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There is evidence that the same neural substrate may support different dynamical regimes and hence give rise to different EEG signals. However, the literature lacks successful attempts to systematically explain the different regimes --and the switching between them-- within a coherent setting. We explore a mathematical model of neural tissue and call upon concepts from dynamical systems to propose a possible explanation of such processes. The model does not aim to capture a high degree of neurophysiological detail. It rather provides an opportunity to discuss the change in the signals from a dynamical perspective. Notwithstanding, realistic values are adopted for the model parameters, and the resulting EEG also shows typical frequencies in a realistic range. We identify three mechanisms accounting for change: external forcing, bifurcation, and small perturbations of a chaotic attractor.