scholarly journals Cognitive Penetration and Cognitive Realism

Episteme ◽  
2021 ◽  
pp. 1-16
Author(s):  
Majid D. Beni

Abstract The paper addresses the issue of theory-ladenness of observation/experimentation. Motivated by a naturalistic reading of Thomas Kuhn's insights into the same topic, I draw on cognitive neuroscience (predictive coding under Free Energy Principle) to scrutinise theory-ladenness. I equate theory-ladenness with the cognitive penetrability of perceptual inferences and argue that strong theory-ladenness prevails only under uncertain circumstances. This understanding of theory-ladenness is in line with Thomas Kuhn's view on the same subject as well as a cognitive version of modest realism rather than downright antirealism.

2019 ◽  
Author(s):  
Dimitris Bolis ◽  
Leonhard Schilbach

Thinking Through Other Minds (TTOM) creatively situates the free energy principle within real-life cultural processes, thereby enriching both sociocultural theories and Bayesian accounts of cognition. Here, shifting the attention from thinking to becoming, we suggest complementing such an account by focusing on the empirical, computational and conceptual investigation of the multiscale dynamics of social interaction.


2019 ◽  
Author(s):  
Beren Millidge

This paper combines the active inference formulation of action (Friston, 2009) with hierarchical predictive coding models (Friston, 2003) to provide a proof-of-concept implementation of an active inference agent able to solve a common reinforcement learning baseline -- the cart-pole environment in OpenAI gym. It demonstrates empirically that predictive coding and active inference approaches can be successfully scaled up to tasks more challenging than the mountain car (Friston 2009, 2012). We show that hierarchical predictive coding models can be learned from scratch during the task, and can successfully drive action selection via active inference. To our knowledge, it is the first implemented active inference agent to combine active inference with a hierarchical predictive coding perceptual model. We also provide a tutorial walk-through of the free-energy principle, hierarchical predictive coding, and active inference, including an in-depth derivation of our agent.


2020 ◽  
Author(s):  
Adam Safron

In introducing a model of “relaxed beliefs under psychedelics” (REBUS), Carhart-Harris and Friston (2019) have presented a compelling account of the effects of psychedelics on brain and mind. This model is contextualized within the Free Energy Principle (Friston et al., 2006; Friston, 2010), which may represent the first unified paradigm in the mind and life sciences. By this view, mental systems adaptively regulate their actions and interactions with the world via predictive models, whose dynamics are governed by a singular objective of minimizing prediction-error, or “free energy.” According to REBUS, psychedelics flatten the depth of free energy landscapes, or the differential attracting forces associated with various (Bayesian) beliefs, so promoting flexibility in inference and learning. Here, I would like to propose an alternative account of the effects of psychedelics that is in many ways compatible with REBUS, albeit with some important differences. Based on considerations of the distributions of 5-HT2a receptors within cortical laminae and canonical microcircuits for predictive coding, I propose that 5-HT2a agonism may also involve a strengthening of beliefs, particularly at intermediate levels of abstraction associated with conscious experience (Safron, 2020).


2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Julian Kiverstein ◽  
Mark Miller ◽  
Erik Rietveld

Abstract In this article, we propose a neurophenomenological account of what moods are, and how they work. We draw upon phenomenology to show how mood attunes a person to a space of significant possibilities. Mood structures a person’s lived experience by fixing the kinds of significance the world can have for them in a given situation. We employ Karl Friston’s free-energy principle to show how this phenomenological concept of mood can be smoothly integrated with cognitive neuroscience. We will argue that mood is a consequence of acting in the world with the aim of minimizing expected free energy—a measure of uncertainty about the future consequences of actions. Moods summarize how the organism is faring overall in its predictive engagements, tuning the organism’s expectations about how it is likely to fare in the future. Agents that act to minimize expected free energy will have a feeling of how well or badly they are doing at maintaining grip on the multiple possibilities that matter to them. They will have what we will call a ‘feeling of grip’ that structures the possibilities they are ready to engage with over long time-scales, just as moods do.


2020 ◽  
Vol 43 ◽  
Author(s):  
Dimitris Bolis ◽  
Leonhard Schilbach

Abstract Thinking through other minds creatively situates the free-energy principle within real-life cultural processes, thereby enriching both sociocultural theories and Bayesian accounts of cognition. Here, shifting the attention from thinking-through to becoming-with, we suggest complementing such an account by focusing on the empirical, computational, and conceptual investigation of the multiscale dynamics of social interaction.


2020 ◽  
Vol 43 ◽  
Author(s):  
Robert Mirski ◽  
Mark H. Bickhard ◽  
David Eck ◽  
Arkadiusz Gut

Abstract There are serious theoretical problems with the free-energy principle model, which are shown in the current article. We discuss the proposed model's inability to account for culturally emergent normativities, and point out the foundational issues that we claim this inability stems from.


Synthese ◽  
2021 ◽  
Author(s):  
Matt Sims ◽  
Giovanni Pezzulo

AbstractPredictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle (FEP)—a normative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., representational versus non-representational. Here we argue that these different interpretations depend on implicit assumptions about what qualifies (or fails to qualify) as representational. We deploy the Free Energy Principle (FEP) instrumentally to distinguish four main notions of representation, which focus on organizational, structural, content-related and functional aspects, respectively. The various ways that these different aspects matter in arriving at representational or non-representational interpretations of the Free Energy Principle are discussed. We also discuss how the Free Energy Principle may be seen as a unified view where terms that traditionally belong to different ontologies—e.g., notions of model and expectation versus notions of autopoiesis and synchronization—can be harmonized. However, rather than attempting to settle the representationalist versus non-representationalist debate and reveal something about what representations are simpliciter, this paper demonstrates how the Free Energy Principle may be used to reveal something about those partaking in the debate; namely, what our hidden assumptions about what representations are—assumptions that act as sometimes antithetical starting points in this persistent philosophical debate.


2021 ◽  
Vol 36 (2) ◽  
Author(s):  
Julian Kiverstein ◽  
Matt Sims

AbstractA mark of the cognitive should allow us to specify theoretical principles for demarcating cognitive from non-cognitive causes of behaviour in organisms. Specific criteria are required to settle the question of when in the evolution of life cognition first emerged. An answer to this question should however avoid two pitfalls. It should avoid overintellectualising the minds of other organisms, ascribing to them cognitive capacities for which they have no need given the lives they lead within the niches they inhabit. But equally it should do justice to the remarkable flexibility and adaptiveness that can be observed in the behaviour of microorganisms that do not have a nervous system. We should resist seeking non-cognitive explanations of behaviour simply because an organism fails to exhibit human-like feats of thinking, reasoning and problem-solving. We will show how Karl Friston’s Free-Energy Principle (FEP) can serve as the basis for a mark of the cognitive that avoids the twin pitfalls of overintellectualising or underestimating the cognitive achievements of evolutionarily primitive organisms. The FEP purports to describe principles of organisation that any organism must instantiate if it is to remain well-adapted to its environment. Living systems from plants and microorganisms all the way up to humans act in ways that tend in the long run to minimise free energy. If the FEP provides a mark of the cognitive, as we will argue it does, it mandates that cognition should indeed be ascribed to plants, microorganisms and other organisms that lack a nervous system.


2021 ◽  
Author(s):  
Hugh McGovern ◽  
Alexander De Foe ◽  
Pantelis Leptourgos ◽  
Philip R. Corlett ◽  
Kavindu Bandara ◽  
...  

Generalized Anxiety Disorder (GAD) is among the world’s most prevalent psychiatric disorders. Affecting an eighth of the world’s population, it often manifests as persistent apprehension which is difficult to control. Despite its prevalence, neuroscientific efforts to understand the cognitive mechanisms of GAD remain sparse. This has resulted in a fractured theoretical landscape, lacking a unitary framework. While prior theories of anxiety describe the cognitive, affective and behavioral dimensions of anxiety, a unified theory is lacking. Here, we point out that postulates derived from the Free Energy Principle (FEP) may allow for a unified theory to emerge. We argue an approach focused on predictive modelling may afford opportunities to re-conceptualize anxiety within the framework of working generative models, rather than static beliefs. We suggest that a biological system—having had persistent uncertainty in its past—will form posteriors in line with uncertainty in its future, irrespective of whether that uncertainty is real. After discussing the FEP, we explain how anxiety develops through learning uncertainty before suggesting predictions for how the model can be tested.


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