Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to (...) adaptive success. This target article critically examines this approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency. (shrink)

Research on surprise relevant to the cognitive-evolutionary model of surprise proposed by Meyer, Reisenzein, and Schützwohl is reviewed. The majority of the assumptions of the model are found empirically supported. Surprise is evoked by unexpected events and its intensity is determined by the degree if schema-discrepancy, whereas the novelty and the valence of the eliciting events probably do not have an independent effect. Unexpected events cause an automatic interruption of ongoing mental processes that is followed by an attentional shift and (...) attentional binding to the events, which is often followed by causal and other event analysis processes and by schema revision. The facial expression of surprise postulated by evolutionary emotion psychologists has been found to occur rarely in surprise, for as yet unknown reasons. A physiological orienting response marked by skin conductance increase, heart rate deceleration, and pupil dilation has been observed to occur regularly in the standard version of the repetition-change paradigm of surprise induction, but the specificity of these reactions as indicators of surprise is controversial. There is indirect evidence for the assumption that the feeling of surprise consists of the direct awareness of the schema-discrepancy signal, but this feeling, or at least the self-report of surprise, is also influenced by experienced interference. In contrast, facial feedback probably does contribute substantially to the feeling of surprise and the evidence for the hypothesis that surprise is affected by the difficulty of explaining an unexpected event is, in our view, inconclusive. Regardless of how the surprise feeling is constituted, there is evidence that it has both motivational and informational effects. Finally, the prediction failure implied by unexpected events sometimes causes a negative feeling, but there is no convincing evidence that this is always the case, and we argue that even if it were so, this would not be a sufficient reason for regarding this feeling as a component, rather than as an effect of surprise. (shrink)

In the past two decades, reinforcement learning has become a popular framework for understanding brain function. A key component of RL models, prediction error, has been associated with neural signals throughout the brain, including subcortical nuclei, primary sensory cortices, and prefrontal cortex. Depending on the location in which activity is observed, the functional interpretation of prediction error may change: Prediction errors may reflect a discrepancy in the anticipated and actual value of reward, a signal indicating the salience or novelty of (...) a stimulus, and many other interpretations. Anterior cingulate cortex has long been recognized as a region involved in processing behavioral error, and recent computational models of the region have expanded this interpretation to include a more general role for the region in predicting likely events, broadly construed, and signaling deviations between expected and observed events. Ongoing modeling work investigating the interaction between ACC and additional regions involved in cognitive control suggests an even broader role for cingulate in computing a hierarchically structured surprise signal critical for learning models of the environment. The result is a predictive coding model of the frontal lobes, suggesting that predictive coding may be a unifying computational principle across the neocortex. (shrink)

Novelty is a pivotal player in cognition, and its contribution to superior memory performance is a widely accepted convention. On the other hand, mnemonic advantages for familiar information are also well documented. Here, we examine the role of experimental distinctiveness as a potential explanation for these apparently conflicting findings. Across two experiments, we demonstrate that conceptual novelty, an unfamiliar combination of familiar constituents, is sensitive to its experimental proportions: Improved memory for novelty was observed when novel stimuli were relatively rare. (...) Memory levels for familiar items, in contrast, were completely unaffected by experimental proportions, highlighting their insensitivity to list-based distinctiveness. Finally, no mnemonic advantage for conceptual novelty over familiarity was observed even when novel stimuli were extremely rare at study. Together, these results imply that novel and familiar items are processed via partially distinct mechanisms, with novelty not providing a mnemonic advantage over familiarity. (shrink)