Facial expression is theorized to be visually represented in a multidimensional expression space, relative to a norm. This norm-based coding is typically argued to be implemented by a two-pool opponent coding system. However, the evidence supporting the opponent coding of expression cannot rule out the presence of a third channel tuned to the center of each coded dimension. Here we used a paradigm not previously applied to facial expression to determine whether a central-channel model is necessary to explain expression coding. Participants identified expressions taken from a fear/antifear trajectory, first at baseline and then in two adaptation conditions. In one condition, participants adapted to the expression at the center of the trajectory. In the other condition, participants adapted to alternating images from the two ends of the trajectory. The range of expressions that participants perceived as lying at the center of the trajectory narrowed in both conditions, a pattern that is not predicted by the central-channel model but can be explained by the opponent-coding model. Adaptation to the center of the trajectory also increased identification of both fear and antifear, which may indicate a functional benefit for adaptive coding of facial expression.
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http://dx.doi.org/10.1167/15.1.1 | DOI Listing |
Cancers (Basel)
December 2024
Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, Ludwig Maximilian University of Munich (LMU), 80337 Munich, Germany.
Skin cancer is one of the most prevalent malignancies in the world, with increasing incidence. In 2022, the World Health Organization estimated over 1.5 million new diagnoses of skin malignancies, primarily affecting the older population.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Computer Science, Tunghai University, Taichung 407224, Taiwan.
Background And Objective: Cardiovascular disease (CVD), one of the chronic non-communicable diseases (NCDs), is defined as a cardiac and vascular disorder that includes coronary heart disease, heart failure, peripheral arterial disease, cerebrovascular disease (stroke), congenital heart disease, rheumatic heart disease, and elevated blood pressure (hypertension). Having CVD increases the mortality rate. Emotional stress, an indirect indicator associated with CVD, can often manifest through facial expressions.
View Article and Find Full Text PDFeNeuro
January 2025
Department of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi 441-8580, Japan
The relationships between facial expression and color affect human cognition functions such as perception and memory. However, whether these relationships influence selective attention and brain activity contributed to selective attention remains unclear. For example, reddish angry faces increase emotion intensity, but it is unclear whether brain activity and selective attention are similarly enhanced.
View Article and Find Full Text PDFSci Rep
January 2025
MIRAI Technology Institute, Shiseido Co., Ltd., 1-2-11 Takashima, Nishi-ku, Yokohama, 220-0011, Kanagawa, Japan.
Like the lines themselves, concerns about facial wrinkles, particularly glabellar lines - the prominent furrows between the eyebrows - intensify with age. These lines can inadvertently convey negative emotions due to their association with negative facial expressions. We investigated the effects of repeated frowning on the development of temporary glabellar lines through the activation of the corrugator muscle.
View Article and Find Full Text PDFJ Oral Facial Pain Headache
March 2024
Department of Oral and Maxillofacial Surgery, Peking University School of Stomatology, 100081 Beijing, China.
Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysiology and developing effective analgesics. However, pain assessment methods for TN mouse models have not been widely studied, resulting in a critical gap in our understanding of TN. With the rapid advancement of deep learning, numerous pain assessment methods based on deep learning have emerged.
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