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George Blackburne

@rhizoqualia.bsky.social
610 followers 246 following 14 posts

Trying to understand how brains store, transmit, and transform information across scales @ucl @imperialcollege gblackburne.github.io

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George Blackburne @rhizoqualia.bsky.social · 11h
Tour de force of lovely stuff from Andrea and co here
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George Blackburne @rhizoqualia.bsky.social · 21/09/2026
Interested in understanding collective information structures in complex dynamical systems like the brain? But don't know how to quantify them? We got you covered! Now out in Cell Reports Phys @cp-cellrepphyssci.bsky.social:
cell.com
A scalable estimator of higher-order information in complex dynamical systems
Liardi et al. introduce M-information, a scalable information-theoretic measure of higher-order dependencies in complex dynamical systems, addressing a long-standing computational bottleneck. M-inform...
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George Blackburne @rhizoqualia.bsky.social · 17/09/2026
Huge congrats Anil and all for this mammoth collection on the possibility of artificial consciousness! Cant wait to read it in its full bloom. You can read our comment on how 'compatibilist emergence', and a taxonomy of its facets, may clarify the relation between subjectivity and substrate here:
doi.org
Compatibilist emergence for the science of consciousness | Behavioral and Brain Sciences | Cambridge Core
Compatibilist emergence for the science of consciousness - Volume 49
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George Blackburne @rhizoqualia.bsky.social · 09/09/2026
The neuroscience of consciousness often feels like imperialist geography; theories laying claim a universally privileged terrain in the brain, as the seat of subjective experience. We provide evidence from >500 neuroimaging studies for a distributed, decentred, and context-sensitive alternative:
biorxiv.org
What is it like to be a blob? A distributed, decentred and context-sensitive neurobiology of consciousness
Consciousness is often studied by asking whether particular brain regions or systems are privileged. We tested a distributed, decentred and context-sensitive alternative using 579 consciousness-focuse...
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Reposted by George Blackburne
bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 09/09/2026
What is it like to be a blob? A distributed, decentred and context-sensitive neurobiology of consciousness www.biorxiv.org/content/10.64898/20…
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George Blackburne @rhizoqualia.bsky.social · 17/08/2026
Small piece in @natmentalhealth.nature.com, calling for greater recognition in the cognitive and computational neurosciences of how weird ligand-receptor interactions are - with @alexpiot.bsky.social, Sunjeev Kamboj and Ravi Das www.nature.com/articles/s44...
nature.com
Embracing pharmacological complexity - Nature Mental Health
Nature Mental Health - Embracing pharmacological complexity
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Reposted by George Blackburne
Keenan Down @keenandown.bsky.social · 11/03/2026
Ready for the biggest review into Partial Information Decomposition ever? We've gone through the literature and collected every PID measure and property we could find and filled in the gaps! Thanks to Alberto Liardi for his superhuman work here! Check it out below! 👇 arxiv.org/abs/2603.06678
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Reposted by George Blackburne
Fernando Rosas @frosas.bsky.social · 20/08/2025
Response to @anilseth.bsky.social great piece “Conscious artificial intelligence and biological naturalism” www.cambridge.org/core/journal... Thanks to the great team lead by the awesome @rhizoqualia.bsky.social!
cambridge.org
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Reposted by George Blackburne
Fernando Rosas @frosas.bsky.social · 20/08/2025
Preprint time: “Compatibilist emergence for the science of consciousness” osf.io/preprints/ps... On how a multifaceted understanding of emergence can illuminate the link between consciousness and life!
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Reposted by George Blackburne
Fernando Rosas @frosas.bsky.social · 24/06/2025
Preprint time: “A scalable estimator of high-order information in complex dynamical systems” arxiv.org/abs/2506.18498 A principled and scalable approach to measure high-order effects in time series data, generalising BROJA for multiple-input multiple-output settings!
arxiv.org
A scalable estimator of high-order information in complex dynamical systems
Our understanding of neural systems rests on our ability to characterise how they perform distributed computation and integrate information. Advances in information theory have introduced several quan...
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