This study investigated the development of contextual dependencies for sequential perceptual-motor learning on static features in the learning environment. In three experiments we assessed the effect of manipulating task irrelevant static context features in a serial reaction-time task. Experiment 1 demonstrated impaired performance after simultaneously changing display color, placeholder shape, and placeholder location. Experiment 2 showed that this effect was mainly caused by changing placeholder shape. Finally, Experiment 3 indicated that changing context affected both the application of sequence knowledge and the selection of individual responses. It is proposed either that incidental stimulus features are integrated with a global sequence representation, or that the changed context causes participants to strategically inhibit sequence skills.

The existence of implicit learning has been tacitly accepted but the relationship of implicit learning with consciousness has been controversial.This research reviewed and explored the focuses of the research on the consciousness of implicit learning in terms of whether or not implicit learning is unconscious,how the second tasks influence implicit learning,and the relation of implicit learning with explicit learning.

在内隐学习的研究中，尽管目前已经默认了内隐学习的存在，但是，内隐学习与意识的关系，一直有着不断的争论。文章从内隐学习是否是无意识的、次级任务对内隐学习的影响和内隐学习的关系等三个方面对内隐学习的意识性研究主要的矛盾焦点进行了述评。

The dominant theory of what people can learn implicitly is that they learn chunks of adjacent elements in sequences. A type of musical grammar that goes beyond specifying allowable chunks is provided by serialist or 12-tone music. The rules constitute operations over variables and could not be appreciated as such by a system that can only chunk elements together. A series of studies investigated the extent to which people could implicitly (or explicitly) learn the structures of serialist music. We found that people who had no background in atonal music did not learn the structures, but highly selected participants with an interest in atonal music could implicitly learn to detect melodies instantiating the structures. The results have implications for both theorists of implicit learning and composers who may wish to know which structures they put into a piece of music can be appreciated.

This paper investigates the conscious status of both the knowledge that an item is legal (judgment knowledge) and the knowledge of why it is legal (structural knowledge) in sequence learning. We compared ability to control use of knowledge (Process Dissociation Procedure) with stated awareness of the knowledge (subjective measures) as measures of the conscious status of knowledge. Experiment 1 showed that when people could control use of judgment knowledge they were indeed conscious of having that knowledge according to their own statements. Yet Experiment 2 showed that people could exert such control over the use of judgment knowledge when claiming they had no structural knowledge: i.e. conscious judgment knowledge could be based on unconscious structural knowledge. Further implicit learning research should be clear over whether judgment or structural knowledge is claimed to be unconscious as the two dissociate in sequence learning.

通现自1967年内隐学习诞生以来三十余年的研究状况，结合人工语法范式研究者的典型实验，分别从四个侧面(从外部到内部、从简单到复杂、从分离到协同、从理论到应用)介绍了内隐学习研究的历程，并夹叙夹议地展开讨论，启示人们关注这一领域。

表征质量理论对意识增长持渐进观点,忽视新异刺激对意识的突变式影响;新异刺激理论强调意识突变,忽视新异刺激本身的表征质量增长。本研究采用经典确定性内隐序列学习范式,将转移组块作为新异刺激,操控其数量和位置,探究新异刺激如何通过表征质量来影响内隐学习和意识。结果表明:(1)数量效应显著,即两个转移组块更能促进内隐学习量,说明新异刺激本身需要足够的表征质量才能发挥"意外事件"的作用。(2)在位置效应上,两个转移组块且靠前的设置更能提高受控意识,表明第一个新异刺激必须出现在原序列初级表征质量阶段,才能使被试对新异刺激和原序列进行对比,加之第二个新异刺激的与之呼应,就可促进原序列意识增加。

ABSTRACT This book provides a foundation to the principles of psychology. It draws upon the natural sciences, avoiding metaphysics, for the basis of its information. According to James, this book, assuming that thoughts and feelings exist and are vehicles of knowledge, thereupon contends that psychology, when it has ascertained the empirical correlation of the various sorts of thought or feeling with definite conditions of the brain, can go no farther as a natural science. (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Abstract Four experiments investigate the differences between implicit and explicit sequence learning concerning their resilience to structural and superficial task changes. A superficial change that embedded the SRT task in the context of a selection task, while maintaining the sequence, did selectively hinder the expression of implicit learning. In contrast, a manipulation that maintained the task surface, but decreased the sequence validity, affected the expression of learning specifically when it was explicit. These results are discussed in the context of a dynamic framework (Cleeremans & Jim茅nez, 2002), which assumes that implicit knowledge is specially affected by contextual factors and that, as knowledge becomes explicit, it allows for the development of relevant metaknowledge that modulates the expression of explicit knowledge.

Abstract Dominant theories of implicit learning assume that implicit learning merely involves the learning of chunks of adjacent elements in a sequence. In the experiments presented here, participants implicitly learned a nonlocal rule, thus suggesting that implicit learning can go beyond the learning of chunks. Participants were exposed to a set of musical tunes that were all generated using a diatonic inversion. In the subsequent test phase, participants either classified test tunes as obeying a rule (direct test) or rated their liking for the tunes (indirect test). Both the direct and indirect tests were sensitive to knowledge of chunks. However, only the indirect test was sensitive to knowledge of the inversion rule. Furthermore, the indirect test was overall significantly more sensitive than the direct test, thus suggesting that knowledge of the inversion rule was below an objective threshold of awareness.

Focuses on the extensive experience gained with artificial grammars in explicit and implicit processing tasks. Sufficiency of implicit processing for learning a finite state grammar; Communication of implicit knowledge of the grammars; Indication of verbal protocols.

Abstract A series of vignette examples taken from psychological research on motivation, emotion, decision making, and attitudes illustrates how the influence of unconscious processes is often measured in a range of different behaviors. However, the selected studies share an apparent lack of explicit operational definition of what is meant by consciousness, and there seems to be substantial disagreement about the properties of conscious versus unconscious processing: Consciousness is sometimes equated with attention, sometimes with verbal report ability, and sometimes operationalized in terms of behavioral dissociations between different performance measures. Moreover, the examples all seem to share a dichotomous view of conscious and unconscious processes as being qualitatively different. It is suggested that cognitive research on consciousness can help resolve the apparent disagreement about how to define and measure unconscious processing, as is illustrated by a selection of operational definitions and empirical findings from modern cognitive psychology. These empirical findings also point to the existence of intermediate states of conscious awareness, not easily classifiable as either purely conscious or purely unconscious. Recent hypotheses from cognitive psychology, supplemented with models from social, developmental, and clinical psychology, are then presented all of which are compatible with the view of consciousness as a graded rather than an all-or-none phenomenon. Such a view of consciousness would open up for explorations of intermediate states of awareness in addition to more purely conscious or purely unconscious states and thereby increase our understanding of the seemingly nconscious aspects of mental life. (PsycINFO Database Record (c) 2012 APA, all rights reserved)

We first describe how the concept of “fringe consciousness” () can characterise gradations of consciousness between the extremes of implicit and explicit learning. We then show that the NEO-PI-R personality measure of ). This provides empirical evidence for the proposed phenomenology and functional role of fringe consciousness in so-called implicit learning paradigms (Mangan, 1993b). Introducing an individual difference variable also helped to identify possible limitations of the exclusion task as a measure of conscious sequence knowledge. Further exploration of individual differences in fringe awareness may help to avoid polarity in the implicit learning debate, and to resolve apparent inconsistencies between previous SRT studies.

We argue performance in the serial reaction time (SRT) task is associated with gradations of awareness that provide examples of fringe consciousness [Mangan, B. (1993b). Taking phenomenology seriously: the “fringe” and its implications for cognitive research. Consciousness and Cognition, 2, 89–108, Mangan, B. (2003). The conscious “fringe”: Bringing William James up to date. In B. J. Baars, W. P. Banks & J. B. Newman (Eds.), Essential sources in the scientific study of consciousness (pp. 741–759). Cambridge, MA: The MIT Press.], and address limitations of the traditional SRT procedure, including criticism of exclusion generation tasks. Two experiments are conducted with a modified SRT procedure where irrelevant stimulus attributes obscure the sequence rule. Our modified paradigm, which includes a novel exclusion task, makes it easier to demonstrate a previously controversial influence of response stimulus interval (RSI) on awareness. It also allows identification of participants showing fringe consciousness rather than explicit sequence knowledge, as reflected by dissociations between different awareness measures. The NEO-PI-R variable Openness to Feelings influenced the diversity of subjective feelings reported during two awareness measures, but not the degree of learning and awareness as previously found with traditional SRT tasks [Norman, E., Price, M. C., & Duff, S. C. (2006). Fringe consciousness in sequence learning: the influence of individual differences. Consciousness and Cognition, 15(4), 723–760.]. This suggests possible distinctions between two components of fringe consciousness.

ABSTRACT Two experiments were carried out to investigate the process by which Ss respond to the statistical nature of the stimulus array, a process defined as “implicit learning”. An artificial grammar was used to generate the stimuli. Experiment I showed that Ss learned to become increasingly sensitive to the grammatical structure of the stimuli, but little was revealed about the nature of such learning. Experiment II showed that information gathered about the grammar in a memorization task could be extended to a recognition task with new stimuli. Various analyses of the data strongly implied that Ss were learning to respond to the general grammatical nature of the stimuli, rather than learning to respond according to specific coding systems imposed upon the stimuli. It was argued that this “implicit” learning is similar in nature to the “differentiation” process of perceptual learning espoused by Gibson and Gibson (1955).

Abstract Artificial grammar learning (AGL) is one of the most commonly used paradigms for the study of implicit learning and the contrast between rules, similarity, and associative learning. Despite five decades of extensive research, however, a satisfactory theoretical consensus has not been forthcoming. Theoretical accounts of AGL are reviewed, together with relevant human experimental and neuroscience data. The author concludes that satisfactory understanding of AGL requires (a) an understanding of implicit knowledge as knowledge that is not consciously activated at the time of a cognitive operation; this could be because the corresponding representations are impoverished or they cannot be concurrently supported in working memory with other representations or operations, and (b) adopting a frequency-independent view of rule knowledge and contrasting rule knowledge with specific similarity and associative learning (co-occurrence) knowledge.

ABSTRACT Mangan's (2001) concept of fringe consciousness is too heavily based on informal introspection, and too all-embracing to constitute a coherent family. It lacks the tight operationalisation needed to identify individual examples of fringe consciousness, and to test Mangan's theoretical account against detailed findings from empirical research. I propose a more focused two-component operationalisation of the fringe. The first component addresses how we can operationalise the consciousness of the fringe; here I draw lessons from research in implicit cognition, and suggest implications for the wider understanding of consciousness. The second component addresses the informational content of the fringe.

Abstract; Attention and implicit learning. John Benjamins Publishing Company, Amsterdam, pp 181–213, ) reported that increasing the response–stimulus interval (RSI) during incidental sequence learning improved participants’ ability to discriminate old and new sequences in a recognition test. However, the original experimental design confounded RSI effects during training and test. I therefore repeated the experiment with an improved design in which RSI was varied systematically during the training phase and the recognition task. Participants learned a sequence of response locations either incidentally or intentionally. As a result, sequence recognition was not affected by the RSI manipulations in the group of incidental learners. With intentional learning instructions, recognition was unaffected by training RSI, but a long RSI in the test phase improved recognition performance over a short RSI. Response latencies while executing the test sequences indicated no effect of training RSI on sequence learning. However, sequence knowledge was expressed more readily when the RSI in the test phase matched the RSI in the training phase.

Research on incidental sequence typically is concerned with the characteristics of implicit or nonconscious . In this article, the authors aim to elucidate the cognitive mechanisms that contribute to the generation of explicit, reportable sequence knowledge. According to the unexpected-event hypothesis (P. A. Frensch, H. Haider, D. R nger, U. Neugebauer, S. Voigt, & J. Werg, 2003), individuals acquire reportable knowledge when they search for the cause of an experienced deviation from the expected task performance. The authors experimentally induced unexpected events by disrupting the sequence process with a modified serial reaction time task and found that, unlike random transfer sequences, a systematic transfer sequence increased the availability of reportable sequence knowledge. The lack of a facilitative effect of random sequences is explained by the detrimental effect of random events on the presumed search process that generates reportable knowledge. This view is corroborated in a final experiment in which the facilitative effect of systematic transfer blocks is offset by a concurrent secondary task that was introduced to interfere with the search process during transfer.

For nearly two decades, researchers have investigated spatial sequence learning in an attempt to identify what specifically is learned during sequential tasks (e.g., stimulus order, response order, etc.). Despite extensive research, controversy remains concerning the information-processing locus of this learning effect. There are three main theories concerning the nature of spatial sequence learning, corresponding to the perceptual, motor, or response selection (i.e., central mechanisms underlying the association between stimulus and response pairs) processes required for successful task performance. The present data investigate this controversy and support the theory that stimulus—response (S—R) rules are critical for sequence learning. The results from two experiments demonstrate that sequence learning is disrupted only when the S—R rules for the task are altered. When the S—R rules remain constant or involve only a minor transformation, significant sequence learning occurs. These data implicate spatial response selection as a likely mechanism mediating spatial sequential learning.

Some spatio-temporal structures are easier to transfer implicitly in sequential learning. In this study, we investigated whether the consistent reversal of triads of learned components would support the implicit transfer of their temporal structure in visuomotor sequence learning. A triad comprised three sequential button presses ([1][2][3]) and seven consecutive triads comprised a sequence. Participants learned sequences by trial and error, until they could complete it 20 times without error. Then, they learned another sequence, in which each triad was reversed ([3][2][1]), partially reversed ([2][1][3]), or switched so as not to overlap with the other conditions ([2][3][1] or [3][1][2]). Even when the participants did not notice the alternation rule, the consistent reversal of the temporal structure of each triad led to better implicit transfer; this was confirmed in a subsequent experiment. These results suggest that the implicit transfer of the temporal structure of a learned sequence can be influenced by both the structure and consistency of the change.

Implicit learning and transfer in sequence acquisition play important roles in daily life. Several previous studies have found that even when participants are not aware that a transfer sequence has been transformed from the learning sequence, they are able to perform the transfer sequence faster and more accurately; this suggests implicit transfer of visuomotor sequences. Here, we investigated whether implicit transfer could be modulated by the number of trials completed in a learning session. Participants learned a sequence through trial and error, known as the m n task (Hikosaka et al. in J Neurophysiol 74:16521661, 1995 ). In the learning session, participants were required to successfully perform the same sequence 4, 12, 16, or 20 times. In the transfer session, participants then learned one of two other sequences: one where the button configuration Vertically Mirrored the learning sequence, or a randomly generated sequence. Our results show that even when participants did not notice the alternation rule (i.e., vertical mirroring), their total working time was less and their total number of errors was lower in the transfer session compared with those who performed a Random sequence, irrespective of the number of trials completed in the learning session. This result suggests that implicit transfer likely occurs even over a shorter learning duration.

Consciousness has always been much concerned in cognition science and, with the discovery of implicit learning in artificial grammar learning(AGL) researches, influences of unconscious processes on human cognition have been unprecedentedly highlighted. Dozens of empirical investigations have distinguished two different types of learning, i.e. explicit learning and implicit learning which involve conscious and unconscious processing respectively. Hence their critical attributes and interactive patterns have undergone tentative explorations and several theoretical frameworks have been proposed to demonstrate the underlying mental mechanisms, most of which take the side of dualistic logic. Empirical data tend to indicate that, rather than stand in dichotomy, so often they co-exist only with a quantitative difference. The academic dilemma is now broken through by the graded consciousness hypothesis, as a result of which new perspective arises from the graded consciousness dimension to deeply investigate implicit learning. In the present research the dynamic mental evolution pattern has been explored in artificial grammar learning, concerning both consciousness and knowledge representation. The current research adopts hypothesis of distributive representation and representation rehearsal which indicates that the ever-optimizing distributive representation dominates the learning process. Thus graded consciousness comes into form due to the increasing contribution of conscious processing. A dual-task design was introduced in current study with reference to the PDP paradigm formerly adopted in implicit memory researches. The innovative paradigm adopted a low' learning task and a uick' task and the contribution patterns of consciousness and unconsciousness are different in the two tasks, as a result of which the contributions of conscious and unconscious processes could be extracted dynamically along the learning course. This innovative paradigm also makes possible a direct investigation of graded consciousness during the learning phase. The results of current study show that, in the implicit phase of artificial grammar learning, the contribution of conscious processing exhibited a slow-first-fast-later growing pattern while a slow-first-stable-later pattern was found with unconscious processing. In the beginning unconscious contribution prevailed but was eventually exceeded by conscious process in the subsequent blocks. However, in the first half of learning phase, consciousness contribution suffered an undulating performance while unconsciousness more stable. While entering the second half of learning phase, unconsciousness contribution exhibited a stagnating pattern and the uneven mode faded with consciousness process. These findings, compatible with those empirical researches assuming dichotomy logic, not only define distinguishable features for implicit learning and explicit learning, but also demonstrate the graded consciousness in artificial grammar learning and make possible a learning continuum progressing throughout the learning phase of artificial grammar. In the current study which assumed graded consciousness perspective the structures of knowledge representations have also been discussed indirectly. Conclusions are that the developing of unconscious representations precedes that of conscious representations, considering the undulation in the first half phase for consciousness and the stagnation in the second half phase for unconsciousness, which indicates a possible synergic effect between conscious and unconscious processing.

Consciousness has always been much concerned in cognition science and, with the discovery of implicit learning in artificial grammar learning (AGL) researches, influences of unconscious processes on human cognition have been unprecedentedly highlighted. Dozens of empirical investigations have distinguished two different types of learning, i.e. explicit learning and implicit learning which involve conscious and unconscious processing respectively. Hence their critical attributes and interactive patterns have undergone tentative explorations and several theoretical frameworks have been proposed to demonstrate the underlying mental mechanisms, most of which take the side of dualistic logic. Empirical data tend to indicate that, rather than stand in dichotomy, so often they co-exist only with a quantitative difference. The academic dilemma is now broken through by the graded consciousness hypothesis, as a result of which new perspective arises from the graded consciousness dimension to deeply investigate implicit learning. In the present research the dynamic mental evolution pattern has been explored in artificial grammar learning, concerning both consciousness and knowledge representation. The current research adopts hypothesis of distributive representation and representation rehearsal which indicates that the ever-optimizing distributive representation dominates the learning process. Thus graded consciousness comes into form due to the increasing contribution of conscious processing. A dual-task design was introduced in current study with reference to the PDP paradigm formerly adopted in implicit memory researches. The innovative paradigm adopted a low learning task and a uick task and the contribution patterns of consciousness and unconsciousness are different in the two tasks, as a result of which the contributions of conscious and unconscious processes could be extracted dynamically along the learning course. This innovative paradigm also makes possible a direct investigation of graded consciousness during the learning phase. The results of current study show that, in the implicit phase of artificial grammar learning, the contribution of conscious processing exhibited a slow-first-fast-later growing pattern while a slow-first-stable-later pattern was found with unconscious processing. In the beginning unconscious contribution prevailed but was eventually exceeded by conscious process in the subsequent blocks. However, in the first half of learning phase, consciousness contribution suffered an undulating performance while unconsciousness more stable. While entering the second half of learning phase, unconsciousness contribution exhibited a stagnating pattern and the uneven mode faded with consciousness process. These findings, compatible with those empirical researches assuming dichotomy logic, not only define distinguishable features for implicit learning and explicit learning, but also demonstrate the graded consciousness in artificial grammar learning and make possible a learning continuum progressing throughout the learning phase of artificial grammar. In the current study which assumed graded consciousness perspective the structures of knowledge representations have also been discussed indirectly. Conclusions are that the developing of unconscious representations precedes that of conscious representations, considering the undulation in the first half phase for consciousness and the stagnation in the second half phase for unconsciousness, which indicates a possible synergic effect between conscious and unconscious processing.

Norman, Price and Duff (2006) found that scores on the openness/feeling scale of NEO-PI-R could predict performance on deterministic implicit sequence learning. In another study, no such correlation was identified in complex probabilistic implicit sequence learning (Norman, Price, Duff, & Mentzoni, 2007). However, Kaufman, et al. (2010) found that performance on probabilistic implicit sequence learning was significantly related to the openness scale (i.e., it includes four dimensions of aesthetics, imagination, feeling and plot) of NEO-PI-R. The researchers concluded that implicit learning might be relate to experience openness rather than to feeling openness. In the present study, by adopting Norman, et al. experimental design (2007), but with fewer blocks (11 blocks) and more response stimulus intervals (5 RSIs), it was found that scores on the openness/feeling scale could predict performance on probabilistic implicit sequence learning. Specifically, individuals with high vs. low openness/feeling tend to show significant differences in implicit gradient process. In Experiment 1, a complex probabilistic implicit sequence learning procedure (Norman, et al., 2007) was used. There were two sequences in the training stage. One was probable sequence (SOC1 or SOC2) with a probability of 0.88, The other was improbable sequence (SOC2 or SOC1) with the probability of 0.12. For the experimental group, a 2 (high vs. low openness/feeling group) 2 (probable vs. improbable sequence) 11 (block) mixed design was used. The procedure for the experimental group was consisted of a training phase, a recognition phase, and a generation test phase (the generation test includes both a contain task and a rotation task). Each openness/feeling group was consisted of 38 subjects. For the control group, a 2 (high vs. low openness/feeling group) 11 (block) mixed design was used. The control group was asked to study a random sequence and received only a training phase. In experiment 2, a 2 (high vs. low openness/feeling group) 4 (RSI: 0 ms, 250 ms, 750 ms, 1000 ms) 2 (probable vs. improbable sequence) 11 (block) mixed design was used. Numbers of subjects for each openness/feeling group were around 20. The experimental process was the same as the experiment 1. No significant reaction time decrement was found in the control group in experiment 1. Therefore, reaction time decrement was used as an indicator of implicit learning for the experimental group. It was found that, when RSI was 500 ms, both high and low openness/feeling groups could learn probable sequence, but only high openness/feeling group eventually acquired improbable sequence. In experiment 2, When RSI was smaller than 500ms, high openness/feeling group failed to acquire either probable or improbable sequence before transfer block 9, but acquire both after transfer block 9. When RSI was greater than or equal to 500ms, high openness/feeling group acquired probable sequence before transfer block 9 and improbable sequence after transfer block 9. In contrast, low openness/feeling group could acquire probable sequence before transfer block 9 in all RSIs, but failed to learn improbable sequence regardless of RSI setting. Different from previous researchs, significant block reaction time differences (i.e., between transfer block 9 and block 8, as well as between transfer block 9 and block 10) used as the amount of implicit learning in previous researchs were not detected for the high and low openness/feeling groups in all RSIs, except for low openness/feeling group in RSI -0 ms. And surprisingly, in all RSIs, participants scores for recognition, contain task and rotation tasks were at or below the random level. Low openness/feeling group performed significantly better than high openness/feeling group in recognition task when RSI was 750 ms and rotation task when RSI was 500 ms. Results from the two experiments proved that scores on the openness/feeling scale of NEO-PI-R can predict individual differences in probabilistic implicit sequence learning. Essential differences between high and low openness/feeling groups exist in implicit acquisition process of probable and improbable sequences along with the increase of the RSI. High openness/feeling group could learn probable and improbable sequences by using collateral elaboration, but low openness/feeling group could only learn probable sequence. For studying implicit learning and individual differences in probabilistic implicit sequence learning, improbable sequence leaning can be a sensitive measure, while other measures such as transfer block, recognition task, and generation task are limited in terms of their predictability because of the interference of improbable sequence learning.