Task‐relevant actions can facilitate mathematical thinking, even for complex topics, such as mathematical proof. We investigated whether such cognitive benefits also occur for action predictions. The action‐cognition transduction (ACT) model posits a reciprocal relationship between movements and reasoning. Movements—imagined as well as real ones operating on real or imaginary objects—activate feedforward mechanisms for the plausible predicted outcomes of motor system planning, along with feedback from the effect actions have on the world. Thus, ACT posits cognitive influences for making (...) action predictions regardless of whether those actions are performed. Using a two‐by‐two factorial design, we investigated how generating task‐relevant action predictions or performing task‐relevant directed actions influenced undergraduates’ (N = 127) geometry proof performance. As predicted, making action predictions significantly enhanced participants’ proof production. No evidence suggests that combining action predictions and directed actions provided additional benefits, supporting the claim that predicting and performing actions engage overlapping processes, as theorized by ACT. Gestural replays, reenactments of previously performed actions during explanations, were associated with significantly better insight and proof performance for both (actor‐generated) predicted actions and (investigator‐generated) directed actions. Prompting people to predict task‐relevant actions enhances mathematical cognition, possibly through simulated actions of transformations on imagined mathematical objects, as revealed by increased production of speech describing mathematical operations and increased production of gestural replays. We discuss the theoretical implications of these findings regarding the influences of embodied simulation of movements on cognition, and the educational implications of facilitating mathematical reasoning through interventions prompting students to perform and imagine performing task‐relevant body movements. (shrink)

Both mindreading and stereotyping are forms of social cognition that play a pervasive role in our everyday lives, yet too little attention has been paid to the question of how these two processes are related. This paper offers a theory of the influence of stereotyping on mental-state attribution that draws on hierarchical predictive coding accounts of action prediction. It is argued that the key to understanding the relation between stereotyping and mindreading lies in the fact that stereotypes centrally (...) involve character-trait attributions, which play a systematic role in the action–prediction hierarchy. On this view, when we apply a stereotype to an individual, we rapidly attribute to her a cluster of generic character traits on the basis of her perceived social group membership. These traits are then used to make inferences about that individual’s likely beliefs and desires, which in turn inform inferences about her behavior. (shrink)

Predictive processing has begun to offer new insights into the nature of conscious experience—but the link is not straightforward. A wide variety of systems may be described as predictive machines, raising the question: what differentiates those for which it makes sense to talk about conscious experience? One possible answer lies in the involvement of a higher-order form of prediction error, termed expected free energy. In this paper we explore under what conditions the minimization of this new quantity might underpin (...) conscious experience. Our suggestion is that the minimisation of Expected Free Energy is not in itself sufficient for the occurrence of conscious experience. Instead, it is relevant only insofar as it helps deliver what Ward et al. ( 2011 ) have previously described as a _sense of our own poise over an action space_. Perceptual experience, we will argue, is nothing other than the process that puts current actions in contact with goals and intentions, enabling some creatures to know the space of options that their current situation makes available. This proposal fits with recent work suggesting a deep link between conscious contents and contents computed at an ‘intermediate’ level of processing, apt for controlling action. (shrink)

This chapter considers the possible convergence of predictive processing and embodied cognition. It is argued that the embodied view of cognition comprises a subset (if not all) of the following theses: (1) the constitutive thesis, (2) the nonrepresentational thesis, (3) the cognitive-affective inseparability thesis, and (iv) the metaplasticity thesis. It is then argued that predictive processing is prima facie at odds with some (if not all) of these embodied cognition theses. The reason is that predictive processing is often understood in (...) epistemic, inferential, and representational terms, promoting an internalist and skepticism-prone view of the mind-world relation. The chapter proceeds to establish that this perceived tension between predictive processing and embodied cognition can be overcome. The chapter concludes that it is possible to accept predictive processing and endorse all four theses central to the embodied view of cognition. (shrink)

Recent theory suggests that action prediction relies of a motor emulation mechanism that works by mapping observed actions onto the observer action system so that predictions can be generated using that same predictive mechanisms that underlie action control. This suggests that action prediction may be more accurate when there is a more direct mapping between the stimulus and the observer. We tested this hypothesis by comparing prediction accuracy for two stimulus types. A mannequin (...) stimulus which contained information about the effectors used to produce the action and a point stimulus, which contained identical dynamic information but no effector information. Prediction was more accurate for the mannequin stimulus. However, this effect was dependent on the observer having previous experience performing the observed action. This suggests that experienced and na¨ıve observers might generate predictions in qualitatively difference ways, which may relate to the presence of an internal representation of the action laid down through action performance. (shrink)

Action semantics enables us to plan actions with objects and to predict others' object-directed actions as well. Previous studies have suggested that action semantics are represented in a fronto-parietal action network that has also been implicated to play a role in action observation. In the present fMRI study it was investigated how activity within this network changes as a function of the predictability of an action involving multiple objects and requiring the use of action (...) semantics. Participants performed an action prediction task in which they were required to anticipate the use of a centrally presented object that could be moved to an associated target object (e.g., hammer—nail). The availability of actor information (i.e., presenting a hand grasping the central object) and the number of possible target objects (i.e., 0, 1, or 2 target objects) were independently manipulated, resulting in different levels of predictability. It was found that making an action prediction based on actor information resulted in an increased activation in the extrastriate body area (EBA) and the fronto-parietal action observation network (AON). Predicting actions involving a target object resulted in increased activation in the bilateral IPL and frontal motor areas. Within the AON, activity in the left inferior parietal lobe (IPL) and the left premotor cortex (PMC) increased as a function of the level of action predictability. Together these findings suggest that the left IPL represents stored hand-postures that can be used for planning object-directed actions and for predicting other's actions as well. (shrink)

Accurately predicting other people's actions may involve two processes: internal real-time simulation (dynamic updating) and matching recently perceived action images (static matching). Using a priming of body parts, this study aimed to differentiate the two processes. Specifically, participants played a motion-controlled video game with either their arms or legs. They then observed arm movements of a point-light actor, which were briefly occluded from view, followed by a static test pose. Participants judged whether this test pose depicted a coherent continuation (...) of the previously seen action (i.e., “action prediction task”). Evidence of dynamic updating was obtained after compatible effector priming (i.e., arms), whereas incompatible effector priming (i.e., legs) indicated static matching. Together, the results support action prediction as engaging two distinct processes, dynamic simulation and static matching, and indicate that their relative contributions depend on contextual factors like compatibility of body parts involved in performed and observed action. (shrink)

The key to action control is one’s ability to adequately predict the consequences of one’s actions. Predictive processing theories assume that forward models enable rapid “preplay” to assess the match between predicted and intended action effects. Here we propose the novel hypothesis that “reading” another’s action intentions requires a rich forward model of that agent’s action. Such a forward model can be obtained and enriched through learning by either practice or simulation. Based on this notion, we (...) ran a series of studies on soccer goalkeepers and novices, who predicted the intended direction of penalties being kicked at them in a computerized penalty-reading task. In line with hypotheses, extensive practice in penalty kicking improved performance in penalty reading among goalkeepers who had extensive prior experience in penalty blocking but not in penalty kicking. A robust benefit in penalty reading did not result from practice in kinesthetic motor imagery of penalty kicking in novice participants. To test whether goalkeepers actually use such penalty-kicking imagery in penalty reading, we trained a machine-learning classifier on multivariate fMRI activity patterns to distinguish motor-imagery-related from attention-related strategies during a penalty-imagery training task. We then applied that classifier to fMRI data related to a separate penalty-reading task and showed that 2/3 of all correctly read penalty kicks were classified as engaging the motor-imagery circuit rather than merely the attention circuit. This study provides initial evidence that, in order to read our opponent’s action intention, it helps to observe their action kinematics, and use our own forward model to predict the sensory consequences of “our” penalty kick if we were to produce these action kinematics ourselves. In sum, it takes practice as a penalty kicker to become a penalty killer. (shrink)

Drawing on recent findings in the cognitive and neurosciences, this article discusses how people manage to predict each other’s actions, which is fundamental for joint action. We explore how a common coding of perceived and performed actions may allow actors to predict the what, when, and where of others’ actions. The “what” aspect refers to predictions about the kind of action the other will perform and to the intention that drives the action. The “when” aspect is critical (...) for all joint actions requiring close temporal coordination. The “where” aspect is important for the online coordination of actions because actors need to effectively distribute a common space. We argue that although common coding of perceived and performed actions alone is not sufficient to enable one to engage in joint action, it provides a representational platform for integrating the actions of self and other. The final part of the paper considers links between lower‐level processes like action simulation and higher‐level processes like verbal communication and mental state attribution that have previously been at the focus of joint action research. (shrink)

This chapter contains sections titled: Introduction Classes of Uncertainty Our Argument Predicting Other People's Action Predicting One's Own Actions Predicting Group Action The Danger of Prediction References.

Intentional action involves both a series of neural events in the motor areas of the brain, and also a distinctive conscious experience that ''I'' am the author of the action. This paper investigates some possible ways in which these neural and phenomenal events may be related. Recent models of motor prediction are relevant to the conscious experience of action as well as to its neural control. Such models depend critically on matching the actual consequences of a (...) movement against its internally predicted effects. However, it remains unclear whether our conscious experience of action depends on a precise matching process, or a retrospective inference that ''I'' must have been responsible for a particular event. We report an experiment in which normal subjects judged the perceived time of either intentional actions, involuntary movements, or subsequent effects (auditory tones) of these. We found that the subject's intention to produce the auditory tone produced an intentional binding between the perceived times of the subject's action and the tone. However, if the intention was interrupted by an imposed involuntary movement, followed by the identical tone, no such binding occurred. The phenomenology of intentional action requires an appropriate predictive link between intentions and effects, rather than a retrospective inference that ''I'' caused the effect. (shrink)

Prior research suggests that the action system is responsible for creating an immediate sense of self by determining whether certain sensations and perceptions are the result of one's own actions. In addition, it is assumed that declarative, episodic, or autobiographical memories create a temporally extended sense of self or some form of identity. In the present article, we review recent evidence suggesting that action (procedural) knowledge also forms part of a person's identity, an action identity, so to (...) speak. Experiments that addressed self-recognition of past actions, prediction, and coordination provide ample evidence for this assumption. The phenomena observed in these experiments can be explained by the assumption that observing an action results in the activation of action representations, the more so, when the action observed corresponds to the way in which the observer would produce it. (shrink)

Storchak, Ehlis, and Fallgatter provide an extensive literature review on electrophysiological measurements, which indicate that general predictive deficits in self‐monitoring are associated with various positive symptoms in patients with schizophrenia.

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind is (...) that the mechanism explains the rich, deep, and multifaceted character of our conscious perception. It also gives a unified account of how perception is sculpted by attention, and how it depends on action. The mind is revealed as having a fragile and indirect relation to the world. Though we are deeply in tune with the world we are also strangely distanced from it. (shrink)

This chapter seeks to recover an approach to consciousness from a general theory of brain function, namely the prediction error minimization theory. The way this theory applies to mental and developmental disorder demonstrates its relevance to consciousness. The resulting view is discussed in relation to a contemporary theory of consciousness, namely the idea that conscious perception depends on Bayesian metacognition; this theory is also supported by considerations of psychopathology. This Bayesian theory is first disconnected from the higher-order thought theory, (...) and then, via a prediction error conception of action, connected instead to the global neuronal workspace theory. Considerations of mental and developmental disorder therefore show that a very general theory of brain function is relevant to explaining the structure of conscious perception; furthermore, this theory can subsume and unify two contemporary approaches to consciousness, in a move that seeks to elucidate the fundamental mechanism for selection of representational content into consciousness. (shrink)

How is it that thoroughly physical material beings such as ourselves can think, dream, feel, create and understand ideas, theories and concepts? How does mere matter give rise to all these non-material mental states, including consciousness itself? An answer to this central question of our existence is emerging at the busy intersection of neuroscience, psychology, artificial intelligence, and robotics.In this groundbreaking work, philosopher and cognitive scientist Andy Clark explores exciting new theories from these fields that reveal minds like ours to (...) be prediction machines - devices that have evolved to anticipate the incoming streams of sensory stimulation before they arrive. These predictions then initiate actions that structure our worlds and alter the very things we need to engage and predict. Clark takes us on a journey in discovering the circular causal flows and the self-structuring of the environment that define "the predictive brain." What emerges is a bold, new, cutting-edge vision that reveals the brain as our driving force in the daily surf through the waves of sensory stimulation. (shrink)

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress response times to a cued target, and thus it cannot reveal the full time‐course of motion, including predictive movements. This paper describes a mouse (...) movement trajectory SRT task in which the cursor must be moved to a cued location. We replicated keypress SRT results, but also found that predictive movement—before the next cue appears—increased during the experiment. Moreover, trajectory analyses revealed that people developed a centering strategy under uncertainty. In a second experiment, we made prediction explicit, no longer cueing targets. Thus, participants had to explore the response alternatives and learn via reinforcement, receiving rewards and penalties for correct and incorrect actions, respectively. Participants were not told whether the sequence of stimuli was deterministic, nor if it would repeat, nor how long it was. Given the difficulty of the task, it is unsurprising that some learners performed poorly. However, many learners performed remarkably well, and some acquired the full 10‐item sequence within 10 repetitions. Comparing the high‐ and low‐performers’ detailed results in this reinforcement learning (RL) task with the first experiment's cued trajectory SRT task, we found similarities between the two tasks, suggesting that the effects in Experiment 1 are due to predictive, rather than reactive processes. Finally, we found that two standard model‐free reinforcement learning models fit the high‐performing participants, while the four low‐performing participants provide better fit with a simple negative recency bias model. (shrink)

The main objective of this study was to examine whether children’s ability to justify their action predictions in terms of mental states is related, in a similar way as the ability to predict actions, to such aspects of executive function as executive control and working memory. An additional objective was to check whether the frequency of different types of justifications made by children in false-belief tasks is associated with aforementioned aspects of EF, as well as language. The study included (...) 59 children aged 3-4 years. The ability to predict actions and to justify these predictions was measured with false-belief tasks. Luria’s hand-game was used to assess executive control, and the Counting and Labelling dual-task was used to assess working memory capacity. Language development was controlled using an embedded syntax test. It was found that executive control was a significant predictor of the children’s ability to justify their action predictions in terms of mental states, even when age and language were taken into account. Results also indicated a relationship between the type of justification in the false-belief task and language development. With the development of language children gradually cease to justify their action predictions in terms of current location, and they tend to construct irrelevant justifications before they begin to refer to beliefs. Data suggest that executive control, in contrast to language, is a factor which affects the development of the children’s ability to justify their action predictions only in its later phase, during a shift from irrelevant to correct justifications. (shrink)

Looking times and gaze behavior indicate that infants can predict the goal state of an observed simple action event (e.g., object‐directed grasping) already in the first year of life. The present paper mainly focuses on infants’ predictive gaze‐shifts toward the goal of an ongoing action. For this, infants need to generate a forward model of the to‐be‐obtained goal state and to disengage their gaze from the moving agent at a time when information about the action event is (...) still incomplete. By about 6 months of age, infants show goal‐predictive gaze‐shifts, but mainly for familiar actions that they can perform themselves (e.g., grasping) and for familiar agents (e.g., a human hand). Therefore, some theoretical models have highlighted close relations between infants’ ability for action‐goal prediction and their motor development and/or emerging action experience. Recent research indicates that infants can also predict action goals of familiar simple actions performed by non‐human agents (e.g., object‐directed grasping by a mechanical claw) when these agents display agency cues, such as self‐propelled movement, equifinality of goal approach, or production of a salient action effect. This paper provides a review on relevant findings and theoretical models, and proposes that the impacts of action experience and of agency cues can be explained from an action‐event perspective. In particular, infants’ goal‐predictive gaze‐shifts are seen as resulting from an interplay between bottom‐up processing of perceptual information and top‐down influences exerted by event schemata that store information about previously executed or observed actions. (shrink)

According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of (...) sorts, in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system. (shrink)

The predictive processing literature contains at least two different versions of the framework with different theoretical resources at their disposal. One version appeals to so-called optimistic priors to explain agents’ motivation to act (call this optimistic predictive processing). A more recent version appeals to expected free energy minimization to explain how agents can decide between different action policies (call this preference predictive processing). The difference between the two versions has not been properly appreciated, and they are not sufficiently separated (...) in the literature. They constitute two different theories with strikingly different accounts of motivation and action. By reducing all desire-like constructs to belief-like constructs, optimistic predictive processing entails a substantial revision of standard accounts of motivation and action in philosophy and cognitive science. By contrast, preference predictive processing introduces desire-like constructs that play Humean motivational roles in the explanation of action. In this Humean iteration, predictive processing resembles other prominent computational frameworks implementing a distinction between beliefs and desires, such as reinforcement learning and Bayesian decision theory. Ultimately, predictive processing faces a dilemma between parsimony of mental constructs and completeness of its explanations of agency and the mind. (shrink)

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress response times to a cued target, and thus it cannot reveal the full time‐course of motion, including predictive movements. This paper describes a mouse (...) movement trajectory SRT task in which the cursor must be moved to a cued location. We replicated keypress SRT results, but also found that predictive movement—before the next cue appears—increased during the experiment. Moreover, trajectory analyses revealed that people developed a centering strategy under uncertainty. In a second experiment, we made prediction explicit, no longer cueing targets. Thus, participants had to explore the response alternatives and learn via reinforcement, receiving rewards and penalties for correct and incorrect actions, respectively. Participants were not told whether the sequence of stimuli was deterministic, nor if it would repeat, nor how long it was. Given the difficulty of the task, it is unsurprising that some learners performed poorly. However, many learners performed remarkably well, and some acquired the full 10‐item sequence within 10 repetitions. Comparing the high‐ and low‐performers’ detailed results in this reinforcement learning (RL) task with the first experiment's cued trajectory SRT task, we found similarities between the two tasks, suggesting that the effects in Experiment 1 are due to predictive, rather than reactive processes. Finally, we found that two standard model‐free reinforcement learning models fit the high‐performing participants, while the four low‐performing participants provide better fit with a simple negative recency bias model. (shrink)

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)

We argue that brains generate predictions only within the constraints of the action repertoire. This makes the computational complexity tractable and fosters a step-by-step parallel development of sensory and motor systems. Hence, it is more of a benefit than a literal constraint and may serve as a universal normative principle to understand sensorimotor coupling and interactions with the world.

The folk Psychology frames propositional attitudes as fundamental theoretical entities for the construction of a model designed to predict the behavior of a subject. A trivial, such as grasping a pen and writing reveals - something complex - about the behavior. When I take a pen and start writing I do, trivially, because I believe that a certain object in front of me is a pen and who performs a specific function that is, in fact, that of writing. When I (...) believe that the object that stands before me is a pen, I am in relation to "believe" with the propositional content: that in front of me is a pen. Philosophers of the proposition, from Frege onwards, have dedicated their studies to the analysis of what kinds of entities are the propositional attitudes. Jerry Fodor says that now, the proper prediction of the psychology of common sense, can not be questioned and that the propositional attitudes represent the most effective way to describe our behavior. What Fodor says, however, is that propositional attitudes function, but not how they work. Most philosophers interested in the issue, we are dedicated to the search for a theory that can account consistently both a semantics for propositional attitudes, both of these entities that seem to cause the behavior of a rational subject. There are two main paradigms in the theory of the proposition that contributed to the discussion of the propositional attitudes. One is the one that begins with Gottlob Frege, the other with Bertrand Russell. Defenders of Frege argue that the paradigm scrub objects and properties can not be constituents of the propositional content which have a purely conceptual. In other words, the philosophers belonging to the paradigm of Frege, but not all, mean that you can test in a rigorous way the truth conditions of propositional attitudes. Who defends the russellian’s paradigm argues that the propositional content are made by the objects and properties on which propositional attitudes relate. The purpose of this article is not to rebuild - in detail - both paradigms, nor to reconstruct one but, in a sense, my work will be a completely partial objective is to demonstrate how the paradigm is more profitable russell not only to make a coherent semantic theory for propositional attitudes2 but also to predict the behavior of a rational subject thing, completely innovative, given the repeated objections in contemporary literature3. At the end of this paper will be drafted a proposal to build a consistent model to predict the behavior,of a rational agent, based on a referential theory of propositional attitudes. (shrink)

Clark expresses reservations about Friston's reductive interpretation of action-oriented predictive processing (AOPP) models of cognition, but he doesn't link these reservations to specific alternatives. Neuroeconomic models of sub-cognitive reward valuation, which, like AOPP, integrate attention with action based on prediction error, are such an alternative. They interpret reward valuation as an input to neocortical processing instead of reducing it.

This study is a comparison of the validity of theory of reasoned action and theory of planned behavior as applied to the area of moral behavior (i.e., illegal copying of software) using structural equation modeling. Data were collected from 181 university students on the various components of the theories and used to asses the influence of attitude, subjective norm, and perceived behavioral control on the intention to make unauthorized software copies. Theory of planned behavior was found to be better (...) than the theory of reasoned action in predicting unethical behavior. A modified version of the theory of planned behavior, with a causal path linking subjective norm to attitude, provided a significant improvement on model fit. The results indicated that perceived behavioral control is a better predictor of behavioral intention then attitude. The direct effect of subjective norm on behavioral intention was not significant, but the indirect effect through attitude was highly significant. Applicability of the theory of planned behavior for moral behavior and the implications for future research are discussed. (shrink)

This paper examines Lockie’s theory of libertarian self-determinism in light of the question of prediction: “Can we know (or justifiably believe) how an agent will act, or is likely to act, freely?” I argue that, when Lockie's theory is taken to its full logical extent, free actions cannot be predicted to any degree of accuracy because, even if they have probabilities, these cannot be known. However, I suggest that this implication of his theory is actually advantageous, because it is (...) able to explain and justify an important feature of the practices we use to determine whether someone has acted culpably: our hostility to the use of predictive evidence. (shrink)

This study investigates whether the conscious awareness of action is based on predictive motor control processes, or on inferential “sense-making” process that occur after the action itself. We investigated whether the temporal binding between perceptual estimates of operant actions and their effects depends on the occurrence of the effect (inferential processes) or on the prediction that the effect will occur (predictive processes). By varying the probability with which a simple manual action produced an auditory effect, we (...) showed that both the actual and the predicted occurrence of the effect played a role. When predictability of the effect of action was low, temporal binding was found only on those trials where the auditory effect occurred. In contrast, when predictability of the effect of action was high, temporal binding occurred even on trials where the action produced no effect. Further analysis showed that the predictive process is modulated by recent experience of the action-effect relation. We conclude that the experience of action depends on a dynamic combination of predictive and inferential processes. (shrink)

Challenges to visual prediction as an organizing concept come from three main sources: (1) from observations arising from the results of experiments employing unpredictable motion, (2) from the assertions that motor processes compensate for all neural delays, and (3) from multiple interpretations specific to the flash-lag effect. One clarification that has emerged is that visual prediction is a process that either complements or reflects non-visual (e.g., motor) prediction.

A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, (...) the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. (shrink)

Butz, Achimova, Bilkey, and Knott provide a topic overview and discuss whether the special issue contributions may imply that event‐predictive abilities constitute a root for conceptual human thought, because they enable complex, mutually beneficial, but also intricately competitive, social interactions and language communication.

A method is presented for deciding whether correct predictions about other people are based on simulation or theory use. The differentiating power of this method was assessed with cognitive estimation biases (e.g. estimating the area of Brazil) in two variations. Experiments 1 and 2 operated with the influence of response scales of different length. Experiment 3 used the difference between free estimates that tended to be far off the true value and estimates constrained by an appropriate response scale, where estimates (...) became greatly more realistic. The critical question is how well observer subjects can predict these target biases under two different presentation conditions. Response scale biases (Experiments 1 and 2) were more strongly predicted when observer subjects were presented with the two scales juxtaposed, than when responses for each scale were given independently. This speaks for the use of a theory, since simulation should, if there is any difference at all, be made more difficult by the juxtaposition of conditions. The difference between free and constrained estimations (Experiment 3) was more strongly predicted under independent than under juxtaposed presentation. This speaks for the use of simulation since use of a theory should, if anything, be helped by juxtaposition of problems since it helps highlight the theoretically relevant factor. Results are discussed in view of recent proposals about when simulation is likely to be used, i.e. for belief fixation but not action prediction (Stich and Nichols, 1995b), for content fixation (Heal, 1996a), and for rational effects only (Heal, 1996b). (shrink)

Recent work in computational and cognitive neuroscience depicts the brain as an ever‐active prediction machine: an inner engine continuously striving to anticipate the incoming sensory barrage. I briefly introduce this class of models before contrasting two ways of understanding the implied vision of mind. One way (Conservative Predictive Processing) depicts the predictive mind as an insulated inner arena populated by representations so rich and reconstructive as to enable the organism to ‘throw away the world’. The other (Radical Predictive Processing) (...) stresses the use of fast and frugal, action‐involving solutions of the kind highlighted by much work in robotics and embodied cognition. But it goes further, by showing how predictive schemes can combine frugal and more knowledge‐intensive strategies, switching between them fluently and continuously as task and context dictate. I end by exploring some parallels with work in enactivism, and by noting a certain ambivalence concerning internal representations and their role in the predictive mind. (shrink)

The purpose of this study is to investigate the salient factors that influence accounting students to engage in software and music piracy. This study uses the theory of reasoned action and the theory of planned behavior, and extends these models to incorporate other variables to predict individuals’ behavioral intentions. Specifically, we hypothesize that attitudes toward the behavior, subjective norms, perceived behavioral control, moral obligation and perceived prosecution risk influence intentions to engage in software and music piracy. Data were obtained (...) from 237 university accounting students in a Caribbean university to assess the influence of the components of the theories and other modified and extended models. Findings reveal that attitudes, subjective norms, perceived behavioral control, moral obligation and perceived prosecution risk significantly influence intentions to engage in software and music piracy. These findings lend full support to the hypothesized relationships in our extended theory of planned behavior. (shrink)

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising (...) levels of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture. (shrink)