Optimizing the Electric Field Strength in Multiple Targets for Multichannel Transcranial Electric Stimulation

Abstract

Objective:Most approaches to optimize the electric field pattern generated by multichannel Transcranial Electric Stimulation (TES) require the definition of a preferred direction of the electric field in the target region(s). However, this requires knowledge about how the neural effects depend on the field direction, which is not always available. Thus, it can be preferential to optimize the field strength in the target(s), irrespective of the field direction. However, this results in a more complex optimization problem. Approach:We introduce and validate a novel optimization algorithm that maximizes focality while controlling the electric field strength in the target to maintain a defined value. It obeys the safety constraints, allows limiting the number of active electrodes and allows also for multi-target optimization. Main Results:The optimization algorithm outperformed naïve search approaches in both quality of the solution and computational efficiency. Using the amygdala as test case, we show that it allows for reaching a reasonable trade-off between focality and field strength in the target. In contrast, simply maximizing the field strength in the target results in far more extended fields. In addition, by maintaining the pre-defined field strengths in the targets, the new algorithm allows for a balanced stimulation of two or more regions. Significance:The novel algorithm can be used to automatically obtain individualized, optimal montages for targeting regions without the need to define preferential directions. It will automatically select the field direction that achieves the desired field strength in the target(s) with the most focal stimulation pattern.

Mapping cortical excitability in the human dorsolateral prefrontal cortex

“…Although our results suggest that absolute intensity differences did not contribute significantly to early TEP strength (Fig. S5), E-field modeling could influence the effective intensities used to probe different targets (48,49). In the future as these models continue to improve, it is worth re-examining these targets with more sophisticated E-field matching.…”

A Systematic Review and Large-Scale tES and TMS Electric Field Modeling Study Reveals How Outcome Measure Selection Alters Results in a Person- and Montage-Specific Manner

“…While both metrics pursue a common goal, they do so in a substantially different manner. Whereas the ROI focuses on a specific, user-defined brain region (e.g., the left primary motor cortex [M1]) [17][18][19][20][21][22], a percentile whole-brain approach studies E-fields across the entire brain and does not restrict the analyses to any region [23][24][25]. Moreover, even within the same approach, wide methodological variations prevail.…”

“…; https://doi.org/10.1101/2023.02. 22.529540 doi: bioRxiv preprint 3 spherical ROIs of considerably different radii, ranging between 0.5 and 45 mm, whereas others used different geometric shapes such as a cubical ROI [17][18][19][20][21][22].…”