Implicit learning of first-, second-, and third-order transition probabilities

Most sequence-learning studies have confounded different types of information, making it difficult to know precisely what is learned. Addressing many of the confounds, the current study shows that people can learn 1st-, 2nd-, and 3rd-order transition probabilities. Measures directly assessing awareness of the probabilities show that the knowledge is implicit early in training and becomes explicit with extended training.     

Pure perceptual-based learning of second-, third-, and fourth-order sequential probabilities

There is evidence that sequence learning in the traditional serial reaction time task (SRTT), where target location is the response dimension, and sequence learning in the perceptual SRTT, where target location is not the response dimension, are handled by different mechanisms. The ability of the latter mechanism to learn sequential contingencies that can be learned by the former mechanism was examined. Prior research has established that people can learn second-, third-, and fourth-order probabilities in the traditional SRTT. The present study reveals that people can learn such probabilities in the perceptual SRTT. This suggests that the two mechanisms may have similar architectures. A possible neural basis of the two mechanisms is discussed.     

Implicit learning of second-, third-, and fourth-order adjacent and nonadjacent sequential dependencies

Serial reaction time (SRT) task studies have established that people can implicitly learn first- and second-order adjacent dependencies. Sequential confounds have made it impossible to draw conclusions regarding learning of nonadjacent dependencies and learning of third- and fourth-order adjacent dependencies. Addressing the confounds, the present study shows that people can implicitly learn second-, third-, and fourth-order adjacent and nonadjacent dependencies embedded in probabilistic sequences of target locations.     

Implicit learning of second-, third-, and fourth-order adjacent and nonadjacent sequential dependencies

Serial reaction time (SRT) task studies have established that people can implicitly learn first- and second-order adjacent dependencies. Sequential confounds have made it impossible to draw conclusions regarding learning of nonadjacent dependencies and learning of third- and fourth-order adjacent dependencies. Addressing the confounds, the present study shows that people can implicitly learn second-, third-, and fourth-order adjacent and nonadjacent dependencies embedded in probabilistic sequences of target locations.     

Implicit learning of semantic category sequences: response-independent acquisition of abstract sequential regularities

Through the use of a new serial naming task, the authors investigated implicit learning of repeating sequences of abstract semantic categories. Participants named objects (e.g., table, shirt) appearing in random order. Unbeknownst to them, the semantic categories of the objects (e.g., furniture, clothing) followed a repeating sequence. Irrespective of whether participants were instructed to attend to the categories (Experiment 1) or whether no mention was made of the categories (Experiments 2 and 3), naming latencies reliably increased when the repeating category sequence was switched to a random sequence. This was the case even for participants showing no explicit knowledge in reproduction and recognition tests. Results indicate that abstract sequential structures are learned implicitly, even if neither the surface stimuli nor the responses follow a sequence.     

Implicit learning

Implicit learning appears to be a fundamental and ubiquitous process in cognition. Although defining and operationalizingimplicit learning remains a central theoretical challenge, scientists' understanding of implicit learning has progressed significantly. Beyond establishing the existence of "learning without awareness," current research seeks to identify the cognitive processes that support implicit learning and addresses the relationship between learning and awareness of what was learned. The emerging view of implicit learning emphasizes the role of associative learning mechanisms that exploit statistical dependencies in the environment in order to generate highly specific knowledge representations.     

Implicit visual learning and the expression of learning

Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response devices (keyboard vs. mouse) in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes.     

Implicit learning of social predictions

Humans exchange a range of nonverbal social signals in every interaction. It is an open question whether people use these signals, consciously or unconsciously, to guide social behavior. This experiment directly tested whether participants could learn to predict another person’s behavior using nonverbal cues in a single interaction, and whether explicit knowledge of the cue-outcome relationship was necessary for successful prediction. Participants played a computerized game of rock-paper-scissors against an avatar they believed was another participant. Sometimes the avatar generated a predictive facial cue before the play. On these trials, participants’ win-frequency increased over time, even if they did not acquire explicit knowledge of the predictive cue. The degree to which participants could predict the avatar (wins on cued trials) related to their self-reported liking of the avatar. These findings demonstrate the importance of implicit associative learning mechanisms in guiding social behavior on a moment-to-moment basis during interaction.     

Implicit sequence learning and conscious awareness

This paper uses the Process Dissociation Procedure to explore whether people can acquire unconscious knowledge in the serial reaction time task [Destrebecqz, A., & Cleeremans, A. (2001). Can sequence learning be implicit? New evidence with the Process Dissociation Procedure. Psychonomic Bulletin &Review, 8, 343-350; Wilkinson, L., & Shanks, D. R. (2004). Intentional control and implicit sequence learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 354-369]. Experiment 1 showed that people generated legal sequences above baseline levels under exclusion instructions. Reward moved exclusion performance towards baseline, indicating that the extent of motivation in the test phase influenced the expression of unconscious knowledge. Experiments 2 and 3 revealed that even with reward, adding noise to the sequences or shortening training led to above-baseline exclusion performance, suggesting that task difficulty and the amount of training also affected the expression of unconscious knowledge. The results help resolve some current debates about the role of conscious awareness in sequence learning.     

Implicit learning as an ability

The ability to automatically and implicitly detect complex and noisy regularities in the environment is a fundamental aspect of human cognition. Despite considerable interest in implicit processes, few researchers have conceptualized implicit learning as an ability with meaningful individual differences. Instead, various researchers (e.g., Reber, 1993; Stanovich, 2009) have suggested that individual differences in implicit learning are minimal relative to individual differences in explicit learning. In the current study of English 16–17 year old students, we investigated the association of individual differences in implicit learning with a variety of cognitive and personality variables. Consistent with prior research and theorizing, implicit learning, as measured by a probabilistic sequence learning task, was more weakly related to psychometric intelligence than was explicit associative learning, and was unrelated to working memory. Structural equation modeling revealed that implicit learning was independently related to two components of psychometric intelligence: verbal analogical reasoning and processing speed. Implicit learning was also independently related to academic performance on two foreign language exams (French, German). Further, implicit learning was significantly associated with aspects of self-reported personality, including intuition, Openness to Experience, and impulsivity. We discuss the implications of implicit learning as an ability for dual-process theories of cognition, intelligence, personality, skill learning, complex cognition, and language acquisition.     

Implicit learning is order dependent

Psychological Research - We report two experiments using the artificial-grammar task that demonstrate order dependence in implicit learning. Studying grammatical training strings in different...     

Sequence learning and sequential effects

In a serial reaction time (RT) task with a probabilistic stimulus sequence, the length of the response-to-stimulus interval (RSI) and the sequence complexity was manipulated to investigate the relationship between sequence learning and sequential effects in serial RT tasks. Sequential effects refer to the influence of previous stimulus presentations on the RT to the current stimulus. Sequence learning is stimulus-transition specific and is demonstrated as the difference between practiced and unpracticed sequences within an interpolated random block of trials. There is a clear parallel between sequence learning and specific changes in sequential effect in the short RSI conditions, suggesting that a common mechanism may lie at the basis of sequence learning and automatic facilitation, which is responsible for sequential effects at short RSI. Importantly, the changes in sequential effects accompanying sequence learning are the same as those observed with practice in random serial RT tasks, indicating that the learning process underlying sequence learning is the same as in random tasks.     

Implicit learning of sequences of tasks

Task sets can be configured in advance of performing a new task. However, the degree to which advance information is actually used for advance configuration depends on the nature of the available information. The role of implicit learning was explored in 2 experiments by means of a modified serial reaction time task with repeated sequences of 4 dimensionally organized tasks. Although there was clear evidence for implicit learning of the sequence (of length 8), the learning was not associated with a reduction of shift costs, either with a short (200 ms) or with a long (1,200 ms) response-stimulus interval. In contrast, a reduction of shift costs was observed when external precues were introduced in a 3rd experiment. According to these results, the sequences of stimulus features that serve as cues for the tasks to perform on the stimuli are learned, but the representation of the features is void of their task-associated meanings.     

Implicit learning of ignored visual context

Humans process a visual display more efficiently when they encounter it for a second time, showing learning of the display. This study tests whether implicit learning of complex visual contexts depends on attention. Subjects searched for a white target among black and white distractors. When the locations of the target and the attended set (white distractors) were repeated, search speed was enhanced, but when the locations of the target and the ignored set (black distractors) were repeated, search speed was unaffected. This suggests that the expression of learning depends on attention. However, during the transfer test, when the previously ignored set now was attended, it immediately facilitated performance. In contrast, when the previously attended set now was ignored, it no longer enhanced search speed. We conclude that the expression of visual implicit learning depends on attention but that latent learning of repeated information does not.     

Implicit learning of new verbal associations

Implicit learning of a series of new verbal associations was studied in four experiments. The first two experiments demonstrated that learning of a repeating sequence of verbal stimuli may occur without awareness, but only when the stimulus-response mapping requires an attention-demanding activity: Subjects who were unaware of the sequence learned when instructed to categorize the stimuli, but not when instructed simply to read them. However, in both situations, unaware subjects performed no better than untrained control subjects in expressing their knowledge of the sequence explicitly. In Experiments 3 and 4, subjects showed implicit learning when the task involved either motor responses to verbal stimuli or verbal responses to spatially arranged stimuli. These findings are discussed in terms of the conditions under which implicit learning can be obtained. First, they demonstrate implicit learning of a set of new associations in the verbal domain. Second, the data suggest that attention is important in implicit learning. Finally, the degree of interitem organization that is familiar preexperimentally seems to partially determine the amount of implicit learning.     

Implicit learning of sequential bias in a guessing task: failure to demonstrate effects of dopamine administration and paranormal belief

Previous research suggests that implicit sequence learning (ISL) is superior for believers in the paranormal and individuals with increased cerebral dopamine. Thirty-five healthy participants performed feedback-guided anticipations of four arrow directions. A 100-trial random sequence preceded two 100-trial biased sequences in which visual targets (arrows) on trial t tended to be displaced 90 degrees clockwise (CW) or counter-clockwise (CCW) from those on t - 1. ISL was defined as a positive change during the course of the biased run in the difference between pro-bias and counter-bias responses. It was hypothesized that this difference would be greater for believers in the paranormal than for skeptics, for those who received dopamine than for those who received placebo, and for believers who received dopamine than for the other groups. None of the hypotheses were supported by the data. It is suggested that a simple binary guessing task with a focus on prediction accuracy during early trials should be considered for future explorations.     

The use of sequential probabilities in the segmentation of speech

The present investigation addresses the possible utility of sequential probabilities in the segmentation of spoken language. In a series of five word- spotting and two control lexical decision experiments, high- versus low-probability consonant-vowel (Experiments 1, 2, 5, and 7) and vowel-consonant (Experiments 1, 3, 4, and 6) strings were presented either in the nonsense contexts of target words (Experiments 1-3) or within the target words themselves (Experiments 4-7). The results suggest that listeners, at least for sequences in the onset position, indeed use sequential probabilities as cues for segmentation. The probability of a sound sequence influenced segmentation more when the sequence occurred within the target words (Experiments 4-7 vs. Experiments 1-3). Furthermore, the effects were reliable only when the sequences occurred in the onset position (Experiments 1, 2, 5, and 7 vs. Experiments 1, 3, 4, and 6).     

Implicit learning and statistical learning: one phenomenon, two approaches

The domain-general learning mechanisms elicited in incidental learning situations are of potential interest in many research fields, including language acquisition, object knowledge formation and motor learning. They have been the focus of studies on implicit learning for nearly 40 years. Stemming from a different research tradition, studies on statistical learning carried out in the past 10 years after the seminal studies by Saffran and collaborators, appear to be closely related, and the similarity between the two approaches is strengthened further by their recent evolution. However, implicit learning and statistical learning research favor different interpretations, focusing on the formation of chunks and statistical computations, respectively. We examine these differing approaches and suggest that this divergence opens up a major theoretical challenge for future studies.