scholarly journals Is the brain an organ for free energy minimisation?

2021 ◽  
Author(s):  
Daniel Williams
Keyword(s):  
Free Energy ◽  
Cognitive Science ◽  
Neural Mechanisms ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Energy Minimisation ◽  
Process Theories ◽  
Fallacy Of Equivocation ◽  
The Brain ◽  
Structure And Functions

AbstractTwo striking claims are advanced on behalf of the free energy principle (FEP) in cognitive science and philosophy: (i) that it identifies a condition of the possibility of existence for self-organising systems; and (ii) that it has important implications for our understanding of how the brain works, defining a set of process theories—roughly, theories of the structure and functions of neural mechanisms—consistent with the free energy minimising imperative that it derives as a necessary feature of all self-organising systems. I argue that the conjunction of claims (i) and (ii) rests on a fallacy of equivocation. The FEP can be interpreted in two ways: as a claim about how it is possible to redescribe the existence of self-organising systems (the Descriptive FEP), and as a claim about how such systems maintain their existence (the Explanatory FEP). Although the Descriptive FEP plausibly does identify a condition of the possibility of existence for self-organising systems, it has no important implications for our understanding of how the brain works. Although the Explanatory FEP would have such implications if it were true, it does not identify a condition of the possibility of existence for self-organising systems. I consider various ways of responding to this conclusion, and I explore its implications for the role and importance of the FEP in cognitive science and philosophy.

scholarly journals Is free-energy minimisation the mark of the cognitive?

2021 ◽  
Vol 36 (2) ◽  
Author(s):  
Julian Kiverstein ◽  
Matt Sims
Keyword(s):  
Nervous System ◽  
Free Energy ◽  
Problem Solving ◽  
Living Systems ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Energy Minimisation ◽  
Long Run ◽  
Evolution Of Life ◽  
Mark Of The Cognitive

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.

scholarly journals Strengthened beliefs under psychedelics (SEBUS)? A Commentary on “REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics”

2020 ◽  
Author(s):  
Adam Safron
Keyword(s):  
Free Energy ◽  
Conscious Experience ◽  
Predictive Coding ◽  
Alternative Account ◽  
Levels Of Abstraction ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Free Energy Landscapes ◽  
The Mind ◽  
The Brain

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).

scholarly journals From Learning to Consciousness: An Example Using Expected Float Entropy Minimisation

Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 60
Author(s):  
Jonathan Mason
Keyword(s):  
Information Theory ◽  
Free Energy ◽  
Learning Processes ◽  
Brain State ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Association Learning ◽  
The Relationship ◽  
The Brain ◽  
Integrated Information Theory

Over recent decades several mathematical theories of consciousness have been put forward including Karl Friston’s Free Energy Principle and Giulio Tononi’s Integrated Information Theory. In this article we further investigate theory based on Expected Float Entropy (EFE) minimisation which has been around since 2012. EFE involves a version of Shannon Entropy parameterised by relationships. It turns out that, for systems with bias due to learning, certain choices for the relationship parameters are isolated since giving much lower EFE values than others and, hence, the system defines relationships. It is proposed that, in the context of all these relationships, a brain state acquires meaning in the form of the relational content of the associated experience. EFE minimisation is itself an association learning process and its effectiveness as such is tested in this article. The theory and results are consistent with the proposition of there being a close connection between association learning processes and the emergence of consciousness. Such a theory may explain how the brain defines the content of consciousness up to relationship isomorphism.

scholarly journals A free energy principle for the brain

2006 ◽  
Vol 100 (1-3) ◽  
pp. 70-87 ◽  
Author(s):  
Karl Friston ◽  
James Kilner ◽  
Lee Harrison
Keyword(s):  
Free Energy ◽  
Energy Principle ◽  
Free Energy Principle ◽  
The Brain

scholarly journals Recognition Dynamics in the Brain under the Free Energy Principle

2018 ◽  
Vol 30 (10) ◽  
pp. 2616-2659 ◽  
Author(s):  
Chang Sub Kim
Keyword(s):  
Free Energy ◽  
Numerical Solutions ◽  
Coarse Grained ◽  
Biophysical Model ◽  
Hierarchical Architecture ◽  
Bayesian Filtering ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Least Action ◽  
The Brain

We formulate the computational processes of perception in the framework of the principle of least action by postulating the theoretical action as a time integral of the variational free energy in the neurosciences. The free energy principle is accordingly rephrased, on autopoetic grounds, as follows: all viable organisms attempt to minimize their sensory uncertainty about an unpredictable environment over a temporal horizon. By taking the variation of informational action, we derive neural recognition dynamics (RD), which by construction reduces to the Bayesian filtering of external states from noisy sensory inputs. Consequently, we effectively cast the gradient-descent scheme of minimizing the free energy into Hamiltonian mechanics by addressing only the positions and momenta of the organisms' representations of the causal environment. To demonstrate the utility of our theory, we show how the RD may be implemented in a neuronally based biophysical model at a single-cell level and subsequently in a coarse-grained, hierarchical architecture of the brain. We also present numerical solutions to the RD for a model brain and analyze the perceptual trajectories around attractors in neural state space.

scholarly journals A Measure of Information Available for Prediction

2017 ◽  
Author(s):  
Takuya Isomura
Keyword(s):  
Free Energy ◽  
External World ◽  
Brain State ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Predictive Information ◽  
World State ◽  
Amount Of Information ◽  
The Brain ◽  
Prediction Capability

Mutual information between the brain state and the external world state represents the amount of information stored in the brain that is associated with the external world. On the other hand, surprise of sensory input indicates the unpredictability of the current input. In other words, this is a measure of prediction capability, and an upper bound of surprise is known as free energy. According to the free-energy principle (FEP), the brain continues to minimize free energy to perceive the external world. For animals to survive, prediction capability is considered more important than just memorizing information. In this study, the fact that free energy represents a gap between the amount of information stored in the brain and that available for prediction is established, where the latter will be referred to as predictive information as an analogy with Bialek's predictive information. This concept involves the FEP, the infomax principle, and the predictive information theory, and will be a useful measure to quantify the amount of information available for prediction.

scholarly journals Brain Entropy During Aging Through a Free Energy Principle Approach

2021 ◽  
Vol 15 ◽  
Author(s):  
Filippo Cieri ◽  
Xiaowei Zhuang ◽  
Jessica Z. K. Caldwell ◽  
Dietmar Cordes
Keyword(s):  
Free Energy ◽  
Cognitive Aging ◽  
Dynamic State ◽  
Neural Signals ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Pathological Aging ◽  
Spontaneous Neural Activity ◽  
Brain Entropy ◽  
The Brain

Neural complexity and brain entropy (BEN) have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of “the entropic brain hypothesis.” In this manuscript we propose an extension of this hypothesis to physiological and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging.

scholarly journals Thinking through prior bodies: autonomic uncertainty and interoceptive self-inference

2020 ◽  
Vol 43 ◽  
Author(s):  
Micah Allen ◽  
Nicolas Legrand ◽  
Camile Maria Costa Correa ◽  
Francesca Fardo
Keyword(s):  
Free Energy ◽  
Cognitive Science ◽  
Prior Beliefs ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Bayesian Brain ◽  
Sociocultural Interaction

Abstract The Bayesian brain hypothesis, as formalized by the free-energy principle, is ascendant in cognitive science. But, how does the Bayesian brain obtain prior beliefs? Veissière and colleagues argue that sociocultural interaction is one important source. We offer a complementary model in which “interoceptive self-inference” guides the estimation of expected uncertainty both in ourselves and in our social conspecifics.

Sign in / Sign up

Export Citation Format

Share Document