Implicit learning is a core process for the acquisition of a complex, rule‐based environment from mere interaction, such as motor action, skill acquisition, or language. A body of evidence suggests that implicit knowledge governs music acquisition and perception in nonmusicians and musicians, and that both expert and nonexpert participants acquire complex melodic, harmonic, and other features from mere exposure. While current findings and computational modeling largely support the learning of chunks, some results indicate learning of more complex structures. Despite the (...) body of evidence, more research is required to support the cross‐cultural validity of implicit learning and to show that core and more complex music theoretical features are acquired implicitly. (shrink)

The hallmark of implicit learning is that complex knowledge can be acquired unconsciously. The second order conditionals of Reed and Johnson were developed to be complex, and they are popular materials for implicit learning research. Recently, it was demonstrated that in a sequence made noisy , shared features of the SOCs may be learned explicitly . What are these shared features? We hypothesized that low reversal frequency may play a significant role. We have varied reversal frequency, and discovered that reversal (...) frequency affected response times, inclusion exclusion behavior, and recognition ratings. Not only does it appear to be important to distinguish implicit and explicit knowledge, but also to distinguish what the knowledge is of. (shrink)

How do we find out whether someone is conscious of some information or not? A simple answer is “We just ask them”! However, things are not so simple. Here, we review recent developments in the use of subjective and objective methods in implicit learning research and discuss the highly complex methodological problems that their use raises in the domain.

We investigated the automaticity of implicit sequence learning by varying perceptual load in a pure perceptual sequence learning paradigm. Participants responded to the randomly changing identity of a target, while the irrelevant target location was structured. In Experiment 1, the target was presented under low or high perceptual load during training, whereas testing occurred without load. Unexpectedly, no sequence learning was observed. In Experiment 2, perceptual load was introduced during the test phase to determine whether load is required to express (...) perceptual knowledge. Learning itself was unaffected by visuospatial demands, but more learning was expressed under high load test conditions. In Experiment 3, we demonstrated that perceptual load is not required for the acquisition of perceptual sequence knowledge. These findings suggest that perceptual load does not mediate the perceptual sequence learning process itself, supporting the automaticity of implicit learning, but is mandatory for the expression of pure perceptual sequence knowledge. (shrink)

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The demonstration of a sequential congruency effect in sequence learning has been offered as evidence for control processes that act to inhibit automatic response tendencies via unconscious conflict monitoring. Here we propose an alternative interpretation of this effect based on the associative learning of chains of sequenced contingencies. This account is supported by simulations with a Simple Recurrent Network, an associative model of sequence learning. We argue that the control- and associative-based accounts differ in their predictions concerning the magnitude of (...) the sequential congruency effect across training. These predictions are tested by reanalysing data from a study by Shanks, Wilkinson, and Channon . The results support the associative learning account which explains the sequential congruency effect without appealing to control processes. (shrink)