Abstract

The Predictive Processing (PP) framework casts the brain as a probabilistic prediction engine that continually generates predictions of the causal structure of the world in order to construct for itself, from the top down, incoming sensory signals. Conceiving of the brain in this way has yielded incredible explanatory power, offering what many believe to be our first glimpse at a unified theory of the mind. In this paper, the picture of the mind brought into view by predictive processing theories is shown to be embodied, deeply affective and nicely poised for cognitive extension. We begin by giving an overview of the main themes of the framework, and situating this approach within embodied cognitive science. We show perception, action, homeostatic regulation and emotion to be underpinned by the very same predictive machinery. We conclude by showing how predictive minds will increasingly be understood as deeply interwoven with, and perhaps extended into, the surrounding social, cultural and technological landscape. This article is categorized under: Philosophy > Foundations of Cognitive Science Psychology > Emotion and Motivation Philosophy > Action.

Highlights

  • A new perspective dominates many discussions of mind and cognition

  • Part of the power of the framework lies in the elegant suggestion that much of what we take to be central to human intelligence—perception, action, attention, emotion, learning, and language—can be understood within a simple framework of predictions and error reduction

  • In what follows we will refer to this general approach to understanding the mind and brain as predictive processing (PP)

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Summary

Introduction

A new perspective dominates many discussions of mind and cognition. That perspective depicts the brain as essentially a probabilistic prediction engine, dedicated to the task of minimizing the disparity between how it expects (predicts) the world to be and the evidence presented by the sensory flow.1 Part of the power of the framework lies in the elegant suggestion that much of what we take to be central to human intelligence—perception, action, attention, emotion, learning, and language—can be understood within a simple framework of predictions and error reduction. In what follows we will refer to this general approach to understanding the mind and brain as predictive processing (PP). We turn to recent work on feelings and emotions, and review a new take on affect value and its role in directing core estimations of the reliability and value of prediction errors.

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