319 research outputs found

    An Enactive Theory of Need Satisfaction

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    In this paper, based on the predictive processing approach to cognition, an enactive theory of need satisfaction is discussed. The theory can be seen as a first step towards a computational cognitive model of need satisfaction

    Why does any body have a self?

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    Is body dysmorphic disorder associated with abnormal bodily self-awareness? A study using the rubber hand illusion.

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    Evidence from past research suggests that behaviours and characteristics related to body dissatisfaction may be associated with greater instability of perceptual body image, possibly due to problems in the integration of body-related multisensory information. We investigated whether people with body dysmorphic disorder (BDD), a condition characterised by body image disturbances, demonstrated enhanced susceptibility to the rubber hand illusion (RHI), which arises as a result of multisensory integration processes when a rubber hand and the participant\u27s hidden real hand are stimulated in synchrony. Overall, differences in RHI experience between the BDD group and healthy and schizophrenia control groups (n = 17 in each) were not significant. RHI strength, however, was positively associated with body dissatisfaction and related tendencies. For the healthy control group, proprioceptive drift towards the rubber hand was observed following synchronous but not asynchronous stimulation, a typical pattern when inducing the RHI. Similar drifts in proprioceptive awareness occurred for the BDD group irrespective of whether stimulation was synchronous or not. These results are discussed in terms of possible abnormalities in visual processing and multisensory integration among people with BDD

    Mechanistic unity of the predictive mind

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    It is often recognized that cognitive science employs a diverse explanatory toolkit. It has also been argued that cognitive scientists should embrace this explanatory diversity rather than pursue search for some grand unificatory framework or theory. This pluralist stance dovetails with the mechanistic view of cognitive-scientific explanation. However, one recently proposed theory – based on an idea that the brain is a predictive engine – opposes the spirit of pluralism by unapologetically wearing unificatory ambitions on its sleeves. In this paper, my aim is to investigate those pretentions to elucidate what sort of unification is on offer. I challenge the idea that explanatory unification of cognitive science follows from the Free Energy Principle. I claim that if the predictive story is to provide an explanatory unification, it is rather by proposing that many distinct cognitive mechanisms fall under the same functional schema that pertains to prediction error minimization. Seen this way, the brain is not simply a predictive mechanism – it is a collection of predictive mechanisms. I also pursue a more general aim of investigating the value of unificatory power for mechanistic explanations. I argue that even though unification is not an absolute evaluative criterion for mechanistic explanations, it may play an epistemic role in evaluating the credibility of an explanation relative to its direct competitors

    The hierarchically mechanistic mind: an evolutionary systems theory of the human brain, cognition, and behavior

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    The purpose of this review was to integrate leading paradigms in psychology and neuroscience with a theory of the embodied, situated human brain, called the Hierarchically Mechanistic Mind (HMM). The HMM describes the brain as a complex adaptive system that functions to minimize the entropy of our sensory and physical states via action-perception cycles generated by hierarchical neural dynamics. First, we review the extant literature on the hierarchical structure of the brain. Next, we derive the HMM from a broader evolutionary systems theory that explains neural structure and function in terms of dynamic interactions across four nested levels of biological causation (i.e., adaptation, phylogeny, ontogeny, and mechanism). We then describe how the HMM aligns with a global brain theory in neuroscience called the free-energy principle, leveraging this theory to mathematically formulate neural dynamics across hierarchical spatiotemporal scales. We conclude by exploring the implications of the HMM for psychological inquiry

    Fenneman, Frankenhuis, and Todd’s (2022) review of formal impulsivity models : implications for theory and measures of impulsivity

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    In Fenneman, Frankenhuis, and Todd's (2022) review of theories and integrated impulsivity model, the authors distinguish between information impulsivity (i.e., acting without considering consequences) and temporal impulsivity (i.e., the tendency to pick sooner outcomes over later ones). The authors find that both types of impulsivity can be adaptive in different contexts. For example, when individuals experience scarcity of resources or when they are close to a minimum level of reserves (critical threshold). In this commentary, we extend their findings to a discussion about the measurement of impulsivity. We argue that a common method for measuring temporal impulsivity in which people make decisions between outcomes that are spaced out in time (intertemporal choice tasks), puts individuals in a specific context that is unlikely to generalize well to other situations. Furthermore, trait measures of impulsivity may only be modestly informative about future impulsive behavior because they largely abstract away from important context. To address these issues, we advocate for the development of dynamic measures of the two types of impulsivity. We argue that measuring temporal impulsivity in naturalistic contexts with varying environmental and state parameters could provide insight into whether individuals (i.e., humans and non-human animals) react to environmental changes adaptively, while trait measures of impulsivity more generally should collect and provide more contextual information. Dynamic measurement of different types of impulsivity will also allow for more discussion about adaptive impulsive responses in different contexts, which could help combat the stigmatization of various disorders associated with impulsivity

    Context sensitivity in action decreases along the autism spectrum: a predictive processing perspective

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    Recent predictive processing accounts of perception and action point towards a key challenge for the nervous system in dynamically optimizing the balance between incoming sensory information and existing expectations regarding the state of the environment. Here, we report differences in the influence of the preceding sensory context on motor function, varying with respect to both clinical and subclinical features of autism spectrum disorder (ASD). Reach-to-grasp movements were recorded subsequent to an inactive period in which illusory ownership of a prosthetic limb was induced. We analysed the sub-components of reach trajectories derived using a minimum-jerk fitting procedure. Non-clinical adults low in autistic features showed disrupted movement execution following the illusion compared to a control condition. By contrast, individuals higher in autistic features (both those with ASD and non-clinical individuals high in autistic traits) showed reduced sensitivity to the presence of the illusion in their reaching movements while still exhibiting the typical perceptual effects of the illusion. Clinical individuals were distinct from non-clinical individuals scoring high in autistic features, however, in the early stages of movement. These results suggest that the influence of high-level representations of the environment differs between individuals, contributing to clinical and subclinical differences in motor performance that manifest in a contextual manner. As high-level representations of context help to explain fluctuations in sensory input over relatively longer time scales, more circumscribed sensitivity to prior or contextual information in autistic sensory processing could contribute more generally to reduced social comprehension, sensory impairments and a stronger desire for predictability and routine

    Deep brain stimulation for Parkinson\u27s disease changes perception in the Rubber Hand Illusion

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    Parkinson\u27s disease (PD) alters cortico-basal ganglia-thalamic circuitry and susceptibility to an illusion of bodily awareness, the Rubber Hand Illusion (RHI). Bodily awareness is thought to result from multisensory integration in a predominantly cortical network; the role of subcortical connections is unknown. We studied the effect of modulating cortico-subcortical circuitry on multisensory integration for bodily awareness in 24 PD patients treated with subthalamic nucleus (STN) deep brain stimulation (DBS), in comparison to 21 healthy volunteers, using the RHI experiment. Typically, synchronous visuo-tactile cues induce a false perception of touch on the rubber hand as if it were the subject\u27s hand, whereas asynchronous visuo-tactile cues do not. However, we found that in the asynchronous condition, patients in the off-stimulation state did not reject the RHI as strongly as healthy controls; patients\u27 rejection of the RHI strengthened when STN-DBS was switched on, although it remained weaker than that of controls. Patients in the off-stimulation state also misjudged the position of their hand, indicating it to be closer to the rubber hand than controls. However, STN-DBS did not affect proprioceptive judgements or subsequent arm movements altered by the perceptual effects of the illusion. Our findings support the idea that the STN and subcortical connections have a key role in multisensory integration for bodily awareness. Decision-making in multisensory bodily illusions is discussed

    Individual Differences in Moral Behaviour: A Role for Response to Risk and Uncertainty?

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    Investigation of neural and cognitive processes underlying individual variation in moral preferences is underway, with notable similarities emerging between moral- and risk-based decision-making. Here we specifically assessed moral distributive justice preferences and non-moral financial gambling preferences in the same individuals, and report an association between these seemingly disparate forms of decision-making. Moreover, we find this association between distributive justice and risky decision-making exists primarily when the latter is assessed with the Iowa Gambling Task. These findings are consistent with neuroimaging studies of brain function during moral and risky decision-making. This research also constitutes the first replication of a novel experimental measure of distributive justice decision-making, for which individual variation in performance was found. Further examination of decision-making processes across different contexts may lead to an improved understanding of the factors affecting moral behaviour

    Models, Brains, and Scientific Realism

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    Prediction Error Minimization theory (PEM) is one of the most promising attempts to model perception in current science of mind, and it has recently been advocated by some prominent philosophers as Andy Clark and Jakob Hohwy. Briefly, PEM maintains that “the brain is an organ that on average and over time continually minimizes the error between the sensory input it predicts on the basis of its model of the world and the actual sensory input” (Hohwy 2014, p. 2). An interesting debate has arisen with regard to which is the more adequate epistemological interpretation of PEM. Indeed, Hohwy maintains that given that PEM supports an inferential view of perception and cogni-tion, PEM has to be considered as conveying an internalist epistemological perspective. Contrary to this view, Clark maintains that it would be incorrect to interpret in such a way the indirectness of the link between the world and our inner model of it, and that PEM may well be combined with an externalist epistemological perspective. The aim of this paper is to assess those two opposite interpretations of PEM. Moreover, it will be suggested that Hohwy’s position may be considerably strengthened by adopting Carlo Cellucci’s view on knowledge (2013)
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