Traditional explanations of multistable visual phenomena (e.g. ambiguous figures, perceptual rivalry) suggest that the basis for spontaneous reversals in perception lies in antagonistic connectivity within the visual system. In this review, we suggest an alternative, albeit speculative, explanation for visual multistability – that spontaneous alternations reflect responses to active, programmed events initiated by brain areas that integrate sensory and non-sensory information to coordinate a diversity of behaviors. Much evidence suggests that perceptual reversals are themselves more closely related to the expression (...) of a behavior than to passive sensory responses: (1) they are initiated spontaneously, often voluntarily, and are influenced by subjective variables such as attention and mood; (2) the alternation process is greatly facilitated with practice and compromised by lesions in non-visual cortical areas; (3) the alternation process has temporal dynamics similar to those of spontaneously initiated behaviors; (4) functional imaging reveals that brain areas associated with a variety of cognitive behaviors are specifically activated when vision becomes unstable. In this scheme, reorganizations of activity throughout the visual cortex, concurrent with perceptual reversals, are initiated by higher, largely non-sensory brain centers. Such direct intervention in the processing of the sensory input by brain structures associated with planning and motor programming might serve an important role in perceptual organization, particularly in aspects related to selective attention. (shrink)

In this section, we will start with an influential attempt to define `intelligence', and then we will move to a consideration of how human intelligence is to be investigated on the machine model. The last part of the section will discuss the relation between the mental and the biological.

Although our subjective impression is of a richly detailed visual world, numerous empirical results suggest that the amount of visual information observers can perceive and remember at any given moment is limited. How can our subjective impressions be reconciled with these objective observations? Here, we answer this question by arguing that, although we see more than the handful of objects, claimed by prominent models of visual attention and working memory, we still see far less than we think we do. Taken (...) together, we argue that these considerations resolve the apparent conflict between our subjective impressions and empirical data on visual capacity, while also illuminating the nature of the representations underlying perceptual experience. (shrink)

We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...) construct new causal maps and that their learning is consistent with the Bayes net formalism. (shrink)

Does perceptual consciousness require cognitive access? Ned Block argues that it does not. Central to his case are visual memory experiments that employ post-stimulus cueing—in particular, Sperling's classic partial report studies, change-detection work by Lamme and colleagues, and a recent paper by Bronfman and colleagues that exploits our perception of ‘gist’ properties. We argue contra Block that these experiments do not support his claim. Our reinterpretations differ from previous critics' in challenging as well a longstanding and common view of visual (...) memory as involving declining capacity across a series of stores. We conclude by discussing the relation of probabilistic perceptual representations and phenomenal consciousness. (shrink)

The target article sketched and explored a mechanism (action-oriented predictive processing) most plausibly associated with core forms of cortical processing. In assessing the attractions and pitfalls of the proposal we should keep that element distinct from larger, though interlocking, issues concerning the nature of adaptive organization in general.

According to a growing trend in theoretical neuroscience, the human perceptual system is akin to a Bayesian machine. The aim of this article is to clearly articulate the claims that perception can be considered Bayesian inference and that the brain can be considered a Bayesian machine, some of the epistemological challenges to these claims; and some of the implications of these claims. We address two questions: (i) How are Bayesian models used in theoretical neuroscience? (ii) From the use of Bayesian (...) models in theoretical neuroscience, have we learned or can we hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine? From actual practice in theoretical neuroscience, we argue for three claims. First, currently Bayesian models do not provide mechanistic explanations; instead they are useful devices for predicting and systematizing observational statements about people's performances in a variety of perceptual tasks. That is, currently we should have an instrumentalist attitude towards Bayesian models in neuroscience. Second, the inference typically drawn from Bayesian behavioural performance in a variety of perceptual tasks to underlying Bayesian mechanisms should be understood within the three-level framework laid out by David Marr ( [1982] ). Third, we can hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine to the extent that Bayesian models will prove successful in yielding secure and informative predictions of both subjects' perceptual performance and features of the underlying neural mechanisms. (shrink)

One of the most important issues concerning the foundations ofconscious perception centerson thequestion of whether perceptual consciousness is rich or sparse. The overflow argument uses a form of ‘iconic memory’ toarguethatperceptual consciousnessisricher (i.e.,has a higher capacity) than cognitive access: when observing a complex scene we are conscious of more than we can report or think about. Recently, the overflow argumenthas been challenged both empirically and conceptually. This paper reviews the controversy, arguing that proponents of sparse perception are committed to the (...) postulation of (i) a peculiar kind of generic conscious representation that has no independent rationale and (ii) an unmotivated form of unconscious representation that in some cases conflicts with what we know about unconscious representation. (shrink)

We discuss cases where subjects seem to enjoy conscious experience when the relevant first-order perceptual representations are either missing or too weak to account for the experience. Though these cases are originally considered to be theoretical possibilities that may be problematical for the higher-order view of consciousness, careful considerations of actual empirical examples suggest that this strategy may backfire; these cases may cause more trouble for first-order theories instead. Specifically, these cases suggest that (I) recurrent feedback loops to V1 are (...) most likely not the neural correlate of first-order representations for conscious experience, (II) first-order views seem to have a problem accounting for the phenomenology in these cases, and either (III) a version of the ambitious higher-order approach is superior in that it is the simplest theory that can account for all results at face value, or (IV) a view where phenomenology is jointly determined by both first-order and higher-order states. In our view (III) and (IV) are both live options and the decision between them may ultimately be an empirical question that cannot yet be decided. (shrink)

Here, we argue that any neurobiological theory based on an experience/function division cannot be empirically confirmed or falsified and is thus outside the scope of science. A ‘perfect experiment’ illustrates this point, highlighting the unbreachable boundaries of the scientific study of consciousness. We describe a more nuanced notion of cognitive access that captures personal experience without positing the existence of inaccessible conscious states. Finally, we discuss the criteria necessary for forming and testing a falsifiable theory of consciousness.

In this response to 32 commentators, I start by clarifying the overflow argument. I explain why the distinction between generic and specific phenomenology is important and why we are justified in acknowledging specific phenomenology in the overflow experiments. Other issues discussed are the relations among report, cognitive access, and attention; panpsychic disaster; the mesh between psychology and neuroscience; and whether consciousness exists.