Functional neuroanatomy of mania

Cotovio, Gonçalo; Oliveira‐Maia, Albino J.

doi:10.1038/s41398-022-01786-4

Cited by 28 publications

(20 citation statements)

References 153 publications

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“…This model was fit to QIDS-SR data collected from 25 patients with BD, ultimately predicting that if a system of neural oscillators underlying mood dynamics can be identified, they will oscillate independently of each other in the majority of BD patients. This prediction may be supported by existing empirically-derived models of hemispheric mood lateralization [ 48 , 49 ].…”

Section: Resultssupporting

confidence: 61%

A critical evaluation of dynamical systems models of bipolar disorder

et al. 2022

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Bipolar disorder (BD) is a mood disorder involving recurring (hypo)manic and depressive episodes. The inherently temporal nature of BD has inspired its conceptualization using dynamical systems theory, which is a mathematical framework for understanding systems that evolve over time. In this paper, we provide a critical review of the dynamical systems models of BD. Owing to the heterogeneity of methodological and experimental designs in computational modeling, we designed a structured approach that parallels the appraisal of animal models by their face, predictive, and construct validity. This tool, the validity appraisal guide for computational models (VAG-CM), is not an absolute measure of validity, but rather a guide for a more objective appraisal of models in this review. We identified 26 studies published before November 18, 2021 that proposed generative dynamical systems models of time-varying signals in BD. Two raters independently applied the VAG-CM to the included studies, obtaining a mean Cohen’s κ of 0.55 (95% CI [0.45, 0.64]) prior to establishing consensus ratings. Consensus VAG-CM ratings revealed three model/study clusters: data-driven models with face validity, theory-driven models with predictive validity, and theory-driven models lacking all forms of validity. We conclude that future modeling studies should employ a hybrid approach that first operationalizes BD features of interest using empirical data to achieve face validity, followed by explanations of those features using generative models with components that are homologous to physiological or psychological systems involved in BD, to achieve construct validity. Such models would be best developed alongside long-term prospective cohort studies involving a collection of multimodal time-series data. We also encourage future studies to extend, modify, and evaluate the VAG-CM approach for a wider breadth of computational modeling studies and psychiatric disorders.

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Section: Resultssupporting

confidence: 61%

A critical evaluation of dynamical systems models of bipolar disorder

et al. 2022

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“…Additionally, behavioral patterns appear to vary across different illnesses in human subjects. For instance, the manic phase of bipolar disorder and obsessive compulsive disorder tend to be associated with increased obsessive/repetitive behaviors and hyperactivity, whereas depression tends to be associated with increased suppressive behavior [ 36 , 60 , 61 ]. In this study, the RB domain was related to active behavior, and the SW domain was related to suppressive behavior.…”

Section: Discussionmentioning

confidence: 99%

The Brain Overwork Scale: A Population-Based Cross-Sectional Study on the Psychometric Properties of a New 10-Item Scale to Assess Mental Distress in Mongolia

et al. 2023

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Identifying mental distress is a complex task, particularly when individuals experience physical symptoms. Traditional self-report questionnaires that detect psychiatric symptoms using emotional words may not work for these individuals. Consequently, there is a need for a screening tool that can identify both the physical and mental symptoms of mental distress in individuals without a clinical diagnosis. Our study aimed to develop and validate a scale that measures mental distress by measuring the extent of brain overwork, which can be extrapolated as the burden of mental distress. In this population-based cross-sectional study, we recruited a total of 739 adults aged 16–65 years from 64 sampling centers of a cohort in Mongolia to validate a 10-item self-report questionnaire. Internal consistency was measured using McDonald’s ω coefficient. Test–retest reliability was analyzed using intraclass correlation coefficients. Construct and convergent validities were examined using principal component analysis (PCA) and confirmatory factor analysis (CFA). The Hospital Anxiety and Depression Scale (HADS) and the abbreviated version of World Health Organization Quality of Life (WHOQOL-BREF) were used to evaluate criterion validity. Among the participants, 70.9% were women, 22% held a bachelor’s degree or higher, 38.8% were employed, and 66% were married. The overall McDonald’s ω coefficient was 0.861, demonstrating evidence of excellent internal consistency. The total intraclass correlation coefficient of the test–retest analysis was 0.75, indicating moderate external reliability. PCA and CFA established a three-domain structure that provided an excellent fit to the data (RMSEA = 0.033, TLI = 0.984, CFI = 0.989, χ2 = 58, p = 0.003). This 10-item scale, the Brain Overwork Scale (BOS-10), determines mental distress in three dimensions: excessive thinking, hypersensitivity, and restless behavior. All the items had higher item-total correlations with their corresponding domain than they did with the other domains, and correlations between the domain scores had a range of 0.547–0.615. BOS-10 correlated with HADS, whereas it was inversely correlated with WHOQOL-BREF. In conclusion, the results suggest that BOS-10 is a valid and reliable instrument for assessing mental distress in the general population. The scale screens for mental distress that is characterized by subjective symptoms such as excessive thinking, hypersensitivity, and restless behavior. The current findings also demonstrate that the BOS-10 is quantitative, simple, and applicable for large group testing. This scale may be useful for identifying at-risk individuals who may require further evaluation and treatment for mental distress.

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“…34 Functional neuroimaging studies have consistently shown increased limbic region activity during emotional processing tasks and reduced connectivity between the amygdala and prefrontal cortical regions. 35,36 However, there is considerable diversity in findings across studies, depending on mood state, experimental conditions (e.g., resting state v. task based) and illness stage. 35,36…”

Section: Synaptic Cellular Circuit and Structural Heterogeneitymentioning

confidence: 99%

“…35,36 However, there is considerable diversity in findings across studies, depending on mood state, experimental conditions (e.g., resting state v. task based) and illness stage. 35,36…”

Section: Synaptic Cellular Circuit and Structural Heterogeneitymentioning

confidence: 99%