2016
DOI: 10.1016/j.neulet.2016.09.017
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Detecting facial emotion recognition deficits in schizophrenia using dynamic stimuli of varying intensities

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Cited by 22 publications
(18 citation statements)
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References 65 publications
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“…Dynamic, audio-visual emotion perception was found to be impaired in patients with SCZ compared to healthy individuals, as demonstrated by poorer overall performance (lower accuracy, response speed, ability to discriminate emotional videos and greater omissions). This is in line with previous research showing that dynamic emotion perception is impaired in general in schizophrenia (Chan et al, 2010;Feingold et al, 2016;Hargreaves et al, 2016;Huang et al, 2013;Johnston et al, 2010) and may reflect domain-general deficits, such as poor attention. In addition, patients with SCZ had less activity in the superior temporal gyri, often implicated in audio-visual integration and representation of dynamic emotional expressions (Robins et al, 2009;Said et al, 2010).…”
Section: Discussionsupporting
confidence: 93%
See 1 more Smart Citation
“…Dynamic, audio-visual emotion perception was found to be impaired in patients with SCZ compared to healthy individuals, as demonstrated by poorer overall performance (lower accuracy, response speed, ability to discriminate emotional videos and greater omissions). This is in line with previous research showing that dynamic emotion perception is impaired in general in schizophrenia (Chan et al, 2010;Feingold et al, 2016;Hargreaves et al, 2016;Huang et al, 2013;Johnston et al, 2010) and may reflect domain-general deficits, such as poor attention. In addition, patients with SCZ had less activity in the superior temporal gyri, often implicated in audio-visual integration and representation of dynamic emotional expressions (Robins et al, 2009;Said et al, 2010).…”
Section: Discussionsupporting
confidence: 93%
“…Naturalistic emotion displays may better capture the complex neural processes associated with emotion perception (Arsalidou et al, 2011). In line with previous studies (Hargreaves et al, 2016;Johnston et al, 2010) we predicted that SCZ patients would have deficits in discriminating dynamic emotion perception in general, with greater deficits compared to healthy controls when emotion perception relies on prior expectations (Chambon et al, 2011); in other words, detecting emotions congruent with prior expectations. At the neural level, we predicted reduced activation in frontal regions in patients with SCZ during emotion perception that is congruent with prior expectations (Anticevic et al, 2014;Barbalat et al, 2013).…”
Section: Introductionsupporting
confidence: 82%
“…Specifically, we found that patients had lower accuracy, response speed and ability to discriminate emotional videos, in line with previous research Feingold et al, 2016;Hargreaves et al, 2016;Huang et al, 2013;Johnston et al, 2010). In addition, patients with SCZ had less activity in the superior temporal gyri, a region often implicated in audio-visual integration and representation of dynamic emotional expressions (Robins et al, 2009;Said et al, 2010).…”
Section: Discussionsupporting
confidence: 91%
“…In line with previous studies (Hargreaves et al, 2016;Johnston et al, 2010) we predicted that SCZ patients would have deficits in discriminating dynamic emotion perception in general, with greater deficits compared to healthy controls when emotion perception requires precise prior expectations (Adams et al, 2016); in other words, detecting emotions congruent with prior expectations. At the neural level, we predicted reduced activation in frontal regions in patients with SCZ during emotion perception that is congruent with prior expectations (Adams et al, 2016;Anticevic et al, 2014).…”
Section: Introductionsupporting
confidence: 86%
“…Emotion recognition is an active research topic in the affective computing community. During the last decade, emotion recognition systems have been integrated in a number of applications across a growing number of domain fields such as cognitive science [31], clinical diagnosis [15], entertainment [38] and human-machine interaction [3]. Automatic emotion analysis and recognition in realworld videos (i.e.…”
Section: Introductionmentioning
confidence: 99%