Abstract
Stimulation with rhythmic light flicker (photic driving) plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment) is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM) of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect.
Highlights
Electrophysiological measurements such as magneto- and electroencephalography (M/EEG), local field potentials (LFP) or single unit recordings contain rich information on brain function, which may be related to specific cognitive processes, to general brain states, or to certain pathological conditions
We show that the neural mass model (NMM) is a suitable model for the dynamics of brain resonance phenomena at the cortical level and demonstrate that useful predictions concerning the parameter choice of entrainment experiments can be derived
The model was able to account for the EEG dynamics of a photic driving experiment
Summary
Electrophysiological measurements such as magneto- and electroencephalography (M/EEG), local field potentials (LFP) or single unit recordings contain rich information on brain function, which may be related to specific cognitive processes, to general brain states, or to certain pathological conditions. Neurons in the human visual cortex synchronize their firing to the frequency of flickering light (at rates of about 5 to 30 Hz), causing the EEG alpha frequency to change toward the stimulation frequency [1,2,3]. This resonance effect is called photic driving. A review of the clinical routine can be found in Niedermeyer et al [4] The occurrence of this effect is often interpreted as an indicator for the functional flexibility of the cortex and as a sign of healthiness. That only 50 to 80% of healthy volunteers show a response in the alpha range of EEG [9,10]
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