Periodic visual stimulation can induce stable steady-state visual evoked potentials (SSVEPs) distributed in multiple brain regions and has potential applications in both neural engineering and cognitive neuroscience. However, the underlying dynamic mechanisms of SSVEPs at the whole-brain level are still not completely understood. Here, we addressed this issue by simulating the rich dynamics of SSVEPs with a large-scale brain model designed with constraints of neuroimaging data acquired from the human brain. By eliciting activity of the occipital areas using an external periodic stimulus, our model was capable of replicating both the spatial distributions and response features of SSVEPs that were observed in experiments. In particular, we confirmed that alpha-band (8-12 Hz) stimulation could evoke stronger SSVEP responses; this frequency sensitivity was due to nonlinear entrainment and resonance, and could be modulated by endogenous factors in the brain. Interestingly, the stimulus-evoked brain networks also exhibited significant superiority in topological properties near this frequency-sensitivity range, and stronger SSVEP responses were demonstrated to be supported by more efficient functional connectivity at the neural activity level. These findings not only provide insights into the mechanistic understanding of SSVEPs at the whole-brain level but also indicate a bright future for large-scale brain modeling in characterizing the complicated dynamics and functions of the brain.

The neural mechanism of steady-state visual evoked potentials (SSVEP) is still not clearly understood. Especially, only certain frequency stimuli can evoke SSVEP. Our previous network study reveals that 8 Hz stimulus that can evoke strong SSVEP response shows the enhanced linkage strength between frontal and visual cortex. To further probe the directed information flow between the two cortex areas for various frequency stimuli, this paper develops a causality analysis based on the inversion of double columns model using particle swarm optimization (PSO) to characterize the directed information flow between visual and frontal cortices with the intracranial rat electroencephalograph (EEG). The estimated model parameters demonstrate that the 8 Hz stimulus shows the enhanced directional information flow from visual cortex to frontal lobe facilitates SSVEP response, which may account for the strong SSVEP response for 8 Hz stimulus. Furthermore, the similar finding is replicated by data-driven causality analysis. The inversion of neural mass model proposed in this study may be helpful to provide the new causality analysis to link the physiological model and the observed datasets in neuroscience and clinical researches.

Steady state visual evoked potentials (SSVEP) are assumed to be regulated by multiple brain areas, yet the underlying mechanisms are not well understood. In this study, we utilized multi-channel intracranial recordings together with network analysis to investigate the underlying relationships between SSVEP and brain networks in anesthetized rat. We examined the relationship between SSVEP amplitude and the network topological properties for different stimulation frequencies, the synergetic dynamic changes of the amplitude and topological properties in each rat, the network properties of the control state, and the individual difference of SSVEP network attributes existing among rats. All these aspects consistently indicate that SSVEP response is closely correlated with network properties, the reorganization of the background network plays a crucial role in SSVEP production, and the background network may provide a physiological marker for evaluating the potential of SSVEP generation.

Emotion plays an important role in people's lives. However, the neural mechanism of affective perception is still unclear. In this study, steady-state visual evoked potentials (SSVEPs) were used to explore information processing speed and interactions among cortical structures involved in affective perception. Pleasant, unpleasant, and neutral pictures selected from the International Affective Picture System were presented either in intact or phase-scrambled form at a fixed frequency, where the induced SSVEPs could be used as a frequency marker of brain activity with high temporal resolution and signal-to-noise ratio. Source estimation methods were used to reconstruct the cortical signals. The information processing of affective images was studied by phase and causal connection analysis in the cortical space to investigate the information processing speed of the local brain region and the dynamic interactions across brain regions. Experimental results showed that affective and semantic perception was accompanied by the acceleration of information processing speed in the ventral pathway. Unpleasant emotions had the fastest information processing speed in the ventral stream compared with pleasant and neutral emotions, including the middle occipital gyrus and the middle temporal gyrus, with a right hemisphere bias. In addition, unpleasant emotions were stronger than pleasant emotions in long-term causal connections in the bilateral middle temporal gyrus, and the direction was from the right hemisphere to the left hemisphere. These results provide unique insights into the cortical activities for affective perception and support the view that unpleasant emotions have priority in information perception in the middle temporal gyrus compared with pleasant and neutral emotions, with a right hemisphere bias.