Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem
Fig 7
Relating brain data dRDMs to phone model dRDMs and converting to feature fits.
(a) At each vertex and time point, all phone model RDMs are computed (Fig 6) and fitted against the data RDM in a GLM, yielding coefficients βϕ. (b) The rows of the phone-feature matrix of Fig 3 describe for each feature f the phones ϕ exhibiting f, providing a labelling function χf. The example given here is for the feature sonorant, the top row of the feature matrix in Fig 3. (c) The coefficients βϕ were aggregated by sum over each feature f to produce a map of fit for each feature, which was mapped back to the central location of the spatiotemporal searchlight.