2019
DOI: 10.1101/869552
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Feature-specific patterns of attention and functional connectivity in human visual cortex

Abstract: Attending to different features of a scene can alter the responses of neurons in early- and mid- level visual areas but the nature of this change depends on both the (top down) attentional task and the (bottom up) visual stimulus. One outstanding question is the spatial scale at which cortex is modulated by attention to low-level stimulus features such as shape, contrast and orientation. It is unclear whether the recruitment of neurons to particular tasks occurs at an area level or at the level of intra-areal … Show more

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Cited by 3 publications
(2 citation statements)
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“…It is also not yet clear whether feedback signals observed in this study are common with those reported in visual attention studies because the task is different and the effect of attention on visual areas along the hierarchy was variable across studies. [52][53][54][55][56][57] Previous studies suggested preserved retinotopic organization in V1 of JMD patients 58 and congenital bilateral anophthalmia. 59 Consistent with this idea, the task-dependent V1 LPZ ll responses of JMD patients observed in this study suggest preservation rather than remapping of retinotopy.…”
Section: Report Discussionmentioning
confidence: 97%
“…It is also not yet clear whether feedback signals observed in this study are common with those reported in visual attention studies because the task is different and the effect of attention on visual areas along the hierarchy was variable across studies. [52][53][54][55][56][57] Previous studies suggested preserved retinotopic organization in V1 of JMD patients 58 and congenital bilateral anophthalmia. 59 Consistent with this idea, the task-dependent V1 LPZ ll responses of JMD patients observed in this study suggest preservation rather than remapping of retinotopy.…”
Section: Report Discussionmentioning
confidence: 97%
“…Classification accuracy was then averaged across validation sets, for each condition, and across participants, for each ROI and task, separately. The resulting accuracies were then tested against chance performance using one-sample tests (Kriegeskorte et al, 2007; Wailes-Newson et al, 2019) for each ROI separately, with ɑ-level Bonferroni corrected for effects of stimulus category (the higher the classification accuracy, the more distinct the representations of different regular patterns are for a specific area in the visual cortex). Performance of each independent ROI classifier is measured by percent correct classification (accuracy), with the null hypothesis of the classifier to perform at chance level (e.g., 50% for a two-way classification routine).…”
Section: Data Analysesmentioning
confidence: 99%