Psychopathological networks: Theory, methods and practice

Behaviour Research and Therapy, Год журнала: 2021, Номер 149, С. 104011 - 104011

Опубликована: Дек. 1, 2021

In recent years, network approaches to psychopathology have sparked much debate and had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there many important challenges moving from theory empirical research practice vice versa. Therefore, this article, we bring together different points view psychological networks by methodologists clinicians give critical overview these challenges, present an agenda for addressing challenges. contrast previous reviews, especially focus methodological issues related temporal networks. This includes topics such as selecting assessing quality nodes network, distinguishing between- within-person effects networks, relating items that measured at time scales, dealing with changes structures. These not only researchers using models data, but also clinicians, who increasingly likely encounter (person-specific) consulting room.

Язык: Английский

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Multivariate brain-behaviour associations in psychiatric disorders

Translational Psychiatry, Год журнала: 2024, Номер 14(1)

Опубликована: Июнь 1, 2024

Abstract Mapping brain-behaviour associations is paramount to understand and treat psychiatric disorders. Standard approaches involve investigating the association between one brain behavioural variable (univariate) or multiple variables against brain/behaviour feature (‘single’ multivariate). Recently, large multimodal datasets have propelled a new wave of studies that leverage on ‘doubly’ multivariate capable parsing multifaceted nature both behaviour simultaneously. Within this movement, canonical correlation analysis (CCA) partial least squares (PLS) emerge as most popular techniques. Both seek capture shared information in form latent variables. We provide an overview these methods, review literature disorders, discuss main challenges from predictive modelling perspective. identified 39 across four diagnostic groups: attention deficit hyperactive disorder (ADHD, k = 4, N 569), autism spectrum disorders (ASD, 6, 1731), major depressive (MDD, 5, 938), psychosis (PSD, 13, 1150) transdiagnostic group (TD, 11, 5731). Most (67%) used CCA focused either morphology, resting-state functional connectivity fractional anisotropy symptoms and/or cognition. There were three findings. First, diagnoses link clinical/cognitive two measures, namely frontal morphology/brain activity white matter fibres (tracts cortical areas same hemisphere). Second, typically less investigated models such physical health (e.g., BMI, drug use) clinical history childhood trauma) important features. Finally, at risk bias due low sample size/feature ratio in-sample testing only. highlight importance carefully mitigating sources with exemplar application CCA.

Язык: Английский

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The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

NeuroImage Clinical, Год журнала: 2022, Номер 35, С. 103108 - 103108

Опубликована: Янв. 1, 2022

Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered network disorder. In MS, lesional pathology continuously disconnects structural pathways in brain, forming disconnection syndrome. Complex functional changes then occur are poorly understood but closely follow clinical status. Studying these has been remains crucial to further decipher complex symptoms like cognitive impairment physical disability. Recent insights especially implicate importance monitoring hubs thalamus default-mode which seem hit hard. Such MS have led hypothesis as continues become disconnected dysfunctional, exceeding certain threshold efficiency loss leads "network collapse". After this collapse, rigid overloaded, at same time faster neurodegeneration accelerated (and cognitive) progression seen. As neuroscience evolved, field now move towards clearer classification collapse itself specific milestone events leading up it. an updated network-focused conceptual framework could directly impact decision making well design network-tailored rehabilitation strategies. This review therefore provides overview recent concepts enhanced our understanding focusing on cognition, new will likely forward near future.

Язык: Английский

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Possible Futures for Network Psychometrics

Psychometrika, Год журнала: 2022, Номер 87(1), С. 253 - 265

Опубликована: Март 1, 2022

Abstract This commentary reflects on the articles included in Psychometrika Special Issue Network Psychometrics Action. The contributions to special issue are related several possible future paths for research this area. These include development of models analyze and represent interventions, improvement exploratory inferential techniques network psychometrics, articulation psychometric theories addition models, extensions modeling novel data sources. Finally, psychometrics is part a larger movement psychology that revolves around analysis human beings as complex systems, it timely psychometricians start extending their rich tradition improve extend systems psychology.

Язык: Английский

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The future of psychological treatments: The Marburg Declaration

Clinical Psychology Review, Год журнала: 2024, Номер 110, С. 102417 - 102417

Опубликована: Март 25, 2024

Although psychological treatments are broadly recognized as evidence-based interventions for various mental disorders, challenges remain. For example, a substantial proportion of patients receiving such do not fully recover, and many obstacles hinder the dissemination, implementation, training treatments. These problems require those in our field to rethink some basic models disorders their treatments, question how research practice clinical psychology should progress. To answer these questions, group experts convened at Think-Tank Marburg, Germany, August 2022 review evidence analyze barriers current future developments. After this event, an overview state-of-the-art was drafted suggestions improvements specific recommendations were integrated. Recommendations arising from meeting cover further improving through translational approaches, methodology, bridging gap between more nomothetic (group-oriented) studies idiographic (person-centered) decisions, using network approaches addition selecting single mechanisms embrace complexity reality, making use scalable digital options assessments interventions, education psychotherapists, accepting societal responsibilities that has national global health care. The objective Marburg Declaration is stimulate significant change regarding understanding with aim trigger new era interventions.

Язык: Английский

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Do we need a novel framework for classifying psychopathology? A discussion paper

Clinical Psychology in Europe, Год журнала: 2023, Номер 5(4)

Опубликована: Дек. 22, 2023

The ICD-11 and DSM-5 are the leading systems for classification of mental disorders, their relevance clinical work research, as well impact policy making legal questions, has increased considerably. In recent years, other frameworks have been proposed to supplement or even replace ICD DSM, raising many questions regarding utility, scientific relevance, and, at core, how best conceptualize disorders. As examples new approaches that emerged, here we introduce Hierarchical Taxonomy Psychopathology (HiTOP), Research Domain Criteria (RDoC), network approaches, process-based a approach personality We highlight main distinctions between these frameworks, largely related different priorities goals, discuss areas overlap potential compatibility. Synergies among may provide promising avenues research practice.

Язык: Английский

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Symptom Network Analysis Tools for Applied Researchers With Cross-Sectional and Panel Data – A Brief Overview and Multiverse Analysis

Psychological Reports, Год журнала: 2023, Номер unknown

Опубликована: Ноя. 9, 2023

In recent years, there has been a growing interest in utilizing symptom-network models to study psychopathology and relevant risk factors, such as cognitive physical health. Various methodological approaches can be employed by researchers analyzing cross-sectional panel data (i.e., several time points over an extended period). This paper provides overview of some commonly used analytical tools, including moderated network models, comparison tests, cross-lagged analysis, graphical vector-autoregression (VAR) models. Using easily accessible dataset (easySHARE), this demonstrates the use different when investigating (a) association between mental health functioning, (b) role chronic disease mediating or moderating association. multiverse analysis showcases both converging diverging evidence from avenues. These findings underscore importance investigations increase transparency communicate extent which conclusions depend on choices.

Язык: Английский

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Classification of early-MCI patients from healthy controls using evolutionary optimization of graph measures of resting-state fMRI, for the Alzheimer’s disease neuroimaging initiative

PLoS ONE, Год журнала: 2022, Номер 17(6), С. e0267608 - e0267608

Опубликована: Июнь 21, 2022

Identifying individuals with early mild cognitive impairment (EMCI) can be an effective strategy for diagnosis and delay the progression of Alzheimer's disease (AD). Many approaches have been devised to discriminate those EMCI from healthy control (HC) individuals. Selection most parameters has one challenging aspects these approaches. In this study we suggest optimization method based on five evolutionary algorithms that used in neuroimaging data a large number parameters. Resting-state functional magnetic resonance imaging (rs-fMRI) measures, which measure connectivity, shown useful prediction decline. Analysis connectivity using graph measures is common practice results great Using calculated 1155 HC (n = 72) 68) extracted publicly available database initiative (ADNI). These were fed into select subset classification two categories two-layer artificial neural network. All achieved accuracy 94.55%, extremely high considering single-modality input low participants. highlight potential application rs-fMRI efficiency such methods images EMCI. This particular importance MRI cannot easily identified by experts.

Язык: Английский

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A network approach to subjective cognitive decline: Exploring multivariate relationships in neuropsychological test performance across Alzheimer's disease risk states

Cortex, Год журнала: 2024, Номер 173, С. 313 - 332

Опубликована: Фев. 21, 2024

Язык: Английский

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Unraveling robust brain-behavior links of depressive complaints through granular network models for understanding heterogeneity

Journal of Affective Disorders, Год журнала: 2024, Номер 359, С. 140 - 144

Опубликована: Май 14, 2024

Depressive symptoms are highly prevalent, present in heterogeneous symptom patterns, and share diverse neurobiological underpinnings. Understanding the links between psychopathological biological factors is critical elucidating its etiology persistence. We aimed to evaluate utility of using symptom-brain networks parse heterogeneity depressive complaints a large adolescent sample. used data from third wave IMAGEN study, multi-center panel cohort study involving 1317 adolescents (52.49 % female, mean ± SD age = 18.5 0.72). Two network models were estimated: one including an overall severity sum score based on Adolescent Depression Rating Scale (ADRS), incorporating individual ADRS symptom/item scores. Both included measures cortical thickness several regions (insula, cingulate, mOFC, fusiform gyrus) hippocampal volume derived neuroimaging. The scores revealed associations specific complaints, obscured when aggregate depression score. Notably, insula's showed negative with cognitive dysfunction (partial cor. −0.15); cingulate's feelings worthlessness −0.10), mOFC was negatively associated anhedonia −0.05). This cross-sectional relied self-reported assessment non-clinical sample predominantly healthy participants (19 or sub-threshold depression). showcases parsing linking neural substrates. outline next steps integrate markers unravel MDD's phenotypic heterogeneity.

Язык: Английский

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