Subjective experience can be objectively explained in physical terms by moving beyond cognitive functions and understanding how experience is structured. Integrated information theory provides a framework to account for both the essential properties of every experience and the specific properties that make particular experiences feel the way they do, avoiding the fallacy that only objective properties should be explained by science.
A grid-like neural network representing posterior cortical areas can perform the same fixation function as a map-like pretectal circuit, but only the grid-like network's cause-effect structure, as analyzed by Integrated Information Theory, accounts for the subjective experience of space as extended. Standard functional analysis explains what the model does—encoding, decoding, and triggering eye movements—but cannot explain why a human fixating a stimulus would also see it at a location. The map-like network, lacking lateral connections, is functionally equivalent yet cannot account for the phenomenal properties of space.