Selective and interactive neural correlates of visual dimension changes and response changes

Pollmann, Stefan; Weidner, Ralph; Müller, Hermann J.; Maertens, Marianne; Cramon, D. Yves von

doi:10.1016/j.neuroimage.2005.09.013

Cited by 38 publications

(42 citation statements)

References 52 publications

(59 reference statements)

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“…Of note, the present findings closely match the results of previous studies investigating target dimension and target feature changes, despite the fact that these studies used different tasks (i.e., compound search task) and stimuli (e.g., Eimer et al, 2010;Kristjansson et al, 2007;Pollmann et al, 2006;Töllner et al, 2008). Yet, previous work often interpreted the findings very differently, with the greatest discrepancy being that switch costs due to target dimension changes were often attributed to early attentional processes (e.g., Pollmann et al, 2000Pollmann et al, , 2006Töllner et al, 2008).…”

Section: Theoretical Implicationssupporting

confidence: 90%

“…Yet, previous work often interpreted the findings very differently, with the greatest discrepancy being that switch costs due to target dimension changes were often attributed to early attentional processes (e.g., Pollmann et al, 2000Pollmann et al, , 2006Töllner et al, 2008).…”

Section: Theoretical Implicationsmentioning

confidence: 98%

“…Then, to extract differences that are specific to the different kinds of intertrial changes, we contrasted dimension change trials with feature change trials. Both contrasts were computed by linearly combining the respective contrasts from lower-level analyses across sessions and subjects (e.g., Pollmann et al, 2006), and by using permutation testing (FSL's randomise function; 5,000 permutations; Hayasaka & Nichols, 2003). All voxel-wise statistical comparisons are reported at an FDR-corrected alpha level of .05, and only clusters with a minimum voxel cluster size of >27 voxels are reported.…”

Section: Fmrimentioning

confidence: 99%

“…For example, in a target present/absent search task, changing the target dimension (e.g., from a color to a size target) would automatically create a bias to change the response as well, which would lead to switch costs when the target changes but the instructed response is the same as on the previous trial (e.g., a target present response; Becker, 2008aBecker, , 2010aCohen & Magen, 1999;Mortier, Theeuwes & Starreveld, 2005;Pollmann et al, 2006;Yashar & Lamy, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Second, electroencephalography (EEG) studies have found that swapping the target and non-target features leads to large delays in the onset of the N2pc (~50ms; Eimer, Kiss & Cheung, 2010), an electrophysiological marker for spatial attentional selection (e.g., Eimer, 1996;Luck & Hillyard, 1994), whereas dimension changes have only small effects on N2pc latencies (~8ms; e.g., Töllner et al, 2008;6ms, Töllner et al, 2010, Rangelov et al, 2013 that cannot account for the substantial RT delay of 30-50ms. Third, functional imaging data show that feature changes lead to an increased BOLD response in early visual areas (e.g., occipital cortex; Kristjansson et al, 2007), whereas dimension changes had no consistent effects on early visual areas, but instead led to increased activation of a dorsolateral pre-frontal network (DLPFC; Gramann et al, 2007Gramann et al, , 2010Pollmann et al, 2000Pollmann et al, , 2006Weidner et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

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

2014

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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.

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Section: Theoretical Implicationssupporting

confidence: 90%

Section: Theoretical Implicationsmentioning

confidence: 98%

Section: Fmrimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2014

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Biasing the organism for novelty: A pervasive property of the attention system

Chen¹,

Fuentes²,

Zhou³

2010

Human Brain Mapping

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Although the functional and anatomical independences between the orienting and the executive attention networks have been well established, surprisingly little is known about the potential neural interaction between them. Recent studies point out that spatial inhibition of return (IOR), a mechanism associated with the orienting network, and nonspatial inhibition of return, a mechanism associated with the executive network, might bias the organism for novel locations and objects, respectively. By orthogonally combining the spatial and the nonspatial IOR paradigms in this fMRI study, we demonstrate that the orienting and the executive networks interact and compensate each other in biasing the attention system for novelty. Behaviorally, participants responded slower to the target at the old location only when the color of the target was novel, and participants responded slower to the old color representation only when the target appeared at a novel spatial location. Neurally, the orienting network was involved in slowing down responses to the old location only when the nonspatial IOR mechanism in the executive network was not operative (i.e., when the color of the target was novel); the prefrontal executive network was involved in slowing down responses to the old color representation only when the spatial IOR mechanism in the orienting network was not functioning (i.e., when the target appeared at a novel location).

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Domain general and domain preferential brain regions associated with different types of task switching: A Meta‐Analysis

Kim¹,

Cilles²,

Johnson³

et al. 2011

Human Brain Mapping

272

200

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One of our highest evolved functions as human beings is our capacity to switch between multiple tasks effectively. A body of research has identified a distributed frontoparietal network of brain regions which contribute to task switching. However, relatively less is known about whether some brain regions may contribute to switching in a domain-general manner while others may be more preferential for different kinds of switching. To explore this issue, we conducted three meta-analyses focusing on different types of task switching frequently used in the literature (perceptual, response, and context switching), and created a conjunction map of these distinct switch types. A total of 36 switching studies with 562 activation coordinates were analyzed using the activation likelihood estimation method. Common areas associated with switching across switch type included the inferior frontal junction and posterior parietal cortex. In contrast, domain-preferential activation was observed for perceptual switching in the dorsal portion of the premotor cortex and for context switching in frontopolar cortex. Our results suggest that some regions within the frontoparietal network contribute to domain-general switching processes while others contribute to more domain-preferential processes, according to the type of task switch performed.

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Selective and interactive neural correlates of visual dimension changes and response changes

Cited by 38 publications

References 52 publications

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

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

Biasing the organism for novelty: A pervasive property of the attention system

Domain general and domain preferential brain regions associated with different types of task switching: A Meta‐Analysis

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