Abstract
Prediction plays a key role in control of attention but it is not clear which aspects of prediction are most prominent in conscious experience. An evolving view on the brain is that it can be seen as a prediction machine that optimizes its ability to predict states of the world and the self through the top-down propagation of predictions and the bottom-up presentation of prediction errors. There are competing views though on whether prediction or prediction errors dominate the formation of conscious experience. Yet, the dynamic effects of prediction on perception, decision making and consciousness have been difficult to assess and to model. We propose a novel mathematical framework and a psychophysical paradigm that allows us to assess both the hierarchical structuring of perceptual consciousness, its content and the impact of predictions and/or errors on conscious experience, attention and decision-making. Using a displacement detection task combined with reverse correlation, we reveal signatures of the usage of prediction at three different levels of perceptual processing: bottom-up fast saccades, top-down driven slow saccades and consciousnes decisions. Our results suggest that the brain employs multiple parallel mechanism at different levels of perceptual processing in order to shape effective sensory consciousness within a predicted perceptual scene. We further observe that bottom-up sensory and top-down predictive processes can be dissociated through cognitive load. We propose a probabilistic data association model from dynamical systems theory to model the predictive multi-scale bias in perceptual processing that we observe and its role in the formation of conscious experience. We propose that these results support the hypothesis that consciousness provides a time-delayed description of a task that is used to prospectively optimize real time control structures, rather than being engaged in the real-time control of behavior itself.
Highlights
Theories of consciousness can be grouped with respect to their stance on embodiment, sensori-motor interaction, prediction and information integration (Verschure, 2013)
We observe that the number of fast [χ(22) = 3.500, p = 0.174] and slow [F(1.81, 21.789) = 0.319, p = 0.709] saccadically detected displacements does not change with cognitive load, there is a significant decrease in the proportion of slow saccades that are followed by conscious decisions [χ(22) = 10.844, p = 0.004] (Figure 6)
Our results suggest that cognitive load dynamically biases visual anticipation at the level of conscious decision making both in terms of the anticipatory field and the coupling with preceding more rapid attentional processing
Summary
Theories of consciousness can be grouped with respect to their stance on embodiment, sensori-motor interaction, prediction and information integration (Verschure, 2013). We assess whether the functional significance of this dissociation can be interpreted within the predictive brain framework, which suggests that conscious experience represents the top-down predictions of sensory states rather than reflecting the actual bottom-up states of sensory systems (Hohwy, 2012; Verschure, 2012). In this view it is through simulation that an internal world, or self-generated virtual reality (Revonsuo, 1995), can appear in consciousness, freeing the organism from its immediate physical environment and its specific contingencies (Edelman, 2001; Verschure, 2012). Within the predictive brain framework two alternative hypotheses can be considered, either the content of conscious experience represents “generative models” (i.e., top-down predictions) or the internal world is populated by prediction errors
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