Nonlinear functional modeling of scalp recorded auditory evoked responses to maximum length sequences.

The purpose of this study was to model the adult human's scalp recorded evoked response to auditory pulses separated by varying inter pulse intervals (IPIs). The responses modeled probably reflect auditory nerve and brainstem generators. The subjects were 10 young adult humans with normal hearing. They were presented pseudo random sequences of pulses (maximum length sequences, MLSs) in order to characterize their system response. For the stimuli and the responses modeled accounting for temporal nonlinearities (interactions among the pulses) improved model performance only marginally. Nonlinear contributions to the models decreased with increasing interval between the input pulses. Increasing the memory of the model beyond 20 ms did not increase modeled performance dramatically. Model performance varied as a function of minimum IPI (MIPI) of the MLSs. At the shortest MIPI overall model performance deteriorated (due, in part, to a decrease in SNR), but nonlinear effects became relatively more important. At the longest MIPI performance also deteriorated, possibly due to the increasing influence of longer latency, more variable evoked potential components. Modeled performance generalized to responses recorded in the same recording session to the same and different MLSs. This study confirms the similarity between MLS linear kernels and conventionally averaged evoked responses--both are adapted responses reflecting the IPIs of the evoking stimuli.