Abstract
In this work we demonstrate the principles of a systematic modeling approach of the neurophysiologic processes underlying a behavioral function. The modeling is based upon a flexible simulation tool, which enables parametric specification of the underlying neurophysiologic characteristics. While the impact of selecting specific parameters is of interest, in this work we focus on the insights, which emerge from rather accepted assumptions regarding neuronal representation. We show that harnessing of even such simple assumptions enables the derivation of significant insights regarding the nature of the neurophysiologic processes underlying behavior. We demonstrate our approach in some detail by modeling the behavioral go/no-go task. We further demonstrate the practical significance of this simplified modeling approach in interpreting experimental data – the manifestation of these processes in the EEG and ERP literature of normal and abnormal (ADHD) function, as well as with comprehensive relevant ERP data analysis. In-fact we show that from the model-based spatiotemporal segregation of the processes, it is possible to derive simple and yet effective and theory-based EEG markers differentiating normal and ADHD subjects. We summarize by claiming that the neurophysiologic processes modeled for the go/no-go task are part of a limited set of neurophysiologic processes which underlie, in a variety of combinations, any behavioral function with measurable operational definition. Such neurophysiologic processes could be sampled directly from EEG on the basis of model-based spatiotemporal segregation.
Highlights
The manner by which the brain represents information is the subject matter of many models
Other studies report that N2 activity is enhanced in groups of Attention Deficit Hyperactivity Disorder (ADHD) subjects compared with controls
A LIMITED SET OF NEUROPHYSIOLOGIC PROCESSES MANIFESTING IN EEG In the present study we demonstrated the possibility that a rather limited number of neurophysiologic processes can underlie the EEG signal
Summary
The manner by which the brain represents information is the subject matter of many models (see, for example Markram, 2006). Despite significant differences between models, it seems that specific neuronal networks are often considered as the elementary representation units – for instance cortical columns (see, for example Mountcastle, 1997). The activity of such networks and their inter-relations with other networks is constrained by neuronal infrastructure as well as by anatomical division to functional brain regions. Neuronal networks in each region are believed to represent related entities, in terms of perceptual, motor, or other features (see, for example Mesulam, 1998) Such anatomical constraints may restrict the types of possible representations. They seem to restrict the possible inter-connections between the types of elementary representations due to limitation of anatomical connections between the functional regions (see, for example Mesulam, 1998)
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