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The Regularity Account of Phenomenal Unity

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This chapter presents the regularity account of phenomenal unity (RPU). The basic idea of RPU is that when the brain tracks a regularity that is predictive of different features (or of different objects or events), there will be an experienced connection between those features (or the respective objects or events). We can then say that the regularity connects those features (or objects or events). According to RPU, unity comes in degrees, and in ordinary conscious experience we find a hierarchy of experienced wholes. This chapter provides a preliminary taxonomy of experienced wholes, with many examples. Drawing on formal concepts of the predictive processing framework, a formal description of possible computational underpinnings of experienced wholeness is given. Finally, a rigorous formulation of the mélange model (first proposed in chapter 4) is provided.
Title: The Regularity Account of Phenomenal Unity
Description:
This chapter presents the regularity account of phenomenal unity (RPU).
The basic idea of RPU is that when the brain tracks a regularity that is predictive of different features (or of different objects or events), there will be an experienced connection between those features (or the respective objects or events).
We can then say that the regularity connects those features (or objects or events).
According to RPU, unity comes in degrees, and in ordinary conscious experience we find a hierarchy of experienced wholes.
This chapter provides a preliminary taxonomy of experienced wholes, with many examples.
Drawing on formal concepts of the predictive processing framework, a formal description of possible computational underpinnings of experienced wholeness is given.
Finally, a rigorous formulation of the mélange model (first proposed in chapter 4) is provided.

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