A Neuroanatomy of Positive Affect Display – Subcortical Fiber Pathways Relevant for Initiation and Modulation of Smiling and Laughing
Bibliographic record
Abstract
Background We here report two cases of stimulation induced pathological laughter (PL) under thalamic deep brain stimulation (DBS) for essential tremor and interpret the effects based on a modified neuroanatomy of positive affect display (PAD). Objective/Hypothesis The hitherto existing neuroanatomy of PAD can be augmented with recently described parts of the motor medial forebrain bundle (motorMFB). We speculate that a co-stimulation of parts of this fiber structure might lead to a non-volitional modulation of PAD resulting in PL. Methods We describe the clinical and individual imaging workup and combine the interpretation with normative diffusion tensor imaging (DTI)-tractography descriptions of motor connections of the ventral tegmental area (VTA) ( n = 200 subjects, HCP cohort), [[ 18 F] fluorodeoxyglucose ( 18 FDG)] positron emission tomography (PET), and volume of activated tissue simulations. We integrate these results with literature concerning PAD and the neuroanatomy of smiling and laughing. Results DBS electrodes bilaterally co-localized with the MB-pathway (“limiter pathway”). The FDG PET activation pattern allowed to explain pathological PAD. A conceptual revised neuroanatomy of PAD is described. Conclusion Eliciting pathological PAD through chronic thalamic DBS is a new finding and has previously not been reported. PAD is evolution driven, hard wired to the brain and realized over previously described branches of the motorMFB. A major relay region is the VTA/mammillary body complex. PAD physiologically undergoes conscious modulation mainly via the MB branch of the motorMFB (limiter). This limiter in our cases is bilaterally disturbed through DBS. The here described anatomy adds to a previously described framework of neuroanatomy of laughter and humor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".