The effects of ordinal load on incidental temporal learning

How can we grasp the temporal structure of events? A few studies have indicated that representations of temporal structure are acquired when there is an intention to learn, but not when learning is incidental. Response-to-stimulus intervals, uncorrelated temporal structures, unpredictable ordinal information, and lack of metrical organization have been pointed out as key obstacles to incidental temporal learning, but the literature includes piecemeal demonstrations of learning under all these circumstances. We suggest that the unacknowledged effects of ordinal load may help reconcile these conflicting findings, ordinal load referring to the cost of identifying the sequence of events (e.g., tones, locations) where a temporal pattern is embedded. In a first experiment, we manipulated ordinal load into simple and complex levels. Participants learned ordinal-simple sequences, despite their uncorrelated temporal structure and lack of metrical organization. They did not learn ordinal-complex sequences, even though there were no response-to-stimulus intervals nor unpredictable ordinal information. In a second experiment, we probed learning of ordinal-complex sequences with strong metrical organization, and again there was no learning. We conclude that ordinal load is a key obstacle to incidental temporal learning. Further analyses showed that the effect of ordinal load is to mask the expression of temporal knowledge, rather than to prevent learning.     

Redundant sensory information does not enhance sequence learning in the serial reaction time task

In daily life we encounter multiple sources of sensory information at any given moment. Unknown is whether such sensory redundancy in some way affects implicit learning of a sequence of events. In the current paper we explored this issue in a serial reaction time task. Our results indicate that redundant sensory information does not enhance sequence learning when all sensory information is presented at the same location (responding to the position and/or color of the stimuli; Experiment 1), even when the distinct sensory sources provide more or less similar baseline response latencies (responding to the shape and/or color of the stimuli; Experiment 2). These findings support the claim that sequence learning does not (necessarily) benefit from sensory redundancy. Moreover, transfer was observed between various sets of stimuli, indicating that learning was predominantly response-based.     

Effects of sequence length and structure on implicit serial learning

Some data suggest that, as in explicit serial learning, longer sequences are more difficult to learn implicitly. These findings have been used to support the inference that implicit learning is capacity-limited. However, investigations of the effect of sequence length on implicit learning have confounded sequence structure with sequence length. These factors were manipulated independently in 3 experiments using a serial reaction time task. The results showed that sequence structure, not sequence length, largely determines the extent of sequence learning.     

Effector dependent sequence learning in the serial RT task

At least five earlier studies could not find effector-dependent learning in the keying version of the serial reaction time (RT) task. Experiment 1 examined whether effector-dependent learning occurs when participants practice the serial RT task with three fingers of one hand for about 1,300 sequence repetitions instead of the more common 50-100 repetitions. The results confirm that, following extended practice, sequence learning produces an effector-dependent component. Specifically, an unpracticed hand executed a practiced sequence slower than a practiced hand. However, Experiment 2 showed that effector-dependent sequence learning develops only when fingers of one hand are used, suggesting that effector-dependent sequence learning involves adjustment to the mechanical interactions between the fingers of one hand. In addition, when sequences had been practiced with one hand, mirror versions of the practiced sequences in both experiments showed moderate transfer. But when practiced with two hands no transfer to a mirrored version of the sequence was observed. This suggests that only practice with one hand produces a representation that facilitates the execution of mirror sequences. Generally, the same results were found in more or less aware participants, congruent with the idea that the effector-dependent representation and the representation allowing transfer to mirror sequences are implicit.     

Integration of information during problem solving due to a meaningful context of learning

Ninety-seven subjects memorized nine associations among six interlocking elements that were presented as links among nonsense letters, connections among spies with word code names (after Hayes, 1966), or airline flights among major US cities. On tests of problem solving and true-false judgments, the letters group and the words group performed nearly identically; however, relative to these two groups, the cities group performed worse or about the same on short recall problems and much better on longer problems requiring chunking of learned information. The conditions and effects of a meaningful learning context for problem solving were discussed.     

Integration and representation in rats' serial pattern learning in the T-maze

Rats were exposed to three-trial series consisting of reinforced (R) trials and one nonreinforced (N) trial in a fixed order, RRN and RNR (Experiments 1 and 2) or NRR and RRN (Experiment 3), on extended visually distinct runways in a T-maze. When initially presented with the same sequence on each series in a session (separate presentations) with the same runway on all trials within a series (Experiments 1 and 3), all the rats developed slower running speeds on N than on R trials. When a runway was sometimes changed between the first and next two trials during separate presentations training (Experiment 2) or both sequences were later intermixed within each session in each experiment, only rats exposed to each sequence on a specific runway maintained these serial running patterns. Rats displayed serial running patterns on a test RNN sequence similar to that on the RNR sequence (Experiment 2), as would be predicted by an intertrial association model of serial pattern learning (Capaldi & Molina, 1979), but responded on test RRR and NRN sequences (Experiment 3) as would be predicted by an ordinal-trial-tag/intratrial association model (Burns, Wiley, & Payne, 1986). Results from test series of free-choice trials in Experiments 1 and 2 failed to support a prediction of the intratrial association model that these rats would integrate RRN and RNR sequences. Rather than always selecting a baited runway on both the second and the third free-choice trials, the rats only selected a baited runway on the third trial on the basis of their choice on the second trial, as would be predicted by the intertrial association model. Only after experiencing all possible outcome sequences during forced-choice training in Experiment 3 did these rats predominantly select a baited runway on every free-choice trial.     

Effector-related sequence learning in a bimanual-bisequential serial reaction time task

In a bimanual-bisequential version of the serial reaction time (SRT) task participants performed two uncorrelated key-press sequences simultaneously, one with fingers of the left hand and the other with fingers of the right hand. Participants responded to location-based imperative stimuli. When two such stimuli appeared in each trial, the results suggest independent learning of the two sequences and the occurrence of intermanual transfer. Following extended practice in Experiment 2, transfer of acquired sequence knowledge was not complete. Also in Experiment 2, when only one stimulus appeared in each trial specifying the responses for both hands so that there was no basis for separate stimulus-stimulus or separate response-effect learning, independent sequence learning was again evident, but there was no intermanual transfer at all. These findings suggest the existence of two mechanisms of sequence learning, one hand-related stimulus-based and the other motor-based, with only the former allowing for intermanual transfer.     

Oculomotor evidence of sequence learning on the serial reaction time task

Manual and oculomotor measures of sequence learning were examined on the serial reaction time (SRT) task Participants were assigned into four groups differing on response modality (manual, oculomotor) and trial type (sequence, pseudorandom). The pattern of manual RTs replicated previous studies. Frequency of anticipatory eye movements followed similar patterns as RTs. Participants made many anticipations, even in pseudorandom blocks, and frequency of anticipations did not depend on presence of concurrent manual responses. Excluding participants with explicit awareness did not change results. Anticipations were negatively related to RTs in both incidental and intentional learning. Anticipations were positively related to sequence recall in intentional, but not incidental, learning. Results suggest that (1) anticipatory eye movements reflected sequence learning and (2) participants made overt and covert shifts of visuospatial attention to likely stimulus locations prior to stimulus onset, whether or not they made manual responses and whether or not there was a sequence.     

Pause measures during reading and recall in serial list learning

An investigation is reported into pausing and grouping during the serial learning of letter strings, when presented randomly by length and when presented in ascending order. Mean pause times for the reading and recall of longer lists were significantly greater than for lists of shorter span due to extended pausing at specific list positions. In general, reading rhythms were duplicated during recall. Subjects were highly consistent in maintaining their level of pause duration across lists and responded to additions in list length by increasing their number of groups, not by increasing group size. Triadic sequences were the most popular form of spontaneous organization. Pausing measures are discussed as indices of organizational strategies.     

The role of stimulus-based and response-based spatial information in sequence learning

In 4 experiments, relational structures were independently varied in stimulus and response sequences in a serial reaction time task. Moreover, the use of spatial and symbolic stimuli and responses was varied between experiments. In Experiment 1, spatial stimuli (asterisk locations) triggered spatial responses (keystrokes); in Experiment 2, spatial stimuli triggered symbolic responses (verbal digit naming); in Experiment 3, symbolic stimuli (digits) triggered keystrokes; and in Experiment 4, digits triggered verbal responses. The results showed that there is a remarkably stronger effect of relational structures in spatial sequences than in symbolic sequences, irrespective of whether stimulus or response sequences are concerned. This suggests that learning is particularly effective for sequences of spatial locations. It is argued that spatial learning is a critical determinant for the debate on perceptual and motor learning.     

Generalized lessons about sequence learning from the study of the serial reaction time task

Over the last 20 years researchers have used the serial reaction time (SRT) task to investigate the nature of spatial sequence learning. They have used the task to identify the locus of spatial sequence learning, identify situations that enhance and those that impair learning, and identify the important cognitive processes that facilitate this type of learning. Although controversies remain, the SRT task has been integral in enhancing our understanding of implicit sequence learning. It is important, however, to ask what, if anything, the discoveries made using the SRT task tell us about implicit learning more generally. This review analyzes the state of the current spatial SRT sequence learning literature highlighting the stimulus-response rule hypothesis of sequence learning which we believe provides a unifying account of discrepant SRT data. It also challenges researchers to use the vast body of knowledge acquired with the SRT task to understand other implicit learning literatures too often ignored in the context of this particular task. This broad perspective will make it possible to identify congruences among data acquired using various different tasks that will allow us to generalize about the nature of implicit learning.     

Spatial and temporal adaptations that accompany increasing catching performance during learning

The authors studied changes in performance and kinematics during the acquisition of a 1-handed catch. Participants were 8 women who took an intensive 2-week training program during which they evolved from poor catchers to subexpert catchers. An increased temporal consistency, shift in spatial location of ball-hand contact away from the body, and higher peak velocity of the transport of the hand toward the ball accompanied their improvement in catching performance. Moreover, novice catchers first adjusted spatial characteristics of the catch to the task constraints and fine-tuned temporal features only later during learning. A principal components analysis on a large set of kinematic variables indicated that a successful catch depends on (a) forward displacement of the hand and (b) the dynamics of the hand closure, thereby providing a kinematic underpinning for the traditional transport-manipulation dissociation in the grasping and catching literature.     

Situation models and memory: the effects of temporal and causal information on recall sequence

Participants watched an episode of the television show Cheers on video and then reported free recall. Recall sequence followed the sequence of events in the story; if one concept was observed immediately after another, it was recalled immediately after it. We also made a causal network of the show's story and found that recall sequence followed causal links; effects were recalled immediately after their causes. Recall sequence was more likely to follow causal links than temporal sequence, and most likely to follow causal links that were temporally sequential. Results were similar at 10-minute and 1-week delayed recall. This is the most direct and detailed evidence reported on sequential effects in recall. The causal network also predicted probability of recall; concepts with more links and concepts on the main causal chain were most likely to be recalled. This extends the causal network model to more complex materials than previous research.     

Effects of adult aging on utilization of temporal and semantic associations during free and serial recall

Older adults show poorer performance than young adults at word list recall, especially for order information. In contrast with this temporal association deficit, older adults are generally adept at using preexisting semantic associations, when present, to aid recall. We compared the use of temporal and semantic associations in young and older adults' word list recall following both free recall and serial recall instructions. Decomposition of serial position curves confirmed that older adults showed weakened use of temporal context in recall in relation to young adults, a difference that was amplified in serial recall. Older adults' temporal associations were also less effective than young adults' when correlated with serial recall performance. The differential age decrement for serial versus free recall was accompanied by a persistent influence of latent semantic associations in the older adults, even when maladaptive for serial recall.     

Implicit learning of what comes when and where within a sequence: The time-course of acquiring serial position-item and item-item associations to represent serial order

Much research has been conducted aimed at the representations and mechanisms that enable learning of sequential structures. A central debate concerns the question whether item-item associations (i.e., in the sequence A-B-C-D, B comes after A) or associations of item and serial list position (i.e., B is the second item in the list) are used to represent serial order. Previously, we showed that in a variant of the implicit serial reaction time task, the sequence representation contains associations between serial position and item information (Schuck, Gaschler, Keisler, & Frensch, 2011). Here, we applied models and research methods from working memory research to implicit serial learning to replicate and extend our findings. The experiment involved three sessions of sequence learning. Results support the view that participants acquire knowledge about order structure (item-item associations) and about ordinal structure (serial position-item associations). Analyses suggest that only the simultaneous use of the two types of knowledge acquisition can explain learning-related performance increases. Additionally, our results indicate that serial list position information plays a role very early in learning and that inter-item associations increasingly control behavior in later stages.     

Positional and temporal clustering in serial order memory

The well-known finding that responses in serial recall tend to be clustered around the position of the target item has bolstered positional-coding theories of serial order memory. In the present study, we show that this effect is confounded with another well-known finding—that responses in serial recall tend to also be clustered around the position of the prior recall (temporal clustering). The confound can be alleviated by conditioning each analysis on the positional accuracy of the previously recalled item. The revised analyses show that temporal clustering is much more prevalent in serial recall than is positional clustering. A simple associative chaining model with asymmetric neighboring, remote associations, and a primacy gradient can account for these effects. Using the same parameter values, the model produces reasonable serial position curves and captures the changes in item and order information across study-test trials. In contrast, a prominent positional coding model cannot account for the pattern of clustering uncovered by the new analyses.     

Chunking during serial learning by a pigeon: I. Basic evidence

Chunking by pigeons was demonstrated by comparing performance on different types of lists. Experiment 1 showed that Groups II and IV (who learned lists in which colors and achromatic geometric forms were segregated: A----B----C----D'----E' and A----B----C----D----E', respectively) executed lists more rapidly than did Group I (who learned a homogeneous list of colors: A----B----C----D----E) or Groups II and III (who learned lists consisting of unsegregated colors and forms: A----B'----C----D'----E and A----B----C'----D----E, respectively). Experiment 2 showed that Groups II and IV tolerated interruptions of the list better than did Groups I, III, and V. The accuracy of responding of Groups I, III, and V decreased as a function of the duration of the interruption and the point in the sequence at which it occurred. The performance of Group II was unaffected by interruptions; Group IV was minimally affected. These results indicate that Groups II and IV organized their lists as ordered chunks.