The deep insights of neurobiology have relevance far beyond neurons.

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• Neuroscience and mechanistic interpretability have not yet made enough progress to identify neural correlates marking necessary and sufficient conditions of conscious experience in both brains and neural networks.claim0.798
  Paper explicitly identifies this as a current gap requiring alternative experimental approaches
• Neurons can correspond to interpretable functional roles but interpretations in terms of individual neurons are unlikely to be the most parsimoniousclaim0.782
  Claim from footnote 3, acknowledging neuron-level interpretability while arguing subcomponents are better.
• The huge chemical complexity within each synapse suggests that neural models of cognition that refer only to changing weights of synaptic connections and ignore sub-neural chemistry are probably ignoring some of the most important explanatory mechanisms in brains.claim0.781
  Sloman's critique of mainstream neural network theories.
• In the long run, studying circuit motifs may be more important than studying individual circuits for understanding neural networks.claim0.778
  Strategic claim about the relative importance of motif-level abstraction over circuit-level analysis
• Large parts of the human brain are irrelevant or only weakly relevant to awareness and moral status, suggesting engineering could produce more efficient minds at different scalesclaim0.771
  Supports the mind-scale dimension by noting human brain inefficiency relative to morally relevant properties
• The typical case is that neurons (or other directions in activation space) are understandable after thousands of hours of study, even when initially mysterious.claim0.770
  Author's interpretive assertion based on extensive empirical investigation, countering texture-only skepticism
• The conservation of molecular mechanisms between neural and non-neural bioelectricity is why neuroscience tools work everywhere in the body.claim0.768
  Empirical claim about transferability of methods.
• If sub-neural chemical dynamics are crucial for cognition, then neural models ignoring them will fail to capture key cognitive phenomena.hypothesis0.767
  Sloman's implicit hypothesis behind his critique of synaptic weight-only models.