A hierarchical multiscale model of forward and backward alpha-band traveling waves in the visual system. - Jakob C B Schwenk; Andrea Alamia (PLoS Computational Biology)
Recent studies have shown that cortical low-frequency oscillations are often organized as traveling waves. The properties of these waves have been linked to both sensory processing and cognitive functions. In EEG recordings, alpha-band (~10Hz) traveling waves propagate predominantly along the occipital-frontal axis, with forward waves being most prominent during visual processing, while backward waves dominate at rest and during sensory suppression. While a previous study has proposed a functional model to explain their generation and propagation, a biologically plausible implementation is lacking. Here, we present a multi-scale network model with mean-field dynamics that, building on known cortical connectivity, reproduces the dynamics of alpha-band traveling waves observed in EEG recordings. We show that forward and backward waves can arise from two distinct cortical sub-networks that are connected in infragranular layers at each area. At rest, the network generates spontaneous backward waves and switches to a forward state upon sensory stimulation, reproducing the dynamics observed in EEG recordings. We then show that a cortico-thalamic pathway through the pulvinar can bias the dynamics to the forward state and that pulvinar engagement leads to spontaneous forward waves at rest. This is in line with previous studies suggesting a key role for the pulvinar in directing cortical information flow. In summary, our model provides a biologically plausible architecture for modeling the dynamics of macroscale traveling waves. It bridges the gap between scales by connecting laminar activity to scalp-level spatial patterns, providing a biologically grounded and comprehensive view of the spatial propagation of alpha-band traveling waves.