Transcription of Chapter 2: Introduction to Point Processes
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Chapter 2: Introduction to Point Processes
Chapter 2: Introduction to Point Processes I. Point Processes are used to describe data that are localized in space or time In Chapter 1, we saw an example of neuronal activity in the supplemental eye field (SEF) expressed in terms of a raster plot and a peri-stimulus time histogram (Fig. ). The raster plot shows locations of action potentials in time for multiple trials, and the peristimulus time histogram counts the number of such events is small time bins, averaged over all of the trials. These types of plots provide a means to express data that consists of discrete events localized in time. Analyzing data of this sort presents its own unique challenges, and poses its own set of questions.
Neural spike trains are described by temporal point processes because the spike events are localized in time. It is also possible to use point process theory to model data that is localized at a discrete set of locations in space or in both space and time. These models are called spatial and spatiotemporal point processes respectively.
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