Event TabNeuroMatic analysis software for detecting spontaneous events. This page describes the thresholdbelowbaseline (or thresholdabovebaseline) detector similar to that described by Kudoh and Taguchi 2002. Threshold < Baseline. A forward slidingwindow search for the first data point that falls below level y at dt msec after t_{0} (negative events, see image below) or falls above level y at dt msec after t_{0} (positive events, threshold > baseline). This algorithm is similar to that of Kudoh and Taguchi 2002 except for the use of a baseline average (avg) window centered at t_{0} rather than a single baseline point at t_{0}. avg = baseline average window size Y_{avg} = baseline average yvalue y = Y_{avg}  threshold (threshold < baseline, negative events) y = Y_{avg} + threshold (threshold > baseline, positive events) t_{0} = baseline window midwaytimepoint (slides forward during event detection) dt = event detection window beginning at t_{0} t_{event} = ythresholdcrossing event time (t_{0} + dt) There are two baseline parameters, avg and dt. Baseline avg specifies the baseline average window size (orange line). Baseline dt specifies the time after the baseline midwaytimepoint to search for an event; this parameter is equivalent to wi of Kudoh and Taguchi 2002. Previously avg and dt were set equal, but now you have the option to specify a larger dt without increasing the baseline window. If you do not wish to use a baseline window, set avg = 0.
Event Onset Search. This is an optional search creteria for the onset of an event once the event has been detected. If no onset is found, the event is ignored and the search for events continues. If you do not wish to use this onset criteria for limiting what is considered an acceptable event, uncheck the onset checkbox. The onset search is a backward slidingwindow search from t_{event} for the first occurrence of the rightmost window point falling above level y (negative events, see image below) or below level y (positive events). Note, this algorithm is slightly different from Kudoh and Taguchi 2002 in that it searches backward from t_{event}. Searching backward gives a more accurate estimate of the onset time since it is less influenced by the baseline noise. There are three onset search parameters which you can adjust manually: avg, Nstdv and limit. avg = sliding average window size (slides backward from t_{event}) Y_{avg} = average yvalue computed within avg window Y_{stdv} = standard deviation of yvalues computed within avg window Nstdv = number of standard deviations above / below Y_{avg} y = Y_{avg}  Nstdv * Y_{stdv} (negative events) y = Y_{avg} + Nstdv * Y_{stdv} (positive events) t_{onset} = ythresholdcrossing time limit = time before t_{event} to end onset search
Event Peak Search. This is an optional search creteria for the peak of an event once the event has been detected. If no peak is found, the event is ignored and the search for events continues. If you do not wish to use this peak criteria for limiting what is considered an acceptable event, uncheck the peak checkbox. The peak search is a forward slidingwindow search from t_{event} for the first occurrence of the leftmost window point falling below level y (negative events, see image below) or above level y (positive events). Note, this algorithm implements only the forward peak search of Kudoh and Taguchi 2002. There are three peak search parameters: avg, Nstdv and limit. avg = sliding average window size (slides forward from t_{event}) Y_{avg} = average yvalue computed within avg window Y_{stdv} = standard deviation of yvalues computed within avg window Nstdv = number of standard deviations above / below Y_{avg} y = Y_{avg}  Nstdv * Y_{stdv} (negative events) y = Y_{avg} + Nstdv * Y_{stdv} (positive events) t_{peak} = ythresholdcrossing time limit = time after t_{event} to end peak search
Equivalent Parameters of Kudoh and Taguchi 2002 for Threshold Search wi = dt = sliding detection window (they use 1.6  4 msec) bin = onset avg window = peak avg window (they use 1  2 msec) pp = peak limit (they use 4  10 msec) n = onset Nsdv = peak Nsdv (they use 1  1.5) baseline avg they do not use, in which case avg = 0 msec. Adjusting Parameters
