Mining Temporal Dynamics With Support Vector Machine for Predicting the Neural Fate of Target in Attentional Blink.

Yuan Yao,Feiyan Chen,Yunying Wu,Tianyong Xu

doi:10.3389/fnsys.2021.734660

Abstract

Our brains do not mechanically process incoming stimuli; in contrast, the physiological state of the brain preceding stimuli has substantial consequences for subsequent behavior and neural processing. Although previous studies have acknowledged the importance of this top-down process, it was only recently that a growing interest was gained in exploring the underlying neural mechanism quantitatively. By utilizing the attentional blink (AB) effect, this study is aimed to identify the neural mechanism of brain states preceding T2 and predict its behavioral performance. Interarea phase synchronization and its role in prediction were explored using the phase-locking value and support vector machine classifiers. Our results showed that the phase coupling in alpha and beta frequency bands pre-T1 and during the T1–T2 interval could predict the detection of T2 in lag 3 with high accuracy. These findings indicated the important role of brain state before stimuli appear in predicting the behavioral performance in AB, thus, supporting the attention control theories.

Highlights

Our brains do not process incoming stimuli passively; rather, if a certain stimulus is to be perceived, it depends in part on the current state of the brain (Hanslmayr et al, 2011)
Under the alpha frequency band in the time window of (−300, 0), four pairs of electrodes were found to be significantly different in their Phase-locking value (PLV) by using a t-test to compare T2-detected and -undetected trials
Our primary finding demonstrates that classification of EEG PLV patterns using data mining tools with neural cognitive data related to consciousness is achievable

Summary

Introduction

Our brains do not process incoming stimuli passively; rather, if a certain stimulus is to be perceived, it depends in part on the current state of the brain (Hanslmayr et al, 2011). Whether a stimulus is perceived as the result of the interaction of the bottom-up and top-down processing approaches. Prestimulus alpha power has been proved to be a neural predictor of visual awareness (Benwell et al, 2021). Synchronous oscillations in the alpha frequency band inhibit the perception of shortly presented stimuli whereas synchrony in higher frequency ranges (>20 Hz) enhances visual perception, indicating the attentional state could predict perception performance on a single trial basis (Hanslmayr et al, 2007). The early transient global increase of phase synchrony

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