No abstract

Consciousness is now a well-established field of empirical research. A large body of experimental results has been accumulated and is steadily growing. In parallel, many Theories of Consciousness (ToCs) have been proposed. These theories are diverse in nature, ranging from computational to neurophysiological and quantum theoretical approaches. This contrasts with other fields of natural science, which host a smaller number of competing theories. We suggest that one reason for this abundance of extremely different theories may be the lack of stringent criteria specifying how empirical data constrains ToCs. First, we argue that consciousness is a well-defined topic from an empirical point of view and motivate a purely empirical stance on the quest for consciousness. Second, we present a checklist of criteria that, we propose, empirical ToCs need to cope with. Third, we review 13 of the most influential ToCs and subject them to the criteria. Our analysis helps to situate these different ToCs in the theoretical landscapeand sheds light on their strengths and weaknesses from a strictly empirical point of view.

Conscious perception seems to be a continuous stream of percepts. Is this true? Recent research sheds new light on this age-old debate.In long-lasting postdictive effects, later events can determine the perception of events that occurred several hundreds of milliseconds earlier.Long-lasting postdiction requires high capacity buffers, which store information unconsciously for substantial periods of time. This favors a two-stage model, in which continuous unconscious processing precedes discrete conscious percepts.Such a two-stage model solves the problems of both traditional continuous and discrete models.

In crowding, perception of an object deteriorates in the presence of nearby elements. Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation, to date there exists no consensus on how to model it. Previous experiments showed that the global configuration of the entire stimulus must be taken into account. These findings rule out simple pooling or substitution models and favor models sensitive to global spatial aspects. In order to investigate how to incorporate global aspects into models, we tested a large number of models with a database of forty stimuli tailored for the global aspects of crowding. Our results show that incorporating grouping like components strongly improves model performance.

Sensory information must be integrated over time to perceive, for example, motion and melodies. Here, to study temporal integration, we used the sequential metacontrast paradigm in which two expanding streams of lines are presented. When a line in one stream is offset observers perceive all other lines to be offset too, even though they are straight. When more lines are offset the offsets integrate mandatorily, i.e., observers cannot report the individual offsets. We show that mandatory integration lasts for up to 450 ms, depending on the observer. Importantly, integration occurs only when offsets are presented within a discrete window of time. Even stimuli that are in close spatio-temporal proximity do not integrate if they are in different windows. A window of integration starts with stimulus onset and integration in the next window has similar characteristics. We present a two-stage computational model based on discrete time windows that captures these effects.