In Reply: Deep Brain Stimulation of the Pedunculopontine Nucleus Area in Parkinson Disease: Magnetic Resonance Imaging-Based Anatomoclinical Correlations and Optimal Target
Bibliographic record
Abstract
To the Editor: We thank the authors1 for their interest in our recent article.2 In this letter,1 the authors review the key points raised during the last decade on deep brain stimulation of the pedunculopontine nucleus (PPN) to treat resistant gait disorders in Parkinson disease. The authors then seize the opportunity to question the involvement of the PPN in essential tremor (ET). Based on resting-state functional magnetic resonance imaging (fMRI) data, the authors suggest a possible involvement of the PPN in the pathophysiology of ET. We wish to address the author's commentary by providing some points in the context of deep brain stimulation of the PPN and its involvement in neurological disorders. To our knowledge, no study already investigated a potential involvement of the PPN in the pathophysiology of ET, except the data provided by the authors. From an anatomical point of view, an involvement of the PPN in ET is possible due to the projections from the deep cerebellar nuclei to the PPN. Indeed, this group of cerebellar nuclei is in a key position in the cerebello-thalamo-cortical network, known to have a role in the pathophysiology of ET.3-6 This connection (deep cerebellar nuclei >PPN) was studied by Hazrati and Parent7 in 1992 in the squirrel monkey using tracing methods. Projections from the PPN to the cerebellum have also been described in different species including human for decades using different methodology.8 In this regard, it could be interesting to evaluate the functional connectivity between these 2 structures in the context of ET. As pointed out in our article,2 interindividual brainstem anatomical variability makes comparison of electrode placement (or fMRI region of interest [ROI]) in the rostral brainstem difficult and should be analyzed very cautiously. In this regard, we defined the Brainstem Normalized Coordinate System (BNCS) which allows comparison of brainstem anatomical data in between subjects. It would be interesting to evaluate the position of the ROI in the PPN area provided by the authors in the BNCS. Then, it would possible to see whether the ROI corresponds to the area of electrode implantation in the PPN in the mesencephalic reticular formation defined in our study. The PPN is a complex and heterogeneous reticular structure involved in several functions (locomotion, waking state, arousal, rapid eye movement-sleep, etc). It is now accepted that this structure should not be considered as a pure (loco)-motor structure but rather as an integrative one9 and potentially involved in different neurological and psychiatric disorders.10 As an example, the freezing of gait is a complex symptom that cannot be viewed as a motor trouble11 but rather as a possible misintegration of locomotor, postural, attentional, and executive functions. In this perspective, the PPN has certainly a key role in the pathophysiology of this symptom and could explain some positive clinical outcomes of deep brain stimulation of this structure. Could the PPN be also involved in ET regarding its connections with cerebellum, thalamic nuclei, basal ganglia, and other brainstem nuclei is an exciting question? We join the authors1 in encouraging future studies to investigate a role of the PPN in this disorder. Disclosures Dr Chabardès serves as a consultant for Boston Scientific and for Medtronic and has received financial support from Medtronic for pre-clinical research purposes in the field of deep brain stimulation. Medtronic provided the pulse generators for the original study free of charge.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.019 | 0.022 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".