computational model mental illness

The purpose of this work is to analyze how new technologies can enhance clinical practice while also examining the physical traits of emotional expressiveness of face expression in a number of psychiatric illnesses. Hence, in this work, an automatic facial expression recognition system has been proposed that analyzes static, sequential, or video facial images from medical healthcare data to detect emotions in people's facial regions. The proposed method has been implemented in five steps. The first step is image preprocessing, where a facial region of interest has been segmented from the input image...

The clinical burden of mental illness, in particular schizophrenia and bipolar disorder, are driven by frequent chronic courses and increased mortality, as well as the risk for comorbid conditions such as cardiovascular disease and type 2 diabetes. Evidence suggests an overlap of molecular pathways between psychotic disorders and somatic comorbidities. In this study, we developed a computational framework to perform comorbidity modeling via an improved integrative unsupervised machine learning approach based on multi-rank non-negative matrix factorization (mrNMF)...

BACKGROUND: Altered neural haemodynamic activity during decision making and learning has been linked to the effects of inflammation on mood and motivated behaviours. So far, it has been reported that blunted mesolimbic dopamine reward signals are associated with inflammation-induced anhedonia and apathy. Nonetheless, it is still unclear whether inflammation impacts neural activity underpinning decision dynamics. The process of decision making involves integration of noisy evidence from the environment until a critical threshold of evidence is reached...

BACKGROUND: Previous research has demonstrated that both sleep and physical activity (PA) are independently associated with various indicators of mental health among adults. However, their joint contribution to mental health has received limited attention. The present study used cross-sectional data from the Mental Health Million Project to examine the independent and joint effects of sleep and PA on mental health among a global sample of adults, and whether these effects differ among individuals receiving mental health treatment...

Data on the chronicity of mental disorder in children with chronic physical illness (CPI) are limited. We examined the prevalence and predictors of homotypic and heterotypic continuity of mental disorder in children with CPI. A sample of 263 children aged 2-16 years with physician-diagnosed CPI were recruited from outpatient clinics (e.g., dermatology, respiratory) at a Canadian pediatric academic hospital and followed for 24 months. Parent and child-reported mental disorders (mood, anxiety, behavioral, attention-deficit hyperactivity disorder [ADHD]) were assessed using the Mini International Neuropsychiatric Interview for Children and Adolescents at baseline, 6, 12, and 24 months...

Organisms learn to gain reward and avoid punishment through action-outcome associations. Reinforcement learning (RL) offers a critical framework to understand individual differences in this associative learning by assessing learning rate, action bias, Pavlovian factor (i.e., the extent to which action values are influenced by stimulus values), and subjective impact of outcomes (i.e., motivation to seek reward and avoid punishment). Nevertheless, how these individual-level metrics are represented in the brain remains unclear...

INTRODUCTION: The disconnected-interacting protein 2 homolog A (DIP2A), a member of disconnected-interacting 2 protein family, has been shown to be involved in human nervous system-related mental illness. This protein is highly expressed in the nervous system of mouse. Mutation of mouse DIP2A causes defects in spine morphology and synaptic transmission, autism-like behaviors, and defective social novelty [5], [27], indicating that DIP2A is critical to the maintenance of neural development...

Deficient gamma oscillations in prefrontal cortex (PFC) of individuals with schizophrenia appear to involve impaired inhibitory drive from parvalbumin-expressing interneurons (PVIs). Inhibitory drive from PVIs is regulated, in part, by RNA binding fox-1 homolog 1 (Rbfox1). Rbfox1 is spliced into nuclear or cytoplasmic isoforms, which regulate alternative splicing or stability of their target transcripts, respectively. One major target of cytoplasmic Rbfox1 is vesicle associated membrane protein 1 (Vamp1). Vamp1 mediates GABA release probability from PVIs, and the loss of Rbfox1 reduces Vamp1 levels which in turn impairs cortical inhibition...

BACKGROUND: Cognitive impairment is common with schizophrenia spectrum disorders. Cognitive remediation (CR) is effective in improving global cognition, but not all individuals benefit from this type of intervention. A better understanding of the potential mechanism of action of CR is needed. One proposed mechanism is reward learning (RL), the cognitive processes responsible for adapting behavior following positive or negative feedback. It is proposed that the structure of CR enhances RL and motivation to engage in increasingly challenging tasks, and this is a potential mechanism by which CR improves cognitive functioning in schizophrenia...

The constructs of motivation (or needs, motives, etc.) to explain higher-order behavior have burgeoned in psychology. In this article, we critically evaluate such high-level motivation constructs that many researchers define as causal determinants of behavior. We identify a fundamental issue with this predominant view of motivation, which we called the black-box problem. Specifically, high-level motivation constructs have been considered as causally instigating a wide range of higher-order behavior, but this does not explain what they actually are or how behavioral tendencies are generated...

BACKGROUND: Internet-Based Cognitive Behavioral Therapy (iCBT) holds great potential in addressing mental health issues, yet its real-world implementation poses significant challenges. While prior research has predominantly focused on centralized care models, this study explores the implementation of iCBT in the context of decentralized organizational structures within the Swedish primary care setting, where all interventions traditionally are delivered at local Primary Care Centers (PCCs)...

Perceived treatment urgency of mental disorders are important as they determine utilization of health care. The aim was to analyze variations in perceived treatment urgency in cases of psychosis (adolescents), alcoholism (adults), and depression (older adults) with two levels of severity each by characteristics of the case and the respondents. A telephone survey (N = 1200) with vignettes describing cases of psychosis, alcoholism, and depression was conducted in Hamburg, Germany. Vignettes varied by symptom severity and sex...

Depression is a prevalent mental disorder worldwide. Early screening and treatment are crucial in preventing the progression of the illness. Existing emotion-based depression recognition methods primarily rely on facial expressions, while body expressions as a means of emotional expression have been overlooked. To aid in the identification of depression, we recruited 156 participants for an emotional stimulation experiment, gathering data on facial and body expressions. Our analysis revealed notable distinctions in facial and body expressions between the case group and the control group and a synergistic relationship between these variables...

BACKGROUND: Eating disorders and food ingestion (EDs) are serious mental illnesses with a higher prevalence in young adults, with difficult diagnoses that cause serious morbidity and mortality problems. There is not much information about the risk of positive screening for EDs, specifically, anorexia nervosa (AN) and bulimia nervosa (BN) and night eating syndrome (NES) in undergraduate medical interns (UMI) and medical residents (MR) in Mexico. AIM: To determine the risk of AN, BN and NES and to determine the risk factors of such conditions such as age, body mass index (BMI) and gender of MR and UMI with AN/BN and NES at four private hospitals in northeastern Mexico...

BACKGROUND: After the COVID-19 pandemic, the conflict between limited mental health care resources and the rapidly growing number of patients has become more pronounced. It is necessary for psychologists to borrow artificial intelligence (AI)-based methods to analyze patients' satisfaction with drug treatment for those undergoing mental illness treatment. OBJECTIVE: Our goal was to construct highly accurate and transferable models for predicting the satisfaction of patients with mental illness with medication by analyzing their own experiences and comments related to medication intake...

Major Depressive Disorder (MDD) is a common mental illness resulting in immune disorders and even thoughts of suicidal behavior. Neuroimaging techniques serve as a quantitative tool for the assessment of MDD diagnosis. In the domain of computer-aided magnetic resonance imaging diagnosis, current research predominantly focuses on isolated local or global information, often neglecting the synergistic integration of multiple data sources, thus potentially overlooking valuable details. To address this issue, we proposed a diagnostic model for MDD that integrates high-frequency and low-frequency information using data from diffusion tensor imaging (DTI), structural magnetic resonance imaging (sMRI), and functional magnetic resonance imaging (fMRI)...

BACKGROUND AND OBJECTIVES: Depression is a typical mental illness, and early screening can effectively prevent exacerbation of the condition. Many studies have found that the expressions of depressed patients are different from those of other subjects, and microexpressions have been used in the clinical detection of mental illness. However, there are few methods for the automatic detection of depression based on microexpressions. METHODS: A new dataset of 156 participants (76 in the case group and 80 in the control group) was created...

OBJECTIVE: Little is known about self-concept in adolescents with physical-mental comorbidity. This study investigated whether physical-mental comorbidity was associated with self-concept in adolescents and examined if adolescent age or sex moderated the association between physical-mental comorbidity and self-concept. METHODS: Study data were obtained from the Multimorbidity in Youth across the Life-course (MY LIFE), an ongoing Canadian study of adolescents with chronic physical illness who were recruited from outpatient clinics at a pediatric hospital...

[This retracts the article DOI: 10.1155/2022/9404242.].

OBJECTIVE: Caring for a child with epilepsy poses various psychological, physical and medical challenges; these can lead to caregiver burden. The aim of this study was to identify predictors of burden with mothers caring for a child with epilepsy. Our analyses included sociodemographic (e.g., ethnicity), mental health (e.g., symptoms of anxiety, depression) and physiological factors (e.g., extent of pharmacotherapy). METHODS: A total of 168 mothers caring for a child with epilepsy were recruited while attending the Pediatric Neurology Clinic at Soroka Medical Center, Be'er Sheva, Israel...