University of Oxford Podcasts

Moving beyond integration and differentiation in measures of neural dynamics

Pedro Mediano develops information-theoretic ways to distinguish redundancy and synergy when describing neural dynamics.

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University of Oxford Podcasts Pedro Mediano advanced 24 min

Why it is here

Use after an introductory theory discussion to ask what a proposed numerical measure actually captures.

Selection basis: editorial selection. Reason checked 2026-11-07 by agent.

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1024-byte range from the officially listed MP4, HTTP 206, matching content range and MP4 header. No full playback or decoding; YouTube availability is unknown.

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2026-11-07
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Editorial estimate from the inspected scope: Full episode abstract inspected: limitations of integration/differentiation measures, O-information and a decomposition of information dynamics. The source does not provide a formal prerequisite list; this is a navigation aid, not a provider-issued classification.
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Provenance and reuse

University of Oxford Podcasts; original source https://podcasts.ox.ac.uk/index.php/pedro-mediano-moving-beyond-integration-and-differentiation-measures-neural-dynamics. Default copyright restrictions; two Models of Consciousness episodes explicitly CC BY-NC-SA 2.0 UK. Seth episode did not show that licence.. Links, factual metadata and original navigation annotations only. No source page, transcript, image, video or restricted platform metadata is included in the reusable export.

  1. providers-core-79327c8a02db-source

    Full episode abstract inspected: limitations of integration/differentiation measures, O-information and a decomposition of information dynamics. Retrieved 2026-11-07.

  2. providers-media-89075282a203a66e

    Officially linked MP4: HTTP 206 and 1024 bytes with a verified MP4 file header; no playback or complete-file inspection. Retrieved 2026-11-07.

  3. providers-source-53eb7707a80d264c

    Episode description, speaker, duration, date-added and individual licence inspected. Retrieved 2026-11-07.

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