Speedy evoked potential methods for assessing vision in normal and amblyopic eyes: Pros and cons

There is a growing interest in the speedy evoked potential (EP) technique variously called the “sweep averaging” method, “averaging graphs” or the “averaging relutionship” method. Although this technique can be very effective, and can provide data unobtainable by conventional methods (Regan. 1974. 1975a.3 it is not an entirely simple tool. Users should be alert to a number of general problems in the application of the “sweep averaging” method generally, and special problems in the use of the “sweep averaging” method for assessing visual acuity in amblyopia. Discussions of the various advantages and drawbacks of the “sweep averaging” method are individually scattered in the literature. and a more complete treatment is lacking. The present note attempts to provide a concise summary of the pros and cons of the method with the aim of aiding potential users to decide whether the “sweep averaging” method would offer them sufficient advantage over conventional recording to justify switching to an unfamiliar technique. Before discussing the pros and cons I will briefly describe the “sweep averaging” method. Consider. for example. an experimenter who aims to find how EP amplitude depends on the spatial frequency of his grating stimulus. Adopting the conventional approach he would record for (say) 36 set to obtain an averaged EP to a 1 c/deg stimulus grating, then take another 36 set to record an averaged EP to a 2 c/deg grating then record EPs to a 4, 8 and 32 c,‘deg gratings in a total of (say) 180 set recording time. Alternatively, he could use the “sweep averaging” method. He would obtain a running (i.e. moment-by-moment) average of EP amplitude using a grating stimulus that reverses contrast at a rate of (say) 5 times per set while stimulus spatial frequency zooms from I to 32 c/deg in (say) 20sec. One sweep of spatial frequency rapidly samples the whole graph that the experimenter requires. This single sample of the graph may well be noisy. but he can markedly improve the reliability of

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