A neural mass model for the EEG in ischemia

Abstract

AbstractNormal brain function depends on continuous cerebral blood flow for the supply of oxygen and glucose, and is quickly compromised in conditions where the metabolic demand cannot be met. Insufficient cerebral perfusion can result in ischemic stroke, with symptoms ranging from loss of motor or language function to coma, depending on the brain areas affected. Cerebral ischemia also results in changes in the electroencephalogram. Initially, a reduction of the frequency of the rhythms occurs. Depending on the depth and duration of energy deprivation, this eventually leads to the disappearance of all rhythmic activity. Here, we study the relationship between electroencephalogram (EEG) phenomenology and cellular biophysical principles using a model of interacting thalamic and cortical neural masses coupled with energy-dependent synaptic transmission. Our model faithfully reproduces the characteristic EEG phenomenology during acute cerebral ischemia and shows that synaptic arrest occurs before cell swelling and irreversible neuronal depolarization. The early synaptic arrest is attributed to ion homeostatic failure due to dysfunctional Na+/K+-ATPase. Moreover, we show that the excitatory input from relay cells to the cortex controls rhythmic behavior. In particular, weak relay-interneuron interaction manifests in burst-like EEG behavior immediately prior to synaptic arrest. We corroborate our observations with human EEG data from patients undergoing carotid endarterectomy and patients after cardiac arrest with a postanoxic encephalopathy. The model thus reconciles the implications of stroke on a cellular, synaptic and circuit level and provides a basis for exploring other multi-scale therapeutic interventions.Significance statementReliable synaptic transmission and preservation of ion gradients across cellular membranes are essential for physiological brain function and consume significant energy. During cerebral ischemia, synaptic arrest occurs early due to energy deprivation (ED), which is characterized clinically by the loss of physiological electroencephalographic (EEG) rhythms. In this work, we explore connections between cellular and network behavior during ED by means of a novel computational model that describes ion dynamics in the cortex and thalamus, and resulting EEG. We reproduce characteristic EEG behavior during ED and show that synaptic arrest occurs before other pathologies like swelling and depolarization. Moreover, we predict that low excitatory thalamocortical projections cause burst-like EEG patterns before synaptic arrest, which may explain observations regarding post-stroke synaptic reorganization.