Publications by authors named "Melanie Ganz"

Article Synopsis
  • - Serotonin reuptake inhibitors may help boost memory and increase hippocampal volume in patients with Major Depressive Disorder (MDD), particularly through the involvement of the 5-HT4 receptor. - In a study with 91 patients, significant reductions in hippocampal volume were observed after 8 weeks of treatment, especially in those responding well to the antidepressant escitalopram. - The research indicated a negative relationship between 5-HT4 receptor binding and hippocampal volume in females, suggesting a complex interaction that needs further exploration to understand its impact on memory and brain plasticity in MDD.
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Article Synopsis
  • The Brain Imaging Data Structure (BIDS) is a community-created standard for organizing neuroscience data and metadata, helping researchers manage various modalities efficiently.
  • The paper discusses the evolution of BIDS, including the guiding principles, extension mechanisms, and challenges faced during its development.
  • It also highlights key lessons learned from the BIDS project, aiming to inspire and inform researchers in other fields about effective data organization practices.
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Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples ( = 1,384) of medication-free individuals with first-episode and recurrent MDD ( = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls ( = 699).

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To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective interventions, it is necessary to develop biomarkers that can accurately capture age-related biological changes in the human brain. Brain serotonin 2A receptors (5-HT2AR) show a particularly profound age-related decline and are also reduced in neurodegenerative disorders, such as Alzheimer's disease. This study investigates whether the decline in 5-HT2AR binding, measured in vivo using positron emission tomography (PET), can be used as a biomarker for brain aging.

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Background: Early diagnosis of cerebral palsy (CP) is important to enable intervention at a time when neuroplasticity is at its highest. Current mean age at diagnosis is 13 months in Denmark. Recent research has documented that an early-diagnosis set-up can lower diagnostic age in high-risk infants.

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Brain age prediction algorithms using structural magnetic resonance imaging (MRI) aim to assess the biological age of the human brain. The difference between a person's chronological age and the estimated brain age is thought to reflect deviations from a normal aging trajectory, indicating a slower or accelerated biological aging process. Several pre-trained software packages for predicting brain age are publicly available.

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Article Synopsis
  • The Brain Imaging Data Structure (BIDS) is a collaborative standard designed to organize various neuroscience data and metadata.
  • The paper details the history, principles, and mechanisms behind the development and expansion of BIDS, alongside the challenges it faces as it evolves.
  • It also shares lessons learned from the project to help researchers in other fields apply similar successful strategies.
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To ensure equitable quality of care, differences in machine learning model performance between patient groups must be addressed. Here, we argue that two separate mechanisms can cause performance differences between groups. First, model performance may be worse than theoretically achievable in a given group.

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Article Synopsis
  • Major Depressive Disorder (MDD) is a complex brain disorder with various biological and psychosocial factors, leading to inconsistent responses to antidepressant treatments for many patients.
  • A study will recruit 800 patients from outpatient clinics in Denmark to gather extensive clinical and biological data, aiming to uncover predictive markers for treatment success.
  • Treatment effectiveness will be measured through the Quick Inventory of Depressive Symptomatology (QIDS) at multiple time points, focusing on remission rates and overall clinical improvement over six months and beyond.
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Previous studies have suggested that the loudness dependence of auditory evoked potential (LDAEP) is associated with the effectiveness of antidepressant treatment in patients with major depressive disorders (MDD). Furthermore, both LDAEP and the cerebral serotonin 4 receptor (5-HTR) density is inversely related to brain serotonin levels. We included 84 patients with MDD and 22 healthy controls to examined the association between LDAEP and treatment response and its association with cerebral 5-HTR density.

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Background: Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states.

Methods: We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD).

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Background: Psilocin, the neuroactive metabolite of psilocybin, is a serotonergic psychedelic that induces an acute altered state of consciousness, evokes lasting changes in mood and personality in healthy individuals, and has potential as an antidepressant treatment. Examining the acute effects of psilocin on resting-state time-varying functional connectivity implicates network-level connectivity motifs that may underlie acute and lasting behavioral and clinical effects.

Aim: Evaluate the association between resting-state time-varying functional connectivity (tvFC) characteristics and plasma psilocin level (PPL) and subjective drug intensity (SDI) before and right after intake of a psychedelic dose of psilocybin in healthy humans.

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Article Synopsis
  • Neurotransmitter receptors play a key role in signal transmission in the brain, but their organization and impact on brain function are not well understood.
  • Researchers created a comprehensive 3D normative atlas of 19 neurotransmitter receptors and transporters in the brains of over 1,200 healthy individuals using advanced imaging techniques.
  • The study revealed how these receptor profiles relate to brain structure, function, and even abnormalities linked with various mental disorders, paving the way for new research into brain organization and disorders.
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Brain morphology has been suggested to be predictive of drug treatment outcome in major depressive disorders (MDD). The current study aims at evaluating the performance of pretreatment structural brain magnetic resonance imaging (MRI) measures in predicting the outcome of a drug treatment of MDD in a large single-site cohort, and, importantly, to assess the generalizability of these findings in an independent cohort. The random forest, boosted trees, support vector machines and elastic net classifiers were evaluated in predicting treatment response and remission following an eight week drug treatment of MDD using structural brain measures derived with FastSurfer (FreeSurfer).

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Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources.

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Hormone transition phases may trigger depression in some women, yet the underlying mechanisms remain elusive. In a pharmacological sex-hormone manipulation model, we previously reported that estradiol reductions, induced with a gonadotropin-releasing hormone agonist (GnRHa), provoked subclinical depressive symptoms in healthy women, especially if neocortical serotonin transporter (SERT) binding also increased. Within this model, we here evaluated if GnRHa, compared to placebo, reduced hippocampal volume, in a manner that depended on the magnitude of the estradiol decrease and SERT binding, and if this decrease translated to the emergence of subclinical depressive symptoms.

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Background: Major depressive disorder (MDD) is a prevalent neuropsychiatric illness for which it is important to resolve underlying brain mechanisms. Current treatments are often unsuccessful, precipitating a need to identify predictive markers.

Aim: We evaluated (1) alterations in brain responses to an emotional faces functional magnetic resonance imaging (fMRI) paradigm in individuals with MDD, compared to controls, (2) whether pretreatment brain responses predicted antidepressant treatment response, and (3) pre-post change in brain responses following treatment.

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The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data, also known as PET-BIDS, and share several open-access datasets curated following PET-BIDS along with tools for conversion, validation and analysis of PET-BIDS datasets.

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Head motion is one of the major reasons for artefacts in Magnetic Resonance Imaging (MRI), which is especially challenging for children who are often intimidated by the dimensions of the MR scanner. In order to optimise the MRI acquisition for children in the clinical setting, insights into children's motion patterns are essential. In this work, we analyse motion data from 61 paediatric patients.

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As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.

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While several electroencephalogram (EEG)-based biomarkers have been proposed as diagnostic or predictive tools in major depressive disorder (MDD), there is a clear lack of replication studies in this field. Markers that link clinical features such as disturbed wakefulness regulation in MDD with neurophysiological patterns are particularly promising candidates for e.g.

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Several electroencephalogram (EEG) biomarkers for prediction of drug response in major depressive disorder (MDD) have been proposed, but validations in larger independent datasets are missing. In the current study, we investigated the prognostic value of previously suggested EEG biomarkers. We gathered data that matched prior studies in terms of EEG methodology, clinical criteria for MDD, and statistical approach as closely as possible.

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