Eye movements explain decodability during perception and cued attention in MEG

Quax, Silvan C.; Dijkstra, Nadine; Staveren, Mariel J. van; Bosch, Sander; Gerven, Marcel A. J. van

doi:10.1016/j.neuroimage.2019.03.069

Cited by 69 publications

(65 citation statements)

References 19 publications

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“…Although trials with overt eye movements were rejected and ICA-based artifact correction was applied to remove voltage fluctuations generated by micro eye movements, to ensure that the decoding results were not contaminated by eye movements, we conducted an additional set of decoding analyses based on two EEG channels near the eyes (F7/F8), and compared the results between ICA-corrected data and uncorrected data. As suggested by Quax, Dijkstra, van Staveren, Bosch, and van Gerven (2019), if the decoding accuracy contained contributions from eye movements, we should observe above chance level decoding during the cue-target interval even using the ICA-corrected data.…”

Section: Minimizing the Impact Of Eye Movementsmentioning

confidence: 66%

Decoding Attention Control and Selection in Visual Spatial Attention

Hong

Meyyapan

et al. 2020

Preprint

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Event-related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The commonly applied univariate ERP approach, however, has left important questions inadequately answered. Here, we addressed two questions by applying multivariate pattern classification to multichannel ERPs in two spatial-cueing experiments (N = 56 in total): (1) impact of cueing strategies (instructional vs. probabilistic) and (2) neural and behavioral effects of individual differences. Following the cue onset, the decoding accuracy (cue left vs. cue right) began to rise above chance level earlier and remained higher in instructional cueing (~80 ms) than in probabilistic cueing (~160 ms), suggesting that unilateral attention focus leads to earlier and more distinct formation of the attentional set. A similar temporal sequence was also found for target-related processing (cued targets vs.uncued targets), suggesting earlier and stronger attention selection under instructional cueing. Across the two experiments, individuals with higher decoding accuracy during ~460-660 ms post-cue showed higher magnitude of attentional modulation of target-evoked N1 amplitude, suggesting that better formation of anticipatory attentional state leads to better target processing. During target processing, individual difference in decoding accuracy was positively associated with behavioral performance (reaction time), suggesting that stronger selection of task-relevant information leads to better behavioral performance.Taken together, multichannel ERPs combined with machine learning decoding yields new insights into attention control and selection that are not possible with the univariate ERP approach, and along with the univariate ERP approach, provides a more comprehensive methodology to the study of visual spatial attention.

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Section: Minimizing the Impact Of Eye Movementsmentioning

confidence: 66%

Decoding Attention Control and Selection in Visual Spatial Attention

Hong

Meyyapan

et al. 2020

Preprint

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“…Control for saccadic eye movements. Although participants were instructed to keep central gaze during the entire experiment, it might be that systematic differences in saccadic eye movements confounded the results (Quax et al, 2019), even in an auditory attention task. To rule this out, we inspected the EEG for independent components tuned to horizontal saccadic eye movements.…”

Section: Methodsmentioning

confidence: 99%

Alpha Oscillations in the Human Brain Implement Distractor Suppression Independent of Target Selection

2019

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In principle, selective attention is the net result of target selection and distractor suppression. The way in which both mechanisms are implemented neurally has remained contested. Neural oscillatory power in the alpha frequency band (ϳ10 Hz) has been implicated in the selection of to-be-attended targets, but there is lack of empirical evidence for its involvement in the suppression of to-be-ignored distractors. Here, we use electroencephalography recordings of N ϭ 33 human participants (males and females) to test the preregistered hypothesis that alpha power directly relates to distractor suppression and thus operates independently from target selection. In an auditory spatial pitch discrimination task, we modulated the location (left vs right) of either a target or a distractor tone sequence, while fixing the other in the front. When the distractor was fixed in the front, alpha power relatively decreased contralaterally to the target and increased ipsilaterally. Most importantly, when the target was fixed in the front, alpha lateralization reversed in direction for the suppression of distractors on the left versus right. These data show that target-selection-independent alpha power modulation is involved in distractor suppression. Although both lateralized alpha responses for selection and for suppression proved reliable, they were uncorrelated and distractor-related alpha power emerged from more anterior, frontal cortical regions. Lending functional significance to suppression-related alpha oscillations, alpha lateralization at the individual, single-trial level was predictive of behavioral accuracy. These results fuel a renewed look at neurobiological accounts of selection-independent suppressive filtering in attention.

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“…Eye movement control analyses, Experiments 2 and 3. Systematic biases in eye position can contribute to orientation and location performance (e.g., Quax et al, 2019). We did not collect eye position data from Experiment 1 (fMRI).…”

Section: Experiments 3: Eegmentioning

confidence: 99%

Categorical Biases in Human Occipitoparietal Cortex

2019

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Categorization allows organisms to generalize existing knowledge to novel stimuli and to discriminate between physically similar yet conceptually different stimuli. Humans, nonhuman primates, and rodents can readily learn arbitrary categories defined by low-level visual features, and learning distorts perceptual sensitivity for category-defining features such that differences between physically similar yet categorically distinct exemplars are enhanced, whereas differences between equally similar but categorically identical stimuli are reduced. We report a possible basis for these distortions in human occipitoparietal cortex. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivoxel and multielectrode patterns of human brain activity while human participants (both sexes) classified continuous stimulus sets into discrete groups. In each experiment, reconstructed representations of to-be-categorized stimuli were systematically biased toward the center of the appropriate category. These biases were largest for exemplars near a category boundary, predicted participants' overt category judgments, emerged shortly after stimulus onset, and could not be explained by mechanisms of response selection or motor preparation. Collectively, our findings suggest that category learning can influence processing at the earliest stages of cortical visual processing.

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Eye movements explain decodability during perception and cued attention in MEG

Cited by 69 publications

References 19 publications

Decoding Attention Control and Selection in Visual Spatial Attention

Decoding Attention Control and Selection in Visual Spatial Attention

Alpha Oscillations in the Human Brain Implement Distractor Suppression Independent of Target Selection

Categorical Biases in Human Occipitoparietal Cortex

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