The Optimization of a High-Resolution Brain Atlas as a Tool for Surgical Planning by Translating a Review of Language Function to Parcellation
Abstract number :
3.142
Submission category :
3. Neurophysiology / 3E. Brain Stimulation
Year :
2023
Submission ID :
1101
Source :
www.aesnet.org
Presentation date :
12/4/2023 12:00:00 AM
Published date :
Authors :
Presenting Author: Elizabeth Watson, BS – Yale University
Evan Collins, BS – Biological Engineering – Massachusetts Institute of Technology; Omar Chishti, BS – Neurosurgery – Yale School of Medicine; Hari McGrath, BS – King's College London; Adithya Sivaraju, MD – Neurology – Yale School of Medicine; Hitten Zaveri, PhD – Neurology – Yale School of Medicine; Dennis Spencer, MD – Neurosurgery – Yale School of Medicine
Rationale:
The Yale Brain Atlas (YBA) offers a precise form of cortical brain localization based on the MNI152 template with 690 one cm-square parcels. One of the eventual goals of the YBA is to optimize it for education and usage in a medical environment. Correlating distinct task-related functions of the brain to corresponding parcels on the YBA organizes multimodal information into a valuable educational resource. This project begins with transforming the stimulated language maps of medically intractable patients studied intracranially to the YBA parcels. This patient data is then compared to maps gleaned from the literature that have also been transformed to the YBA. This information could be used in planning surgical approaches, and in analyzing quantitative variations from individual patients to composite maps from the literature. The comparison with literature maps and contemporaneous patients may identify developmental abnormalities that have moved a standard language task by plasticity.
Methods:
A systematic search for fMRI studies, direct electrode stimulation studies, and review papers concerning distinctive brain functions related to language was conducted using the online PubMed Database. Seven papers were chosen as presenting an “expert review” of one or more language functions, selected on the basis of having visual identification of the regions associated with a distinct language function or background information for a given function. The anatomic representations from these papers were then mapped manually to their corresponding parcels in the YBA, organized in a way that will facilitate comparisons with the electrical stimulation cohort undertaken at the Yale School of Medicine. Two sets of quantitative analysis will compare the mapped data on the parcel resolution to the YBA’s Neurosynth database, a compilation of functional terms compiled from over 14,000 fMRI papers, and to the electrical stimulation cohort.
Results:
One hundred fifteen parcels from the YBA, approximately 17 percent of the total parcels, were identified as being relevant to the 27 different language-related functions discussed in the chosen papers. For each individual function ascribed to a parcel, a short narrative was written to explain the nature of the function in question, a series of terms from the YBA’s Neurosynth database were assigned to further describe each function, and the paper associated with the localization of that function was cited in a format to allow for ready access and efficient comparison to the electrical stimulation cohort at the Yale School of Medicine.
Conclusions:
Functional language maps described from the chosen studies overlap, providing a cohesive narrative of language function. Transforming these language maps to the YBA space facilitates quantitative analysis and a platform to compare data from prospective patients undergoing electrical stimulation for language mapping.
Funding:
The Swebilius Foundation and NIH R01 NS109062
Neurophysiology