Objective: To precisely characterize patient-specific connectivity changes in response to botulinum toxin injection.

Background: Adductor laryngeal dystonia (ADLD) is a type of task-specific focal dystonia characterized by excessive laryngeal muscle contraction during speech. ADLD is associated with dysfunction in various brain regions including primary motor cortex (M1), basal ganglia, thalamus, and cerebellum^1,4,6. Treatment typically involves repeated injections of botulinum toxin into the laryngeal muscles. Developing less invasive therapies requires a deeper understanding of the neural mechanisms involved in therapeutic response. Prior work suggested changes in functional connectivity (FC), as measured with resting-state functional MRI (rs-fMRI), following successful botulinum injections in dystonia patients⁵. However, these studies lacked detailed individual patient data, making it difficult to detect patient-specific therapeutic responses. To address this gap, we employed precision functional mapping (PFM) which collects more extensive per-patient data^2,3.

Method: We aimed to identify the vocalization-related motor network in ADLD patients and describe individual-specific network alterations following botulinum toxin therapy. We collected five MRI sessions totaling 125 minutes of rs-fMRI and 40 minutes of task fMRI (vocalization task) before and after successful injections in four participants. FMRI images were preprocessed³ and vocalization-related brain regions were identified individually using task fMRI data. These regions served as seeds for FC analysis to calculate correlations between ROI-average rs-fMRI signals and signals from all other brain regions. In each patient, we examined changes between pre- vs post-injection in both vocalization-driven activity and network FC using paired t-tests, with a focus on the basal ganglia and cerebellum.

Results: Our results showed reductions in both vocalization-related activation and vocalization network FC in the putamen and motor cerebellum following injections. Notably, the precise locations of these changes varied across patients.

Conclusion: These findings provide insight into the neural mechanisms related to effective therapy and suggest potential target sites for future therapeutic interventions. Furthermore, our study highlights the value of PFM in understanding patient-specific network alterations in dystonia.

References: 1. Battistella, Giovanni, Pichet Termsarasab, Ritesh A. Ramdhani, Stefan Fuertinger, and Kristina Simonyan. 2017. “Isolated Focal Dystonia as a Disorder of Large-Scale Functional Networks.” Cerebral Cortex 27 (2): 1203–15. https://doi.org/10.1093/cercor/bhv313.
2. Gordon, Evan M., Timothy O. Laumann, Adrian W. Gilmore, Dillan J. Newbold, Deanna J. Greene, Jeffrey J. Berg, Mario Ortega, et al. 2017. “Precision Functional Mapping of Individual Human Brains.” Neuron 95 (4): 791-807.e7. https://doi.org/10.1016/j.neuron.2017.07.011.
3. Gordon, Evan M., Timothy O. Laumann, Scott Marek, Dillan J. Newbold, Jacqueline M. Hampton, Nicole A. Seider, David F. Montez, et al. 2021. “Human Fronto-Striatal Connectivity Is Organized into Discrete Functional Subnetworks.” bioRxiv. https://doi.org/10.1101/2021.04.12.439415.
4. Hanekamp, Sandra, and Kristina Simonyan. 2020. “The Large‐scale Structural Connectome of Task‐specific Focal Dystonia.” Human Brain Mapping 41 (12): 3253–65. https://doi.org/10.1002/hbm.25012.
5. Nevrlý, Martin, Petr Hluštík, Pavel Hok, Pavel Otruba, Zbyněk Tüdös, and Petr Kaňovský. n.d. “Changes in Sensorimotor Network Activation after Botulinum Toxin Type A Injections in Patients with Cervical Dystonia: A Functional MRI Study | Experimental Brain Research.” Accessed November 9, 2023. https://link.springer.com/article/10.1007/s00221-018-5322-3.
6. Norris, Scott A., Aimee E. Morris, Meghan C. Campbell, Morvarid Karimi, Babatunde Adeyemo, Randal C. Paniello, Abraham Z. Snyder, Steven E. Petersen, Jonathan W. Mink, and Joel S. Perlmutter. 2020. “Regional, Not Global, Functional Connectivity Contributes to Isolated Focal Dystonia.” Neurology 95 (16): e2246–58. https://doi.org/10.1212/WNL.0000000000010791.
7. Power, Jonathan D., Anish Mitra, Timothy O. Laumann, Abraham Z. Snyder, Bradley L. Schlaggar, and Steven E. Petersen. 2014. “Methods to Detect, Characterize, and Remove Motion Artifact in Resting State fMRI.” NeuroImage 84 (January): 320–41. https://doi.org/10.1016/j.neuroimage.2013.08.048.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/precision-functional-mapping-of-therapeutic-response-in-task-specific-focal-dystonia/