Applying Symbolic Encoding to Event Related Brain Potentials: trying to get the timing right

 Douglas Saddy

Abstract

We know that the brain behaves as a complex integrated system. Despite this, most of our techniques for analyzing the behavior we can measure in the cortex either assume the opposite or are insensitive to the complexity of the system. A case in point is Evoked Brain Potentials (ERPs). Recordings of electrical activity generated in the brain in response to specific stimuli now provide an important source of information about the temporal and topographical distribution of language processing events in the brain.  Many of our theories of language processing are based upon reaction time studies and use the new brain based findings sparingly. One reason for this is that much of the results from brain recordings are seen to be primarily recapitulations of reaction time findings.  Furthermore, despite ERP's high temporal resolution, data bearing upon the crucial early components of language processing have been difficult to acquire and controversial. In addition there is considerable debate regarding the temporal and topological distinctiveness of the voltage markers themselves.  Part of the problem lies in the nature of the data analysis techniques applied to the raw time series data.  The field of nonlinear dynamics offers new strategies and paradigms for understanding complex systems like the human brain and its relation to mind and behavior.  In this talk I will outline an approach to and present results from the analysis of ERP data based on complex system analysis which provides a richer reflection of the dynamic properties of language-related brain potentials and enhances our view of cognitive cortical events.