trials of the initial training (TI, TI’) and the corresponding retention test (RI, RI’). The fixed effect predictions of the logistic mixed model are shown in Fig. 7. The results showed a significant main effect of the factor condition but no main effect or interaction with the factor group. The estimated reproduction probability tended to be slightly larger (Wald-Test on main effect condition: 2 (1) = 3.51; p = 0.06) at the end of the training (0.94) than during the retention test (0.90), indicating that the sequence memory decayed during the 24 h retention period. The presence or absence of the intermediate mutation training did not affect the reproduction probability since the factor group did not show a significant main effect or an interaction with the factor condition (Wald-Tests: p > 0.36). Thus, neither was one of SI or SI’ better reproduced than the other, nor did the intermediate mutation training interfere with the amount of information lost during the retention period (lack of retrograde interference). The standard deviation of the reproduction probability across subjects was 0.07 (corresponding to 1.4 targets).

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Fig. 6. Examples of local reproduction shifts occurring between the trials (28, 29, 30) and (31, 32, 33) in the valid reproductions of the targets 4 (A), 5 (B), 6 (C). In trial 31, target 5 was displaced by 29.1 cm in the direction of the x-axis (arrows). Targets 4 and 6 remained unchanged throughout trials 28–33. The symbols show the 2D-shift of the mean pointing position (induced by the local mutation of target 5) for the individuals. The isolated modification of the reproduction of the mutated target (B) did not affect the spatial accuracy of reproductions of the neighbored unchanged targets (A, C).

3.5. Proactive interference The retention of a sequence that was trained with or without a preceding training of another sequence was analyzed by comparing the reproduction probabilities of SI’ in the control experiment (without preceding training) with those of SM in the main experiment (with preceding training of SI). Again, reproduction probability during the last 6 trials of the two training sessions and during the first 6 reproductions of SM or SI’ during

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below significance (Wald-Test: p = 0.68). This indicates that the preceding training of SI in the main experiment did not proactively interfere with the retention of SM during the 24 h period between the second and the third session. The standard deviation of the reproduction probability of sequence SM (Fig. 8, solid symbols) and SI’ (Fig. 8, open symbols) across subjects was 0.07 and 0.22 respectively (corresponding to 1.4 and 4.4 targets).

1

reproduction probability

0.95 0.9 0.85 0.8

3.6. Temporal structure of the sequence reproduction without intermediate training with intermediate training

0.75 0.7

end of training

retention test Condition

Fig. 7. Effect of the mutation training on retention. Solid symbols (with intermediate training): the reproduction probabilities of the elements of SI during the main experiment. Open symbols (without intermediate training): the reproduction probabilities of the elements of SI’ during the control experiment. Shown is the probability of a target position being reproduced by a valid pointing position averaged across the last 6 trials of the initial training (condition end of training) and across the 6 trials of the test block (condition: retention test). Large symbols and whiskers show the inverse logit transformation, applied on the log-odds and their 95% confidence interval as predicted by the fixed-effects of the mixed binomial model. Small symbols: reproduction probability for each subject.

the retention tests were estimated using the logistic mixed model. The results depicted in Fig. 8 show significant main effects of both factors condition and group but no significant interaction effect. The reproduction probability was larger at the end of the training (0.91) than at the beginning of the retention test 24 h later (0.79; Wald-Test on the main effect condition: 2 (1) = 8.68; p < 0.005). Reproduction probability was also larger (Wald-Test on the main effect of group: 2 (1) = 7.61; p < 0.01) on the sequence SI’ (0.94) than on the mutated sequence SM (0.76). The tendency for an interaction effect (Fig. 8) between the two factors was far

4. Discussion

0.7

Consistently with a previous study [11], the results confirmed that deferred imitation of long spatial sequences is a spatial learning task in which the memorized sequence is progressively prolonged without simultaneous accuracy improvement (Fig. 3B). This study challenged the buildup of explicit spatial sequence memory by testing the interference of different sequences successively presented. The main findings were: (I) Subjects could transform the learned sequence SI stepwise into the sequence SM during the mutation training. (II) During the progressive mutation training, the spatial accuracy of the reproductions of the unchanged targets were not affected (Figs. 4B and 6). (III) The mutation training did not retroactively interfere with the reproduction of the original sequence SI in the retention test RI (Fig. 7). (IV) Retention of the mutated sequence (SM) across the period between the second and the third session of the main experiment (Fig. 8, dashed) did not differ significantly from the retention observed in the control experiment (Fig. 8, solid) arguing against strong proactive interference. (V) The consistency of the temporal structure of the pointing sequence was not crucial for the retention of the sequence 24 h after the initial training.

0.6

4.1. Lack of consistent chunk patterns

1 0.9 reproduction probability

The average pointing interval was 1285 ± 231 ms (N = 6) and did not differ (paired t-test: T(5) = 0.92; p = 0.40) between the end of the training (TI) and the retention test (RI). On average across subjects, only 0.83 (TI) and 1.17 (RI) chunks were observed per pointing sequences. These chunks were not consistent across subjects since either none (TI) or only 2 (RI) chunks started at the same target in more than one subject. These chunks were also not consistent within subjects across sessions since only one of the chunks occurred in only one subject at the same target during TI and RI. Thus, the consistency of the temporal structure of the pointing sequence was not crucial for the reproduction probability remaining well preserved across the retention period (Fig. 7). Chunks, defined by the pointing interval, were not consistently found either across subjects or across all reproduction within one subject.

0.8

0.5

without preceding training with preceding training

0.4 0.3

end of training

retention test Condition

Fig. 8. Effect of a preceding training on retention. Solid symbols (with preceding training): The reproduction probabilities of the elements of SM learned after a preceding training (TI) of another sequence. Open symbols (without preceding training): the reproduction probabilities of the elements of SI’ during the control experiment. Condition end of training: data from the last 6 trials of the training (TM or TI’). Condition retention test: data for the retention test (RM or RI’). In both cases no intermediate training was applied during the retention interval (24 h). Large symbols and whiskers show the inverse logit transformation, applied on the log-odds and their 95% confidence interval as predicted by the fixed-effects of the mixed binomial-model. Small symbols: Reproduction probability for each subject.

The lack of consistency of the temporal structure of the sequence reproductions seems to be at odds with previous results demonstrating that motor chunks can play an essential role in sequence reproduction. Sakai et al. [15] trained subjects to reproduce a sequence of 20 pointing movements cued by 10 intermediately presented visual stimuli. During repeated training with the same sequence, subjects developed idiosyncratic patterns with 3–6 chunks per sequence, much more than the observed 0.83–1.17 chunks per sequence in the current study. In the experiment of Sakai et al. [15], when a learned sequence was shuffled in a new order, the performance was more accurate and faster when the individual chunks were preserved in the new order than when chunks were broken. This result shows that chunking can play an essential role in learning and reproducing spatial sequences. A possible relation between the chunk development and explicit sequence learning was also shown in other previous studies [18,19].

T. Eggert et al. / Behavioural Brain Research 262 (2014) 21–30

In the results presented here no consistent chunk pattern could be identified even though we used the same method for detecting the chunks as Sakai et al. [15]. Most likely, the absence of a consistent chunk pattern in our experiment is related to the much longer inter-movement interval (about 1200 ms) in the current study compared with the mentioned previous studies (