Luis Jimenez

Comparing the relative sensitivity of direct and indirect measures of learning is proposed as the best way to provide evidence for unconscious learning when both conceptual and operative definitions of awareness are lacking. This approach was first proposed by Reingold & Merikle (1988) in the context of subliminal perception. In this paper, we apply it to a choice reaction time task in which the material is generated based on a probabilistic finite-state grammar (Cleeremans, 1993). We show (1) that participants progressively learn about the statistical structure of the stimulus material over training with the choice reaction time task, and (2) that they can use some of this knowledge to predict the location of the next stimulus in a subsequent “generation” task. However, detailed partial correlational analyses of the correspondence between performance during the reaction time task and the statistical structure of the training material showed that large effects remained even when controlling for explicit knowledge as assessed by the generation task. Hence we conclude (1) that at least some of the knowledge expressed through reaction time performance can not be characterized as conscious, and (2) that even when associations are found at a global level of analysis, dissociations can still be obtained when more detailed analyses are conducted. Finally, we also show that participants are limited in the depth of the contingencies they can learn about, and that these limitations are shared by the Simple Recurrent Network model of Cleeremans & McClelland (1991)

Dienes & Perner's target article is not a satisfactory theory of implicit knowledge because in endorsing the representational theory of knowledge, the authors also inadvertently accept that only explicit knowledge can be causally efficacious, and hence that implicit knowledge is an inert category. This conflation between causal efficacy, knowledge, and explicitness is made clear through the authors' strategy, which consists of attributing any observable effect to the existence of representations that are as minimally explicit as needed to account for behavior. In contrast, we believe that causally efficacious and fully implicit knowledge exists, and is best embodied in frameworks that depart radically from classical assumptions.

Attention is often dichotomized into controlled vs. automatic processing, where controlled processing is slow, flexible, and intentional, and automatic processing is fast, inflexible, and unintentional. In contrast to this strict dichotomy, there is mounting evidence for context-specific processes that are engaged rapidly yet are also flexible. In the present study we extend this idea to the domain of implicit learning to examine whether flexibility in automatic processes can be implemented through the reliance on contextual features. Across three experiments we show that participants can learn implicitly two complementary sequences that are associated with distinct contexts, and that transfer of learning when the two contexts are randomly intermixed depends on the distinctiveness of the two contexts. Our results point to the role of context-specific processes in the acquisition and expression of implicit sequence knowledge, and also suggest that episodic details can be represented in sequence knowledge

Jackson and Jackson (1995) argue that most current tests used to assess awareness of sequential material are flawed because of their emphasis on accuracy. They propose to distinguish two forms of sequence knowledge: Serial knowledge, that is, knowledge about the specific sequence that stimuli follow, which involves information about the statistical relationship between many sequence elements, and statistical knowledge, or knowledge about the probability of different transitions between adjacent sequence elements. Further, they suggest a new method to analyze generation performance, which involves considering the correlation between subjects' responses and the distribution of transition probabilities, regardless of the accuracy of generation performance. In this comment, we first suggest that the distinction between serial and statistical knowledge is unwarranted except in one case which is not addressed by Jackson and Jackson. We propose instead that all sequence knowledge is essentially statistical in nature. Second, we suggest that using probabilistic instead of deterministic sequences is a better way to approach the assessment of explicit knowledge, and illustrate this contention with empirical and simulated examples based on previous and current research (Cleeremans, 1993; Cleeremans and McClelland, 1991; Jimenez, Mendez and Cleeremans

We deal with situations incongruent with our automatic response tendencies much better right after having done so on a previous trial than after having reacted to a congruent trial. The nature of the mechanisms responsible for these sequential congruency effects is currently a hot topic of debate. According to the conflict monitoring model these effects depend on the adjustment of control triggered by the detection of conflict on the preceding situation. We tested whether these conflict monitoring processes can operate implicitly in an implicit learning procedure, modulating the expression of knowledge of which participants are not aware. We reanalyze recently published data, and present an experiment with a probabilistic sequence learning procedure, both showing consistent effects of implicit sequence learning. Despite being implicit, the expression of learning was reduced or completely eliminated right after trials incongruent with the learned sequence, thus showing that sequential congruency effects can be obtained even when the source of congruency itself remains implicit