Literature DB >> 23183741

Spatial frequencies and emotional perception.

Andrea De Cesarei1, Maurizio Codispoti.   

Abstract

It has been suggested that, during evolution, specific mechanisms developed in order to optimize the detection of threats and opportunities even in perceptually degraded conditions. A naturalistic example of perceptual degradation can be found in blurry images, which contain the coarsest elements of a scene (low spatial frequencies) but lack the fine-grained details (high spatial frequencies). In the past decade, several studies have examined the relation between spatial frequencies and emotions, using a variety of methods, stimuli, and rationales. Here, we conduct a literature survey on the studies that have examined the relation between emotion and spatial frequencies. Some studies have suggested that the low spatial frequencies of emotional stimuli may be processed by a subcortical neural pathway, eventually eliciting emotional responses. However, the evidence provided by the reviewed studies does not support this possibility, for conceptual and methodological reasons (e.g., mistaking the processing of a fuzzy stimulus for subcortical processing). Here, the conceptual and methodological problems present in the reviewed studies are analyzed and discussed, along with suggestions for future research.

Mesh:

Year:  2013        PMID: 23183741     DOI: 10.1515/revneuro-2012-0053

Source DB:  PubMed          Journal:  Rev Neurosci        ISSN: 0334-1763            Impact factor:   4.353


  12 in total

1.  Electrocortical amplification for emotionally arousing natural scenes: the contribution of luminance and chromatic visual channels.

Authors:  Vladimir Miskovic; Jasna Martinovic; Matthias J Wieser; Nathan M Petro; Margaret M Bradley; Andreas Keil
Journal:  Biol Psychol       Date:  2015-01-29       Impact factor: 3.251

2.  Recognition memory for low- and high-frequency-filtered emotional faces: Low spatial frequencies drive emotional memory enhancement, whereas high spatial frequencies drive the emotion-induced recognition bias.

Authors:  Michaela Rohr; Johannes Tröger; Nils Michely; Alarith Uhde; Dirk Wentura
Journal:  Mem Cognit       Date:  2017-07

3.  A Rapid Subcortical Amygdala Route for Faces Irrespective of Spatial Frequency and Emotion.

Authors:  Jessica McFadyen; Martial Mermillod; Jason B Mattingley; Veronika Halász; Marta I Garrido
Journal:  J Neurosci       Date:  2017-03-10       Impact factor: 6.167

4.  How arousal modulates the visual contrast sensitivity function.

Authors:  Tae-Ho Lee; Jongsoo Baek; Zhong-Lin Lu; Mara Mather
Journal:  Emotion       Date:  2014-06-16

5.  Early spatial frequency processing of natural images: an ERP study.

Authors:  Andrea De Cesarei; Serena Mastria; Maurizio Codispoti
Journal:  PLoS One       Date:  2013-05-31       Impact factor: 3.240

6.  Can the Outputs of LGN Y-Cells Support Emotion Recognition? A Computational Study.

Authors:  Andrea De Cesarei; Maurizio Codispoti
Journal:  Comput Intell Neurosci       Date:  2015-06-15

7.  Trait Anxiety Is Associated with Negative Interpretations When Resolving Valence Ambiguity of Surprised Faces.

Authors:  Gewnhi Park; Michael W Vasey; Grace Kim; Dixie D Hu; Julian F Thayer
Journal:  Front Psychol       Date:  2016-08-03

8.  Deficits in attentional processing of fearful facial expressions in schizophrenic patients.

Authors:  Yunzhe Liu; Dandan Zhang; Yanli Zhao; Shuping Tan; Yuejia Luo
Journal:  Sci Rep       Date:  2016-09-02       Impact factor: 4.379

9.  Global Image Properties Predict Ratings of Affective Pictures.

Authors:  Christoph Redies; Maria Grebenkina; Mahdi Mohseni; Ali Kaduhm; Christian Dobel
Journal:  Front Psychol       Date:  2020-05-12

10.  Distinct effects of contrast and color on subjective rating of fearfulness.

Authors:  Zhengang Lu; Bingbing Guo; Anne Boguslavsky; Marcus Cappiello; Weiwei Zhang; Ming Meng
Journal:  Front Psychol       Date:  2015-10-08
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