The Free Energy Principle (FEP) offers a physically grounded account of intentional properties in mind and life, framed in the context of Dynamical Systems Theory. Because of this generality, it was proposed as a formal basis to formalize the study of biological autonomy, autopoiesis, and enactive cognition. Yet, those approaches are centered by definition on describing how biological and...
We develop a theoretical proposal linking vacuum stability and brain dynamics through superconductivity-inspired coherence, symmetry reduction, and the thermodynamic stabilization of low-entropy regimes. We take an unbroken SU(3) structure as a candidate stable residue of the low-temperature vacuum. At the neural level, we formulate a coarse-grained analog in which a two-fluid model with...
EntropyMarch 12, 2026Erik Stänicke, Bendik Sparre Hovet, Line Indrevoll Stänicke
The recent paradigm shift within cognitive neuroscience toward predictive processing appears to align with many psychoanalytic conceptualizations of the mind. In this article, we argue that several psychoanalytic concepts, such as projection, transference, wish-fulfillment, and perceptual identity, are particularly compatible with the current neuroscientific conception of the brain as a...
The Free Energy Principle (FEP) and Active Inference provide a unifying variational framework for modelling perception, action, learning, and self-organisation across biological systems. While highly successful at explaining how systems maintain organisation under uncertainty, these frameworks remain explicitly neutral with respect to a foundational question: why there is experience at all....
The measurement problem in quantum mechanics (QM) is related to the inability to include learning about the properties of a quantum system by an agent in the formalism of quantum theory. It includes questions about the physical processes behind the measurement, uniqueness, and randomness of obtained outcomes and an ontic or epistemic role of the state. These issues have triggered various...
Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating...
Many studies on memory emphasize the material substrate and mechanisms by which data can be stored and reliably read out. Here, I focus on complementary aspects: the need for agents to dynamically reinterpret and modify memories to suit their ever-changing selves and environment. Using examples from developmental biology, evolution, and synthetic bioengineering, in addition to neuroscience, I...
We explore the intersection of neural dynamics and the effects of psychedelics in light of distinct timescales in a framework integrating concepts from dynamics, complexity, and plasticity. We call this framework neural geometrodynamics for its parallels with general relativity’s description of the interplay of spacetime and matter. The geometry of trajectories within the dynamical landscape of...
EntropySeptember 30, 2023Günter Schiepek, Tatjana Marinell, Wolfgang Aichhorn et al.
Compared to the extensive evidence of the effectiveness of mindfulness-based interventions, there is only a limited understanding of their mechanisms of change. The three aims of this study are (1) to identify features of self-organization during the process (e.g., pattern transitions), (2) to obtain an impression of the effects of continuous self-assessments and feedback sessions on...
The principle of mental gravity contends that the mind uses physical gravity as a mental model or simulacrum to express the relation between the inner self and the outer world in terms of "UP"-ness and "DOWN"-ness. The simulation of increased gravity characterises a continuum of mental gravity which states includes depression as the paradigmatic example of being down, low, heavy, and slow. The...
Time delays are a signature of many physical systems, including the brain, and considerably shape their dynamics; moreover, they play a key role in consciousness, as postulated by the temporo-spatial theory of consciousness (TTC). However, they are often not known a priori and need to be estimated from time series. In this study, we propose the use of permutation entropy (PE) to estimate time...
Time and space are fundamental elements that permeate the fabric of nature, and their significance in relation to neural activity and consciousness remains a compelling yet unexplored area of research. The Temporospatial Theory of Consciousness (TTC) provides a framework that links time, space, neural activity, and consciousness, shedding light on the intricate relationships among these...
Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of consciousness (called a complex), which are then used to formulate a mathematical framework for assessing both the quality and quantity of experience. The...
Cognition, historically considered uniquely human capacity, has been recently found to be the ability of all living organisms, from single cells and up. This study approaches cognition from an info-computational stance, in which structures in nature are seen as information, and processes (information dynamics) are seen as computation, from the perspective of a cognizing agent. Cognition is...
Time is a key element of consciousness as it includes multiple timescales from shorter to longer ones. This is reflected in our experience of various short-term phenomenal contents at discrete points in time as part of an ongoing, more continuous, and long-term 'stream of consciousness'. Can Integrated Information Theory (IIT) account for this multitude of timescales of consciousness? According...
We examine the theoretical implications of empirical studies developed over recent years. These experiments have explored the biosemiotic nature of communication streams from emotional neuroscience and embodied mind perspectives. Information combinatorics analysis enabled a deeper understanding of the coupling and decoupling dynamics of biosemiotics streams. We investigated intraindividual and...
The Integrated Information Theory (IIT) of consciousness starts from essential phenomenological properties, which are then translated into postulates that any physical system must satisfy in order to specify the physical substrate of consciousness. We recently introduced an information measure (Barbosa et al., 2020) that captures three postulates of IIT-existence, intrinsicality and...
Consciousness is a central issue in neuroscience, however, we still lack a formal framework that can address the nature of the relationship between consciousness and its physical substrates. In this review, we provide a novel mathematical framework of category theory (CT), in which we can define and study the sameness between different domains of phenomena such as consciousness and its neural...
There must be a reason why an experience feels the way it does. A good place to begin addressing this question is spatial experience, because it may be more penetrable by introspection than other qualities of consciousness such as color or pain. Moreover, much of experience is spatial, from that of our body to the visual world, which appears as if painted on an extended canvas in front of our...
Integrated information theory (IIT) describes consciousness as information integrated across highly differentiated but irreducible constituent parts in a system. However, in a complex dynamic system such as the brain, the optimal conditions for large integrated information systems have not been elucidated. In this study, we hypothesized that network criticality, a balanced state between a large...
With the aim of further advancing the understanding of the human brain’s functional connectivity, we propose a network metric which we term the geodesic entropy. This metric quantifies the Shannon entropy of the distance distribution to a specific node from all other nodes. It allows to characterize the influence exerted on a specific node considering statistics of the overall network...
Interaction Information (II) generalizes the univariate Shannon entropy to triplets of variables, allowing the detection of redundant (R) or synergetic (S) interactions in dynamical networks. Here, we calculated II from functional magnetic resonance imaging data and asked whether R or S vary across brain regions and along lifespan. Preserved along lifespan, we found high overlapping between the...
Theoretical consideration predicts that the alteration of local and shared information in the brain is a key element in the mechanism of anesthetic-induced unconsciousness. Ordinal pattern analysis, such as permutation entropy (PE) and symbolic mutual information (SMI), have been successful in quantifying local and shared information in neurophysiological data; however, they have been rarely...
The paper introduces the notion of “metacomputable” processes as those which are the product of computable processes. This notion seems interesting in the instance when metacomputable processes may not be computable themselves, but are produced by computable ones. The notion of computability used here relies on Turing computability. When we talk about something being non-computable, this can be...
EntropyJune 9, 2017G. Pezzulo, Francesco Donnarumma, P. Iodice et al.
There is an on-going debate in cognitive (neuro) science and philosophy between classical cognitive theory and embodied, embedded, extended, and enactive (“4-Es”) views of cognition—a family of theories that emphasize the role of the body in cognition and the importance of brain-body-environment interaction over and above internal representation. This debate touches foundational issues, such as...