Competing rhythmic neural representations of orientations during concurrent attention to multiple orientation features

Ce Mo,Bichan Wu,Jianrong Jia,Huan Luo,Junshi Lu,Fang Fang

doi:10.1038/s41467-019-13282-3

Abstract

When a feature is attended, all locations containing this feature are enhanced throughout the visual field. However, how the brain concurrently attends to multiple features remains unknown and cannot be easily deduced from classical attention theories. Here, we recorded human magnetoencephalography signals when subjects concurrently attended to two spatially overlapping orientations. A time-resolved multivariate inverted encoding model was employed to track the ongoing temporal courses of the neural representations of the attended orientations. We show that the two orientation representations alternate with each other and undergo a theta-band (~4 Hz) rhythmic fluctuation over time. Similar temporal profiles are also revealed in the orientation discrimination performance. Computational modeling suggests a tuning competition process between the two neuronal populations that are selectively tuned to one of the attended orientations. Taken together, our findings reveal for the first time a rhythm-based, time-multiplexing neural machinery underlying concurrent multi-feature attention.

Highlights

When a feature is attended, all locations containing this feature are enhanced throughout the visual field
Attention to multiple features might require a distinctive neural mechanism that globally coordinates activities among multiple dispersed neuronal populations that tuned to the attended features, which remains largely unknown despite recent behavioral evidence for rhythmicity in feature-based attention[10]
A multivariate inverted encoding model (IEM)[19,20,21,22] was applied to the MEG signals to reconstruct the neural representations of these two features at each time point throughout the attentional process

Summary

Introduction

When a feature is attended, all locations containing this feature are enhanced throughout the visual field. Attention samples targets (e.g., locations, objects) rhythmically, with different targets being processed in different phases[16,17] These findings implicate that multi-feature attention might rely on a temporal coordination process in which attention resources are dynamically allocated between multiple features over time. A multivariate inverted encoding model (IEM)[19,20,21,22] was applied to the MEG signals to reconstruct the neural representations of these two features at each time point throughout the attentional process. We performed a time-resolved behavioral study using the same multi-feature attention task, and the results showed a similar rhythmic profile as that in the MEG signals, supporting an essential link between the neural and behavioral findings. The temporal rhythmicity in the orientation representations was associated with a competition process between the neuronal populations tuned to the attended orientations, manifested as periodical changes in their tuning widths

Methods

Results

Conclusion