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. 2017 Dec 7;12(12):e0187763.
doi: 10.1371/journal.pone.0187763. eCollection 2017.

Reduced visual attention in heterogeneous textures is reflected in occipital alpha and theta band activity

Tobias Feldmann-Wüstefeld  1 , Makoto Miyakoshi  2 , Marco Alessandro Petilli  2   3 , Anna Schubö  4 , Scott Makeig  2
Affiliations

Reduced visual attention in heterogeneous textures is reflected in occipital alpha and theta band activity

Tobias Feldmann-Wüstefeld et al. PLoS One. .

Abstract

Increasing context heterogeneity has been found to reduce attention deployment towards an embedded target item. Heterogeneity in visual search tasks is typically induced by segmenting the background into several perceptual groups. In the present study, however, context heterogeneity was induced by varying whole-field heterogeneity, i.e., the degree of distractor variability within the entire context. This allowed us to (i) more gradually vary context heterogeneity, and (ii) investigate attention deployment on a whole-field scale. Results showed that both search performance and amplitude of the N2pc (lateralized ERP; posterior contralateral negativity in the N2 range) monotonically decreased with increasing context heterogeneity, which confirmed that there was less efficient attention deployment for more heterogeneous contexts. The amplitude of the bilateral N2 exhibited a U-shaped function, suggesting global perception for the lowest and highest levels of heterogeneity, but local processing for intermediate heterogeneity levels. Independent component analyses revealed an occipital ERP-contributing effective source cluster that may reflect stimulus representations on a saliency map. With increasing heterogeneity, these sources exhibited more theta band activity for distractors and less theta band activity for targets. Alpha band activity of a second component cluster varied with heterogeneity level, and low-theta/delta activity of a third source cluster distinguished target presence versus absence. In sum, our results suggest that independent brain sources contributed to the differential processing of heterogeneous versus homogeneous contexts.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Stimuli, behavioral, and ERP results.
(A) In the 0° heterogeneity condition, all distractor lines were identical. In the 12°, 24° and 36° heterogeneity condition, orientation of each distractor varied randomly within 12°, 24°, or 36°. Target orientation was always in 69° contrast to average distractor orientation. (B) Mean accuracy for each of the four distractor orientations. (C) Lateralized ERP. Average ERP waveforms recorded at a posterior-occipital electrode pool (PO7, PO8), evoked by search display presentations, separately for sites contra- and ipsilateral to the target. The difference between contralateral (red lines) and ipsilateral (green lines) activity constitutes the N2pc. (D) Mean N2pc amplitude. Difference between contra- and ipsilateral activity at PO7/PO8, separately for the four heterogeneity conditions. (E) Bilateral ERP. Average ERPs recorded at a posterior-occipital electrode pool (PO7, PO8), evoked by search display presentations. Results are shown separately for the four distractor heterogeneity levels. Blue lines represent the ERP time courses in target-absent trials; red lines the ERP time courses in target-present trials. The difference between blue and red lines constitute the differential bilateral N2. (F) Differential bilateral N2. Difference between N2 for target-absent and target-present trials. Grey shaded rectangles show the time window (220–300 ms) for statistical analyses. Error bars in B-F represent standard errors of the mean, corrected for individual differences [66]. Note that the deflection in the ERP in the baseline period is due to the onset asynchrony of fixation cross and search display (300 ms).
Fig 2
Fig 2. Cluster mean scalp maps.
Cluster mean scalp maps are shown with MNI coordinates and respective brain area (BA = Brodman area). Clusters are sorted according to explained variance. In brackets: number of subjects (Ss) contributing to the cluster and total number of independent components (ICs) included in the cluster.
Fig 3
Fig 3. Cluster 4.
(A) Time-frequency plot for all levels of heterogeneity (rows) and target-present (left column), target-absent (middle column) trials and the difference between target-present and–absent trials (right column). (B) Bar graphs indicate mean power for area with significant interaction of trial type and level of heterogeneity (highlighted with black outline in difference time-frequency plot). (C) Cortical density maps.
Fig 4
Fig 4. Cluster 6.
Time-frequency plot for target-present (left panel) and target-absent (right panel) trials, collapsed across all levels of heterogeneity. Bar graphs indicate mean power for area with significant main effect of trial type (highlighted with black outline in each plot). (C) Cortical density maps.
Fig 5
Fig 5. Cluster 14.
Time-frequency plot for all levels of heterogeneity, collapsed across target-present and target-absent trials. Bar graphs indicate mean power for area with significant main effect of heterogeneity (highlighted with black outline in each plot). (C) Cortical density maps.
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