Presidential Symposium

Abstract

1 Gregory L. Holmes, 2 Jermoe Engel, 3 Yehezkel Ben‐Ari, 4 Robert Muller, and 5 John Huguenard ( 1 Dartmouth Medical School, Lebanon, NH ; 2 Department of Neurology, UCLA School of Medicine, Los Angeles, CA ; 3 Inmed Institute, Marseille, France ; 4 SUNDY Downstate Medical Center, Brooklyn, NY ; and 5 Department of Neurology, Stanford University, Stanford, CA ,)The purpose of this symposium is to provide clinicians, basic scientists, and professions in health care with an understanding of the importance of brain rhythms in normal and abnormal brain function. Different brain rhythms, consisting of both low and fast frequencies, are grouped within complex wave‐sequences. These rhythms serve as powerful synchronizing forces and play important roles in all aspects of higher cortical function. During this symposium a review of the normal inherent network properties of brain excitatory and inhibitory circuits will be reviewed along with the cellular and molecular mechanisms responsible for these rhythms. The relationship between intrinsic hippocampal rhythms and learning and memory will be discussed. Aberrant rhythms may contribute to pathological processes such as memory impairment. There is also increasing evidence that high frequency oscillations may precede epilepsy in both the immature and mature brain, having an important role in epileptogenesis.Dr. Jerome Engle will review the physiological basis of brain rhythms and the role of high frequency oscillations in temporal lobe epilepsy. Dr.Yehezkel Ben‐Ari will discuss the role of high frequency stimulations in the mirror focus in immature animals. Dr. Robert Muller will provide information about the relationship between single cell firing patterns, hippocampal rhythms, and learning. Dr. John Huguenard will discuss oscillations in the thalamocortical system and the mechanisms of epileptic synchrony.This session will emphasize that epilepsy and its related morbidities are caused by neuronal network abnormalities. The brain's rhythms are critical in determining whether these networks perform normally or abnormally.