Literature DB >> 24023273

An objective signature for visual binding of face parts in the human brain.

Adriano Boremanse1, Anthony M Norcia, Bruno Rossion.   

Abstract

Whether and how the parts of a visual object are grouped together to form an integrated ("holistic") representation is a central question in cognitive neuroscience. Although the face is considered to be the quintessential example of holistic representation, this issue has been the subject of much debate in face perception research. The implication of holistic processing is that the response to the whole cannot be predicted from the sum of responses to the parts. Here we apply techniques from nonlinear systems analysis to provide an objective measure of the nonlinear integration of parts into a whole, using the left and right halves of a face stimulus as the parts. High-density electroencephalogram (EEG) was recorded in 15 human participants presented with two halves of a face stimulus, flickering at different frequencies (5.88 vs. 7.14 Hz). Besides specific responses at these fundamental frequencies, reflecting part-based responses, we found intermodulation components (e.g., 7.14 - 5.88 = 1.26 Hz) over the right occipito-temporal hemisphere, reflecting nonlinear integration of the face halves. Part-based responses did not depend on the relative alignment of the two face halves, their spatial separation, or whether the face was presented upright or inverted. By contrast, intermodulations were virtually absent when the two halves were spatially misaligned and separated. Inversion of the whole face configuration also reduced specifically the intermodulation components over the right occipito-temporal cortex. These observations indicate that the intermodulation components constitute an objective, configuration-specific signature of an emergent neural representation of the whole face that is distinct from that generated by the parts themselves.

Entities:  

Keywords:  Gestalt; face perception; holistic perception; intermodulation; inversion; nonlinearity; ssVEP

Mesh:

Year:  2013        PMID: 24023273     DOI: 10.1167/13.11.6

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  18 in total

Review 1.  The steady-state visual evoked potential in vision research: A review.

Authors:  Anthony M Norcia; L Gregory Appelbaum; Justin M Ales; Benoit R Cottereau; Bruno Rossion
Journal:  J Vis       Date:  2015       Impact factor: 2.240

Review 2.  Exploring how musical rhythm entrains brain activity with electroencephalogram frequency-tagging.

Authors:  Sylvie Nozaradan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2014-12-19       Impact factor: 6.237

3.  Interaction Between Conscious and Unconscious Information-Processing of Faces and Words.

Authors:  Shiwen Ren; Hanyu Shao; Sheng He
Journal:  Neurosci Bull       Date:  2021-06-25       Impact factor: 5.203

4.  The perception of a familiar face is no more than the sum of its parts.

Authors:  Jason M Gold; Jarrett D Barker; Shawn Barr; Jennifer L Bittner; Alexander Bratch; W Drew Bromfield; Roy A Goode; Mary Jones; Doori Lee; Aparna Srinath
Journal:  Psychon Bull Rev       Date:  2014-12

5.  Does face-selective cortex show a left visual field bias for centrally-viewed faces?

Authors:  Matthew T Harrison; Lars Strother
Journal:  Neuropsychologia       Date:  2021-07-13       Impact factor: 3.054

6.  The power of rhythms: how steady-state evoked responses reveal early neurocognitive development.

Authors:  Claire Kabdebon; Ana Fló; Adélaïde de Heering; Richard Aslin
Journal:  Neuroimage       Date:  2022-03-26       Impact factor: 7.400

7.  Neural markers of predictive coding under perceptual uncertainty revealed with Hierarchical Frequency Tagging.

Authors:  Noam Gordon; Roger Koenig-Robert; Naotsugu Tsuchiya; Jeroen Ja van Boxtel; Jakob Hohwy
Journal:  Elife       Date:  2017-02-28       Impact factor: 8.140

8.  EEG frequency tagging dissociates between neural processing of motion synchrony and human quality of multiple point-light dancers.

Authors:  Nihan Alp; Andrey R Nikolaev; Johan Wagemans; Naoki Kogo
Journal:  Sci Rep       Date:  2017-03-08       Impact factor: 4.379

9.  Single-session label training alters neural competition between objects and faces.

Authors:  Gabriella Silva; Harold A Rocha; Ethan Kutlu; Maeve R Boylan; Lisa S Scott; Andreas Keil
Journal:  J Exp Psychol Hum Percept Perform       Date:  2021-01-21       Impact factor: 3.332

10.  Measuring Integration Processes in Visual Symmetry with Frequency-Tagged EEG.

Authors:  Nihan Alp; Peter Jes Kohler; Naoki Kogo; Johan Wagemans; Anthony Matthew Norcia
Journal:  Sci Rep       Date:  2018-05-03       Impact factor: 4.379

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