Entropy
November 27, 2019
Andrew M. Haun, Giulio Tononi
158 citations
Experience feels the way it does for a reason, and spatial experience offers a promising starting point for investigation because it is more accessible to introspection than qualities like color or pain. Much of experience is spatial, from bodily sensations to the visual world, which appears as an extended canvas. To feel extended, this canvas must consist of countless spots related through connection, fusion, and inclusion, with each spot having a location, size, boundary, and distance from others. The authors propose an account based on integrated information theory (IIT), showing that a simulated grid-like network of units yields a cause-effect structure that explains main properties of spatial experience. This suggests spatial experience is supported by brain areas with grid-like connectivity, and changes in connectivity should warp experienced space.
Entropy
March 18, 2021
Leonardo S. Barbosa, William Marshall, Larissa Albantakis et al.
74 citations
Integrated Information Theory (IIT) begins with essential properties of consciousness and translates them into postulates that any physical system must satisfy to specify the physical substrate of consciousness. A recently introduced information measure captures three of these postulates—existence, intrinsicality, and information—and is unique. This work shows that the measure also satisfies the remaining postulates of integration and exclusion, creating a framework that identifies maximally irreducible mechanisms. These mechanisms can form maximally irreducible systems, which then specify the physical substrate of conscious experience.
Entropy
February 13, 2022
Georg Northoff, Federico Zilio
47 citations
Consciousness operates across multiple timescales, from brief moments to an ongoing 'stream of consciousness'. Integrated Information Theory (IIT) currently places experience at short timescales of 100–300 ms (theta and alpha frequencies), which explains how single inputs become unified phenomenal content. However, this does not address how specific contents relate to one another over time. By integrating IIT with the Temporo-spatial Theory of Consciousness (TTC), which assumes a multitude of timescales, the authors propose that pre-stimulus activity non-additively interacts with input, expanding its temporal features into longer timescales (delta and slower frequencies). This temporo-spatial expansion embeds short-term content within the ongoing stream of consciousness, suggesting that both short and long timescales are needed to account for conscious experience.
Entropy
November 10, 2022
Gordana Dodig-Crnkovic
40 citations
Cognition is not unique to humans but is a property of all living organisms, from single cells upward. Viewed through an info-computational lens, structures in nature are information and their dynamics are computation from an agent's perspective. Cognition arises from networks of morphological and morphogenetic computations driven by self-assembly, self-organization, and autopoiesis. This article critiques the prevailing human-centric view of cognition, which faces unresolved problems, and reviews recent work on morphological computation, agency, basal cognition, and the free energy principle. It argues that older computational models, based on abstract symbol processing, ignored physical constraints and embodiment. Better understanding cognition is crucial for advancing artificial intelligence, robotics, and medicine.
Entropy
January 30, 2019
Aline Viol, Fernanda Palhano-Fontes, Heloisa Onias et al.
37 citations
A new network metric, geodesic entropy, measures the Shannon entropy of distances from one node to all others in a network, characterizing how much influence a node has based on the overall network structure. Applied to resting-state functional brain networks of humans, the metric differentiates ordinary consciousness from the altered state induced by Ayahuasca ingestion. On average, functional networks from subjects in the altered state show larger geodesic entropy than those in the ordinary state, suggesting the metric can reveal differences in brain network organization across states of consciousness.
Entropy
May 31, 2024
Michael Levin
31 citations
Memory is often studied for its ability to store and retrieve information faithfully, but this work argues that a more fundamental function is dynamically reinterpreting and modifying memories to fit an agent's changing self and environment. Drawing on examples from developmental biology, evolution, synthetic bioengineering, and neuroscience, the author proposes that memory preserves salience—what is relevant—rather than fidelity. This perspective applies across scales from cells to societies. The author suggests that continuous creative confabulation, from molecular to behavioral levels, resolves the persistence paradox for individuals and lineages. A processual view of life and mind implies that memories, as patterns in cognitive systems, can act as active agents in sense-making, supporting a view of life as nested perspectives engaged in polycomputation.
Entropy
February 11, 2023
William Marshall, Matteo Grasso, William G. P. Mayner et al.
19 citations
Integrated information theory (IIT) proposes that consciousness is identical to the cause-effect structure generated by a maximally irreducible substrate (a Φ-structure). This work introduces a definition for system-integrated information (φs) grounded in IIT's postulates of existence, intrinsicality, information, and integration. It examines how determinism, degeneracy, and connectivity fault lines affect system-integrated information. The proposed measure identifies complexes as systems whose φs exceeds that of any overlapping candidate systems.
Entropy
January 22, 2024
Giulio Ruffini, Edmundo Lopez-Sola, Jakub Vohryzek et al.
15 citations
A framework called neural geometrodynamics, inspired by general relativity, describes how neural dynamics unfold at three timescales: fast (momentary activity), slow (synaptic plasticity), and ultraslow (metaplasticity). Psychedelics flatten the neural landscape, increasing entropy and complexity of fast dynamics, which disrupts functional integration. This destabilization counteracts pathological, rigid neural patterns by promoting fluid, adaptable states. The plasticity-enhancing effects of psychedelics amplify this shift, leading to acute systemic disorder and potentially longer-lasting increases in complexity that affect both short-term dynamics and long-term plastic processes, offering a holistic view of psychedelics' acute and lasting impacts.
Entropy
November 6, 2024
Giulio Ruffini, Francesca Castaldo, Edmundo Lopez-Sola et al.
10 citations
Major Depressive Disorder (MDD) is a complex condition that computational neuropsychiatry can help model mechanistically. Using the Kolmogorov theory of consciousness, a model was developed in which algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression—defined as persistently low valence—may arise from inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. The model maps to brain circuits and functional networks, linking with depression biotypes. Brain stimulation, psychotherapy, and psychedelics may synergistically repair neural circuits, with therapies optimized using personalized computational models.
Entropy
March 12, 2026
Erik Stänicke, Bendik Sparre Hovet, Line Indrevoll Stänicke
The brain's predictive processing framework, which views the brain as a prediction machine, aligns with several psychoanalytic concepts including projection, transference, wish-fulfillment, and perceptual identity. Projection in psychoanalysis is closely analogous to prediction in cognitive neuroscience, both serving to shape subjective experience and cognitive functions. The article discusses how homeostasis relates to both fields and draws parallels between insight and surprise. Limitations in equating projection with prediction are acknowledged, but integrating these frameworks may allow subjectivity to be studied scientifically.
Entropy
March 9, 2026
Jason Clarke
The Free Energy Principle and Active Inference explain how biological systems maintain organization under uncertainty but remain neutral on why there is experience at all. The Awareness-First Theory inverts the usual explanatory order by starting from the givenness of awareness itself and asking what must be the case for any world to appear coherently. This requirement is formalized as a Coherence Principle, expressed as a variational stationarity condition δA=0, which specifies the invariance of coherent awareness across changing appearances. Familiar variational principles like free-energy minimization (δF=0) and stationary-action physics (δS=0) can be understood as restricted projections of this parent constraint.
Entropy
November 25, 2021
F. Orsucci
Human interactions involve hybrid dynamics that combine biological and semiotic communication streams. Recent empirical studies analyzed intraindividual and interpersonal relations as coevolution processes of coupling, synchronization, and desynchronization. Using cluster analysis and Markov chains, evidence emerged of chimaera states and phase transitions in these dynamics. A probabilistic, nondeterministic approach helped clarify the properties of these hybrid interactions. The findings suggest that multidimensional theoretical models can represent the complex, hybrid nature of human interactions, integrating insights from emotional neuroscience and embodied mind perspectives.
Entropy
December 1, 2019
G. Northoff, Naotsugu Tsuchiya, H. Saigo
A mathematical framework called category theory (CT) can formally define and study the relationship between consciousness and its neural substrates. CT uses concepts such as category, inclusion functor, expansion functor, and natural transformation, each mapped to specific features in the neural correlates of consciousness (NCC). Applying CT to integrated information theory (IIT) and the temporospatial theory of consciousness (TTC) shows that natural transformation reveals the need to go beyond NCC and raises questions that any future neuroscientific theory of consciousness must address.
Entropy
October 11, 2019
Hyoungkyu Kim, UnCheol Lee
Integrated information theory (IIT) holds that consciousness arises from information that is both highly differentiated and integrated across a system's parts. Using a large-scale brain network model and high-density EEG recordings from people under general anesthesia, this work found that network criticality—a balance between flexible functional configurations and structural constraints—coincides with maximal integrated information (Φ). As consciousness diminished, both criticality and Φ decreased. The conscious resting state showed the largest Φ and criticality, while the balance between variation and constraint broke down as behavioral responsiveness declined. The findings suggest network criticality is a necessary condition for large integrated information in the human brain.
Entropy
July 10, 2018
Heonsoo Lee, Zirui Huang, Xiaolin Liu et al.
Permutation entropy (PE) and symbolic mutual information (SMI) analysis of fMRI data from 15 healthy participants under propofol sedation reveals that anesthesia differentially affects local and shared brain information. Global PE decreased from wakefulness to deep (unconscious) sedation and increased upon recovery, with greater reduction in subcortical than cortical networks. SMI's spatial pattern (topographic structure) reconfigures during unconsciousness, and the positive correlation between PE and SMI seen in conscious states is disrupted in deep sedation. PE changes preferentially occur in highly connected hub regions. These results suggest that altered local and shared information exchange is a mechanistic indicator of anesthetic-induced unconsciousness.
Entropy
September 19, 2010
Paul Cobley
Cybersemiotics proposes a new philosophy of science that addresses the failure of existing disciplines to account for qualia and motivation, challenges the computational information-processing view of knowing, and examines the role of the observer. This article argues that the constructivist basis of 'languaging' within cybersemiotics presents a potential impediment. It contends that the central issue for cybersemiotics is the process of 'modelling' in biosemiotics, not language itself. The author argues that future biosemiotics research will benefit from a clearer understanding of 'observership' and that the relationship between constructivism and realism must be clarified, with tools available from general semiotics.
Entropy
August 16, 2010
Søren Brier
Cybersemiotics is distinguished from other transdisciplinary theories of information, cognition, and communication by its absolute naturalism, which treats life, consciousness, and cultural meaning as parts of nature and evolution. It opposes orthodoxies that exclude experiential life, meaning, or first-person consciousness, including physico-chemical science, biological evolution without meaning, linguistic-cultural constructivism without empirical truth, and subject-object dualism. The synthesis integrates second-order cybernetics and autopoiesis (via Luhmann's triple autopoietic system theory) with Peircean phaneroscopic, triadic, pragmaticistic, evolutionary semiotics. Information theory and self-organizing emergent phenomena are inserted into the Peircean framework, making evolutionary experiential and intersubjective sign processes the ground reality, with no scientific or humanistic perspective considered more fundamental.