Subjective measures of awareness and implicit cognition

Masked priming under the Bayesian microscope: Exploring the integration of local elements into global shape through Bayesian model comparison

To investigate whether local elements are grouped into global shapes in the absence of awareness, we introduced two different masked priming designs (e.g., the classic dissociation paradigm and a trial-wise probe and prime discrimination task) and collected both objective (i.e., performance based) and subjective (using the perceptual awareness scale [PAS]) awareness measures. Prime visibility was manipulated using three different prime-mask stimulus onset asynchronies (SOAs) and an unmasked condition. Our results showed that assessing prime visibility trial-wise heavily interfered with masked priming preventing any prime facilitation effect. The implementation of Bayesian regression models, which predict priming effects for participants whose awareness levels are at chance level, provided strong evidence in favor of the hypothesis that local elements group into global shape in the absence of awareness for SOAs longer than 50 ms, suggesting that prime-mask SOA is a crucial factor in the processing of the global shape without awareness.

Reduced Implicit but not Explicit Knowledge of Cross-Situational Statistical Learning in Developmental Dyslexia

Although statistical learning (SL) has been studied extensively in developmental dyslexia (DD), less attention has been paid to other fundamental challenges in language acquisition, such as cross-situational word learning. Such investigation is important for determining whether and how SL processes are affected in DD at the word level. In this study, typically developed (TD) adults and young adults with DD were exposed to a set of trials that contained multiple spoken words and multiple pictures of individual objects, with no information about word-referent correspondences provided within a trial. Nonetheless, cross-trial statistical relations could be exploited to learn word-referent mappings. The degree of within-trial reference uncertainty and the novelty of to-be-learned objects (novel or familiar) were varied under different learning conditions. The results show that across all conditions, young adults with DD were significantly impaired in their ability to exploit cross-trial regularities in co-occurring visual-auditory streams to discover word-referent mappings. Observed impairments were most pronounced when within-trial reference uncertainty was the highest. Subjective measures of knowledge awareness revealed greater development of implicit but not explicit knowledge in the TD group than in the DD group. Together, these findings suggest that the SL deficit in DD affects fundamental language learning challenges at the word level and points to greater reliance on explicit processes due to impaired implicit associative learning among individuals with DD. Such a deficit is likely to influence spoken language acquisition, and in turn affect literacy skills, in people with DD.

Time-sensitive prefrontal involvement in associating confidence with task performance illustrates metacognitive introspection in monkeys

Metacognition refers to the ability to be aware of one's own cognition. Ample evidence indicates that metacognition in the human primate is highly dissociable from cognition, specialized across domains, and subserved by distinct neural substrates. However, these aspects remain relatively understudied in macaque monkeys. In the present study, we investigated the functionality of macaque metacognition by combining a confidence proxy, hierarchical Bayesian meta-d' computational modelling, and a single-pulse transcranial magnetic stimulation technique. We found that Brodmann area 46d (BA46d) played a critical role in supporting metacognition independent of task performance; we also found that the critical role of this region in meta-calculation was time-sensitive. Additionally, we report that macaque metacognition is highly domain-specific with respect to memory and perception decisions. These findings carry implications for our understanding of metacognitive introspection within the primate lineage.

Capturing richer information: On establishing the validity of an interval-valued survey response mode

Obtaining quantitative survey responses that are both accurate and informative is crucial to a wide range of fields. Traditional and ubiquitous response formats such as Likert and visual analogue scales require condensation of responses into discrete or point values—but sometimes a range of options may better represent the correct answer. In this paper, we propose an efficient interval-valued response mode, whereby responses are made by marking an ellipse along a continuous scale. We discuss its potential to capture and quantify valuable information that would be lost using conventional approaches, while preserving a high degree of response efficiency. The information captured by the response interval may represent a possible response range—i.e., a conjunctive set, such as the real numbers between 3 and 6. Alternatively, it may reflect uncertainty in respect to a distinct response—i.e., a disjunctive set, such as a confidence interval. We then report a validation study, utilizing our recently introduced open-source software (DECSYS), to explore how interval-valued survey responses reflect experimental manipulations of several factors hypothesised to influence interval width, across multiple contexts. Results consistently indicate that respondents used interval widths effectively, and subjective participant feedback was also positive. We present this as initial empirical evidence for the efficacy and value of interval-valued response capture. Interestingly, our results also provide insight into respondents’ reasoning about the different aforementioned types of intervals—we replicate a tendency towards overconfidence for those representing epistemic uncertainty (i.e., disjunctive sets), but find intervals representing inherent range (i.e., conjunctive sets) to be well-calibrated.

Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning

In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements in state of the art models. One advantage of this technological boost is to facilitate comparison between different neural networks and human performance, in order to deepen our understanding of human cognition. Here, we investigate which neural network architecture (feedforward vs. recurrent) matches human behavior in artificial grammar learning, a crucial aspect of language acquisition. Prior experimental studies proved that artificial grammars can be learnt by human subjects after little exposure and often without explicit knowledge of the underlying rules. We tested four grammars with different complexity levels both in humans and in feedforward and recurrent networks. Our results show that both architectures can "learn" (via error back-propagation) the grammars after the same number of training sequences as humans do, but recurrent networks perform closer to humans than feedforward ones, irrespective of the grammar complexity level. Moreover, similar to visual processing, in which feedforward and recurrent architectures have been related to unconscious and conscious processes, the difference in performance between architectures over ten regular grammars shows that simpler and more explicit grammars are better learnt by recurrent architectures, supporting the hypothesis that explicit learning is best modeled by recurrent networks, whereas feedforward networks supposedly capture the dynamics involved in implicit learning.

Reactivity to Measures of Metacognition

Metacognition is typically measured by collecting self-reported information from participants while they complete a cognitive task. Recent evidence suggests that eliciting such metacognitive information from participants can impact both their metacognitive processes and their cognitive performance. Although there are contradictory findings regarding the magnitude and even the direction of this effect, recent evidence has converged to provide a clearer picture of the mechanisms that determine reactivity. Here, we provide a review of the evidence that measures of metacognition, namely think-aloud protocols, judgments of learning, and confidence ratings, are reactive. We argue that reactivity has important implications not just for the measurement of metacognition, but for metacognition theorizing because reactivity can provide insights into the cues participants use to monitor their performance. Drawing from this synthesis of evidence, we propose a tentative framework for studying reactivity that integrates cue processing accounts of reactivity with existing models of metacognition. We conclude the review by addressing some of the pertinent questions yet to be comprehensively addressed by reactivity research, including how researchers should best address issues of reactivity when using experimental designs.

Monkey Metacognition Could Generate More Insight

Monkeys demonstrate metacognition by avoiding memory tests when they forget, seeking information when ignorant, and gambling sensibly after making judgments. Some of this metacognition appears to be based on introspection of private mental states. It is likely that nonhuman cognitive systems, like human systems, differ in accessibility to such introspective metacognition, and the extent to which differences in access map to explicit and implicit cognition will be an important topic for future work. It will be exciting to learn more about the distribution of metacognition among species, and the conditions under which metacognition evolves.

A dual-process account of digit invariance learning

Performance in the McGeorge and Burton (1990) digit invariance task was originally thought to be mediated by unconscious abstraction of a “rule” that identified the invariant feature across all study items. Subsequent explanations have suggested explicit strategy use or similarity-to-exemplar matching rather than abstraction. This paper presents data that suggest that both similarity and abstraction can be used under different task demands. Delay between study and test afforded abstraction of the invariant knowledge whereas reducing the pool of study exemplars enhanced responding based on specific similarity. These results parallel effects found in the categorization literature. Rule abstraction in this sense may be due to statistical learning of feature frequency rather than abstraction of a central tendency or a complex/conceptual rule. Categorizing responses into subjective memory states (remember/know/guess) demonstrates that neither the similarity matching nor the abstraction mechanism uses information from episodic memory. Confidence measures show that participants are more confident of responses when the prototypical representation is used but not specific similarity. Taken together, these data suggest that abstracted knowledge is not held consciously but that participants have meta-awareness of when they are using the abstracted representation.

Differences in the types of musical regularity learnt in incidental- and intentional-learning conditions

Several studies have found learning of biconditional grammars only under intentional rule-search conditions (e.g., Johnstone & Shanks, 2001). Memorization of strings merely led to the learning of chunks. We used a musical grammar, a diatonic inversion, that is a type of biconditional grammar. Participants either were required to memorize a set of grammatical tunes (incidental learning), or were asked to search for the underlying rule whilst being given feedback about their performance (intentional learning). The results showed that participants in the incidental-learning condition did not learn the inversion rule and merely acquired explicit knowledge about chunks. However, participants in the intentional-learning condition learnt both the inversion rule and chunks.

Associationism and cognition: Human contingency learning at 25

A major topic within human learning, the field of contingency judgement, began to emerge about 25 years ago following publication of an article on depressive realism by Alloy and Abramson (1979). Subsequently, associationism has been the dominant theoretical framework for understanding contingency learning but this has been challenged in recent years by an alternative cognitive or inferential approach. This article outlines the key conceptual differences between these approaches and summarizes some of the main methods that have been employed to distinguish between them.

The effect of subjective awareness measures on performance in artificial grammar learning task

Systematic research into implicit learning requires well-developed awareness-measurement techniques. Recently, trial-by-trial measures have been widely used. However, they can increase complexity of a study because they are an additional experimental variable. We tested the effects of these measures on performance in artificial grammar learning study. Four groups of participants were assigned to different awareness measures conditions: confidence ratings, post-decision wagering, decision strategy attribution or none. Decision-strategy-attribution participants demonstrated better grammar learning and longer response times compared to controls. They also exhibited a conservative bias. Grammaticality by itself was a stronger predictor of strings endorsement in decision-strategy-attribution group compared to other groups. Confidence ratings and post-decision wagering only affected the response times. These results were supported by an additional experiment that used a balanced chunk strength design. We conclude that a decision-strategy-attribution procedure may force participants to adopt an analytical decision-making strategy and rely mostly on conscious knowledge of artificial grammar.

Objective and subjective measures of cross-situational learning

Statistical learning is often considered to be automatic and implicit, but little is known about the extent to which the resulting representations are available to conscious awareness. In the present study, we focus on whether the knowledge acquired in statistical learning of word-referent pairs is available to conscious control. Using a cross-situational learning paradigm, adult participants were first exposed to a set of pictures associated with auditorily presented words. Immediately thereafter, they were exposed to a second set of word-picture pairs. After the exposure phase, learning and conscious accessibility to the acquired knowledge were measured by using an adaptation of the Process Dissociation Procedure (Jacoby, 1991): two recognition tasks that only differed by instructions. In the Inclusion task, participants were instructed to accept all the correct associations (either from the first or the second set) and reject all the incorrect associations. In the Exclusion task, they had to accept all the correct associations from one of the sets and reject both the correct associations from the other set as well as all incorrect associations. Moreover, binary confidence judgments were recorded after each trial. Results show that participants were able to control the acquired knowledge. However, confidence judgments revealed that participants correctly identified the learned associations even when they claimed to guess, suggesting that cross-situational learning involves a mixture of both conscious and unconscious influences.

Individual consistency in the accuracy and distribution of confidence judgments

We examine which aspects of the confidence distributions - its shape, its bias toward higher or lower values, and its ability to distinguish correct from erred trials - are idiosyncratic of the who (individual specificity), the when (variability across days) and the what (task specificity). Measuring confidence across different sessions of four different perceptual tasks we show that: (1) Confidence distributions are virtually identical when measured in different days for the same subject and the same task, constituting a subjective fingerprint, (2) The capacity of confidence reports to distinguish correct from incorrect responses is only modestly (but significantly) correlated when compared across tasks, (3) Confidence distributions are very similar for tasks that involve different sensory modalities but have similar structure, (4) Confidence accuracy is independent of the mean and width of the confidence distribution, (5) The mean of the confidence distribution (an individual's confidence bias) constitutes the most efficient indicator to infer a subject's identity from confidence reports and (6) Confidence bias measured in simple perceptual decisions correlates with an individual's optimism bias measured with standard questionnaire.

Information theory and artificial grammar learning: inferring grammaticality from redundancy

In artificial grammar learning experiments, participants study strings of letters constructed using a grammar and then sort novel grammatical test exemplars from novel ungrammatical ones. The ability to distinguish grammatical from ungrammatical strings is often taken as evidence that the participants have induced the rules of the grammar. We show that judgements of grammaticality are predicted by the local redundancy of the test strings, not by grammaticality itself. The prediction holds in a transfer test in which test strings involve different letters than the training strings. Local redundancy is usually confounded with grammaticality in stimuli widely used in the literature. The confounding explains why the ability to distinguish grammatical from ungrammatical strings has popularized the idea that participants have induced the rules of the grammar, when they have not. We discuss the judgement of grammaticality task in terms of attribute substitution and pattern goodness. When asked to judge grammaticality (an inaccessible attribute), participants answer an easier question about pattern goodness (an accessible attribute).

Blind insight: metacognitive discrimination despite chance task performance

Blindsight and other examples of unconscious knowledge and perception demonstrate dissociations between judgment accuracy and metacognition: Studies reveal that participants' judgment accuracy can be above chance while their confidence ratings fail to discriminate right from wrong answers. Here, we demonstrated the opposite dissociation: a reliable relationship between confidence and judgment accuracy (demonstrating metacognition) despite judgment accuracy being no better than chance. We evaluated the judgments of 450 participants who completed an AGL task. For each trial, participants decided whether a stimulus conformed to a given set of rules and rated their confidence in that judgment. We identified participants who performed at chance on the discrimination task, utilizing a subset of their responses, and then assessed the accuracy and the confidence-accuracy relationship of their remaining responses. Analyses revealed above-chance metacognition among participants who did not exhibit decision accuracy. This important new phenomenon, which we term blind insight, poses critical challenges to prevailing models of metacognition grounded in signal detection theory.

Modelling unsupervised online-learning of artificial grammars: linking implicit and statistical learning

Humans rapidly learn complex structures in various domains. Findings of above-chance performance of some untrained control groups in artificial grammar learning studies raise questions about the extent to which learning can occur in an untrained, unsupervised testing situation with both correct and incorrect structures. The plausibility of unsupervised online-learning effects was modelled with n-gram, chunking and simple recurrent network models. A novel evaluation framework was applied, which alternates forced binary grammaticality judgments and subsequent learning of the same stimulus. Our results indicate a strong online learning effect for n-gram and chunking models and a weaker effect for simple recurrent network models. Such findings suggest that online learning is a plausible effect of statistical chunk learning that is possible when ungrammatical sequences contain a large proportion of grammatical chunks. Such common effects of continuous statistical learning may underlie statistical and implicit learning paradigms and raise implications for study design and testing methodologies.

Dissociating conscious and unconscious learning with objective and subjective measures

According to functionalist theories, consciousness can be defined by the functions that it serves and by the way it contributes to cognition. For example, when trying to establish dissociations between conscious and unconscious knowledge, conscious representations would be identified by the fact that they allow cognitive control or successful identification or recollection, assessed by verbal reports or forced-choice tasks. Even though the functionalist approach has brought about important dissociation results concerning conscious and unconscious cognition, critics emphasize that it does not account for the qualitative properties of conscious experience. Phenomenal theories are precisely based on the notion that conscious representations are such that it feels like something to have these representations. Thus, one way to assess conscious knowledge is to ask people, after they have produced a forced-choice response, to identify their mental states through the use of subjective confidence ratings, in which they discriminate between a complete guess and a response based on some feeling of knowing. However, these 2 approaches are not mutually exclusive. In this article, we review a series of studies showing that the joint use of objective judgments about some external stimuli and about one's own subjective knowledge concerning these stimuli, provides new insights into the putative dissociation between conscious and unconscious knowledge in learning.

Artificial grammar learning of melody is constrained by melodic inconsistency: Narmour's principles affect melodic learning

Considerable evidence suggests that people acquire artificial grammars incidentally and implicitly, an indispensable capacity for the acquisition of music or language. However, less research has been devoted to exploring constraints affecting incidental learning. Within the domain of music, the extent to which Narmour's (1990) melodic principles affect implicit learning of melodic structure was experimentally explored. Extending previous research (Rohrmeier, Rebuschat & Cross, 2011), the identical finite-state grammar is employed having terminals (the alphabet) manipulated so that melodies generated systematically violated Narmour's principles. Results indicate that Narmour-inconsistent melodic materials impede implicit learning. This further constitutes a case in which artificial grammar learning is affected by prior knowledge or processing constraints.

The speed of metacognition: taking time to get to know one's structural knowledge

The time course of different metacognitive experiences of knowledge was investigated using artificial grammar learning. Experiment 1 revealed that when participants are aware of the basis of their judgments (conscious structural knowledge) decisions are made most rapidly, followed by decisions made with conscious judgment but without conscious knowledge of underlying structure (unconscious structural knowledge), and guess responses (unconscious judgment knowledge) were made most slowly, even when controlling for differences in confidence and accuracy. In experiment 2, short response deadlines decreased the accuracy of unconscious but not conscious structural knowledge. Conversely, the deadline decreased the proportion of conscious structural knowledge in favour of guessing. Unconscious structural knowledge can be applied rapidly but becomes more reliable with additional metacognitive processing time whereas conscious structural knowledge is an all-or-nothing response that cannot always be applied rapidly. These dissociations corroborate quite separate theories of recognition (dual-process) and metacognition (higher order thought and cross-order integration).

Sources of confidence judgments in implicit cognition

Subjective reports of confidence are frequently used as a measure of awareness in a variety of fields, including artificial grammar learning. However, little is known about what information is used to make confidence judgments and whether there are any possible sources of information used to discriminate between items that are unrelated to confidence. The data reported here replicate an earlier experiment by Vokey and Brooks (1992) and show that grammaticality decisions are based on both the grammatical status of items and their similarity to study exemplars. The key finding is that confidence ratings made on a continuous scale (50%-100%) are closely related to grammaticality but are unrelated to all of the measures of similarity that were tested. By contrast, confidence ratings made on a binary scale (high vs. low) are related to both grammaticality and similarity. The data confirm an earlier finding (Tunney & Shanks, 2003) that binary confidence ratings are more sensitive to low levels of awareness than continuous ratings are and suggest that participants are conscious of all the information acquired in artificial grammar learning.

Conscious and unconscious thought in artificial grammar learning

Unconscious Thought Theory posits that a period of distraction after information acquisition leads to unconscious processing which enhances decision making relative to conscious deliberation or immediate choice (Dijksterhuis, 2004). Support thus far has been mixed. In the present study, artificial grammar learning was used in order to produce measurable amounts of conscious and unconscious knowledge. Intermediate phases were introduced between training and testing. Participants engaged in conscious deliberation of grammar rules, were distracted for the same period of time, or progressed immediately from training to testing. No differences in accuracy were found between intermediate phase groups acting on decisions made with meta-cognitive awareness (either feeling-based intuitive responding or conscious rule- or recollection-based responding). However, the accuracy of guess responses was significantly higher after distraction relative to immediate progression or conscious deliberation. The results suggest any beneficial effects of 'unconscious thought' may not always transfer to conscious awareness.

Kinship Recognition by Unrelated Observers Depends on Implicit and Explicit Cognition

Previous studies have shown that neutral observers are able to identify kinship in strangers by matching photographs of children with their parents. We asked whether this ability depended on implicit and/or explicit cognitive processes. Fifty unrelated male observers viewed triads of photographs (one woman in her early 20's and two older women) and had to select which of the two older women was the mother, and rate their confidence in their decision. Observers identified 62.5% of mother-daughter pairs correctly ( p < .001). Signal detection analyses showed that confidence was related to accuracy ( d' = .28) and observers could report the cues they utilized. However, those who failed to show a relationship between confidence and accuracy ( d' ≤ 0) still performed significantly above chance, and both confidence and d' decreased over trials whereas accuracy did not. Results show that neutral observers spontaneously used both explicit and implicit cognitive processes in the task. Recognition of kinship by neutral observers may be a task which allows the interplay between explicit and implicit cognition for a system relevant to ancestral social environments to be observed in the laboratory.

No-loss gambling shows the speed of the unconscious

This paper investigates the time it takes unconscious vs. conscious knowledge to form by using an improved "no-loss gambling" method to measure awareness of knowing. Subjects could either bet on a transparently random process or on their grammaticality judgment in an artificial grammar learning task. A conflict in the literature is resolved concerning whether unconscious rather than conscious knowledge is especially fast or slow to form. When guessing (betting on a random process), accuracy was above chance and RTs were longer than when feeling confident (betting on the grammaticality decision). In a second experiment, short response deadlines only interfered with the quality of confident decisions (betting on grammaticality). When people are unaware of their knowledge, externally enforced decisions can be made rapidly with little decline in quality; but if given ample time, they await a metacognitive process to complete. The dissociation validates no-loss gambling as a measure of conscious awareness.

Measuring strategic control in artificial grammar learning

In response to concerns with existing procedures for measuring strategic control over implicit knowledge in artificial grammar learning (AGL), we introduce a more stringent measurement procedure. After two separate training blocks which each consisted of letter strings derived from a different grammar, participants either judged the grammaticality of novel letter strings with respect to only one of these two grammars (pure-block condition), or had the target grammar varying randomly from trial to trial (novel mixed-block condition) which required a higher degree of conscious flexible control. Random variation in the colour and font of letters was introduced to disguise the nature of the rule and reduce explicit learning. Strategic control was observed both in the pure-block and mixed-block conditions, and even among participants who did not realise the rule was based on letter identity. This indicated detailed strategic control in the absence of explicit learning.

Preserved statistical learning of tonal and linguistic material in congenital amusia

Congenital amusia is a lifelong disorder whereby individuals have pervasive difficulties in perceiving and producing music. In contrast, typical individuals display a sophisticated understanding of musical structure, even in the absence of musical training. Previous research has shown that they acquire this knowledge implicitly, through exposure to music's statistical regularities. The present study tested the hypothesis that congenital amusia may result from a failure to internalize statistical regularities – specifically, lower-order transitional probabilities. To explore the specificity of any potential deficits to the musical domain, learning was examined with both tonal and linguistic material. Participants were exposed to structured tonal and linguistic sequences and, in a subsequent test phase, were required to identify items which had been heard in the exposure phase, as distinct from foils comprising elements that had been present during exposure, but presented in a different temporal order. Amusic and control individuals showed comparable learning, for both tonal and linguistic material, even when the tonal stream included pitch intervals around one semitone. However analysis of binary confidence ratings revealed that amusic individuals have less confidence in their abilities and that their performance in learning tasks may not be contingent on explicit knowledge formation or level of awareness to the degree shown in typical individuals. The current findings suggest that the difficulties amusic individuals have with real-world music cannot be accounted for by an inability to internalize lower-order statistical regularities but may arise from other factors.

Similarity and Confidence in Artificial Grammar Learning

Three experiments examined the relationship between similarity ratings and confidence ratings in artificial grammar learning. In Experiment 1 participants rated the similarity of test items to study exemplars. Regression analyses revealed these to be related to some of the objective measures of similarity that have previously been implicated in categorization decisions. In Experiment 2 participants made grammaticality decisions and rated either their confidence in the accuracy of their decisions or the similarity of the test items to the study items. Regression analyses showed that the grammaticality decisions were predicted by the similarity ratings obtained in Experiment 1. Points on the receiver operating characteristics (ROC) curves for the similarity and confidence ratings were closely matched. These data suggest that meta-cognitive judgments of confidence are predicated on structural knowledge of similarity. Experiment 3 confirmed this by showing that confidence ratings to median similarity probe items changed according to the similarity of preceding items.

Know thyself: metacognitive networks and measures of consciousness

Subjective measures of awareness rest on the assumption that conscious knowledge is knowledge that participants know they possess. Post-Decision Wagering (PDW), recently proposed as a new measure of awareness, requires participants to place a high or a low wager on their decisions. Whereas advantageous wagering indicates awareness of the knowledge on which the decisions are based, cases in which participants fail to optimize their wagers suggest performance without awareness. Here, we hypothesize that wagering and other subjective measures of awareness reflect metacognitive capacities subtended by self-developed metarepresentations that inform an agent about its own internal states. To support this idea, we present three simulations in which neural networks learn to wager on their own responses. The simulations illustrate essential properties that are required for such metarepresentations to influence PDW as a measure of awareness. Results demonstrate a good fit to human data. We discuss the implications of this modeling work for our understanding of consciousness and its measures.

An entropy model for artificial grammar learning

A model is proposed to characterize the type of knowledge acquired in artificial grammar learning (AGL). In particular, Shannon entropy is employed to compute the complexity of different test items in an AGL task, relative to the training items. According to this model, the more predictable a test item is from the training items, the more likely it is that this item should be selected as compatible with the training items. The predictions of the entropy model are explored in relation to the results from several previous AGL datasets and compared to other AGL measures. This particular approach in AGL resonates well with similar models in categorization and reasoning which also postulate that cognitive processing is geared towards the reduction of entropy.

“The Unconscious” in Current Psychology

A series of vignette examples taken from psychological research on motivation, emotion, decision making, and attitudes illustrates how the influence of unconscious processes is often measured in a range of different behaviors. However, the selected studies share an apparent lack of explicit operational definition of what is meant by consciousness, and there seems to be substantial disagreement about the properties of conscious versus unconscious processing: Consciousness is sometimes equated with attention, sometimes with verbal report ability, and sometimes operationalized in terms of behavioral dissociations between different performance measures. Moreover, the examples all seem to share a dichotomous view of conscious and unconscious processes as being qualitatively different. It is suggested that cognitive research on consciousness can help resolve the apparent disagreement about how to define and measure unconscious processing, as is illustrated by a selection of operational definitions and empirical findings from modern cognitive psychology. These empirical findings also point to the existence of intermediate states of conscious awareness, not easily classifiable as either purely conscious or purely unconscious. Recent hypotheses from cognitive psychology, supplemented with models from social, developmental, and clinical psychology, are then presented all of which are compatible with the view of consciousness as a graded rather than an all-or-none phenomenon. Such a view of consciousness would open up for explorations of intermediate states of awareness in addition to more purely conscious or purely unconscious states and thereby increase our understanding of the seemingly “unconscious” aspects of mental life.

The associative nature of human associative learning

The extent to which human learning should be thought of in terms of elementary, automatic versus controlled, cognitive processes is unresolved after nearly a century of often fierce debate. Mitchell et al. provide a persuasive review of evidence against automatic, unconscious links. Indeed, unconscious processes seem to play a negligible role in any form of learning, not just in Pavlovian conditioning. But a modern connectionist framework, in which “cognitive” phenomena are emergent properties, is likely to offer a fuller account of human learning than the propositional framework Mitchell et al. propose.

From the terrible loneliness to the wonderful agreement of human beings

What would be the "terrible loneliness" and what would be the "wonderful agreement" in the present paper? The "terrible loneliness" is the only reality that a person perceives and/or thinks during the now going on. For the person, an enormous quantity of occurrences is in the present moment absent. A very small quantity of occurrences is present. The person is the only being in having this. And, this is only during a little moment. The person never thinks about his loneliness in this moment. On the contrary, he thinks he is plenty of people and full of occurrences. But, if he were thinking about reality, he would live in a terrible loneliness. How does he escape himself from this loneliness? He thinks that the probable occurrences are real occurrences. He may be right in a plenty of times. Going through what I call opening hypotheses--basic hypotheses and non-basic but important hypotheses--and going through what I call simply hypotheses he is able to sanction a wonderful agreement of human beings about the known parts of the Universe. However, they are hypotheses, not absolute realities.

Interference produces different forgetting rates for implicit and explicit knowledge

Exposure to a repeating set of target strings generated by an artificial grammar in a speeded matching task generates both explicit and implicit knowledge. Previous research has shown that implicit knowledge (assessed via a priming measure) is preserved after a retention interval of one week but explicit knowledge (assessed via recognition) is significantly reduced. In two experiments, we replicated and extended Tunney's findings. Experiment 1 was a partial replication of the experiment conducted by Tunney, and demonstrated that the decline in recognition shown by Tunney was not due to a repetition of test items at the pre and post times of assessment. In addition, Experiment 1 lends credibility to Tunney's assumption that recognition scores assess explicit rather than implicit knowledge. Experiment 2 extended Tunney's findings theoretically by demonstrating that interference can produce the pattern of findings demonstrated in the present Experiment 1 as well as in Tunney.

Advance Visual Information, Awareness, and Anticipation Skill

The authors examined 13 skilled, 13 recreational, and 11 novice players' awareness of the advance visual information that they used to judge tennis serve direction. Participants viewed video clips of serve actions under 5 conditions of spatial occlusion. The authors assessed participants' awareness by comparing the different groups' confidence associated with correct and incorrect judgments and by conducting a postexperiment free-recall test. The results indicated that information from the ball toss and the arm + racquet region underpinned players' anticipation skill and that greater expertise was accompained by increasing awareness of the information on which judgments were based. The authors discuss the implications of the present results for researchers' use of confidence ratings to assess awareness in perceptual-judgment tasks.

Repetition priming affects guessing not familiarity

BACKGROUND

The claim that recollection and familiarity based memory processes have distinct retrieval mechanisms is based partly on the observation that masked repetition and semantic priming influence estimates of familiarity derived from know responses but have no effect on estimates of recollection derived from remember responses. Close inspection of the experiments on which this claim is based reveal the effect size to be small, potentially the result of a type-2 error, and/or inflated due to participants not having the opportunity to report guesses. This paper re-evaluates these claims by attempting a partial replication of two such Experiments.

METHODS

In Experiment 1 participants made remember, know, and guess responses following primed and unprimed target words. In Experiment 2 participants made sure, unsure, and guess following primed and unprimed target words.

RESULTS

In Experiment 1 the repetition priming effect occurred only for guess responses and only for unstudied items. In Experiment 2 the priming effect occurred for both unsure and guess responses, but again only for unstudied items.

CONCLUSION

The data are consistent with the view that remembering and knowing do not correspond to confidence ratings; and suggest that contrary to earlier findings, recollection and familiarity do not differ in retrieval mechanisms. As such the effects of repetition priming on subjective reports of remembering should not be cited as evidence for the distinction between recollection and familiarity based memory processes.

Effects of retention intervals on receiver operating characteristics in artificial grammar learning

Current theories of memory suggest that recognition is composed of separate processes of familiarity and recollection (e.g. [Yonelinas, A. P. (2002). The nature of recollection and familiarity: a review of 30 years of research. Journal of Memory and Language, 46, 441-517]). A key feature of these two processes is that they decay, or are forgotten at different rates. The dual-process model has also been useful in understanding artificial grammar learning. We obtained evidence for recollection and familiarity in artificial grammar learning by analyses of receiver operating characteristics (ROC). Furthermore we found that these were dissociated by retention intervals of 14 days. The slope of the zROC curves deviated reliably from 1 immediately after study and increased towards 1 suggesting that recollection contributed to recognition decisions but declined over the 14-day period leaving familiarity as the only basis for recognition. These data show similar patterns to those observed in word-recognition [Gardiner, J. M., & Java, R. I. (1991). Forgetting in recognition memory with and without recollective experience. Memory &Cognition, 19, 617-623; Tunney, R. J. (submitted for publication). Changes in the subjective experience of recognition over time suggest independent processes] and confirm the view that recollection and familiarity are implicated in artificial grammar learning. Moreover, the data confirm the finding that recollection and familiarity-based memory show different patterns of forgetting.

Post-decision wagering objectively measures awareness

The lack of an accepted measure of awareness has made claims that accurate decisions can be made without awareness controversial. Here we introduce a new objective measure of awareness, post-decision wagering. We show that participants fail to maximize cash earnings by wagering high following correct decisions in blindsight, the Iowa gambling task and an artificial grammar task. This demonstrates, without the uncertainties associated with the conventional subjective measures of awareness (verbal reports and confidence ratings), that the participants were not aware that their decisions were correct. Post-decision wagering may be used to study the neural correlates of consciousness.