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Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback.

Cisler JM, Bush K, James GA, Smitherman S, Kilts CD - PLoS ONE (2015)

Bottom Line: By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall.Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy.Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs.

View Article: PubMed Central - PubMed

Affiliation: Brain Imaging Research Center, Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.

ABSTRACT
Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD.

No MeSH data available.


Related in: MedlinePlus

Mean classification accuracy across participants, trained using three runs, as a function of the brain mask used to select voxels: all GM voxels, only voxels within PTSD-related ROIs, all GM voxels except the PTSD-related voxels, and voxels within randomly generated ROIs.
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pone.0134717.g003: Mean classification accuracy across participants, trained using three runs, as a function of the brain mask used to select voxels: all GM voxels, only voxels within PTSD-related ROIs, all GM voxels except the PTSD-related voxels, and voxels within randomly generated ROIs.

Mentions: Fig 3 depicts classification accuracy as a function of the voxels used to train the model when using three memory recall repetitions. Classification accuracy was significantly greater when using all GM voxels compared to the model using only voxels within the ROIs implicated in PTSD neurocircuitry models (p < .001) and the randomly generated ROIs (p < .001). Similarly, classification accuracy was significantly greater when using all GM voxels except those within ROIs implicated in PTSD neurocircuitry models compared to using only voxels within ROIs implicated in PTSD models (p < .001) and the randomly generated ROIs (p < .001). Finally, classification accuracy when using voxels only within ROIs implicated in PTSD models did not significantly differ from using only voxels within 8 randomly generated ROIs (p = .08).


Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback.

Cisler JM, Bush K, James GA, Smitherman S, Kilts CD - PLoS ONE (2015)

Mean classification accuracy across participants, trained using three runs, as a function of the brain mask used to select voxels: all GM voxels, only voxels within PTSD-related ROIs, all GM voxels except the PTSD-related voxels, and voxels within randomly generated ROIs.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4524593&req=5

pone.0134717.g003: Mean classification accuracy across participants, trained using three runs, as a function of the brain mask used to select voxels: all GM voxels, only voxels within PTSD-related ROIs, all GM voxels except the PTSD-related voxels, and voxels within randomly generated ROIs.
Mentions: Fig 3 depicts classification accuracy as a function of the voxels used to train the model when using three memory recall repetitions. Classification accuracy was significantly greater when using all GM voxels compared to the model using only voxels within the ROIs implicated in PTSD neurocircuitry models (p < .001) and the randomly generated ROIs (p < .001). Similarly, classification accuracy was significantly greater when using all GM voxels except those within ROIs implicated in PTSD neurocircuitry models compared to using only voxels within ROIs implicated in PTSD models (p < .001) and the randomly generated ROIs (p < .001). Finally, classification accuracy when using voxels only within ROIs implicated in PTSD models did not significantly differ from using only voxels within 8 randomly generated ROIs (p = .08).

Bottom Line: By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall.Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy.Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs.

View Article: PubMed Central - PubMed

Affiliation: Brain Imaging Research Center, Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.

ABSTRACT
Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD.

No MeSH data available.


Related in: MedlinePlus