Human 5-HT Transporter Availability Predicts Amygdala Reactivity<i>In Vivo</i>
Bibliographic record
Abstract
The amygdala plays a central role in fear conditioning, emotional processing, and memory modulation. A postulated key component of the neurochemical regulation of amygdala function is the neurotransmitter 5-hydroxytryptamine (5-HT), and synaptic levels of 5-HT in the amygdala and elsewhere are critically regulated by the 5-HT transporter (5-HTT). The aim of this study was to directly examine the relationship between 5-HTT availability and amygdala activity using multimodal [positron emission tomography (PET) and functional magnetic resonance imaging (fMRI)] imaging measures in the same individuals. Healthy male volunteers who had previously undergone an [11C]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)-benzonitrile ([11C]-DASB) PET scan to determine 5-HTT availability completed an fMRI emotion recognition task. [11C]-DASB binding potential values were calculated for the amygdala using arterial input function and linear graphical (Logan) analysis. fMRI was performed on a 3T Philips Intera scanner, and data were analyzed using SPM2 (Wellcome Department Imaging Neuroscience, University College London). Percentage signal change during the task was extracted from the amygdala using MarsBaR (Brett et al., 2002). fMRI analysis revealed significant amygdala activation during the emotion recognition task. Region of interest analyses demonstrated a significant negative correlation between fMRI signal change in the left amygdala and 5-HTT availability in the left amygdala, with 5-HTT availability accounting for approximately 42% of the variability in left amygdala activity. Our novel in vivo data highlight the central importance of the serotonergic system in the responsiveness of the human amygdala during emotional processing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".