A global workspace model for phenomenal and access consciousness

Both the global workspace theory and Block’s distinction between phenomenal and access consciousness, are central in the current debates about consciousness and the neural correlates of consciousness. In this article, a unifying global workspace model for phenomenal and access consciousness is proposed. In the model, recurrent neural interactions take place in distinct yet interacting access and phenomenal brain loops. The effectiveness of feedback signaling onto sensory cortical maps is emphasized for the neural correlates of phenomenal consciousness. Two forms of top-down attention, attention for perception and attention for access, play differential roles for phenomenal and access consciousness. The model is implemented in a neural network form, with the simulation of single and multiple visual object processing, and of the attentional blink.     

A theory of consciousness

Consciousness is the subjective awareness of momentary experience interpreted in the context of personal memory and present state. I propose that two brain systems converge to create consciousness. The exogenous system sends information about multimodal external stimuli to basal dendrites in widely dispersed pyramidal cell ensembles in the cortex of the brain; this system produces synchronized fragments of sensations. The endogenous system distributes readout of representations of memories, activated in systems established by associative learning, diffusely to apical dendrites. Convergence of exogenous and endogenous inputs enhances cellular excitability, and fragmented sensations are thereby converted to fragments of perception. Local field potentials periodically modulate all cortical membrane potentials and facilitate synchronous discharge of these excited elements. Feedback between the cortex and the thalamus results in a cortico-thalamo-cortical reverberation, binding the fragments into a unified global percept. Sustained reverberation produces a resonating electromagnetic field of synchronized elements. The momentary content of information in the brain is this distributed coherence, which is negative entropy. Consciousness is a physical property of this field, producing the subjective awareness of this information.     

A general latent trait model for response processes

The purpose of the current paper is to propose a general multicomponent latent trait model (GLTM) for response processes. The proposed model combines the linear logistic latent trait (LLTM) with the multicomponent latent trait model (MLTM). As with both LLTM and MLTM, the general multicomponent latent trait model can be used to (1) test hypotheses about the theoretical variables that underlie response difficulty and (2) estimate parameters that describe test items by basic substantive properties. However, GLTM contains both component outcomes and complexity factors in a single model and may be applied to data that neither LLTM nor MLTM can handle. Joint maximum likelihood estimators are presented for the parameters of GLTM and an application to cognitive test items is described.This research was partially supported by the National Institute of Education grant number NIE-6-7-0156 to Susan Embretson (Whitely), principal investigator. However the optinions expressed herein do not necessarily reflect the position or policy of the National Institute of Education, and no official endorsement by the National Institute of Education should be inferred.     

A general parametric model of similarity and subjective difference

The field of multidimensional scaling is dominated by models that lack inherent parameters. Correcting parameters have been introduced, e.g. INDSCAL, to increase power of prediction. Although a nonparametirc model with correcting parameters may exhibit a very good fit to data, a parametric model is intrinsically superior. The general parametric model proposed here yields measures of both absolute and relative subjective differences (dissimilarity) in addition to similarity. It is basically unidimensioanal. Rules for combining values of attributes into a single multidimensional value may be applied either to the input or to the output of the model. One of the resulting functions is a generalization of the Eisler-Ekman similarity function. A special case of another function is identical to the Minkowski class of distance functions (including INDSCAL). The model is not limited to pairwise relations. It yields unitary measures for any number of objects.     

A general model for the analysis of multilevel data

A general model is developed for the analysis of multivariate multilevel data structures. Special cases of the model include repeated measures designs, multiple matrix samples, multilevel latent variable models, multiple time series, and variance and covariance component models.We would like to acknowledge the helpful comments of Ruth Silver. We also wish to thank the referees for helping to clarify the paper. This work was partly carried out with research funds provided by the Economic and Social Research Council (U.K.).     

Perception: a model comprising two modes of consciousness

A model of human perception is proposed in which conscious awareness is assumed to be the result of two separate mechanisms each involving consciousness, one outer, sensori-produced, and one inner, conceptual. By mediation of flexible memory representations the sensory data of the outer consciousness give rise to a matched "copy" in the inner consciousness which conceptually organizes the former and also serves as input to the memory store. The model is applied to some perceptual problems in vision such as ambiguous stimuli, subjective contours, space perception, a case of metacontrast, and subliminal perception.     

A general diagnostic model applied to language testing data

Probabilistic models with one or more latent variables are designed to report on a corresponding number of skills or cognitive attributes. Multidimensional skill profiles offer additional information beyond what a single test score can provide, if the reported skills can be identified and distinguished reliably. Many recent approaches to skill profile models are limited to dichotomous data and have made use of computationally intensive estimation methods such as Markov chain Monte Carlo, since standard maximum likelihood (ML) estimation techniques were deemed infeasible. This paper presents a general diagnostic model (GDM) that can be estimated with standard ML techniques and applies to polytomous response variables as well as to skills with two or more proficiency levels. The paper uses one member of a larger class of diagnostic models, a compensatory diagnostic model for dichotomous and partial credit data. Many well‐known models, such as univariate and multivariate versions of the Rasch model and the two‐parameter logistic item response theory model, the generalized partial credit model, as well as a variety of skill profile models, are special cases of this GDM. In addition to an introduction to this model, the paper presents a parameter recovery study using simulated data and an application to real data from the field test for TOEFL^® Internet‐based testing.     

A general model of consensus and accuracy in interpersonal perception

Consensus refers to the extent to which 2 judges agree in their ratings of a common target. A general model of interpersonal perception based on Anderson's (1981) weighted-average model is developed. The model shows that increased acquaintance does not always lead to large changes in consensus. Degree of overlap between the target behaviors observed by the judges and similarity of meaning systems are key but neglected parameters. The model can also be used as a basis for determining the accuracy of person perception. In some cases, accuracy can increase with greater acquaintance, whereas consensus may not.     

A note on the derivation of the general latent class model

A general formulation of the latent structure principle is suggested, from which it is possible to derive Lazarsfeld's accounting equations in their most general form. The basic equations of Gibson's latent profile model can thence be derived in a single step.     

A quantum approach to visual consciousness

A theoretical approach relying on quantum computation in microtubules within neurons can potentially resolve the enigmatic features of visual consciousness, but raises other questions. For example, how can delicate quantum states, which in the technological realm demand extreme cold and isolation to avoid environmental ‘decoherence’, manage to survive in the warm, wet brain? And if such states could survive within neuronal cell interiors, how could quantum states grow to encompass the whole brain? We present a physiological model for visual consciousness that can accommodate brain-wide quantum computation according to the Penrose–Hameroff ‘Orch OR’ model. In this view, visual consciousness occurs as a series of several-hundred-millisecond epochs, each comprising ‘crescendo sequences’ of quantum computations occurring at ∼40 Hz.     

Why religious movements succeed or fail: A revised general model

In this essay I refine and greatly expand the scope of my 1987 theory of why religious groups succeed or fail. The initial version was limited to new religions (cult movements). This version applies to all movements, including sects. The theory now consists of 10 propositions which attempt to specify the necessary and sufficient conditions for success or failure.     

A neural correlate of consciousness related to repression

In previous research Libet (1966) discovered that a critical time period for neural activation is necessary in order for a stimulus to become conscious. This necessary time period varies from subject to subject. In this current study, six subjects for whom the time for neural activation of consciousness had been previously determined were administered a battery of psychological tests on the basis of which ratings were made of degree of repressiveness. As hypothesized, repressive subjects had a longer critical time period for neural activation of consciousness, suggesting the possibility that this neurophysiological time factor is a necessary condition for the development of repression.