Willed Attentional Selection of Visual Features: An EEG Study

Wang, Jingyi; Wang, Jiaqi; Hu, Jingyi; Tong, Shanbao; Hong, Xiangfei; Sun, Junfeng · 2024 · OpenAlex-citations

DOI: 10.1109/tnsre.2024.3383669

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Summary

This study investigates the neural mechanisms of "willed attention," where individuals voluntarily direct their focus without external instructions, specifically within a feature-based attention paradigm. While previous research established that volitional spatial attention involves distinct event-related potentials (ERPs) and is biased by pre-cue alpha oscillations, it remained unclear whether these mechanisms generalize to feature-based selection. The authors aimed to determine if willed attention to visual features (color) shares similar neural correlates with spatial willed attention and whether ongoing alpha activity can predict voluntary feature choices. The researchers conducted an EEG study with 34 healthy participants who performed a feature-based selective attention task. Participants viewed superimposed random dot kinematograms (RDKs) flickering in blue (15 Hz) and yellow (20 Hz). In "instruct cue" trials, participants were explicitly told which color to attend; in "choice cue" trials, they freely chose which color to attend. The primary task involved detecting coherent motion in the attended color. The study measured steady-state visual evoked potentials (SSVEPs) as markers of attentional processing, cue-evoked ERPs to identify willed-attention components, and pre-cue alpha oscillations to test for predictive decoding of color choices. Multivariate pattern analysis using support vector machines was employed to decode cue types and color choices from EEG data. The results demonstrated that SSVEP responses were similarly modulated by attention in both choice and instruct conditions, indicating comparable attentional engagement. Consistent with spatial willed attention findings, the study isolated two distinct ERP components associated with volitional choice: the Early Willed-Attention Component (EWAC, 300–400 ms) and the Willed-Attention Component (WAC, 400–800 ms). These components were successfully decoded from the EEG data, confirming their presence in feature-based tasks. However, contrary to findings in spatial attention, pre-cue ongoing alpha oscillations did not predict the participants' color choices (yellow vs. blue), as decoding accuracy remained at chance levels (50%). This suggests that while the volitional control system exists for feature-based attention, the predictive role of alpha oscillations observed in spatial attention does not generalize to feature selection. The study concludes that willed attention mechanisms involve shared neural signatures across spatial and feature domains, evidenced by the presence of EWAC and WAC components. However, the lack of alpha-mediated prediction in feature-based tasks highlights a key difference between spatial and feature-based volitional attention. These findings extend the understanding of volitional attentional control, suggesting that while the executive processes of making a voluntary attentional choice are consistent across domains, the preparatory neural biases may be domain-specific. This distinction is crucial for developing brain-computer interfaces and understanding how the brain manages limited processing resources in naturalistic, instruction-free environments.

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• attention selective divided