finding
active
finding:in-aomic-piop2-resting-state-fmri-data-nis-finds-a-seven-dimensional-macro-state-with-widely-distributed-attributionsIn AOMIC PIOP2 resting-state fMRI data, NIS+ finds a seven-dimensional macro-state with widely distributed attributions.
Contrast to movie-watching condition, showing context-dependent emergence.
Source paper
extracted_from(2023) · Bing Yuan · Jiang Zhang · Aobo Lyu · Jiayun Wu +5
Neighborhood — ranked by edge-count
Communities (3)
community
- Causal emergence in biological systemsmembers_ofExamines how macro-scale causal power exceeds micro-scale in living and learning systems.
- Causal emergence in learning agentsmembers_ofUses effective information (EI) and coarse-graining to link causal emergence with RL and biological learning.
- Framework using effective information (EI) and NIS+ to automatically discover macro-scale dynamics from micro-level data, validated on fMRI, Conway's Game of Life, and SIR models.
Findings (1)
finding
- In AOMIC ID1000 movie-watching fMRI data, NIS+ finds a one-dimensional macro-state representing 100-dimensional micro-states.associated_withReal brain imaging result suggesting a compressed emergent representation.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
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