Direct and inverse solution for a stimulus adaptation problem using SVR

Adapting stimuli to stabilize neural responses is an important problem in the context of cortical prostheses. This paper describes two approaches for stimulus adaptation using support vector regression (SVR). One approach involves the solution of an inverse problem and it is shown that for linear SVR an analytical solution exists. The proposed algorithms are evaluated in conjunction with different preprocessing methods an three datasets recorded from the barrel cortex of anasthesized rats.