Computer simulation of the generation of the electroencephalogram

We have used a computer program for modeling some features of the scalp electroencephalogram (EEG) in terms of the time- and space-dependent interactions of populations of neurons in different hypothetical brain configurations of increasing levels of complexity. The input of the model consists of: (1) geometric and anatomic data characterizing the brain configuration, including interconnecting fiber pathways between neuronal groups; (2) physiologic characteristics of neurons, such as thresholds, driving potentials and conductances of excitatory and inhibitory synapses, synaptic delay times, and rise and fall times of postsynaptic potentials; and (3) functions describing the time-dependent afferent impulses to the brain configuration under study. The output of the model consists of plots of selected intracellular and extracellular potentials, including electrical potentials measured by an array of electrodes on the surface of the head, as a function of time. The objective was to assess how the characteristic frequencies seen in scalp EEG recordings might be determined by characteristics of local neuronal circuits (such as thalamic 'pacemakers') and by global circuit characteristics (such as cortico-cortical and thalamo-cortical interactions). We find that in our model the basic requirement for rhythmic behavior is the existence of local feedback circuits containing inhibitory neurons and that, when parameters of the model are chosen so that sustained rhythmic oscillations in the alpha frequency range are generated, the characteristic frequencies of these oscillations are primarily determined by the local circuit parameters, especially the duration of the inhibitory postsynaptic potentials, and are relatively independent of global circuit parameters such as the ranges of the long interconnecting axons and the propagation velocity of action potentials in these axons.