Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback
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{"title"=>"Decoding the traumatic memory among women with PTSD: Implications for neurocircuitry models of PTSD and real-time fMRI neurofeedback", "type"=>"journal", "authors"=>[{"first_name"=>"Josh M.", "last_name"=>"Cisler", "scopus_author_id"=>"15822105000"}, {"first_name"=>"Keith", "last_name"=>"Bush", "scopus_author_id"=>"7102318934"}, {"first_name"=>"G. Andrew", "last_name"=>"James", "scopus_author_id"=>"7201399294"}, {"first_name"=>"Sonet", "last_name"=>"Smitherman", "scopus_author_id"=>"55514850500"}, {"first_name"=>"Clinton D.", "last_name"=>"Kilts", "scopus_author_id"=>"7004384138"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"doi"=>"10.1371/journal.pone.0134717", "sgr"=>"84941946239", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"26241958", "issn"=>"19326203", "scopus"=>"2-s2.0-84941946239", "pui"=>"606057548"}, "id"=>"dd0c713a-a16b-3535-aa59-1799d742c4c5", "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.", "link"=>"http://www.mendeley.com/research/decoding-traumatic-memory-among-women-ptsd-implications-neurocircuitry-models-ptsd-realtime-fmri-neu", "reader_count"=>71, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>10, "Student > Doctoral Student"=>9, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>3, "Student > Master"=>14, "Other"=>1, "Student > Bachelor"=>9, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>10, "Student > Doctoral Student"=>9, "Student > Ph. D. 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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2199733"], "description"=>"<p>Note. PCL = Posttraumatic Checklist—civilian version; BDI-II = Beck Depression Inventory-II.</p><p>Demographic and clinical characteristics of the 16 adult women in this sample.</p>", "links"=>[], "tags"=>["trauma memory vs", "multivariate pattern analysis", "brain regions", "roi", "mvpa", "processing mechanisms", "trauma memory", "neurocircuitry models", "assaultive violence exposure", "PTSD symptom severity", "accuracy"], "article_id"=>1501568, "categories"=>["Biological Sciences"], "users"=>["Josh M. Cisler", "Keith Bush", "G. Andrew James", "Sonet Smitherman", "Clinton D. Kilts"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0134717.t001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_and_clinical_characteristics_of_the_16_adult_women_in_this_sample_/1501568", "title"=>"Demographic and clinical characteristics of the 16 adult women in this sample.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-08-04 02:46:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/2199731"], "description"=>"<p>a) Mean SVM feature weights across participants with PTSD-related ROIs. b) scatter plot depicting negative linear relationship between PTSD symptom severity and mean SVM feature weight within the left amygdalohippocampal (p value comes from robust regression analysis also controlling for age, comorbid depression, and comorbid substance use disorders).</p>", "links"=>[], "tags"=>["trauma memory vs", "multivariate pattern analysis", "brain regions", "roi", "mvpa", "processing mechanisms", "trauma memory", "neurocircuitry models", "assaultive violence exposure", "PTSD symptom severity", "accuracy"], "article_id"=>1501566, "categories"=>["Biological Sciences"], "users"=>["Josh M. Cisler", "Keith Bush", "G. Andrew James", "Sonet Smitherman", "Clinton D. Kilts"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0134717.g004", "stats"=>{"downloads"=>2, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Decoding_the_Traumatic_Memory_among_Women_with_PTSD_Implications_for_Neurocircuitry_Models_of_PTSD_and_Real_Time_fMRI_Neurofeedback_Fig_4_/1501566", "title"=>"Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback - Fig 4", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-04 02:46:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/2199728"], "description"=>"<p>Mean classification accuracy across participants (and standard error) as a function of number of runs used to train the model and spatial smoothing.</p>", "links"=>[], "tags"=>["trauma memory vs", "multivariate pattern analysis", "brain regions", "roi", "mvpa", "processing mechanisms", "trauma memory", "neurocircuitry models", "assaultive violence exposure", "PTSD symptom severity", "accuracy"], "article_id"=>1501563, "categories"=>["Biological Sciences"], "users"=>["Josh M. Cisler", "Keith Bush", "G. Andrew James", "Sonet Smitherman", "Clinton D. Kilts"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0134717.g001", "stats"=>{"downloads"=>4, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mean_classification_accuracy_across_participants_and_standard_error_as_a_function_of_number_of_runs_used_to_train_the_model_and_spatial_smoothing_/1501563", "title"=>"Mean classification accuracy across participants (and standard error) as a function of number of runs used to train the model and spatial smoothing.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-04 02:46:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/2199730"], "description"=>"<p>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.</p>", "links"=>[], "tags"=>["trauma memory vs", "multivariate pattern analysis", "brain regions", "roi", "mvpa", "processing mechanisms", "trauma memory", "neurocircuitry models", "assaultive violence exposure", "PTSD symptom severity", "accuracy"], "article_id"=>1501565, "categories"=>["Biological Sciences"], "users"=>["Josh M. Cisler", "Keith Bush", "G. Andrew James", "Sonet Smitherman", "Clinton D. Kilts"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0134717.g003", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_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_gen/1501565", "title"=>"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.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-04 02:46:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/2199729"], "description"=>"<p>a) scatter plots for a single participant showing the spatial correlation between SVM feature weights for each voxel when trained using a single run with SVM feature weights when trained using two runs (top) and correlation between SVM feature weights when trained using a single run and SVM feature weights when trained using 5 runs. b) spatial correlation across participants for the voxelwise SVM feature weights between the different models.</p>", "links"=>[], "tags"=>["trauma memory vs", "multivariate pattern analysis", "brain regions", "roi", "mvpa", "processing mechanisms", "trauma memory", "neurocircuitry models", "assaultive violence exposure", "PTSD symptom severity", "accuracy"], "article_id"=>1501564, "categories"=>["Biological Sciences"], "users"=>["Josh M. Cisler", "Keith Bush", "G. Andrew James", "Sonet Smitherman", "Clinton D. Kilts"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0134717.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Decoding_the_Traumatic_Memory_among_Women_with_PTSD_Implications_for_Neurocircuitry_Models_of_PTSD_and_Real_Time_fMRI_Neurofeedback_Fig_2_/1501564", "title"=>"Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback - Fig 2", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-04 02:46:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/2199734"], "description"=>"<div><p>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.</p></div>", "links"=>[], "tags"=>["trauma memory vs", "multivariate pattern analysis", "brain regions", "roi", "mvpa", "processing mechanisms", "trauma memory", "neurocircuitry models", "assaultive violence exposure", "PTSD symptom severity", "accuracy"], "article_id"=>1501569, "categories"=>["Biological Sciences"], "users"=>["Josh M. Cisler", "Keith Bush", "G. Andrew James", "Sonet Smitherman", "Clinton D. Kilts"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0134717", "stats"=>{"downloads"=>3, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Decoding_the_Traumatic_Memory_among_Women_with_PTSD_Implications_for_Neurocircuitry_Models_of_PTSD_and_Real_Time_fMRI_Neurofeedback_/1501569", "title"=>"Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-04 02:46:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/2199732"], "description"=>"<p>top) Mean classification accuracy across participants for the three run model and the model trained to differentiate high- and low-motion TRs. Bottom) Spatial correlation between the three and two run models trained to differentiate trauma from neutral memory recall, and spatial correlation between three run model trained to differentiate trauma recall and three run model trained to differentiate motion.</p>", "links"=>[], "tags"=>["trauma memory vs", "multivariate pattern analysis", "brain regions", "roi", "mvpa", "processing mechanisms", "trauma memory", "neurocircuitry models", "assaultive violence exposure", "PTSD symptom severity", "accuracy"], "article_id"=>1501567, "categories"=>["Biological Sciences"], "users"=>["Josh M. Cisler", "Keith Bush", "G. Andrew James", "Sonet Smitherman", "Clinton D. Kilts"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0134717.g005", "stats"=>{"downloads"=>3, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Decoding_the_Traumatic_Memory_among_Women_with_PTSD_Implications_for_Neurocircuitry_Models_of_PTSD_and_Real_Time_fMRI_Neurofeedback_Fig_5_/1501567", "title"=>"Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback - Fig 5", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-04 02:46:45"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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