Computation for the implicit components of ERP in attention.
EEG reveals brain functions with high temporal resolution. Yet, multiple implicit variables may be involved in limited ERP measures. Special computation techniques are needed to recover these parameters. In the study of attention, we can obtain the ERP in attended (V) and unattended (U) conditions. Usually, the effect of attention is computed as the difference (D) between V and U with the assumption that D and U are independent. Yet, they should be related. Treating V as a function of U, a linear model V = W + GU is assumed, where W and G are implicit in the ERP measures. G is the gain control on the unattended function. Provided G and W are constant over a local brain region, we can use the Total Least Square (TLS) algorithm to compute their values. In the experiment, participants attended to one side of a fixed point, and stimulus of circular checkerboard was flashed either to the attended or the unattended side. The values of W and G as functions of V and U were computed showing that multiple implicit variables are involved in attention. The gain amplification (G) is found to be greater than 1 before 200 msec and much less than 1 afterwards. The values of G and W may shed light on the nature of attention.