When is perception conscious

Reidel, Dordrecht. Gibson J. Grice, H. Hannay, A. Heil, J. Heil, J and Mele A. Helmholtz, H. Southall, Dover Publications , New York. Hume, D. Steinberg ed. Hume D. Selby-Bigge ed. Lewis C. Locke, J.

McLaughlin, B. Marr, D. Longuet-Higgins and N. Sutherland eds. Quine, W. However, the distinction between gist and full perception is not well understood and there are more specific views on gist perception, also within the broad predictive coding framework Bar, In some cases of inattentional blindness, large and otherwise very salient stimuli can go unnoticed. Famously, when counting basketball passes a gorilla can be unseen, and when chasing someone a nearby fistfight can be unseen Simons and Chabris, ; Chabris et al.

This is somewhat difficult to explain because endogenous attention as described so far should raise the baseline for precision expectation for a specific location such that any stimulus there, whether it is a basketball pass or a gorilla, should be more likely to be perceived. A smaller proportion of participants experience this effect, so it does in fact seem harder to induce blindness in this kind of paradigm than paradigms using central—peripheral or foreground-background tasks.

For those who do have inattentional blindness under these conditions, the explanation could be high precision expectations for the basketball passes specifically, given the context of the passes that have occurred before the gorilla enters. This combines with the way this precision error has driven up the conditional confidence of the basketball model, explaining away the gorilla model, even if the latter is fed some prediction error.

This more speculative account predicts that inattentional blindness should diminish if the gorilla, for example, occurs at the beginning of the counting task. This is then a way to begin conceptualizing feature- and object-based based attention instead of purely spatial attention.

Van Boxtel et al. A further aspect can be added to this account of inattentional blindness. Attending, especially endogenous attending, is an activity. As such, performing an attention demanding task is a matter of active inference where a model of the world is used to selectively sample sensory input to minimize surprise. This means that high precision input are expected and sampled on the basis of one, initial e. Since the active inference required to comply with an attentional task must favor one model in a sustained way, blindness to unexpected stimuli follows.

On the other hand, the cost of sustained attention is that the prediction error landscape may change during the task; increasing the free energy and making things evade consciousness.

It can thus be disadvantageous for a system to be stuck in active inference and neglecting to revisit the bound on surprise by updating the model e. Perhaps the reason attention can be hard to maintain is that to avoid such disadvantage the system continually seeks, perhaps via spontaneous fluctuations, to alternate between perceptual and active inference.

Minor lapses of attention e. It is interesting here to speculate further that the functional role of exogenous attention can be to not only facilitate processing of salient stimuli but in particular to make the system snap out of active inference, which is often associated with endogenous attention, and back into revision of its generative model.

Exogenous and endogenous attention seem to have opposing functional roles in precision optimization. There remains the rather important and difficult question whether or not the unseen stimulus is in fact consciously perceived but not accessible for introspective report, or whether it is not consciously perceived at all; this question relates to the influential distinction between access consciousness and phenomenal consciousness Block, , To some, this question borders on the incomprehensible or at least untestable Cohen and Dennett, , and there is agreement it cannot be answered directly e.

Instead some indirect, abductive answer must be sought. We cannot answer this question here but we can speculate that the common intuition that there is both access and phenomenal consciousness is fueled by the moments of predictive coding such that i access consciousness goes with active inference i.

If this is right, then a prediction is that in passive viewing, where attention and active inference is kept as minimal as possible, there should be more possibility of having incompatible conscious percepts at the same time, since without active inference there is less imperative to favor just one initial model. There is some evidence for this in binocular rivalry where the absence of attention seems to favor fusion Zhang et al.

Overall, some inroads on inattentional blindness can be made by an appeal to precision expectations giving the attended stimulus a probabilistic advantage. A more full, and speculative, explanation conceives attention in agential terms and appeals to the way active inference can lead to very precise but eventually overall inaccurate perceptual states.

These are cases where abrupt and scene-incongruent changes like sudden mudsplashes attract attention and make invisible other abrupt but scene-congruent changes like a rock turning into a log or an aircraft engine going missing Rensink et al. Only with attention directed at or on repeated exposures grabbed by the scene-congruent change will it be detected. This makes sense if the distractor e. This weights prediction error for a mudsplash model rather than for a natural scenery model with logs or aircrafts.

Even if both models are updated in the light of their respective prediction errors from the mudsplashes and the rock changing to the log, the mudsplash model will have higher conditional confidence because it can explain away precisely a larger part of the bottom-up error signal.

More subtly, change blindness through attention grabbing seems to require that the abrupt stimuli activate a competing model of the causes in the world. This means that the prediction error can be relevant to the states and parameters of one of these models. Thus, the mudsplashes mostly appear to be superimposed on the original image, which activates a model with parameters for causal interaction between mudsplashes and something like a static photo. In other words, the best explanation for the visual input is the transient occlusion or change to a photo, where, crucially, we have strong prior beliefs that photographs do not change over short periods of time.

This contrasts with the situation prior to the mudsplashes occurring where the model would be tuned more to the causal relations inherent in the scene itself that is, the entire scene is not treated as a unitary object that can be mudsplashed. With two models, one can begin to be probabilistically explained away by the other: as the posterior probability of the model that treats the scene as a unitary object increases, the probability of the model that treats it as composite scene will go down.

All this predicts that there should be less change blindness for mudsplashes on dynamic stimuli such as movies because the causal model for such stimuli has higher accuracy; it also predicts less blindness if the mudsplashes are meaningful in the original scene such that competition between models is not engendered. For some scene changes it is harder to induce change blindness. Mudsplashes can blind us when a rock in the way of a kayak changes into a log, but blinds us less when the rock changes into another kayak Sampanes et al.

This type of situation is often dealt with in terms of gist changes but it is also consistent with the interpretation given above. The difference between a log and another kayak in the way of the kayak is in the change in parameters of the model explaining away the prediction error. The change from an unmoving object rock to another unmoving object log incurs much less model revision than the change to a moving, intentional object other kayak : the scope for causal interaction between two kayaks is much bigger than for one kayak and a log.

The prediction error is thus much bigger for the latter, and updating the model to reflect this will increase its probability more, and make blindness less likely. A different type of change blindness occurs when there is no distractor but the change is very slow and incremental e.

Without attention directed at the changing property, the change is not noted. In this case it seems likely that each incremental change is within the expected variability for the model of the entire scene. When attention is directed at the slowly changing component of the scene, the precision expectation and thus the weighting goes up, and it is more likely that the incremental change will generate a prediction error.

This is then an example of change blindness due to imprecise prediction error minimization. If this is right, a prediction is that change of precision expectation through learning, or individual differences in such expectations, should affect this kind of change blindness. If a peripheral cue attracts covert attention to a grating away from fixation, then conscious experience of its contrast is enhanced Carrasco et al.

Similar effects are found for spatial frequency and gap size Gobell and Carrasco, In terms of precision, the peripheral cue induces a high precision expectation for the cued region, which increases the weighting for prediction error from the low contrast grating placed there. Specifically, the expectation will be for a stimulus with an improved signal to noise ratio, that is, a stronger signal. This then seems to be a kind of self-fulfilling prophecy: an expectation for a strong bottom-up signal causing a stronger error signal.

The result is that the world is being represented as having a stronger, more precise signal than it really has, and this is then reflected in conscious perception. From this perspective, the attentional effect is parasitic on a causal regularity in the world. Normally, when attention is attracted to a region there will indeed be a high signal to noise event in that region.

This is part of the prediction error minimization role for attention described above. If this regularity did not hold, then exogenous attention would be costly in free energy. A further study provides evidence for just this notion of an invariant relation between cue strength and expectation for subsequent signal strength: the effect is weakened as the cue contrast decreases Fuller et al.

The cue sets up an expectation for high signal strength i. It is thus an illusion because a causal regularity about precision is applied to a case where it does not in fact hold. If it is correct that this effect relies on learned causal regularities, then it can be predicted that the effect should be reversible through learning, such that strong cues come to be associated with expectations for imprecise target stimuli and vice versa 6.

At the limit, this paradigm provides an example of attention directed at subthreshold stimuli, and thereby enabling their selection into conscious perception e. This shows nicely the modulation by precision weighting of the overall free energy landscape: prediction error, which initially is so imprecise that it is indistinguishable from expected noise can be up-weighted through precision expectations such that the internal model is eventually revised to represent it.

Paradoxically, however, here what we have deemed an attentional illusion of stimulus precision facilitates veridical perception of stimulus occurrence. It is an interesting question if the self-fulfilling prophecy suggested to be in play here is always present under attention, such that attention perpetually enhances phenomenology. If central fixation is abolished and the low contrast grating is fixated, the bound on free energy is again minimized, and this time the error between the model and the actual input from the grating is likely to override the expectation for a strong signal.

This attentional illusion works for exogenous cueing but also for endogenous cueing Liu et al. There does not seem to be any studies of the effect of endogenous attention that is entirely volitional and not accompanied by high contrast cues in the target region even Ling and Carrasco, has high contrast static indicators at the target locations. From the point of view of predictive coding, the prediction is then that there will be less enhancing effect of such pure endogenous attention since the high precision expectation increased baseline in this case is not induced via a learned causal regularity linking strong signal cues to strong signal targets.

A more general prediction follows from the idea that attention is driven by the hyper- prior that cues with high signal strength have high signal to noise ratio. It may be possible to revert this prior through learning such that attention eventually is attracted by low strength cues and stronger cues are ignored. In support of this prediction, there is evidence that some hyperpriors can be altered, such as the light from above prior Morgenstern et al.

This attentional effect is then explained by precision optimization leading to an illusory perceptual inference. It is a case of misrepresented high precision combined with relatively low accuracy. In Troxler fading Troxler, peripheral targets fade out of conscious perception during sustained central fixation.

If attention but not fixation is endogenously directed at one type of sensory attribute, such as the color of some of the peripheral stimuli, then those stimuli fade faster than the unattended stimuli Lou, It is interesting that here attention seems to diminish conscious perception whereas in the cases discussed in the previous section it enhances it.

A key factor here is the duration of trials: fading occurs after several seconds and enhancement is seen in trials lasting only 1—2 s. This temporal signature is consistent with predictive coding insofar as when the prediction error from a stimulus is comprehensively suppressed and no further exploration is happening since active inference is subdued due to central fixation during covert attention probability should begin to drop.

This follows from the idea that what drives conscious perception is the actual process of suppressing prediction error. It translates to the notion that the system expects that the world cannot be unchanging for very long periods of time Hohwy et al. In Troxler fading there is an element of filling-in as the fading peripheral stimuli are substituted by the usually gray background.

This filling-in aspect is seen more dramatically if the background is dynamic De Weerd et al. A similar effect is seen in motion induced blindness MIB. Here peripheral targets fade when there is also a stimulus of coherently moving dots, and the fading of the peripheral dots happens faster when they are covertly attended Geng et al.

The question is then why attention conceived as precision weighting should facilitate the fading of target stimuli together with enhancing filling-in in these cases. In Troxler fading with filling-in of dynamic background as well as in MIB there is an element of model competition. In MIB, there is competition between a model representing the coherently moving dots as a solid rotating disk, which if real would occlude the stationary target dots, and a model representing isolated moving dots, which would not occlude the target dots.

The first model wins due to the coherence of the motion. In the Troxler case with a dynamic background, there is competition between models representing the world as having vs. Sustained attention increases the precision weighting for all prediction error from the attended region, that is, for both the target stimuli and the context in which they are shown i.

This context is processed not only at that region but also globally in the stimulus array and this would boost the confidence that it fills the locations of the target stimuli. This means that as the prediction error for the peripheral target stimuli is explained away, the probabilistic balance might tip in favor of the model that represents the array as having an unbroken background, or a solid moving foreground or a perceptual scotoma. It is thus possible to accommodate these quite complex effects of covert attention within the notion of attention as precision expectation.

On the one hand, exogenous cues can engender high precision expectations that can facilitate target perception, and, on the other hand these expectations can facilitate filling-in of the target location.

At the same time, covert attention stifles active inference and engenders a degree of inaccuracy. During continuous flash suppression, perceptually suppressed images of nudes can attract attention in the sense that they function as exogenous cues in a version of the Posner paradigm Jiang et al. This shows that a key attentional mechanism works in the absence of conscious perception. When there are competing models, conscious perception is determined by the model with the highest posterior probability.

It is conceivable that though the nude image is a state in a losing model it may still induce precision-related gain for a particular region. In general, in the processing of emotional stimuli, there is clear empirical evidence to suggest that fast salient processing that could mediate optimization of precision expectations can be separated from slower perceptual classification Vuilleumier et al. Evidence for this separation rests on the differences in visual pathways, in terms of processing speeds and spatial frequencies that may enable the salience of stimuli to be processed before their content.

Even though a high precision expectation could thus be present for the region of the suppressed stimulus, it is possible for the overall prediction error landscape to not favor the generative model for that stimulus over the model for the abruptly flashing Mondrian pattern in the other eye. The result is that the nude image is not selected for conscious perception but that there nevertheless is an expectation of high precision for its region of the visual field, explaining the effect.

The relation between conscious perception and attention is poorly understood. It has proven difficult to connect the two bodies of empirical findings, based as they are on separate conceptual analyses of each of these core phenomena, and fit them into one unified picture of our mental lives.

In this kind of situation, it can be useful to instead begin with a unified theoretical perspective, apply it to the phenomena at hand and then explore if it is possible to reasonably interpret the bodies of evidence in the light of the theory.

This is the strategy pursued here. The idea that the brain is a precision-weighted hypothesis tester provides an attractive vision of the relationship. Because the states of the world have varying levels of noise or uncertainty, perceptual inference must be modulated by expectations about the precisions of the sensory signal i.

Optimization of precision expectations, it turns out Feldman and Friston, , fits remarkably well the functional role often associated with attention. And the perceptual inference which, thus modulated by attention, achieves the highest posterior probability fits nicely with being what determines the contents of conscious perception. In this perspective, attention and conscious perception are distinct but naturally connected in a way that allows for what appears to be reasonable and fruitful interpretations of some key empirical studies of them and their relationship.

Crudely, perception and attention stand to each other as accuracy and precision, statistically speaking, stand to each other. We have seen that this gives rise to reasonably coherent interpretations of specific types of experimental paradigms. Further mathematical modeling and empirical evidence is needed to fully bring out this conjecture, and a number of the interpretations were shown to lead to testable predictions.

To end, I briefly suggest this unifying approach also sits reasonably well with some very general approaches to attention and perception.

From a commonsense perspective, endogenous and exogenous attention have different functional roles. Endogenous attention can only be directed at contents that are already conscious how can I direct attention to something I am not conscious of? This is an oversimplification, as can be seen from the studies reviewed above. The mapping of conscious perception and attention onto the elements of predictive coding can explain the commonsense understanding of their relationship but also why it breaks down.

Normally endogenous attention is directed at things we already perceive so that no change is missed, i. But precision gain itself is neutral on the actual state of affairs, it just makes the system more sensitive to prediction error, so if we direct attention at a location that seems empty but that has a subthreshold stimulus we are still more likely to spot it in the end.

Conversely, even if precision expectations are driven up by an increase in signal strength somewhere, and attention in this sense is grabbed, it does not follow that this signal must drive conscious perception.

A competing model may as a matter of fact have higher probability. It is sometimes said that a good way to conceive of conscious perception and attention is in terms of the former as a synthesizer that allows us to make sense of our otherwise chaotic sensory input, and the latter as an analyzer that allows us to descend from the overall synthesized picture and focus on a few more salient things Van Boxtel et al.

The predictive coding account allows this sentiment: prediction error minimization is indeed a way of solving the inverse problem of figuring out what in the world caused the sensory input, and attention does allow us to weight the least uncertain parts of this signal. The key insight from this perspective is however that though these are distinct neural processes they are both needed to allow the brain to solve its inverse problem.

But when there are competing models, they can work against each other, and conscious perception can shift between models as precisions and bounds are optimized and the world selectively sampled. Everyone knows what attention is. It is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought.

Focalization, concentration, of consciousness are of its essence. It implies withdrawal from some things in order to deal effectively with others, and is a condition which has a real opposite in the confused, dazed, scatter-brained state which in French is called distraction , and Zerstreutheit in German James, , Vol.

I, pp. This does not mean the predictive coding account of attention stands in direct opposition to the Jamesian description. The sentiment that attention is intimately connected with perception in a hypothesis testing framework was captured very early on by Helmholtz. He argued, for example, that binocular rivalry is an attentional effect but he explicated attention in terms of activity, novelty, and surprise, which is highly reminiscent of the contemporary predictive coding framework:.

The natural unforced state of our attention is to wander around to ever new things, so that when the interest of an object is exhausted, when we cannot perceive anything new, then attention against our will goes to something else. The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Thanks to Karl Friston, Tim Bayne, and the reviewers for very helpful comments and suggestions.

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