PLoS Computational Biology
March 1, 2026
Miłosz Danilczuk, Marek Pokropski, Piotr Suffczynski
Integrated Information Theory is a theoretical framework proposing that consciousness is a fundamental property of systems capable of integrating information. To bridge the gap between the theoretical concept and the practical use in actual neurobiological systems, we have applied the Integrated Information Theory approach to a simulated network of integrate and fire neurons (IAF). The primary...
PLoS Computational Biology
February 1, 2026
Tao Xia, Chuan-Peng Hu, Başak Türker et al.
Sleep has traditionally been conceptualized as a state of cognitive disconnection, yet emerging evidence indicates that decision-making capacities persist across sleep stages. Here, we elucidate the computational mechanisms underlying real-time lexical decision-making during polysomnographically-verified sleep, using facial electromyography and hierarchical drift diffusion modeling in both...
PLoS Computational Biology
December 15, 2025
Lingyu Zhang, Weiyang Shi, Ziyang Zhao et al.
Lysergic acid diethylamide (LSD) has shown remarkable potential in modulating brain functional organization and dynamics. However, the exact mechanisms underlying its effects remain unclear. In this study, we employed a data-driven approach to analyze recurrent functional connectivity patterns in resting-state fMRI data and developed a parameterized feedback inhibition model to characterize...
PLoS Computational Biology
October 28, 2025
Fernando Lehue, Carlos Coronel-Oliveros, Vicente Medel et al.
1 citation
Sleep onset is characterized by a departure from arousal, and can be separated into well-differentiated stages: NREM (which encompasses three substages: N1, N2 and N3) and REM (Rapid Eye Movement). Awake brain dynamics are maintained by various wake-promoting mechanisms, particularly the neuromodulators Acetylcholine (ACh) and Noradrenaline (NA), whose levels naturally decrease during the...
PLoS Computational Biology
September 1, 2025
Jordy Peeters, Dimitri de Bundel, Kenno Vanommeslaeghe
The serotonin-2A receptor (5-HT2AR) is an interesting target for drug design in the context of antidepressants that might have a rapid onset of action and/or be effective in treatment-resistant cases. The main challenge, however, is that the activation of this receptor can provoke hallucinations. Recent studies have shown that activating the receptor with certain (partial) agonists could...
PLoS Computational Biology
June 9, 2025
Jessie Rademacher, Tineke Grent-'t-Jong, Davide Rivolta et al.
2 citations
Ketamine, an NMDA receptor (NMDA-R) antagonist, produces psychotomimetic effects when administered in sub-anesthetic dosages. While previous research suggests that Ketamine alters the excitation/inhibition (E/I)-balance in cortical microcircuits, the precise neural mechanisms by which Ketamine produces these effects are not well understood. We analyzed resting-state MEG data from n = 12...
PLoS Computational Biology
June 6, 2025
Wiep Stikvoort, Eider Pérez-Ordoyo, Iván Mindlin et al.
3 citations
Assessing someone's level of consciousness is a complex matter, and attempts have been made to aid clinicians in these assessments through metrics based on neuroimaging data. Many studies have empirically investigated measures related to the complexity elicited after the brain is stimulated to quantify the level of consciousness across different states. Here we hypothesized that the level of...
PLoS Computational Biology
October 1, 2023
Christoffer Lundbak Olesen, Peter Thestrup Waade, Larissa Albantakis et al.
The Free Energy Principle (FEP) and Integrated Information Theory (IIT) are two ambitious theoretical approaches. The first aims to make a formal framework for describing self-organizing and life-like systems in general, and the second attempts a mathematical theory of conscious experience based on the intrinsic properties of a system. They are each concerned with complementary aspects of the...
PLoS Computational Biology
August 2, 2023
Alexander Tscshantz, Beren Millidge, Anil K. Seth et al.
56 citations
Predictive coding is an influential model of cortical neural activity. It proposes that perceptual beliefs are furnished by sequentially minimising "prediction errors"-the differences between predicted and observed data. Implicit in this proposal is the idea that successful perception requires multiple cycles of neural activity. This is at odds with evidence that several aspects of visual...
PLoS Computational Biology
February 1, 2023
Giulio Ruffini, Giada Damiani, Diego Lozano-Soldevilla et al.
28 citations
A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at...
PLoS Computational Biology
July 1, 2022
Michelle J. Redinbaugh, Mohsen Afrasiabi, Jessica M. Phillips et al.
Anesthetic manipulations provide much-needed causal evidence for neural correlates of consciousness, but non-specific drug effects complicate their interpretation. Evidence suggests that thalamic deep brain stimulation (DBS) can either increase or decrease consciousness, depending on the stimulation target and parameters. The putative role of the central lateral thalamus (CL) in consciousness...
PLoS Computational Biology
August 18, 2021
Sourish Chakravarty, Indie C. Garwood, S. Chakravarty et al.
32 citations
Ketamine is an NMDA receptor antagonist commonly used to maintain general anesthesia. At anesthetic doses, ketamine causes high power gamma (25-50 Hz) oscillations alternating with slow-delta (0.1-4 Hz) oscillations. These dynamics are readily observed in local field potentials (LFPs) of non-human primates (NHPs) and electroencephalogram (EEG) recordings from human subjects. However, a detailed...
PLoS Computational Biology
February 1, 2021
Angus Leung, Dror Cohen, Bruno van Swinderen et al.
The physical basis of consciousness remains one of the most elusive concepts in current science. One influential conjecture is that consciousness is to do with some form of causality, measurable through information. The integrated information theory of consciousness (IIT) proposes that conscious experience, filled with rich and specific content, corresponds directly to a hierarchically...
PLoS Computational Biology
September 1, 2018
Francisco J. Esteban, Javier A. Galadí, José A. Langa et al.
Integrated Information Theory (IIT) has become nowadays the most sensible general theory of consciousness. In addition to very important statements, it opens the door for an abstract (mathematical) formulation of the theory. Given a mechanism in a particular state, IIT identifies a conscious experience with a conceptual structure, an informational object which exists, is composed of identified...
PLoS Computational Biology
August 30, 2018
Hyoungkyu Kim, Joon-Young Moon, George A. Mashour et al.
79 citations
Hysteresis, the discrepancy in forward and reverse pathways of state transitions, is observed during changing levels of consciousness. Identifying the underlying mechanism of hysteresis phenomena in the brain will enhance the ability to understand, monitor, and control state transitions related to consciousness. We hypothesized that hysteresis in brain networks shares the same underlying...
PLoS Computational Biology
August 24, 2017
Peter J. Hellyer, Claudia Clopath, Angie A. Kehagia et al.
21 citations
In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic...
PLoS Computational Biology
June 10, 2016
Masafumi Oizumi, Shun-ichi Amari, Toru Yanagawa et al.
Accumulating evidence indicates that the capacity to integrate information in the brain is a prerequisite for consciousness. Integrated Information Theory (IIT) of consciousness provides a mathematical approach to quantifying the information integrated in a system, called integrated information, Φ. Integrated information is defined theoretically as the amount of information a system generates...
PLoS Computational Biology
April 14, 2015
Joon-Young Moon, UnCheol Lee, Stefanie Blain-Moraes et al.
143 citations
The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified. One critical step in elucidating this relationship is the identification of governing principles underlying the directionality of interactions between nodes....
PLoS Computational Biology
October 16, 2014
Srivas Chennu, Paola Finoia, Evelyn Kamau et al.
249 citations
Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness,...
PLoS Computational Biology
January 20, 2011
Adam B. Barrett, Anil K. Seth
243 citations
A recent measure of 'integrated information', Φ(DM), quantifies the extent to which a system generates more information than the sum of its parts as it transitions between states, possibly reflecting levels of consciousness generated by neural systems. However, Φ(DM) is defined only for discrete Markov systems, which are unusual in biology; as a result, Φ(DM) can rarely be measured in practice....
PLoS Computational Biology
August 13, 2009
David Balduzzi, Giulio Tononi
272 citations
According to the integrated information theory, the quantity of consciousness is the amount of integrated information generated by a complex of elements, and the quality of experience is specified by the informational relationships it generates. This paper outlines a framework for characterizing the informational relationships generated by such systems. Qualia space (Q) is a space having an...
PLoS Computational Biology
October 1, 2008
Anandamohan Ghosh, Y Rho, A R McIntosh et al.
Traditionally brain function is studied through measuring physiological responses in controlled sensory, motor, and cognitive paradigms. However, even at rest, in the absence of overt goal-directed behavior, collections of cortical regions consistently show temporally coherent activity. In humans, these resting state networks have been shown to greatly overlap with functional architectures...
PLoS Computational Biology
June 12, 2008
David Balduzzi, Giulio Tononi
433 citations
This paper introduces a time- and state-dependent measure of integrated information, phi, which captures the repertoire of causal states available to a system as a whole. Specifically, phi quantifies how much information is generated (uncertainty is reduced) when a system enters a particular state through causal interactions among its elements, above and beyond the information generated...
PLoS Computational Biology
November 7, 2007
Marco Loh, Edmund T Rolls, Gustavo Deco
172 citations
We propose a top-down approach to the symptoms of schizophrenia based on a statistical dynamical framework. We show that a reduced depth in the basins of attraction of cortical attractor states destabilizes the activity at the network level due to the constant statistical fluctuations caused by the stochastic spiking of neurons. In integrate-and-fire network simulations, a decrease in the NMDA...