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Mapping psychopathology with mri and connectivity analysis
  • Language: en
  • Pages: 113
Multi-parametric perfusion MRI by arterial spin labeling
  • Language: en
  • Pages: 157

Multi-parametric perfusion MRI by arterial spin labeling

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Machine Learning in Neuroscience, Volume II
  • Language: en
  • Pages: 168

Machine Learning in Neuroscience, Volume II

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Mapping Psychopathology with fMRI and Effective Connectivity Analysis
  • Language: en
  • Pages: 142

Mapping Psychopathology with fMRI and Effective Connectivity Analysis

There is a growing appreciation that many psychiatric (and neurological) conditions can be understood as functional disconnection syndromes – as reflected in aberrant functional integration and synaptic connectivity. This Research Topic considers recent advances in understanding psychopathology in terms of aberrant effective connectivity – as measured noninvasively using functional magnetic resonance imaging (fMRI). Recently, there has been increasing interest in inferring directed connectivity (effective connectivity) from fMRI data. Effective connectivity refers to the influence that one neural system exerts over another and quantifies the directed coupling among brain regions – and ...

Trajectories of Brain Abnormalities in Early Schizophrenia
  • Language: en
  • Pages: 152

Trajectories of Brain Abnormalities in Early Schizophrenia

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Genetic Mechanisms of Biomarkers in Schizophrenia, Bipolar Disorder and Depression
  • Language: en
  • Pages: 171
Digital Mental Health Research: Understanding Participant Engagement and Need for User-centered Assessment and Interventional Digital Tools
  • Language: en
  • Pages: 179

Digital Mental Health Research: Understanding Participant Engagement and Need for User-centered Assessment and Interventional Digital Tools

Mental health researchers are increasingly looking towards digital health tools to gather day-to-day lived experiences of people living with mental health conditions, by using apps and wearable devices complementing episodic clinical assessments. One of the key goals of collecting longitudinal real-world multimodal data (RWD) is to help build personalized computational models that may help explain the heterogeneity in clinical outcomes, mechanisms of action, and pathophysiology of mental health disorders across individuals.