ArticleEntropy (Basel, Switzerland)2018
Efficient Algorithms for Searching the Minimum Information Partition in Integrated Information Theory.
Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Electrophysiological Signatures of Visual Sensations Elicited by Direct Electrical Stimulation.Neuroscience bulletin · 2025Article
- Association of Bidirectional Network Cores in the Brain with Perceptual Awareness and Cognition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Association of bidirectional network cores in the brain with perceptual awareness and cognition.bioRxiv : the preprint server for biology · 2025Article
- Meta-representations as representations of processes.Neuroscience of consciousness · 2025Article
- Article
- Integrated information theory reveals the potential role of the posterior parietal cortex in sustaining conditioning responses in classical conditioning tasks.Frontiers in neuroscience · 2025Article
- Information structure of heterogeneous criticality in a fish school.Scientific reports · 2024Article
- Information-Theoretic Approaches in EEG Correlates of Auditory Perceptual Awareness under Informational Masking.Biology · 2023Article
- Non-Separability of Physical Systems as a Foundation of Consciousness.Entropy (Basel, Switzerland) · 2022Article
- The ambiguous feeling between "mine" and "not-mine" measured by integrated information theory during rubber hand illusion.Scientific reports · 2022Article
- Different Approximation Methods for Calculation of Integrated Information Coefficient in the Brain during Instrumental Learning.Brain sciences · 2022Article
- Self-organized criticality as a framework for consciousness: A review study.Frontiers in psychology · 2022Article
- Integrated information structure collapses with anesthetic loss of conscious arousal in Drosophila melanogaster.PLoS computational biology · 2021Article
- Whole-Brain Models to Explore Altered States of Consciousness from the Bottom Up.Brain sciences · 2020Review
- Evaluating Approximations and Heuristic Measures of Integrated Information.Entropy (Basel, Switzerland) · 2019Article
- Dynamic Computation in Visual Thalamocortical Networks.Entropy (Basel, Switzerland) · 2019Review
- Exclusion and Underdetermined Qualia.Entropy (Basel, Switzerland) · 2019Article
- Integrated Information as a Measure of Cognitive Processes in Coupled Genetic Repressilators.Entropy (Basel, Switzerland) · 2019Article
- Information integration in large brain networks.PLoS computational biology · 2019Article
- Information Theory in Neuroscience.Entropy (Basel, Switzerland) · 2019Article
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3 authors.
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Abstract
The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ( Φ ) in the brain is related to the level of consciousness. IIT proposes that, to quantify information integration in a system as a whole, integrated information should be measured across the partition of the system at which information loss caused by partitioning is minimized, called the Minimum Information Partition (MIP). The computational cost for exhaustively searching for the MIP grows exponentially with system size, making it difficult to apply IIT to real neural data. It has been previously shown that, if a measure of Φ satisfies a mathematical property, submodularity, the MIP can be found in a polynomial order by an optimization algorithm. However, although the first version of Φ is submodular, the later versions are not. In this study, we empirically explore to what extent the algorithm can be applied to the non-submodular measures of Φ by evaluating the accuracy of the algorithm in simulated data and real neural data. We find that the algorithm identifies the MIP in a nearly perfect manner even for the non-submodular measures. Our results show that the algorithm allows us to measure Φ in large systems within a practical amount of time.
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