  Determining how much of the sensory information carried by a neural code
contributes to behavioral performance is key to understand sensory function and
neural information flow. However, there are as yet no analytical tools to
compute this information that lies at the intersection between sensory coding
and behavioral readout. Here we develop a novel measure, termed the
information-theoretic intersection information $I_{II}(S;R;C)$, that quantifies
how much of the sensory information carried by a neural response R is used for
behavior during perceptual discrimination tasks. Building on the Partial
Information Decomposition framework, we define $I_{II}(S;R;C)$ as the part of
the mutual information between the stimulus S and the response R that also
informs the consequent behavioral choice C. We compute $I_{II}(S;R;C)$ in the
analysis of two experimental cortical datasets, to show how this measure can be
used to compare quantitatively the contributions of spike timing and spike
rates to task performance, and to identify brain areas or neural populations
that specifically transform sensory information into choice.
