Method Article

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

DOI:

10.3791/51651

July 1st, 2014

In This Article

Summary

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This protocol describes the complementary neuroimaging techniques of resting state structural connectivity, task-induced deactivation, and structural connectivity analyses to examine the default network in post-traumatic stress disorder. The use of synergistic methods could potentially lead to improved diagnostics and assessments of severity, outcome, and other relevant clinical factors.

Abstract

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Complementary structural and functional neuroimaging techniques used to examine the Default Mode Network (DMN) could potentially improve assessments of psychiatric illness severity and provide added validity to the clinical diagnostic process. Recent neuroimaging research suggests that DMN processes may be disrupted in a number of stress-related psychiatric illnesses, such as posttraumatic stress disorder (PTSD).

Although specific DMN functions remain under investigation, it is generally thought to be involved in introspection and self-processing. In healthy individuals it exhibits greatest activity during periods of rest, with less activity, observed as deactivation, during cognitive tasks, e.g., working memory. This network consists of the medial prefrontal cortex, posterior cingulate cortex/precuneus, lateral parietal cortices and medial temporal regions.

Multiple functional and structural imaging approaches have been developed to study the DMN. These have unprecedented potential to further the understanding of the function and dysfunction of this network. Functional approaches, such as the evaluation of resting state connectivity and task-induced deactivation, have excellent potential to identify targeted neurocognitive and neuroaffective (functional) diagnostic markers and may indicate illness severity and prognosis with increased accuracy or specificity. Structural approaches, such as evaluation of morphometry and connectivity, may provide unique markers of etiology and long-term outcomes. Combined, functional and structural methods provide strong multimodal, complementary and synergistic approaches to develop valid DMN-based imaging phenotypes in stress-related psychiatric conditions. This protocol aims to integrate these methods to investigate DMN structure and function in PTSD, relating findings to illness severity and relevant clinical factors.

Introduction

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Neuroimaging represents a tool with unprecedented potential to examine diagnostic validity, severity of illness, prognostics and treatment response in neuropsychiatry. A wide range of complementary neuroimaging techniques is now available to characterize the structure and function of key brain systems, and to aid in the identification of neuroimaging phenotypes in psychiatric populations. Of these systems, the Default Mode Network (DMN) has received a great deal of attention in the cognitive and clinical neuroscience literature over the last decade.

The DMN is a so-called “resting state network” that includes the medial prefront....

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Protocol

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Eligible participants sign written, informed consent to participate in the research project. Research is performed in compliance with institutional, national and international guidelines for human welfare.

1. Participant Screening and Diagnostic Interviews

  1. After informed consent, perform diagnostic interviews to verify the diagnosis of PTSD and illness severity. NOTE: These measures include the Structured Clinical Interview for DSM-IV-TR (SCID)24 and the Clinician Administered PTSD Scale (CAPS)25, as well as the Folstein Mini-Mental Status Exam (MMSE)26 to evaluate cognitive status.
  2. As....

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Results

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Representative results are based on data collected using the same imaging approach in two different samples of individuals with a history of childhood trauma and maltreatment, but without PTSD21,22. Results from resting state functional connectivity analyses revealed a spatial pattern consistent with major nodes of the DMN (Figure 1)1-3,8 including the MPFC, PCC, angular gyrus/inferior parietal lobule and middle temporal regions. Confirmation of this spatial distribution serves as a.......

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Discussion

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The two most critical steps for successful implementation of the neuroimaging protocol are accurately capturing resting state and working memory effects.

Conceptually, the acquisition of resting state images is straightforward. Since there is no task to perform, experimenters often describe brain activity during these epochs as “rest.” However, as this field is relatively new compared to other areas of the neuroimaging1, there is no explicit consensus of how to precisely.......

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Disclosures

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The authors have no conflicts of interest to disclose relevant to the content of this manuscript. Both Dr. Philip and Ms. Carpenter are US Government Employees.

Acknowledgements

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Generation of representative data was supported by NIH Grant R01HL084178, 5R01MH068767-08, and grants from the Brown MRI Research Facility and Rhode Island Foundation. VA CSR&D Grant 1 IK2 CX000724-01A2 supported protocol development and further work. We thank all of our participants.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
3T TIM TRIOSiemens3T MRI 
MRI-compatible pulse oxymeterSiemensmodel # 07389567
Analysis of Functional NeuroimagingNIHhttp://afni.nimh.nih.gov/Data analysis software package
EprimePsychology Software Tools, LLChttp://www.pstnet.com/eprime.cfmStimulus presentation software
SlicerBrigham and Women's Hospitalhttp://www.slicer.org/Probabilistic tractography software

References

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  1. Raichle, M. E., et al. A default mode of brain function. Proc Natl Acad Sci U S A. 98, 676-682 (2001).
  2. Fransson, P. How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations. Neuropsychologia

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Tags

Default Mode NetworkPTSD NeuroimagingResting State ConnectivityWorking Memory TaskStructural ConnectivityFunctional MRIDiffusion Tensor ImagingTask Induced DeactivationMultimodal NeuroimagingBrain Network Analysis

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