Spatial frequency and valence interact in complex emotion perception

Cassidy, Brittany S.; Wiley, Robert W.; Sim, Mattea; Hugenberg, Kurt

doi:10.1080/02699931.2021.1979474

Cited by 7 publications

(5 citation statements)

References 22 publications

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“…First, these data were collected online and thus could not control for viewing distance or lighting (both of which influence the information available to the retina). However, in light of our findings supporting patterns seen in previous work (e.g., Smith & Schyns, 2009) and other research that has used similar online methodology to examine the effects of spatial frequency filtering on emotion perception (Cassidy et al, 2021), we do not believe this is a major concern for interpreting these findings. Future research should directly compare online to in-lab spatial frequency experiments to gain a better understanding of the sensitivity of these effects to minor environmental differences.…”

Section: Discussionsupporting

confidence: 88%

The effects of spatial frequency on the decoding of emotional facial expressions.

Wylie,

Tracy,

Young

2023

Emotion

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The accurate identification of emotion is critical to effectively navigating our social lives. However, it is not clear how distinct types of visual information afford the accurate perception of others' emotion states. Here, we sought to examine the influence of different spatial frequency visual information on emotion categorization, and whether distinctive emotional dimensions (valence and arousal) are differentially influenced by specific spatial frequency content. Across one pilot and two experiments (N = 603), we tested whether emotional facial expressions that vary in valence, arousal, and functional significance differ in accuracy of categorization as a function of low, intact, and high spatial frequency band information. Overall, we found a general decrease in the breadth of emotional expressions for filtered images but did not see a decrease in accuracy of categorization for the positive emotion, joy. Together, these results suggest that spatial frequency information influences perception of emotional expressions that differ in valence and arousal.

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Section: Discussionsupporting

confidence: 88%

The effects of spatial frequency on the decoding of emotional facial expressions.

Wylie,

Tracy,

Young

2023

Emotion

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“…Indeed, this is in line with the idea that there is a flexible use of spatial frequencies for facial expression decoding. Different frequencies would be extracted depending on the expression (Cassidy et al, 2021;Morrison & Schyns, 2001;Oliva & Schyns, 1997;Smith et al, 2005) and the task (Schyns & Oliva, 1999;Smith & Merlusca, 2014). For example, Schyns and Oliva found that when participants were asked to categorise facial expressions as angry, happy or neutral, they relied more on LSF information whereas they relied on HSF when they had to indicate whether the face was expressive or neutral (Schyns & Oliva, 1999), a result that is consistent with our data.…”

Section: A Primary Use Of Hsf Despite the Statistical Sufficiency Of ...supporting

confidence: 88%

“…Also, several studies underlined a more flexible use of spatial frequencies to decode facial expressions, occurring later in the time course of visual processing (Schyns et al, 2009). Different spatial frequency bands would be used depending on the facial expression (Cassidy et al, 2021;Kumar et al 2011, Morrison & Schyns, 2001Oliva & Schyns, 1997; and the task (Schyns & Oliva, 1999;Smith & Merlusca, 2014). For example, fearful face categorisation might rely mostly on the wide-opened eyes and therefore on the extraction of HSF, whereas a larger scale would be used for other expressions (Adolphs et al, 2005;M.…”

Section: Introductionmentioning

confidence: 99%

Detection of emotional faces: the role of spatial frequencies and local features

ENTZMANN¹,

Guyader²,

Kauffmann³

et al. 2022

Preprint

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Models of emotion processing suggest that threat-related stimuli such as fearful faces can be detected based on the rapid extraction of low spatial frequencies. However, this remains debated as other models argue that the decoding of facial expressions occurs with a more flexible use of spatial frequencies. The purpose of this study was to clarify the role of spatial frequencies and differences in luminance contrast between spatial frequencies, on the detection of facial emotions. We used a saccadic choice task in which emotional-neutral face pairs were presented and participants were asked to make a saccade toward the neutral or the emotional (happy or fearful) face. Faces were displayed either in low, high, or broad spatial frequencies. Results showed that participants were better to saccade toward the emotional face. They were also better for high or broad than low spatial frequencies, and the accuracy was higher with a happy target. An analysis of the eye and mouth saliency of our stimuli revealed that the mouth saliency of the target correlates with participants’ performance. Overall, this study underlines the importance of local more than global information, and of the saliency of the mouth region in the detection of emotional and neutral faces.

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“…Different studies revealed that each route is specialised in encoding specific features of the stimuli, with facial sex and identity preferentially processed by the cortical route, primarily based on the analysis of the High Spatial Frequencies (HSF) of the stimulus, and with emotional expressions preferentially processed through the subcortical route, which is primarily based on the analysis of the Low Spatial Frequencies (LSF) of the image (Lacroix et al 2021 ; Vuilleumier et al 2003 ; Williams et al 2004 ). Interestingly, some evidence also suggests an association between different ranges of spatial frequencies and specific emotional expressions (Cassidy et al 2021 ; Kumar and Srinivasan 2011 ), making the field of the cortical/subcortical correlates of facial expressions even more complex.…”

Section: Introductionmentioning

confidence: 99%

Detecting implicit and explicit facial emotions at different ages

Prete,

Ceccato,

Bartolini

et al. 2024

Eur J Ageing

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Emotions are processed in the brain through a cortical route, responsible for detailed-conscious recognition and mainly based on image High Spatial Frequencies (HSF), and a subcortical route, responsible for coarse-unconscious processing and based on Low SF (LSF). However, little is known about possible changes in the functioning of the two routes in ageing. In the present go/no-go online task, 112 younger adults and 111 older adults were asked to press a button when a happy or angry face appeared (go) and to inhibit responses for neutral faces (no-go). Facial stimuli were presented unfiltered (broadband image), filtered at HSF and LSF, and hybrids (LSF of an emotional expression superimposed to the HSF of the same face with a neutral expression). All stimuli were also presented rotated on the vertical axis (upside-down) to investigate the global analysis of faces in ageing. Results showed an overall better performance of younger compared to older participants for all conditions except for hybrid stimuli. The expected face-inversion effect was confirmed in both age groups. We conclude that, besides an overall worsening of the perceptual skill with ageing, no specific impairment in the functioning of both the cortical and the subcortical route emerged.

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Spatial frequency and valence interact in complex emotion perception

Cited by 7 publications

References 22 publications

The effects of spatial frequency on the decoding of emotional facial expressions.

The effects of spatial frequency on the decoding of emotional facial expressions.

Detection of emotional faces: the role of spatial frequencies and local features

Detecting implicit and explicit facial emotions at different ages

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