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Fast And Accurate Population Level Transcranial Magnetic Stimulation via Low-Rank Probabilistic Matrix Decomposition (PMD)

Hasan, N. I.; Wang, D.; Gomez, L.

2023-02-09 neuroscience
10.1101/2023.02.08.527758 bioRxiv
Show abstract

Transcranial magnetic stimulation (TMS) is used to study brain function and treat mental health disorders. During TMS, a coil placed on the scalp induces an E-field in the brain that modulates its activity. TMS is known to stimulate regions that are exposed to a large E-field. Clinical TMS protocols prescribe a coil placement based on scalp landmarks. There are inter-individual variations in brain anatomy that result in variations in the TMS-induced E-field at the targeted region and its outcome. These variations across individuals could in principle be minimized by developing a large database of head subjects and determining scalp landmarks that maximize E-field at the targeted brain region while minimizing its variation using computational methods. However, this approach requires repeated execution of a computational method to determine the E-field induced in the brain for a large number of subjects and coil placements. We developed a probabilistic matrix decomposition-based approach for rapidly evaluating the E-field induced during TMS for a large number of coil placements. Our approach can determine the E-field induced in over 1 Million coil placements in 9.5 hours, in contrast, to over 5 years using a bruteforce approach. After the initial set-up stage, the E-field can be predicted over the whole brain within 2-3 milliseconds and to 2% accuracy. We tested our approach in over 200 subjects and achieved an error of < 2% in most and < 3.5% in all subjects. We will present several examples of bench-marking analysis for our tool in terms of accuracy and speed across and its applicability for population level optimization of coil placement. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=125 HEIGHT=200 SRC="FIGDIR/small/527758v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@1650e2dorg.highwire.dtl.DTLVardef@185e477org.highwire.dtl.DTLVardef@15a4376org.highwire.dtl.DTLVardef@10304fa_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA method for practical E-field informed population-level TMS coil placement strategies is developed. C_LIO_LIThis algorithm enables the determination of E-field informed optimal coil placement in seconds enabling its use for close-loop and on-the-fly reconfiguration of TMS. C_LIO_LIAfter the initial set-up stage of less than 10 hours, the E-field can be predicted for any coil placement across the whole brain within in 2-3 milliseconds. C_LI

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