Seasonal Variation in Human Brain Serotonin Transporter Binding
Bibliographic record
Abstract
CONTEXT: It is a common experience in temperate zones that individuals feel happier and more energetic on bright and sunny days and many experience a decline in mood and energy during the dark winter season. Brain serotonin is involved in the regulation of physiologic functions, such as mating, feeding, energy balance, and sleep. Although these behaviors and serotonin-related conditions show a clear seasonal pattern in humans, the molecular background of seasonal changes in serotonin function is entirely unknown. The serotonin transporter is a key element in regulating intensity and spread of the serotonin signal. OBJECTIVES: To detect seasonal variations in serotonin transporter binding in the living human brain and to detect correlations between serotonin transporter binding and duration of daily sunshine. DESIGN: Regional serotonin transporter binding potential values, an index of serotonin transporter density, were assessed from December 1, 1999, to December 9, 2003, in a consecutive sample of healthy volunteers. Binding potential values were related to meteorologic data. SETTING: Tertiary care psychiatric hospital. PARTICIPANTS: Volunteer sample of 88 drug-naive healthy individuals. INTERVENTION: Carbon 11-labeled 3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)-benzonitrile positron emission tomography. MAIN OUTCOME MEASURE: Regional serotonin transporter binding potential values. RESULTS: Serotonin transporter binding potential values were significantly higher in all investigated brain regions in individuals investigated in the fall and winter compared with those investigated in the spring and summer (P = .01 to .001). Moreover, binding potential values showed negative correlations with average duration of daily sunshine in all brain regions (rho = -0.21 to -0.39; P = .05 to <.001), such that higher values occurred at times of lesser light. CONCLUSIONS: Serotonin transporter binding potential values vary throughout the year with the seasons. Since higher serotonin transporter density is associated with lower synaptic serotonin levels, regulation of serotonin transporter density by season is a previously undescribed physiologic mechanism that has the potential to explain seasonal changes in normal and pathologic behaviors.
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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) | 0.001 | 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".