Neural Annealing

Michael Johnson's prior work on how neural networks (and brains) can be 'annealed' to find optimal states.

Neighborhood — ranked by edge-count

thinker

Michael Edward Johnson
introduces
Author of the vasocomputation paper; researcher at Symmetry Institute (QRI) studying consciousness, active inference, and Buddhist phenomenology.

concept

Vasocomputation
extends
Unifying framework proposing that Buddhist tanha operates through vascular smooth muscle cells as the brain's compression/prediction infrastructure.

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Neural Decodingframework0.810
Neural codeconcept0.807
The model's parameters considered as the actual 'code' implementing its algorithms, as opposed to human-written code.
neural substratesconcept0.807
Brain-based physical implementations of consciousness-related functions, assumed by many ToCs to be exclusive.
Neural Decoding Programframework0.804
Neural Cellular Automataframework0.800
Prior framework combining cellular automata with deep learning, extended by this work
neural cognitionconcept0.791
Cognition in nervous systems, used as a modelling target
Neural Networksconcept0.778
Neural Representation Geometryconcept0.776
The broader conceptual framework that neural activations exhibit non-Euclidean geometric structure causally linked to behavior.