Functional Fractionation of the Stimulus-Driven Attention Network

Han, Suk Won; Marois, René

doi:10.1523/jneurosci.4975-13.2014

Cited by 51 publications

(77 citation statements)

References 175 publications

(17 reference statements)

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“…These findings do not necessarily imply that the right TPJ sends an early signal that triggers attentional reorienting. This idea was initially proposed by Corbetta and Shulman (2002), but more recent work provides evidence against an early reorienting signal in the right TPJ (Geng and Vossel, 2013;Macaluso and Doricchi, 2013;DiQuattro et al, 2014;Han and Marois, 2014). Instead, the TPJ might be involved in the updating of internal models (Geng and Vossel, 2013;Han and Marois, 2014) and the detection of mismatches between expected and actual stimuli (Doricchi et al, 2010).…”

Section: Discussionmentioning

confidence: 97%

“…This idea was initially proposed by Corbetta and Shulman (2002), but more recent work provides evidence against an early reorienting signal in the right TPJ (Geng and Vossel, 2013;Macaluso and Doricchi, 2013;DiQuattro et al, 2014;Han and Marois, 2014). Instead, the TPJ might be involved in the updating of internal models (Geng and Vossel, 2013;Han and Marois, 2014) and the detection of mismatches between expected and actual stimuli (Doricchi et al, 2010). Our present finding can be plausibly interpreted along these lines: depending on the confirmation or violation of the model predictions that the target appears at the cued location, the TPJ suppressed or boosted activity in the FEF (and, to a lesser degree, also in the putamen), respectively.…”

Section: Discussionmentioning

confidence: 97%

“…Before the functional scans, a B0 field map was acquired using a double-echo FLASH sequence for distortion correction of the acquired EPI images (Weiskopf et al, 2006). Field maps were estimated from the phase difference between the images acquired at the short and long TE using the FieldMap toolbox (Hutton et al, 2002). Additional high-resolution anatomical images (voxel size 1 ϫ 1 ϫ 1 mm 3 ) were acquired using a T1-weighted 3D MDEFT sequence (Deichmann et al, 2004).…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Cortical Coupling Reflects Bayesian Belief Updating in the Deployment of Spatial Attention

et al. 2015

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The deployment of visuospatial attention and the programming of saccades are governed by the inferred likelihood of events. In the present study, we combined computational modeling of psychophysical data with fMRI to characterize the computational and neural mechanisms underlying this flexible attentional control. Sixteen healthy human subjects performed a modified version of Posner's location-cueing paradigm in which the percentage of cue validity varied in time and the targets required saccadic responses. Trialwise estimates of the certainty (precision) of the prediction that the target would appear at the cued location were derived from a hierarchical Bayesian model fitted to individual trialwise saccadic response speeds. Trial-specific model parameters then entered analyses of fMRI data as parametric regressors. Moreover, dynamic causal modeling (DCM) was performed to identify the most likely functional architecture of the attentional reorienting network and its modulation by (Bayes-optimal) precision-dependent attention. While the frontal eye fields (FEFs), intraparietal sulcus, and temporoparietal junction (TPJ) of both hemispheres showed higher activity on invalid relative to valid trials, reorienting responses in right FEF, TPJ, and the putamen were significantly modulated by precision-dependent attention. Our DCM results suggested that the precision of predictability underlies the attentional modulation of the coupling of TPJ with FEF and the putamen. Our results shed new light on the computational architecture and neuronal network dynamics underlying the contextsensitive deployment of visuospatial attention.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 99%

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Cortical Coupling Reflects Bayesian Belief Updating in the Deployment of Spatial Attention

et al. 2015

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“…The two-network model of attentional control suggests that the ventral fronto-parietal network contributes a reorienting signal to the dorsal network in the presence of behaviorally relevant information in order to dynamically modulate goal-directed behavior (Corbetta et al, 2008;Greene and Soto, 2014;Han and Marois, 2013;Serences et al, 2005). Results of our activation and brain-behavior correlation analyses indicated that activation in the right AI during distractor onsets reflected change detection performance and predicted individual differences in distraction costs observed at test during Related and Matched array conditions.…”

Section: Right Ai Functional Connectivity (Fc) Analysismentioning

confidence: 70%

“…Recent work has focused on delineating the functional roles played by two major nodes of the ventral network, the right TPJ and the right AI (Greene and Soto, 2014;Han and Marois, 2013;Shulman et al, 2009). Current evidence suggests that while both regions are sensitive to attention arresting information, the right TPJ may play more of an evaluative role where the right…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Ventral fronto-parietal contributions to the disruption of visual working memory storage

Hakun

Ravizza

2016

NeuroImage

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The ability to maintain information in visual working memory (VWM) in the presence of ongoing visual input allows for flexible goal-directed behavior. Previous evidence suggests that categorical overlap between visual distractors and the contents of VWM is associated with both the degree to which distractors disrupt VWM performance and activation among fronto-parietal regions of cortex. While within-category distractors have been shown to elicit a greater response in ventral fronto-parietal regions, to date, no study has linked distractor-evoked response of these regions to VWM performance costs. Here we examined the contributions of ventral fronto-parietal cortex to the disruption of VWM storage by manipulating memoranda-distractor similarity. Our results revealed that the degree of activation across cortex was graded in a manner suggesting that similarity between the contents of VWM and visual distractors influenced distractor processing. While abrupt visual onsets failed to engage ventral fronto-parietal regions during VWM maintenance, objects sharing categorical- (Related objects) and feature-overlap (Matched objects) with VWM elicited a significant response in the right TPJ and right AI. Of central relevance, the magnitude of activation in the right AI elicited by both types of distractor objects subsequently predicted costs to binding change detection accuracy. In addition, Related and Matched distractors differentially affected ventral-dorsal connectivity between the right AI and dorsal parietal regions, uniquely contributing to disruption of VWM storage. Together, our current results implicate activation of ventral fronto-parietal cortex in disruption of VWM storage, and disconnection between ventral frontal and dorsal parietal cortices as a mechanism to protect the contents of VWM.

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Opposing effects of memory-driven and stimulus-driven attention on distractor perception

Han¹

2017

Cogn Process

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It is well known that a match between working memory contents and a visual stimulus creates attentional bias toward the memory-matching stimulus. The present study investigated whether this memory-driven attentional bias exerts similar effects with conventional, spatial attention driven by a cue stimulus. Specifically, we examined how the effect of a distracting, task-irrelevant stimulus is modulated when attention was oriented toward the distractor in memory- and stimulus-driven manners. The results showed that significant interference by a distractor decreased when attention was allocated to the distractor in a memory-driven manner, whereas the distracter captured attention in a stimulus-driven manner exerted increased interference. By contrast, memory-driven attention brought an unattended stimulus into attentional focus, while stimulus-driven attention failed to do so. These results provide evidence that the mechanisms underlying working memory-driven and stimulus-driven attention are separable, pointing to the dynamic and flexible relationship between working memory and attention.

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Functional Fractionation of the Stimulus-Driven Attention Network

Cited by 51 publications

References 175 publications

Cortical Coupling Reflects Bayesian Belief Updating in the Deployment of Spatial Attention

Cortical Coupling Reflects Bayesian Belief Updating in the Deployment of Spatial Attention

Ventral fronto-parietal contributions to the disruption of visual working memory storage

Opposing effects of memory-driven and stimulus-driven attention on distractor perception

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