Objective: Emotion recognition, an important aspect of social cognition, can be impaired already in early Alzheimer disease dementia and amnestic mild cognitive impairment (aMCI) and may underly social behavioral changes, which can increase caregiver burden. However, social behavior is difficult to assess in outpatient settings. We evaluated whether impaired emotion recognition is related to proxy-rated social behavioral problems and thus can serve as a marker of these changes.
Patients And Method: Emotion recognition was assessed with Ekman 60 Faces Test (EFT-total, 6 separate emotions) in patients (n = 31 AD; n = 37 aMCI) and healthy controls (n = 60 HCs). Social behavioral problems were rated by proxies with the neuropsychiatric inventory (agitation, apathy, irritability, disinhibition, and a sum score). It tested whether EFT scores differed between patients with and without behavioral problems.
Results: AD had worse EFT-total ( P <0.001), disgust ( P = 0.02), and fear ( P = 0.001) than HC, but not than aMCI, who did not differ from HC. AD displayed more disinhibition ( P < 0.05). EFT and neuropsychiatric inventory sum scores were not significantly correlated. Patients with apathy had lower EFT-total ( P = 0.02).
Conclusions: Measuring emotion recognition adds value: it is impaired in early neurodegeneration and associated with apathy but not necessarily related to overall changes in social behavior in this population.
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http://dx.doi.org/10.1097/WAD.0000000000000567 | DOI Listing |
Pilot Feasibility Stud
January 2025
Department of Health Service & Population Research, David Goldberg Centre, King's College London, Denmark Hill, London, UK.
Background: Mental health disorders are one of the leading causes of illness globally. The importance of psychosocial skills acquired in early childhood, such as executive functions, inhibitory control, emotional regulation, and social problem-solving, in preventing mental disorders has been reported. Furthermore, mental health care delivery is evolving, and mobile technology is becoming the medium for assessment and intervention.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of AI Convergence, Sungshin Women's University, 34 da-gil 2, Bomun-ro, Seongbuk-gu, Seoul 02844, Republic of Korea.
This paper proposes a machine learning approach to detect threats using short-term PPG (photoplethysmogram) signals from a commercial smartwatch. In supervised learning, having accurately annotated training data is essential. However, a key challenge in the threat detection problem is the uncertainty regarding how accurately data labeled as 'threat' reflect actual threat responses since participants may react differently to the same experiments.
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 PDFJ Neurosci
January 2025
Department of Psychology, Chinese University of Hong Kong, Hong Kong SAR, China
The extraction and analysis of pitch underpin speech and music recognition, sound segregation, and other auditory tasks. Perceptually, pitch can be represented as a helix composed of two factors: height monotonically aligns with frequency, while chroma cyclically repeats at doubled frequencies. Although the early perceptual and neurophysiological mechanisms for extracting pitch from acoustic signals have been extensively investigated, the equally essential subsequent stages that bridge to high-level auditory cognition remain less well understood.
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.
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