The interocular suppression technique termed continuous flash suppression (CFS) has become an immensely popular tool for investigating visual processing outside of awareness. The emerging picture from studies using CFS is that extensive processing of a visual stimulus, including its semantic and affective content, occurs despite suppression from awareness of that stimulus by CFS. However, the current implementation of CFS in many studies examining processing outside of awareness has several drawbacks that may be improved upon for future studies using CFS. In (...) this paper, we address some of those shortcomings, particularly ones that affect the assessment of unawareness during CFS, and ones to do with the use of ‘visible’ conditions that are often included as a comparison to a CFS condition. We also discuss potential biases in stimulus processing as a result of spatial attention and feature-selective suppression. We suggest practical guidelines that minimize the effects of those limitations in using CFS to study visual processing outside of awareness. (shrink)

Post-decision wagering has been proposed as a method of demonstrating that perception can occur without conscious awareness. When wagering is independent from above-chance performance there is evidence of a lack of awareness of the correctness of the first-order discriminations. However, there are reasons to believe that the contingency analysis conducted by Persaud and colleagues failed to measure “the zero accuracy-wagering criterion”. The author shows that a Pearson chi-square test employed by Persaud and colleagues is unable to accommodate the hypothesis of (...) partial independence between accuracy and advantageous wagering. On the contrary, the problem of “the zero accuracy-wagering criterion” is best conducted with log-linear models. Moreover, log-linear analysis suggests that absence of advantageous wagering is not sufficient evidence for a lack of conscious awareness. In the case of the blindsight study, there was compelling evidence that the patient GY was partially aware of having information about the correctness of his decisions. (shrink)

What is the best way of assessing the extent to which people are aware of a stimulus? Here, using a masked visual identification task, we compared three measures of subjective awareness: The Perceptual Awareness Scale , through which participants are asked to rate the clarity of their visual experience; confidence ratings , through which participants express their confidence in their identification decisions, and Post-decision wagering , in which participants place a monetary wager on their decisions. We conducted detailed explorations of (...) the relationships between awareness and identification performance, looking to determine which scale best correlates with performance, and whether we can detect performance in the absence of awareness and how the scales differ from each other in terms of revealing such unconscious processing. Based on these findings we discuss whether perceptual awareness should be considered graded or dichotomous. Results showed that PAS showed a much stronger performance-awareness correlation than either CR or PDW, particularly for low stimulus intensities. In general, all scales indicated above-chance performance when participants claimed not to have seen anything. However, such above-chance performance only showed when we also observed a correlation between awareness and performance. Thus PAS seems to be the most exhaustive measure of awareness, and we find support for above-chance performance in the absence of subjective awareness, but such unconscious knowledge only contributes to performance when we observe conscious knowledge as well. Similarities and differences between scales are discussed in the light of consciousness theories and response strategies. (shrink)

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 accurate measurement of the level of consciousness of a creature remains a major scientific challenge, nevertheless a number of new accounts that attempt to address this problem have been proposed recently. In this paper we analyze the principles of these new measures of consciousness along with other classical approaches focusing on their applicability to Machine Consciousness (MC). Furthermore, we propose a set of requirements of what we think a suitable measure for MC should be, discussing the associated theoretical and (...) practical issues. Using the proposed requirements as a framework for the design of an integrative measure of consciousness, we explore the possibility of designing such a measure in the context of current state of the art in consciousness studies. (shrink)

Dienes and Seth (2010) conclude that confidence ratings and post-decision wagering are two comparable and recommendable measures of conscious experience. In a recently submitted paper, we have however found that both methods are problematic and seem less suited to measure consciousness than a direct introspective measure. Here, we discuss the methodology and conclusions put forward by Dienes and Seth, and why we think the two experiments end up with so different recommendations.

In consciousness science, theories often differ not only in the account of consciousness they arrive at, but also with respect to how they understand their starting point. Some approaches begin with experimentally gathered data, whereas others begin with phenomenologically gathered data. In this paper, I analyse how the most influential phenomenology-first approach, namely the Integrated Information Theory (IIT) of consciousness, fits its phenomenologically gathered data with explanatory hypotheses. First, I show that experimentally driven approaches hit an explanatory roadblock, since we (...) cannot tell, at the present stage, which model of consciousness is best. Then, I show that IIT’s phenomenology-first approach implies a self-evidencing explanation according to which consciousness can be explained by starting from consciousness itself. I claim that IIT can take advantage of the virtuous circularity of this reasoning, but it also faces a data-fitting issue that is somehow similar to that faced by experiment-driven approaches: we are not given enough information to decide whether the explanatory hypotheses IIT employs to explain its phenomenological data are in fact best. I call this problem “the self-evidencing problem” for IIT, and after introducing it, I propose a possible way for IIT to solve it. (shrink)

Methodological problems of how awareness during learning should be measured have been extensively discussed and investigated in cognitive psychology. This review considers; 1)whether amnesics can perform implicit learning tasks at a similar level to normal controls, 2) whether differences in instructional orientations create dissociations in performance in tests of implicit and explicit knowledge, and 3) whether participants can retrospectively verbalise the learning outcomes. The paper concludes that; amnesics’ implicit learning abilities differ from the normal controls, instructions on implicit learning do (...) not guarantee the occurrence of implicit learning, and objective and subjective awareness measures used in the literature face inherent problems and so the awareness controversy remains unsettled. (shrink)

Neuroscientific studies have shown that brain activity correlated with a decision to move can be observed before a person reports being consciously aware of having made that decision . Given that a later event cannot cause an earlier one , such results have been interpreted as evidence that decisions are made unconsciously . We argue that this interpretation depends upon an all-or-none view of consciousness, and we offer an alternative interpretation of the early decision-related brain activity based on models in (...) which conscious awareness of the decision to move develops gradually up to the level of a reporting criterion. Under this interpretation, the early brain activity reflects sub-criterion levels of awareness rather than complete absence of awareness and thus does not suggest that decisions are made unconsciously. (shrink)

To study consciousness, scientists need to determine when participants are conscious and when they are not. They do so with consciousness detection procedures. A recurring skeptical argument against those procedures is that they cannot be calibrated: there is no way to make sure that detection outcomes are accurate. In this article, I address two main skeptical arguments purporting to show that consciousness scientists cannot calibrate detection procedures. I conclude that there is nothing wrong with calibration in consciousness science.

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 decisions are made most rapidly, followed by decisions made with conscious judgment but without conscious knowledge of underlying structure , and guess responses 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 and metacognition. (shrink)

Working memory, an important posit in cognitive science, allows one to temporarily store and manipulate information in the service of ongoing tasks. Working memory has been traditionally classified as an explicit memory system – that is, as operating on and maintaining only consciously perceived information. Recently, however, several studies have questioned this assumption, purporting to provide evidence for unconscious working memory. In this paper, we focus on visual working memory and critically examine these studies as well as studies of unconscious (...) perception that seem to provide indirect evidence for unconscious working memory. Our analysis indicates that current evidence does not support an unconscious working memory store, though we offer independent reasons to think that working memory may operate on unconsciously perceived information. (shrink)

There is an increasing interest in the relationship between imagery and emotion . The present research examined whether unconscious emotions affect visual imagery. In particular, participants were invited to perform a mental rotation test following subliminal presentation of happy, sad and neutral expressions. This study revealed an increase in mental rotation abilities after unconscious visual processing of emotional expressions. Altogether, these findings support the hypothesis of a bidirectional relationship between imagery and emotions.

The possibility of consciousness in human brain organoids is sometimes viewed as determinative in terms of the moral status such entities possess, and, in turn, in terms of the research protections such entities are due. This commonsense view aligns with a prominent stance in neurology and neuroscience that consciousness admits of degrees. My paper outlines these views and provides an argument for why this picture of correlating degrees of consciousness with moral status and research protections is mistaken. I then provide (...) an alternative account of the correlation between moral status and consciousness, and consider the epistemic ramifications for research protections of this account. (shrink)

Any neurobiological model claiming explanation of a complex human phenomenon should start with an explicit definition of the explanandum. If a classical intensional definition is impossible, we can use a descriptive definition by listing necessary criteria. This commentary suggests four meta-criteria that different proposed criteria of consciousness should fulfill: phenomenological consensus, empirical evidence, domain specificity, and non-circularity.

Vision is inseparably connected to perceptual awareness which can be seen as the culmination of sensory processing. Studies on conscious vision reveal that object recognition is just one of the means through which our representation of the world is built. We propose an operationalization of subjective experience in the context of deep neural networks (DNNs) that could encourage a more thorough comparison of human and artificial vision.

Within theoretical and empirical enquiries, many different meanings associated with consciousness have appeared, leaving the term itself quite vague. This makes formulating an abstract and unifying version of the concept of consciousness – the main aim of this article –into an urgent theoretical imperative. It is argued that consciousness, characterized as dually accessible (cognized from the inside and the outside), hierarchically referential (semantically ordered), bodily determined (embedded in the working structures of an organism or conscious system), and useful in action (...) (pragmatically functional), is a graded rather than an all-or-none phenomenon. A gradational approach, however, despite its explanatory advantages, can lead to some counterintuitive consequences and theoretical problems. In most such conceptions consciousness is extended globally (attached to primitive organisms or artificial systems), but also locally (connected to certain lower-level neuronal and bodily processes). For example, according to information integration theory (as introduced recently by Tononi and Koch, 2014), even such simple artificial systems as photodiodes possess miniscule amounts of consciousness. The major challenge for this article, then, is to establish reasonable, empirically justified constraints on how extended the range of a graded consciousness could be. It is argued that conscious systems are limited globally by the ability to individuate information (where individuated information is understood as evolutionarily embedded, socially altered, and private), whereas local limitations should be determined on the basis of a hypothesis about the action-oriented nature of the processes that select states of consciousness. Using these constraints, an abstract concept of consciousness is arrived at, hopefully contributing to a more unified state of play within consciousness studies itself. (shrink)

Consciousness is now a hot topic in both philosophy and the cognitive sciences, yet there is much controversy over how to measure it. First, it is not clear whether biased subjective reports should be taken as adequate for measuring consciousness, or if more objective measures are required. Ways to benefit from the advantages of both these measures in the form of ‘Type 2’ metacognitive measures are under development, but face criticism. Research into neurophysiological measures of consciousness is potentially very valuable, (...) but often hindered by its dependence on behavioural measures that are themselves controversial. Newer informational measures are theoretically interesting, but as yet not easily applicable, while other measures of consciousness are designed for application in clinical cases . Although much optimism accompanies research into measures of consciousness, the controversies and methodological problems reviewed here suggest that making progress in this area may be more difficult than is often acknowledged. (shrink)

This paper argues for a position of ‘dark pessimism’ towards introspective reports playing a strong justificatory role in consciousness science, based on the application of frameworks and concepts of measurement. I first show that treating introspective reports as measurements fits well within current discussions of the reliability of introspection, and argue that introspective reports must satisfy at least a minimal definition of measurement in order to play a justificatory role in consciousness science. I then show how treating introspective reports as (...) measurements makes it possible to identify the foundational methodological problems that underlie much of the current philosophical and scientific debate about the status of introspective evidence in studying consciousness. I argue that these problems prevent introspective reports from playing a strong justificatory role and resolving long-standing debates in consciousness science, both in contemporary work and in the future. (shrink)

The Hard Problem is surrounded by a vast literature, to which it is increasingly hard to contribute to in any meaningful way. Accordingly, the strategy here is not to offer any new metaphysical or ‘in principle’ arguments in favour of the success of materialism, but to assume a Type Q(uinian) approach and look to contemporary consciousness science to see how the concept of consciousness fares there, and what kind of explanations we can hope to offer of it. It is suggested (...) that while they will be materialist explanations, they will not be of the form that many scientists and philosophers would have us believe, but instead prompt a very different set of expectations and research projects. (shrink)

Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes (...) clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems—these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness. (shrink)

Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response (...) devices in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes. (shrink)

A long lasting debate in the field of implicit learning is whether participants can learn without acquiring conscious knowledge. One crucial problem is that no clear criterion exists allowing to identify participants who possess explicit knowledge. Here, we propose a method to diagnose during a serial reaction time task those participants who acquire conscious knowledge. We first validated this method by using Stroop-like material during training. Then we assessed participants’ knowledge with the Inclusion/Exclusion task and the wagering task . Both (...) experiments confirmed that for participants diagnosed as having acquired conscious knowledge about the underlying sequence the Stroop congruency effect disappeared, whereas for participants not diagnosed as possessing conscious knowledge it only slightly decreased. In addition, both experiments revealed that only participants diagnosed as conscious were able to strategically use their acquired knowledge. Thus, our method allows to reliably distinguish between participants with and without conscious knowledge. (shrink)

We explore three methods for measuring the conscious status of knowledge using the artificial grammar learning paradigm. We show wagering is no more sensitive to conscious knowledge than simple verbal confidence reports but is affected by risk aversion. When people wager rather than give verbal confidence they are less ready to indicate high confidence. We introduce a “no-loss gambling” method which is insensitive to risk aversion. We show that when people are just as ready to bet on a genuine random (...) process as their own classification decisions, their classifications are still above baseline, indicating knowledge participants are not aware of having. Our results have methodological implications for any study investigating whether people are aware of knowing. (shrink)

Consciousness remains a mystery—“a phenomenon that people do not know how to think about—yet” (Dennett, , p. 21). Here, I consider how the connectionist perspective on information processing may help us progress toward the goal of understanding the computational principles through which conscious and unconscious processing differ. I begin by delineating the conceptual challenges associated with classical approaches to cognition insofar as understanding unconscious information processing is concerned, and to highlight several contrasting computational principles that are constitutive of the connectionist (...) approach. This leads me to suggest that conscious and unconscious processing are fundamentally connected, that is, rooted in the very same computational principles. I further develop a perspective according to which the brain continuously and unconsciously learns to redescribe its own activity itself based on constant interaction with itself, with the world, and with other minds. The outcome of such interactions is the emergence of internal models that are metacognitive in nature and that function so as to make it possible for an agent to develop a (limited, implicit, practical) understanding of itself. In this light, plasticity and learning are constitutive of what makes us conscious, for it is in virtue of our own experiences with ourselves and with other people that our mental life acquires its subjective character. The connectionist framework continues to be uniquely positioned in the Cognitive Sciences to address the challenge of identifying what one could call the “computational correlates of consciousness” (Mathis & Mozer, ) because it makes it possible to focus on the mechanisms through which information processing takes place. (shrink)

Contemporary studies in unconscious cognition are essentially founded on dissociation, i.e., on how it dissociates with respect to conscious mental processes and representations. This is claimed to be in so many and diverse ways that one is often lost in dissociation. In order to reduce this state of confusion we here carry out two major tasks: based on the central distinction between cognitive processes and representations, we identify and isolate the main dissociation paradigms; we then critically analyze their key tenets (...) and reported findings. (shrink)

Machine consciousness is not only a technological challenge, but a new way to approach scientific and theoretical issues which have not yet received a satisfactory solution from AI and robotics. We outline the foundations and the objectives of machine consciousness from the standpoint of building a conscious robot.