OBJECTIVE: We describe q-sequence deconvolution (QSD), a new data acquisition/analysis method for evoked-responses that solves the problem of waveform distortion at high stimulus repetition-rates, due to response overlap. QSD can increase the sensitivity of clinically useful evoked-responses because it is well known that high stimulus repetition-rates are better for detecting pathophysiology. METHODS: QSD is applicable to a variety of experimental conditions. Because some QSD-parameters must be chosen by the experimenter, the underlying principles and assumptions of the method are described in detail. The theoretical and mathematical bases of the QSD method are also described, including some equivalent computational formulations. RESULTS: QSD was applied to recordings of the human auditory brainstem response (ABR) at stimulus repetition-rates that overlapped the responses. The transient ABR was recovered at all rates tested (highest 160/s), and showed systematic changes with stimulus repetition-rate within a single subject. CONCLUSIONS: QSD offers a new method of recovering brain evoked-response activity having a duration longer than the time between stimuli. SIGNIFICANCE: The use of this new technique for analysis of evoked responses will permit examination of brain activation patterns across a broad range of stimulus repetition-rates, some never before studied. Such studies will improve the sensitivity of evoked-responses for the detection of brain pathophysiology. New measures of brain activity may be discovered using QSD. The method also permits the recovery of the transient brain waveforms that overlap to form 'steady-state' waveforms. An additional benefit of the QSD method is that repetition-rate can be isolated as a variable, independent of other stimulus characteristics, even if the response is a nonlinear function of rate.
OBJECTIVE: We describe q-sequence deconvolution (QSD), a new data acquisition/analysis method for evoked-responses that solves the problem of waveform distortion at high stimulus repetition-rates, due to response overlap. QSD can increase the sensitivity of clinically useful evoked-responses because it is well known that high stimulus repetition-rates are better for detecting pathophysiology. METHODS:QSD is applicable to a variety of experimental conditions. Because some QSD-parameters must be chosen by the experimenter, the underlying principles and assumptions of the method are described in detail. The theoretical and mathematical bases of the QSD method are also described, including some equivalent computational formulations. RESULTS:QSD was applied to recordings of the human auditory brainstem response (ABR) at stimulus repetition-rates that overlapped the responses. The transient ABR was recovered at all rates tested (highest 160/s), and showed systematic changes with stimulus repetition-rate within a single subject. CONCLUSIONS:QSD offers a new method of recovering brain evoked-response activity having a duration longer than the time between stimuli. SIGNIFICANCE: The use of this new technique for analysis of evoked responses will permit examination of brain activation patterns across a broad range of stimulus repetition-rates, some never before studied. Such studies will improve the sensitivity of evoked-responses for the detection of brain pathophysiology. New measures of brain activity may be discovered using QSD. The method also permits the recovery of the transient brain waveforms that overlap to form 'steady-state' waveforms. An additional benefit of the QSD method is that repetition-rate can be isolated as a variable, independent of other stimulus characteristics, even if the response is a nonlinear function of rate.