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9 - Patterns of cortical connection in children with learning problems

Published online by Cambridge University Press:  22 September 2009

Frank H. Duffy
Affiliation:
Associate Professor of Neurology Harvard Medical School; Director of the Clinical Neurophysiology Laboratory Children's Hospital Boston
Kurt W. Fischer
Affiliation:
Harvard University, Massachusetts
Jane Holmes Bernstein
Affiliation:
The Children's Hospital, Boston
Mary Helen Immordino-Yang
Affiliation:
University of Southern California
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Summary

Overview: Behavior is based on brain functioning, and measures of brain activity such as the electroencephalogram (EEG) provide powerful tools for analyzing the relation between brain and behavior, including learning and development. In a study of brain activity in children with learning disorders, which included two of the boys who are a focus of this book (Andrew and Brian), EEG coherence was used to measure connectivity among cortical regions. Learning problems were associated with reduced connectivity of the left mid-temporal region with a cluster of central, frontal, and parietal locations: weaker connections seemed to relate to learning problems. Limited connectivity among brain regions also appears to characterize many victims of child abuse, as discussed in an Nessay for this chapter by Martin Teicher. At the same time, caution is required because of methodological issues about interpretation of brain activity measures, which are still in their infancy.

The Editors

The neurological perspective on behavior is based on the assumption that all behavior derives from the brain, a position based on lesion studies and aphasia. Having had the privilege of working with people such as Derek Denny-Brown, Ray Adams, and Norman Geschwind, all of whom contributed enormously to the understanding of brain–behavior relationships based on studies of brain lesions, I find this position difficult to resist. Indeed, it is amazing what complex patterns of behavior can be produced by very simple lesions that simply unhook key portions of a neural network that is otherwise functional.

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Publisher: Cambridge University Press
Print publication year: 2007

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