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Electrophysiology and Psychophysiology in Psychiatry and Psychopharmacology

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Cover of 'Electrophysiology and Psychophysiology in Psychiatry and Psychopharmacology'

Table of Contents

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    Book Overview
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    Chapter 295 Personalized Medicine in ADHD and Depression: Use of Pharmaco-EEG.
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    Chapter 296 Physiological Correlates of Premenstrual Dysphoric Disorder (PMDD)
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    Chapter 297 Physiological Correlates of Bipolar Spectrum Disorders and their Treatment
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    Chapter 298 ASD: Psychopharmacologic Treatments and Neurophysiologic Underpinnings
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    Chapter 303 Electrophysiological Aberrations Associated with Negative Symptoms in Schizophrenia
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    Chapter 308 The Spectrum of Borderline Personality Disorder: A Neurophysiological View.
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    Chapter 316 Neurophysiological Biomarkers Informing the Clinical Neuroscience of Schizophrenia: Mismatch Negativity and Prepulse Inhibition of Startle
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    Chapter 320 Psychophysiology of Dissociated Consciousness.
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    Chapter 321 Nonlinear Measures and Dynamics in Psychophysiology of Consciousness.
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    Chapter 322 Physiological Correlates of Positive Symptoms in Schizophrenia
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    Chapter 323 Psychophysiology-Informed (Multimodal) Imaging
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    Chapter 324 Physiological Correlates of Insomnia
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    Chapter 325 Postmenopausal Physiological Changes.
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    Chapter 345 Electrophysiology and Psychophysiology in Psychiatry and Psychopharmacology
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    Chapter 346 Psychophysiology in the Study of Psychological Trauma: Where Are We Now and Where Do We Need to Be?
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    Chapter 347 Physiological Aberrations in Panic Disorder
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    Chapter 348 Connectivity Measurements for Network Imaging
Attention for Chapter 316: Neurophysiological Biomarkers Informing the Clinical Neuroscience of Schizophrenia: Mismatch Negativity and Prepulse Inhibition of Startle
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Chapter title
Neurophysiological Biomarkers Informing the Clinical Neuroscience of Schizophrenia: Mismatch Negativity and Prepulse Inhibition of Startle
Chapter number 316
Book title
Electrophysiology and Psychophysiology in Psychiatry and Psychopharmacology
Published in
Current topics in behavioral neurosciences, May 2014
DOI 10.1007/7854_2014_316
Pubmed ID
Book ISBNs
978-3-31-912768-2, 978-3-31-912769-9
Authors

Gregory A. Light, Neal R. Swerdlow, Light, Gregory A., Swerdlow, Neal R.

Abstract

With the growing recognition of the heterogeneity of major brain disorders, and particularly the schizophrenias (SZ), biomarkers are being sought that parse patient groups in ways that can be used to predict treatment response, prognosis, and pathophysiology. A primary focus to date has been to identify biomarkers that predict damage or dysfunction within brain systems in SZ patients, that could then serve as targets for interventions designed to "undo" the causative pathology. After almost 50 years as the predominant strategy for developing SZ therapeutics, evidence supporting the value of this "find what's broke and fix it" approach is lacking. Here, we suggest an alternative strategy of using biomarkers to identify evidence of spared neural and cognitive function in SZ patients, and matching these residual neural assets with therapies toward which they can be applied. We describe ways to extract and interpret evidence of "spared function," using neurocognitive, and neurophysiological measures, and, suggest that further evidence of available neuroplasticity might be gleaned from studies in which the response to drug challenges and "practice effects" are measured. Finally, we discuss examples in which "better" (more normal) performance in specific neurophysiological measures predict a positive response to a neurocognitive task or therapeutic intervention. We believe that our field stands to gain tremendous therapeutic leverage by focusing less on what is "wrong" with our patients, and instead, focusing more on what is "right".

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 55 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 23%
Student > Bachelor 8 14%
Researcher 8 14%
Student > Master 6 11%
Student > Doctoral Student 3 5%
Other 7 13%
Unknown 11 20%
Readers by discipline Count As %
Psychology 14 25%
Neuroscience 12 21%
Medicine and Dentistry 7 13%
Agricultural and Biological Sciences 3 5%
Nursing and Health Professions 1 2%
Other 4 7%
Unknown 15 27%