Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI

Abstract

Publisher's copyright statement: NOTICE: this is the author's version of a work that was accepted for publication in NeuroImage. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be re ected in this document. Changes may have been made to this work since it was submitted for publication. A de nitive version was subsequently published in NeuroImage, 102, Part 2, 15 November 2014, 10.1016/j.neuroimage.2014.08.058. Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractIn visual search, responses are slowed, from one trial to the next, both when the target dimension changes (e.g., from a color target to a size target) and when the target feature changes (e.g., from a red target to a green target) relative to being repeated across trials. The present study examined whether such feature and dimension switch costs can be attributed to the same underlying mechanism(s). Contrary to this contention, an EEG study showed that feature changes influenced visual selection of the target (i.e., delayed N2pc onset), whereas dimension changes influenced the later process of response selection (i.e., delayed s-LRP onset). An fMRI study provided convergent evidence for the two-system view: Compared with repetitions, feature changes led to increased activation in the occipital cortex, and superior and inferior parietal lobules, which have been implicated in spatial attention. By contrast, dimension changes led to activation of a frontoposterior network that is primarily linked with response selection (i.e., pre-motor cortex, supplementary motor area and frontal areas). Taken together, the results suggest that feature and dimension switch costs are based on different processes. Specifically, whereas target feature changes delay attention shifts to the target, target dimension changes interfere with later response selection operations.

Correlations between exploratory eye movement, hallucination, and cortical gray matter volume in people with schizophrenia

“…It is of importance to know whether some of these brain regions with the GMV positively correlated with RSS play a critical role in mediating the perceptual / cognitive / executive processes underlying the RSS. It has been known that in addition to the contribution of the SMA and precentral gyrus to eye-movement control [ 80 ], the SMA is involved in response selection operations in visual search tasks [ 81 ], perhaps through its functional connectivity with the posterior parietal cortex, which is the core cortical region for the visual search performance [ 82 ], especially when the cognitive demand becomes higher [ 83 ]. The SMA plays a role in both awareness of intention to make a physical movement [ 71 , 72 ] and mental imagery [ 69 , 73 ], which are also important to EEM.…”

Conjunction search is relational: Behavioral and electrophysiological evidence.

“…EEG data were referenced to the common average and filtered at 45Hz. Trials with artifacts (eye movements, or scalp channels exceeding +/-75µV) were excluded from the EEG data analysis (see Becker, Grubert & Dux, 2014, for a similar procedure).…”

Identification of Resting State Networks Involved in Executive Function

“…Network 11, a visual network involving the occipital poles, has been shown to be involved in attentional control when features of a target stimulus are changed (Becker et al, 2014;Kristjansson et al, 2007).…”