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Automated analysis of facial emotions in subjects with cognitive impairment.

ABSTRACT: Differences in expressing facial emotions are broadly observed in people with cognitive impairment. However, these differences have been difficult to objectively quantify and systematically evaluate among people with cognitive impairment across disease etiologies and severity. Therefore, a computer vision-based deep learning model for facial emotion recognition trained on 400.000 faces was utilized to analyze facial emotions expressed during a passive viewing memory test. In addition, this study was conducted on a large number of individuals (n = 493), including healthy controls and individuals with cognitive impairment due to diverse underlying etiologies and across different disease stages. Diagnoses included subjective cognitive impairment, Mild Cognitive Impairment (MCI) due to AD, MCI due to other etiologies, dementia due to Alzheimer's diseases (AD), and dementia due to other etiologies (e.g., Vascular Dementia, Frontotemporal Dementia, Lewy Body Dementia, etc.). The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance across all participants. A participant with a score of less than or equal to 24 was considered cognitively impaired (CI). Compared to cognitively unimpaired (CU) participants, CI participants expressed significantly less positive emotions, more negative emotions, and higher facial expressiveness during the test. In addition, classification analysis revealed that facial emotions expressed during the test allowed effective differentiation of CI from CU participants, largely independent of sex, race, age, education level, mood, and eye movements (derived from an eye-tracking-based digital biomarker for cognitive impairment). No screening methods reliably differentiated the underlying etiology of the cognitive impairment. The findings provide quantitative and comprehensive evidence that the expression of facial emotions is significantly different in people with cognitive impairment, and suggests this may be a useful tool for passive screening of cognitive impairment.

SUBMITTER: Jiang Z

PROVIDER: S-EPMC8782312 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Until recently, research in animal welfare science has mainly focused on negative experiences like pain and suffering, often neglecting the importance of assessing and promoting positive experiences. In rodents, specific facial expressions have been found to occur in situations thought to induce negatively valenced emotional states (e.g., pain, aggression and fear), but none have yet been identified for positive states. Thus, this study aimed to investigate if facial expressions indicative of positive emotional state are exhibited in rats. Adolescent male Lister Hooded rats (Rattus norvegicus, N = 15) were individually subjected to a Positive and a mildly aversive Contrast Treatment over two consecutive days in order to induce contrasting emotional states and to detect differences in facial expression. The Positive Treatment consisted of playful manual tickling administered by the experimenter, while the Contrast Treatment consisted of exposure to a novel test room with intermittent bursts of white noise. The number of positive ultrasonic vocalisations was greater in the Positive Treatment compared to the Contrast Treatment, indicating the experience of differentially valenced states in the two treatments. The main findings were that Ear Colour became significantly pinker and Ear Angle was wider (ears more relaxed) in the Positive Treatment compared to the Contrast Treatment. All other quantitative and qualitative measures of facial expression, which included Eyeball height to width Ratio, Eyebrow height to width Ratio, Eyebrow Angle, visibility of the Nictitating Membrane, and the established Rat Grimace Scale, did not show differences between treatments. This study contributes to the exploration of positive emotional states, and thus good welfare, in rats as it identified the first facial indicators of positive emotions following a positive heterospecific play treatment. Furthermore, it provides improvements to the photography technique and image analysis for the detection of fine differences in facial expression, and also adds to the refinement of the tickling procedure.

Project description:ObjectiveTo estimate the incidence of psychotic symptoms in Alzheimer's disease.MethodsThe study consists of 776 elderly subjects presenting to the Alzheimer Disease Research Center at the University of Pittsburgh (Pittsburgh, Pennsylvania) between May 9, 2000, and August 19, 2014. All participants were diagnosed with mild cognitive impairment (National Institute on Aging-Alzheimer's Association workgroup criteria) or possible or probable Alzheimer's disease (National Institute of Neurologic and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association criteria) and were without psychosis at entry. Psychotic symptoms were evaluated using the Consortium to Establish a Registry for Alzheimer's Disease Behavioral Rating Scale every 6 months. One-, 3- and 5-year cumulative incidences of psychosis were calculated.ResultsThe 1-year psychosis incidence was 10% (95% CI, 8%-12%), and this annual rate remained remarkably consistent at 3 and 5 years. Psychosis incidence was related to cognitive status at all time points. However, the incidence rate reached a plateau during the disease course. Cumulative psychosis incidence at 5 years was 61% (95% CI, 52%-69%) in individuals with moderate to severe Alzheimer's disease, not statistically significantly different from the cumulative incidence at 3 years in this group, which was 48% (95% CI, 40%-55%) or from the 5-year incidence in individuals who entered the study with mild Alzheimer's disease, which was 48% (95% CI, 41%-56%).ConclusionsPsychosis in Alzheimer's disease has been associated with a number of adverse clinical outcomes. We provide estimates of the risk of psychosis onset within clinically defined subgroups of individuals, a tool clinicians can use in treatment planning. Anticipating which subjects are at high risk for psychosis and the poor outcomes associated with it can help with family education and support decisions to implement nonpharmacologic strategies that may reduce or prevent symptoms.

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Automated analysis of facial emotions in subjects with cognitive impairment.

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