scholarly journals Dissociation between the neural correlates of conscious face perception and visual attention

2017 ◽  
Vol 54 (8) ◽  
pp. 1138-1150 ◽  
Author(s):  
Joaquin Navajas ◽  
Aleksander W. Nitka ◽  
Rodrigo Quian Quiroga
2017 ◽  
Vol 12 (8) ◽  
pp. 1342-1350
Author(s):  
Wookyoung Jung ◽  
Joong-Gu Kang ◽  
Hyeonjin Jeon ◽  
Miseon Shim ◽  
Ji Sun Kim ◽  
...  

2019 ◽  
Vol 9 (11) ◽  
pp. 315 ◽  
Author(s):  
Andrea Orlandi ◽  
Alice Mado Proverbio

It has been shown that selective attention enhances the activity in visual regions associated with stimulus processing. The left hemisphere seems to have a prominent role when non-spatial attention is directed towards specific stimulus features (e.g., color, spatial frequency). The present electrophysiological study investigated the time course and neural correlates of object-based attention, under the assumption of left-hemispheric asymmetry. Twenty-nine right-handed participants were presented with 3D graphic images representing the shapes of different object categories (wooden dummies, chairs, structures of cubes) which lacked detail. They were instructed to press a button in response to a target stimulus indicated at the beginning of each run. The perception of non-target stimuli elicited a larger anterior N2 component, which was likely associated with motor inhibition. Conversely, target selection resulted in an enhanced selection negativity (SN) response lateralized over the left occipito-temporal regions, followed by a larger centro-parietal P300 response. These potentials were interpreted as indexing attentional selection and categorization processes, respectively. The standardized weighted low-resolution electromagnetic tomography (swLORETA) source reconstruction showed the engagement of a fronto-temporo-limbic network underlying object-based visual attention. Overall, the SN scalp distribution and relative neural generators hinted at a left-hemispheric advantage for non-spatial object-based visual attention.


2014 ◽  
Vol 26 (5) ◽  
pp. 927-937 ◽  
Author(s):  
Shai Gabay ◽  
Adrian Nestor ◽  
Eva Dundas ◽  
Marlene Behrmann

The ability to recognize faces accurately and rapidly is an evolutionarily adaptive process. Most studies examining the neural correlates of face perception in adult humans have focused on a distributed cortical network of face-selective regions. There is, however, robust evidence from phylogenetic and ontogenetic studies that implicates subcortical structures, and recently, some investigations in adult humans indicate subcortical correlates of face perception as well. The questions addressed here are whether low-level subcortical mechanisms for face perception (in the absence of changes in expression) are conserved in human adults, and if so, what is the nature of these subcortical representations. In a series of four experiments, we presented pairs of images to the same or different eyes. Participants' performance demonstrated that subcortical mechanisms, indexed by monocular portions of the visual system, play a functional role in face perception. These mechanisms are sensitive to face-like configurations and afford a coarse representation of a face, comprised of primarily low spatial frequency information, which suffices for matching faces but not for more complex aspects of face perception such as sex differentiation. Importantly, these subcortical mechanisms are not implicated in the perception of other visual stimuli, such as cars or letter strings. These findings suggest a conservation of phylogenetically and ontogenetically lower-order systems in adult human face perception. The involvement of subcortical structures in face recognition provokes a reconsideration of current theories of face perception, which are reliant on cortical level processing, inasmuch as it bolsters the cross-species continuity of the biological system for face recognition.


2020 ◽  
Vol 11 ◽  
Author(s):  
Viktoria Ritter ◽  
Jürgen M. Kaufmann ◽  
Franziska Krahmer ◽  
Holger Wiese ◽  
Ulrich Stangier ◽  
...  

Author(s):  
Daan Scheepers ◽  
Belle Derks ◽  
Sander Nieuwenhuis ◽  
Gert-Jan Lelieveld ◽  
Félice Van Nunspeet ◽  
...  

NeuroImage ◽  
2011 ◽  
Vol 54 (3) ◽  
pp. 2547-2555 ◽  
Author(s):  
Vaidehi Natu ◽  
David Raboy ◽  
Alice J. O'Toole

2018 ◽  
Author(s):  
Brad Wyble ◽  
Chloe Callahan-Flintoft ◽  
Hui Chen ◽  
Toma Marinov ◽  
Aakash Sarkar ◽  
...  

AbstractA quintessential challenge for any perceptual system is the need to focus on task-relevant information without being blindsided by unexpected, yet important information. The human visual system incorporates several solutions to this challenge, one of which is a reflexive covert attention system that is rapidly responsive to both the physical salience and the task-relevance of new information. This paper presents a model that simulates behavioral and neural correlates of reflexive attention as the product of brief neural attractor states that are formed across the visual hierarchy when attention is engaged. Such attractors emerge from an attentional gradient distributed over a population of topographically organized neurons and serve to focus processing at one or more locations in the visual field, while inhibiting the processing of lower priority information. The model moves towards a resolution of key debates about the nature of reflexive attention, such as whether it is parallel or serial, and whether suppression effects are distributed in a spatial surround, or selectively at the location of distractors. Most importantly, the model develops a framework for understanding the neural mechanisms of visual attention as a spatiotopic decision process within a hierarchy and links them to observable correlates such as accuracy, reaction time, and the N2pc and PD components of the EEG. This last contribution is the most crucial for repairing the disconnect that exists between our understanding of behavioral and neural correlates of attention.


2010 ◽  
Vol 8 (6) ◽  
pp. 407-407 ◽  
Author(s):  
M. Meng ◽  
G. Singal ◽  
T. Cherian ◽  
P. Sinha

Sign in / Sign up

Export Citation Format

Share Document