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van Driel, J.

Publications and source records attributed to van Driel, J..

3 recordsLinked to original sources

Anticipatory distractor suppression elicited by statistical regularities in visual search

Salient yet irrelevant objects often capture our attention and interfere with our daily tasks. Distraction by salient objects can be reduced by suppressing the location where they are likely to appear. The question we addressed here was whether suppression of frequent distractors is already implemented beforehand, in anticipation of the stimulus. Using electroencephalography (EEG), we recorded cortical activity of human participants searching for a target while ignoring a salient distractor. The distractor was presented more often at one location than at any other location. We found reduced capture for distractors at frequent locations, indicating that participants learned to avoid distraction. Critically, we found evidence for proactive suppression as already prior to display onset, there was enhanced power in parieto-occipital alpha oscillations contralateral to the frequent distractor location - a signal known to occur in anticipation of irrelevant information. Locked to display onset, event-related potentials analysis showed a distractor-suppression-related PD component for this location. Importantly, this PD was found regardless of whether distracting information was presented at the frequent location. In addition, there was an early PD component representing an early attentional index of the frequent distractor location. Our results are show anticipatory (proactive) suppression of frequent distractor locations in visual search already starting prior to display onset.

neuroscience↗

High-pass filtering artifacts in multivariate classification of neural time series data

0.BackgroundTraditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown. New MethodTo prevent potential displacement effects, we extend an alternative method of removing slow drift noise - robust detrending - with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending. ResultsIn both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements. Comparison with Existing Method(s)Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial. ConclusionsDecoding analyses benefits from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

neuroscience↗

Beta and theta oscillations differentially support free versus forced control over target selection in visual search

Many important situations require human observers to simultaneously search for more than one object. Despite a long history of research into visual search, the behavioral and neural mechanisms associated with multiple-target search are poorly understood. Here we test the novel theory that the efficiency of looking for multiple targets critically depends on the mode of cognitive control the environment affords to the observer. We used an innovative combination of EEG and eye tracking while participants searched for two targets, within two different contexts: Either both targets were present in the search display and observers were free to prioritize either one of them, thus enabling proactive control over selection; or only one of the two targets would be present in each search display, which requires reactive control to reconfigure selection when the wrong target is prioritized. During proactive control, both univariate and multivariate signals of beta-band (15-35 Hz) power suppression prior to display onset predicted switches between target selections. This signal originated over midfrontal and sensorimotor regions and has previously been associated with endogenous state changes. In contrast, imposed target selections requiring reactive control elicited prefrontal power enhancements in the delta/theta-band (2-8 Hz), but only after display onset. This signal predicted individual differences in associated oculomotor switch costs, reflecting reactive reconfiguration of target selection. The results provide compelling evidence that multiple target representations are differentially prioritized during visual search, and for the first time reveal distinct neural mechanisms underlying proactive and reactive control over multiple-target search.\n\nSignificance StatementSearching for more than one object in complex visual scenes can be detrimental for search performance. While perhaps annoying in daily life, this can have severe consequences in professional settings such as medical and security screening. Previous research has not yet resolved whether multiple-target search involves changing priorities in what people attend to, and how such changes are controlled. We approached these questions by concurrently measuring cortical activity and eye movements using EEG and eye tracking, while observers searched for multiple possible targets. Our findings provide the first unequivocal support for the existence of two modes of control during multiple-target search, which are expressed in qualitatively distinct time-frequency signatures of the EEG both before and after visual selection.

neuroscience↗