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Cellularsynaptic generation of EEG activity György Buzsáki1, Roger D. Traub2 and Timothy Pedley3 1Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, 197 University Avenue, Newark, NJ 07102 2 Department of Physiology, Neuroscience Unit Medical School, University of Birmingham Birmingham B15 2TT, U.K and 3Department of Neurology Columbia University, New York, NY 10032 Correspondence: György Buzsáki Center for Molecular and Behavioral Neuroscience, Rutgers University 197 University Avenue Newark, NJ 07102 Tel: (973) 3531080 ext. 3131 Fax: (973) 3531588 Email: buzsaki@axon.rutgers.edu Key words: EEG, cellular activity, synchrony, extracellular currents, intrinsic oscillations, synaptic activity, currentsource density analysis Supported by NIH (NS34994, MH54671) and the Wellcome Trust Introduction To date, three methods can provide high temporal resolution of neuronal interactions at the network level: electric field recording (EEG), magnetoencephalogram (MEG; 51, 70) and optical imaging (32, 86). Each of these have their advantages and shortcomings. MEG is not practical for experimental work on freely moving subjects due to the large size of magnetic sensors. A major obstacle of the optical imaging method is that its "view" is confined to surface events. Since most of the network interactions occur in the depth of the brain at the level of the synapses, a search for alternative methods is warranted. In addition, research in both MEG and optical imaging fields face the same fundamental questions as those arose decades ago in connection with scalprecorded EEG: the "reverse engineering" problem of signal interpretation (cf. 10, 31, 63) Membrane currents generated by neurons pass through the extracellular space. These currents can be measured by electrodes placed outside the neurons. The field potential (i. e., local mean field), recorded at any given site, reflects the linear sum of numerous overlapping fields generated by current sources (current from the intracellular space to the extracellular space) and sinks (current from the extracellular space to the intracellular space) distributed along multiple cells. This macroscopic state variable can be recorded with electrodes as a field potential or electroencephalogram (EEG) or with magnetosensors (SQUIDs) as a magnetoencephalogram (MEG). These local field patterns, therefore, provide experimental access to the spatiotemporal activity of afferent, associational and local operations in a given structure. To date, field potential measurements provide the best experimental and clinical tool for assessing cooperative neuronal activity at high temporal resolution. However, without a mechanistic description of the underlying neuronal processes, the scalp or depth EEG simply remains a gross correlate of brain activity rather than a predictive descriptor of the specific functional/anatomic events. The essential experimental tools for the exploration of EEG generation have yet to come. In this chapter we provide a basic description of field potential generation in the mammalian archicortex and neocortex and summarize recent progress and future directions A straightforward approach to deconvolve the surface (scalp) recorded event is to simultaneously study electrical activity on the surface and at the sites of the extracellular current generation. Electrical recording from deep brain structures using wire electrodes is one of the oldest methods in neuroscience. Local field potential measurements or "microEEG" (66) combined with recording of neuronal discharges is the best experimental tool available to study the influence of cytoarchitectural properties, such as cortical lamination, distribution, size and network connectivity of neural elements on electrogenesis. However, large number of observation points combined with decreased distance between the recording sites are required for high spatial resolution and for making interpretation of the underlying cellular events possible. Progress in this field is expected to be accelerated by the availability of micromachined siliconbased probes with numerous recording sites (60). The information obtained from the depth of the brain will then help interpret the surface recorded events. Clearly, such a task requires collaborative work among neuroscience, silicon nanotechnology, micromachinery, electric engineering, mathematics and computer science. The stake is high, since interpretation of macrosignals such as those obtained with EEG, MEG, fast MRI, PET or optical imaging methods will still require network (submillimeter) level interpretation of the cellular synapic interactions. In principle, every event associated with membrane potential changes of individual cells (neurons and glia) should contribute to the perpetual voltage variability of the extracellular space. Until recently, synaptic activity has been viewed as the exclusive source of extracellular current flow or EEG. As will be discussed below, however, synaptic activity is only one of the several membrane voltage changes that contributes to the measured field potential. Progress during the past decade revealed numerous sources of relatively slow membrane potential fluctuations, not directly associated with synaptic activity. Such nonsynaptic events may contribute also significantly to the generation of local field potentials. These include calcium spikes, voltagedependent oscillations and spike afterpotentials observed in various neurons Sources of extracellular current flow 1. Fast (Na+) action potentials The largest amplitude intracellular event is the sodiumpotassium spike, referred to as the fast (Na+) action potential intracellularly and as unit activity extracellularly. Individual fast action potentials are usually not considered to contribute significantly to the scalp recorded EEG, mainly because of their short duration (