Biomedical subjects

Axel Cleeremans

Publications and source records attributed to Axel Cleeremans.

9 recordsLinked to original sources

PubMed2006

Can amnesic patients learn without awareness? New evidence comparing deterministic and probabilistic sequence learning.

Can associative learning take place without awareness? We explore this issue in a sequence learning paradigm with amnesic and control participants, who were simply asked to react to one of four possible stimuli on each trial. Unknown to them, successive stimuli occurred in a sequence. We manipulated the extent to which stimuli followed the sequence in a deterministic manner (noiseless condition) or only probabilistically so (noisy condition). Through this paradigm, we aimed at addressing two central issues: first, we asked whether sequence learning takes place in either condition with amnesic patients. Second, we asked whether this learning takes place without awareness. To answer this second question, participants were asked to perform a subsequent sequence generation task under inclusion and exclusion conditions, as well as a recognition task. Reaction times results show that amnesic patients learned the sequence only in the deterministic condition. However, they failed to be able to reproduce the sequence in the generation task. In contrast, we found learning for both sequence structures in control participants, but only control participants exposed to a deterministic sequence were successful in performing the generation task, thus suggesting that the acquired knowledge can be used consciously in this condition. Neither amnesic nor control participants showed correct old/new judgments in the recognition task. The results strengthen the claim that implicit learning is at least partly spared in amnesia, and the role of contextual information available for learning is discussed.

Adult↗

PubMed2006

Dissociating the effects of automatic activation and explicit expectancy on reaction times in a simple associative learning task.

After repeated associations between two events, E1 and E2, responses to E2 can be facilitated either because participants consciously expect E2 to occur after E1 or because E1 automatically activates the response to E2, or because of both. In this article, the authors report on 4 experiments designed to pit the influence of these 2 factors against each other. The authors found that the fastest responses to a target in a reaction time paradigm occurred when automatic activation was highest and conscious expectancy lowest. These results, when considered together with previous findings indicating that, under most conditions, the relation between expectancy and reaction times is in the opposite direction, are indicative of a reversed association-an interaction pattern that J. C. Dunn and K. Kirsner (1988) demonstrated to be the only one that unambiguously points to the involvement of independent processes.

Adolescent↗

PubMed2005

The neural correlates of implicit and explicit sequence learning: Interacting networks revealed by the process dissociation procedure.

In two H2(15)O PET scan experiments, we investigated the cerebral correlates of explicit and implicit knowledge in a serial reaction time (SRT) task. To do so, we used a novel application of the Process Dissociation Procedure, a behavioral paradigm that makes it possible to separately assess conscious and unconscious contributions to performance during a subsequent sequence generation task. To manipulate the extent to which the repeating sequential pattern was learned explicitly, we varied the pace of the choice reaction time task-a variable that is known to have differential effects on the extent to which sensitivity to sequence structure involves implicit or explicit knowledge. Results showed that activity in the striatum subtends the implicit component of performance during recollection of a learned sequence, whereas the anterior cingulate/mesial prefrontal cortex (ACC/MPFC) supports the explicit component. Most importantly, we found that the ACC/MPFC exerts control on the activity of the striatum during retrieval of the sequence after explicit learning, whereas the activity of these regions is uncoupled when learning had been essentially implicit. These data suggest that implicit learning processes can be successfully controlled by conscious knowledge when learning is essentially explicit. They also supply further evidence for a partial dissociation between the neural substrates supporting conscious and nonconscious components of performance during recollection of a learned sequence.

Adolescent↗

PubMed2005

Processing abstract sequence structure: learning without knowing, or knowing without learning?

Constant interaction with a dynamic environment-from riding a bicycle to segmenting speech-makes sensitivity to the sequential structure of the world a fundamental dimension of information processing. Accounts of sequence learning vary widely, with some authors arguing that parsing and segmentation processes are central, and others proposing that sequence learning involves mere memorization. In this paper, we argue that sequence knowledge is essentially statistical in nature, and that sequence learning involves simple associative prediction mechanisms. We focus on a choice reaction situation introduced by Lee (1997), in which participants were exposed to material that follows a single abstract rule, namely that stimuli are selected randomly, but never appear more than once in a legal sequence. Perhaps surprisingly, people can learn this rule very well. Or can they? We offer a conceptual replication of the original finding, but a very different interpretation of the results, as well as simulation work that makes it clear how highly abstract dimensions of the stimulus material can in fact be learned based on elementary associative mechanisms. We conclude that, when relevant, memory is optimized to facilitate responding to events that have not occurred recently, and that sequence learning in general always involves sensitivity to repetition distance.

Adolescent↗

PubMed2005

Consciousness: converging insights from connectionist modeling and neuroscience.

Over the past decade, many findings in cognitive neuroscience have resulted in the view that selective attention, working memory and cognitive control involve competition between widely distributed representations. This competition is biased by top-down projections (notably from prefrontal cortex), which can selectively enhance some representations over others. This view has now been implemented in several connectionist models. In this review, we emphasize the relevance of these models to understanding consciousness. Interestingly, the models we review have striking similarities to others directly aimed at implementing 'global workspace theory'. All of these models embody a fundamental principle that has been used in many connectionist models over the past twenty years: global constraint satisfaction.

Consciousness↗

PubMed2005

Computational correlates of consciousness.

Over the past few years numerous proposals have appeared that attempt to characterize consciousness in terms of what could be called its computational correlates: Principles of information processing with which to characterize the differences between conscious and unconscious processing. Proposed computational correlates include architectural specialization (such as the involvement of specific regions of the brain in conscious processing), properties of representations (such as their stability in time or their strength), and properties of specific processes (such as resonance, synchrony, interactivity, or information integration). In exactly the same way as one can engage in a search for the neural correlates of consciousness, one can thus search for the computational correlates of consciousness. The most direct way of doing is to contrast models of conscious versus unconscious information processing. In this paper, I review these developments and illustrate how computational modeling of specific cognitive processes can be useful in exploring and in formulating putative computational principles through which to capture the differences between conscious and unconscious cognition. What can be gained from such approaches to the problem of consciousness is an understanding of the function it plays in information processing and of the mechanisms that subtend it. Here, I suggest that the central function of consciousness is to make it possible for cognitive agents to exert flexible, adaptive control over behavior. From this perspective, consciousness is best characterized as involving (1) a graded continuum defined over quality of representation, such that availability to consciousness and to cognitive control correlates with properties of representation, and (2) the implication of systems of meta-representations.

Cognition↗

PubMed2005

Intuitive decision making in complex situations: somatic markers in an artificial grammar learning task.

In this article, we explore the extent to which implicit learning is subtended by somatic markers, as evidenced by skin conductance measures. On each trial, subjects were asked to decide which "word" from a pair of "words" was the "correct" one. Unknown to the subjects, each "word" of a pair was constructed using a different set of rules (Grammar A and Grammar B). A (monetary) reward was given if the subject chose the "word" from Grammar A. Choosing the Grammar B word resulted in (monetary) punishment. Skin conductance was measured during each of 100 trials. After each set of 10 trials, the subjects were asked how they selected the "correct word." Task performance increased long before the subjects could even formulate a single relevant rule. In this preconceptual phase of the experiment, skin conductance was larger before incorrect than before correct choices. Thus, it was shown that artificial grammar learning is accompanied by a somatic marker, possibly "warning" the subject of the incorrect decision.

Adolescent↗

PubMed2003

Cerebral correlates of explicit sequence learning.

Using positron emission tomography (PET) and regional cerebral blood flow (rCBF) measurements, we investigated the cerebral correlates of consciousness in a sequence learning task through a novel application of the Process Dissociation Procedure, a behavioral paradigm that makes it possible to separately assess conscious and unconscious contributions to performance. Results show that the metabolic response in the anterior cingulate/mesial prefrontal cortex (ACC/MPFC) is exclusively and specifically correlated with the explicit component of performance during recollection of a learned sequence. This suggests a significant role for the ACC/MPFC in the explicit processing of sequential material.

Adolescent↗

PubMed2003

Learned material content and acquisition level modulate cerebral reactivation during posttraining rapid-eye-movements sleep.

We have previously shown that several brain areas are activated both during sequence learning at wake and during subsequent rapid-eye-movements (REM) sleep (Nat. Neurosci. 3 (2000) 831-836), suggesting that REM sleep participates in the reprocessing of recent memory traces in humans. However, the nature of the reprocessed information remains open. Here, we show that regional cerebral reactivation during posttraining REM sleep is not merely related to the acquisition of basic visuomotor skills during prior practice of the serial reaction time task, but rather to the implicit acquisition of the probabilistic rules that defined stimulus sequences. Moreover, functional connections between the reactivated cuneus and the striatum--the latter being critical for implicit sequence learning--are reinforced during REM sleep after practice on a probabilistic rather than on a random sequence of stimuli. Our results therefore support the hypothesis that REM sleep is deeply involved in the reprocessing and optimization of the high-order information contained in the material to be learned. In addition, we show that the level of acquisition of probabilistic rules attained prior to sleep is correlated to the increase in regional cerebral blood flow during subsequent REM sleep. This suggests that posttraining cerebral reactivation is modulated by the strength of the memory traces developed during the learning episode. Our data provide the first experimental evidence for a link between behavioral performance and cerebral reactivation during REM sleep.

Adult↗