Real-time fMRI and Neurofeedback of Brain Networks Mediating Trauma Memory Recall in PTSD

July 26, 2021 updated by: University of Arkansas

Real-time Functional MRI and Neurofeedback of Brain Networks Mediating Trauma Memory Recall in PTSD

The purpose of the current study is to develop a better understanding of the brain mechanisms involved in psychological treatments for posttraumatic stress disorder (PTSD). This project will build on past research using script-driven imagery in our lab by investigating brain activity in areas activated during exposure to trauma-related cues. This project will also develop new knowledge concerning volitional control of those areas. The ultimate goal of this study is a better understanding of whether volitional control of these brain areas will improve therapeutic outcomes. This process will first be piloted in a sample of healthy controls. This will allow investigators to refine the methodology prior to recruiting a sample with PTSD.

Study Overview

Detailed Description

Post-traumatic stress disorder (PTSD) is characterized by intense emotional distress upon exposure to trauma reminders and avoidance of people and places that can trigger the trauma memory. Neurocircuitry models of PTSD that seek to explain symptoms of heightened emotional reactivity, hypervigilance for threat, and avoidance suggest abnormal activity of neural regions involved in emotional reactivity (e.g., amygdala) and cognitive control of emotional responding (e.g., ventral medial prefrontal cortex, anterior cingulate cortex). While knowledge exists about neurobiological abnormalities associated with PTSD, these data are cross-sectional in nature and ignore individual differences in both neural encoding and subjective aspects of the trauma itself (e.g., whether it elicits fear vs guilt vs disgust). Additionally, the manner by which existing psychological treatments alter these neural mechanisms mediating core PTSD symptoms is unknown. This is problematic, given that state-of-the-art treatment for PTSD is only effective ~60% of the time.

Here, the investigator proposes to utilize a novel computational modeling approach combined with state-of-the-art functional magnetic resonance imaging (fMRI)-based neurofeedback to directly identify and modulate the idiosyncratic neural network encoding the trauma memory. Successful pursuit of these aims would 1) provide scientific support for the hypothesis that a distributed network including the amygdala, hippocampus, medial prefrontal cortex (PFC), lateral PFC, and anterior insula mediates emotional responding upon trauma memory recall, and 2) provide proof-of-concept evidence that neurofeedback modulation of this network can boost existing therapy efficacy.

Study Type

Interventional

Enrollment (Actual)

30

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Arkansas
      • Little Rock, Arkansas, United States, 72205
        • University of Arkansas for Medical Sciences

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

21 years to 50 years (Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

Female

Description

Inclusion Criteria:

  • Female
  • Aged 21-50
  • Medically healthy

Exclusion Criteria:

  • Claustrophobia, or the inability to lie still in a confined space
  • Major medical disorders (e.g., HIV, cancer)
  • Magnetic metallic implants (such as screws, pins, shrapnel remnants, aneurysm clips, artificial heart valves, inner ear (cochlear) implants, artificial joints, and vascular stents)
  • Electronic or magnetic implants, such as pacemakers
  • Permanent makeup or tattoos with metallic dyes
  • Currently pregnant
  • A self-reported history of loss of consciousness (greater than 10 minutes)
  • Physical disabilities that prohibit task performance (such as blindness or deafness)
  • Psychotic disorders (e.g., schizophrenia)
  • Any other condition that the investigator believes might put the participant at risk

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: Non-Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Healthy Participants
A group of healthy participants will be enrolled first in the pilot phase of the study. This phase allows for the refinement (prior to the implementing in our PTSD participant group) the application of our support vector machine based real-time functional magnetic resonance imaging (rt-fMRI) algorithm, which evaluates brain networks thought to mediate emotional arousal and presents them (in real time) to subjects to aide in volitional manipulation of arousal.
A support vector machine algorithm will be applied in real-time to fMRI data to identify distributed patterns of co-activated brain regions that specifically encode high emotional arousal (i.e,. high SCR) to the stress/trauma memory (note, this is equivalent to predictions of fitted Q-iteration in which the all actions are specified as zero, reward is equal to the support vector machine predicted arousal, and the discount factor of 0). The resulting idiosyncratic brain map would inform the neurofeedback phase in the next stage of fMRI data collection. This approach will first be piloted in the healthy participant group, then implemented in the PTSD participant group.
Other Names:
  • Machine Learning Algorithm
  • Real-time Neurofeedback
Experimental: PTSD Participants
A group of participants with symptoms of PTSD will be enrolled in the implementation phase of the study. This phase allows for the evaluation of rt-fMRI guidance of brain networks thought to mediate emotional arousal, specifically whether participants can learn volitional control of these networks.
A support vector machine algorithm will be applied in real-time to fMRI data to identify distributed patterns of co-activated brain regions that specifically encode high emotional arousal (i.e,. high SCR) to the stress/trauma memory (note, this is equivalent to predictions of fitted Q-iteration in which the all actions are specified as zero, reward is equal to the support vector machine predicted arousal, and the discount factor of 0). The resulting idiosyncratic brain map would inform the neurofeedback phase in the next stage of fMRI data collection. This approach will first be piloted in the healthy participant group, then implemented in the PTSD participant group.
Other Names:
  • Machine Learning Algorithm
  • Real-time Neurofeedback

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Patient Emotional Response to Volitional Engagement and Disengagement of Emotional Arousal as Measured Using Support Vector Machine Decodings When the Decoding is Provided as Real-time Neurofeedback Guidance or Not.
Time Frame: Real-time within the measurement of functional MRI (within 10 seconds of functional MRI volume acquisition and reconstruction)
Support vector machine decodings of functional MRI data acquired during volitional engagement or disengagement of emotional arousal. Each decoding represents the Euclidean distance and direction (either positive or negative) of the functional MRI data volume with respect to the patient's support vector machine decision hyperplane. Positive distances denote engagement of emotional arousal and negative distances denote disengagement of emotion arousal. Distance represents the magnitude of volitional engagement or disengagement. Decodings can either be provided to patients as real-time neurofeedback (via visual representation of the distance) or hidden from view. When hidden, the visual representation of neurofeedback remains stationary.
Real-time within the measurement of functional MRI (within 10 seconds of functional MRI volume acquisition and reconstruction)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Keith Bush, PhD., University of Arkansas

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 15, 2015

Primary Completion (Actual)

April 1, 2019

Study Completion (Actual)

April 1, 2019

Study Registration Dates

First Submitted

July 7, 2015

First Submitted That Met QC Criteria

July 14, 2015

First Posted (Estimate)

July 16, 2015

Study Record Updates

Last Update Posted (Actual)

August 20, 2021

Last Update Submitted That Met QC Criteria

July 26, 2021

Last Verified

April 1, 2021

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

Yes

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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