Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity
Bibliographic record
Abstract
Abstract Three-dimensional atlases of subcortical brain structures are valuable tools to reference anatomy in neuroscience and neurology. In the special case of deep brain stimulation (DBS), the three most common targets are the subthalamic nucleus (STN), the internal part of the pallidum (GPi) and the ventral intermediate nucleus of the thalamus (VIM). With the help of atlases that define the position and shape of these target regions within a well-defined stereotactic space, their spatial relationship to implanted deep brain stimulation (DBS) electrodes may be determined. Here we present a composite atlas based on manual segmentations of a multi-modal high-resolution MNI template series, histology and structural connectivity. To attain exact congruence to the template anatomy, key structures were defined using all four modalities of the template simultaneously. In a first step tissue probability maps were defined based on the multimodal intensity profile of each structure. These observer-independent probability maps provided an excellent basis for the subsequent manual segmentation particularly when defining the outline of the target regions. Second, the key structures were used as an anchor point to coregister a histology based atlas into standard space. Finally, a sub-segmentation of the subthalamic nucleus into three functional zones was estimated based on structural connectivity. The resulting composite atlas uses the spatial information of the MNI template for DBS key structures that are visible on the template itself. For remaining structures, it relies on histology or structural connectivity. In this way the final atlas combines the anatomical detail of a histology based atlas with the spatial accuracy of key structures in relationship to the template anatomy. Thus, the atlas provides an ideal tool for the analysis of DBS electrode placement. Highlights: Composite subcortical atlas based on a multimodal, high definition MNI template series, histology and tractography High definition atlas of DBS targets exactly matching MNI 152 NLIN 2009b space Multimodal subcortical segmentation algorithm applied to MNI template
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".