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. (shrink)
While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current (...) thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems. (shrink)
By assuming that conscious states are the only constructs entitled to bear a cognitive status, while denying this status both to the learning processes and to their nonconscious outcomes, the SOC view leaves consciousness alone as the single tool to explain itself. This does not endow consciousness with any self-organizing properties, but rather, draws a deliberately shallow outline of cognition.
Electronic Mail: jimenez@usc.es Abstract Stability of activation, while it may be necessary for information to become available to consciousness, is not sufficient to produce phenomenal experience. We suggest that consciousness involves access to information and that access makes information symbolic. From this perspective, implicit representations exist, and are best thought of as sub-symbolic. Crucially, such representations can be causally efficacious in the absence of consciousness.
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. (shrink)
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). (shrink)