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First target timing influences the attentional blink under low, but not high working memory load. Atten Percept Psychophys 2023; 85:1-8. [PMID: 36123500 DOI: 10.3758/s13414-022-02564-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/26/2022] [Indexed: 01/10/2023]
Abstract
A growing literature posits attention as a core component of working memory (Baddeley, European Psychologist, 7(2), 85-97, 2002), yet research exploring this relationship is scarce in the temporal attention domain. The present research provided further evidence that the magnitude of the attentional blink (AB) can be influenced by working memory load (WML; Akyürek et al., Memory & Cognition 35, 621-627, 2007). Additionally, we behaviorally tested Akyürek and colleagues' (Psychophysiology, 47(6), 1134-1141, 2010) conclusion that working memory influences attention at an early stage by systematically manipulating the timing of the first target in relation to the stimuli preceding and following it. In two experiments, we demonstrated that the AB effect increases as the temporal interval between the first target and the stimulus following it decreases. Importantly, this effect was observed only when WML was low, indicating that WM influences attending to a second target at an early stage of attentional processing.
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Yuan P, Hu R, Zhang X, Wang Y, Jiang Y. Cortical entrainment to hierarchical contextual rhythms recomposes dynamic attending in visual perception. eLife 2021; 10:65118. [PMID: 34086558 PMCID: PMC8177885 DOI: 10.7554/elife.65118] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 05/12/2021] [Indexed: 02/07/2023] Open
Abstract
Temporal regularity is ubiquitous and essential to guiding attention and coordinating behavior within a dynamic environment. Previous researchers have modeled attention as an internal rhythm that may entrain to first-order regularity from rhythmic events to prioritize information selection at specific time points. Using the attentional blink paradigm, here we show that higher-order regularity based on rhythmic organization of contextual features (pitch, color, or motion) may serve as a temporal frame to recompose the dynamic profile of visual temporal attention. Critically, such attentional reframing effect is well predicted by cortical entrainment to the higher-order contextual structure at the delta band as well as its coupling with the stimulus-driven alpha power. These results suggest that the human brain involuntarily exploits multiscale regularities in rhythmic contexts to recompose dynamic attending in visual perception, and highlight neural entrainment as a central mechanism for optimizing our conscious experience of the world in the time dimension.
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Affiliation(s)
- Peijun Yuan
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,Chinese Institute for Brain Research, Beijing, China
| | - Ruichen Hu
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,Chinese Institute for Brain Research, Beijing, China
| | - Xue Zhang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,Chinese Institute for Brain Research, Beijing, China
| | - Ying Wang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,Chinese Institute for Brain Research, Beijing, China
| | - Yi Jiang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,Chinese Institute for Brain Research, Beijing, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
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Robbins KA, Touryan J, Mullen T, Kothe C, Bigdely-Shamlo N. How Sensitive Are EEG Results to Preprocessing Methods: A Benchmarking Study. IEEE Trans Neural Syst Rehabil Eng 2020; 28:1081-1090. [PMID: 32217478 DOI: 10.1109/tnsre.2020.2980223] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Although several guidelines for best practices in EEG preprocessing have been released, even studies that strictly adhere to those guidelines contain considerable variation in the ways that the recommended methods are applied. An open question for researchers is how sensitive the results of EEG analyses are to variations in preprocessing methods and parameters. To address this issue, we analyze the effect of preprocessing methods on downstream EEG analysis using several simple signal and event-related measures. Signal measures include recording-level channel amplitudes, study-level channel amplitude dispersion, and recording spectral characteristics. Event-related methods include ERPs and ERSPs and their correlations across methods for a diverse set of stimulus events. Our analysis also assesses differences in residual signals both in the time and spectral domains after blink artifacts have been removed. Using fully automated pipelines, we evaluate these measures across 17 EEG studies for two ICA-based preprocessing approaches (LARG, MARA) plus two variations of Artifact Subspace Reconstruction (ASR). Although the general structure of the results is similar across these preprocessing methods, there are significant differences, particularly in the low-frequency spectral features and in the residuals left by blinks. These results argue for detailed reporting of processing details as suggested by most guidelines, but also for using a federation of automated processing pipelines and comparison tools to quantify effects of processing choices as part of the research reporting.
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Keitel C, Keitel A, Benwell CSY, Daube C, Thut G, Gross J. Stimulus-Driven Brain Rhythms within the Alpha Band: The Attentional-Modulation Conundrum. J Neurosci 2019; 39:3119-3129. [PMID: 30770401 PMCID: PMC6468105 DOI: 10.1523/jneurosci.1633-18.2019] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 01/16/2019] [Accepted: 02/03/2019] [Indexed: 01/23/2023] Open
Abstract
Two largely independent research lines use rhythmic sensory stimulation to study visual processing. Despite the use of strikingly similar experimental paradigms, they differ crucially in their notion of the stimulus-driven periodic brain responses: one regards them mostly as synchronized (entrained) intrinsic brain rhythms; the other assumes they are predominantly evoked responses [classically termed steady-state responses (SSRs)] that add to the ongoing brain activity. This conceptual difference can produce contradictory predictions about, and interpretations of, experimental outcomes. The effect of spatial attention on brain rhythms in the alpha band (8-13 Hz) is one such instance: alpha-range SSRs have typically been found to increase in power when participants focus their spatial attention on laterally presented stimuli, in line with a gain control of the visual evoked response. In nearly identical experiments, retinotopic decreases in entrained alpha-band power have been reported, in line with the inhibitory function of intrinsic alpha. Here we reconcile these contradictory findings by showing that they result from a small but far-reaching difference between two common approaches to EEG spectral decomposition. In a new analysis of previously published human EEG data, recorded during bilateral rhythmic visual stimulation, we find the typical SSR gain effect when emphasizing stimulus-locked neural activity and the typical retinotopic alpha suppression when focusing on ongoing rhythms. These opposite but parallel effects suggest that spatial attention may bias the neural processing of dynamic visual stimulation via two complementary neural mechanisms.SIGNIFICANCE STATEMENT Attending to a visual stimulus strengthens its representation in visual cortex and leads to a retinotopic suppression of spontaneous alpha rhythms. To further investigate this process, researchers often attempt to phase lock, or entrain, alpha through rhythmic visual stimulation under the assumption that this entrained alpha retains the characteristics of spontaneous alpha. Instead, we show that the part of the brain response that is phase locked to the visual stimulation increased with attention (as do steady-state evoked potentials), while the typical suppression was only present in non-stimulus-locked alpha activity. The opposite signs of these effects suggest that attentional modulation of dynamic visual stimulation relies on two parallel cortical mechanisms-retinotopic alpha suppression and increased temporal tracking.
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Affiliation(s)
- Christian Keitel
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK,
| | - Anne Keitel
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
- Psychology, School of Social Sciences, University of Dundee, Dundee DD1 4HN, UK, and
| | - Christopher S Y Benwell
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
- Psychology, School of Social Sciences, University of Dundee, Dundee DD1 4HN, UK, and
| | - Christoph Daube
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
| | - Gregor Thut
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
- Institut für Biomagnetismus und Biosignalanalyse, Westfälische Wilhelms-Universität, 48149 Münster, Germany
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