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Record W4253878734 · doi:10.32920/ryerson.14657403.v1

Subregional activation of the amygdala during emotional memory encoding in posttraumatic stress disorder: an FMRI investigation

2021· preprint· en· W4253878734 on OpenAlexaffabout
Ronak Patel

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsSystems, Applications & Products in Data Processing (Canada)Toronto Metropolitan UniversityQueen's University
Fundersnot available
KeywordsAmygdalaPsychologyFunctional magnetic resonance imagingNeuroscienceArousalCognitionBasolateral amygdala

Abstract

fetched live from OpenAlex

Posttraumatic stress disorder (PTSD) is characterized as a debilitating and disruptive psychiatric condition that arises following exposure to a single or multiple traumatic events. The disorder expresses itself as a constellation of physical, cognitive, and emotional symptoms and leads to significant impairment in social and occupation functioning. In Canada, the majority of Canadians are exposed to at least one traumatic event in their lifetime and almost one in ten Canadians go on to develop the disorder. Despite evolving conceptualizations of PTSD, re-experiencing symptoms related to recurrent and intrusive memories remains a core feature of the disorder, and these recollections often accompany other changes in memory. The mechanisms underlying memory disturbances in PTSD however, remain less clear. Early fear conditioning studies in non-human primates implicated alterations to the basolateral subdivision of the amygdala (BLA) in the pathogenesis of PTSD, due to its role in learning and memory for threatening events. The overall goal of this dissertation was to examine whether PTSD is associated with alterations in functional brain activation across three distinct subregions of the amygdala during memory encoding of emotional events varying in valence and arousal. Specifically, using functional magnetic resonance imaging (fMRI) and analysis methods based on probabilistic cytoarchitectonic mapping, activation of the amygdala subregions was examined for a series of photos that participants viewed in the fMRI scanner, and then later remembered during a recognition memory test. Consistent with the study’s primary hypothesis, results those with PTSD (n = 11) showed greater activation of the BLA during encoding of negative relative to positive photos. This effect was unique to the BLA compared with the centromedial amygdala. No subregional differences emerged in the trauma-exposed control group (n = 11). Moreover, the BLA memory effect in the PTSD group was also observed when comorbid depressive symptoms were statistically controlled, and showed a marginally significant effect toward independently predicting symptom severity. Contrary to the study’s hypotheses, there was no evidence of altered BLA activity during memory encoding of high arousing relative to low arousing events. Overall, the results of this dissertation suggest that task-based activation of the amygdala in PTSD is not consistent across the entire structure, and that memory-related processing of negative information is associated with recruitment of the BLA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.299
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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