A hierarchical multiscale model of forward and backward alpha-band traveling waves in the visual system

Recent studies have shown that low-frequency oscillations in the cortex are often organized as traveling waves. The dynamical properties of these waves, that span different scales, have been linked to both sensory processing and cognitive functions. In EEG recordings, alpha-band ([~]10Hz) traveling waves propagate predominantly in both directions of 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 multi-scale, biologically plausible implementation is still lacking. Here, we present a multi-scale network model with mean-field dynamics that, building on known interlaminar and cortico-cortical projections, reproduces the dynamics of alpha-band traveling waves observed in EEG recordings. We show that scalp-level forward and backward waves can arise from two distinct 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 bottom-up sensory stimulation, reproducing the dynamics we observed in EEG recordings in healthy participants.. We then expand our model to a cortico-thalamic network with a parallel feedforward pathway through the pulvinar. Our results show that this pathway biases the cortical dynamics to the forward state and that high pulvinar engagement leads to spontaneous forward waves without external input. This result is in line with previous studies suggesting a key role for the pulvinar in directing information flow in the cortex, and provide a computational basis to investigate the role of the pulvinar in cortical dynamics. In summary, our model provides a biologically plausible architecture for modeling the dynamics of macroscale traveling waves. Importantly, our study bridges the gap between distinct scales by connecting laminar mean-field activity to spatial patterns at the scalp level, providing a biologically grounded and comprehensive view of the generation and propagation of alpha-band traveling waves.