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Biomarkers in Psychiatry

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Cover of 'Biomarkers in Psychiatry'

Table of Contents

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    Book Overview
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    Chapter 41 Network Neuroscience: A Framework for Developing Biomarkers in Psychiatry
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    Chapter 42 Reappraising Preclinical Models of Separation Anxiety Disorder, Panic Disorder, and CO 2 Sensitivity: Implications for Methodology and Translation into New Treatments
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    Chapter 43 Immunological Processes in Schizophrenia Pathology: Potential Biomarkers?
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    Chapter 44 Translational Shifts in Preclinical Models of Depression: Implications for Biomarkers for Improved Treatments
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    Chapter 45 Neuroimmune Biomarkers in Mental Illness
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    Chapter 46 Imaging and Genetic Biomarkers Predicting Transition to Psychosis
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    Chapter 47 Using Pattern Classification to Identify Brain Imaging Markers in Autism Spectrum Disorder
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    Chapter 48 Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification
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    Chapter 49 Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
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    Chapter 50 Cognitive Phenotypes for Biomarker Identification in Mental Illness: Forward and Reverse Translation
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    Chapter 52 Genomic and Imaging Biomarkers in Schizophrenia
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    Chapter 57 Stem Cells to Inform the Neurobiology of Mental Illness
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    Chapter 58 Biomarkers in Neuropsychiatry: A Prospect for the Twenty-First Century?
  15. Altmetric Badge
    Chapter 64 Correction to: Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
Attention for Chapter 41: Network Neuroscience: A Framework for Developing Biomarkers in Psychiatry
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Chapter title
Network Neuroscience: A Framework for Developing Biomarkers in Psychiatry
Chapter number 41
Book title
Biomarkers in Psychiatry
Published in
Current topics in behavioral neurosciences, January 2018
DOI 10.1007/7854_2018_41
Pubmed ID
Book ISBNs
978-3-31-999641-7, 978-3-31-999642-4
Authors

David M. Lydon-Staley, Danielle S. Bassett, Lydon-Staley, David M., Bassett, Danielle S.

Abstract

Psychiatric disorders are disturbances of cognitive and behavioral processes mediated by the brain. Emerging evidence suggests that accurate biomarkers for psychiatric disorders might benefit from incorporating information regarding multiple brain regions and their interactions with one another, rather than considering local perturbations in brain structure and function alone. Recent advances in the field of applied mathematics generally - and network science specifically - provide a language to capture the complexity of interacting brain regions, and the application of this language to fundamental questions in neuroscience forms the emerging field of network neuroscience. This chapter provides an overview of the use and utility of network neuroscience for building biomarkers in psychiatry. The chapter begins with an overview of the theoretical frameworks and tools that encompass network neuroscience before describing applications of network neuroscience to the study of schizophrenia and major depressive disorder. With reference to work on genetic, molecular, and environmental correlates of network neuroscience features, the promises and challenges of network neuroscience for providing tools that aid in the diagnosis and the evaluation of treatment response in psychiatric disorders are discussed.

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X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 21%
Researcher 5 11%
Other 4 9%
Student > Postgraduate 4 9%
Student > Doctoral Student 3 6%
Other 10 21%
Unknown 11 23%
Readers by discipline Count As %
Neuroscience 11 23%
Medicine and Dentistry 9 19%
Psychology 8 17%
Engineering 2 4%
Social Sciences 1 2%
Other 3 6%
Unknown 13 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 June 2018.
All research outputs
#6,664,999
of 24,862,067 outputs
Outputs from Current topics in behavioral neurosciences
#193
of 521 outputs
Outputs of similar age
#124,919
of 453,913 outputs
Outputs of similar age from Current topics in behavioral neurosciences
#5
of 10 outputs
Altmetric has tracked 24,862,067 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 521 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has gotten more attention than average, scoring higher than 62% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 453,913 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.