Automated search of stimulation targets with closed-loop transcranial magnetic stimulation

Tervo, Anne; Metsomaa, Johanna; Nieminen, Jaakko O.; Sarvas, Jukka; Ilmoniemi, Risto J.

doi:10.1016/j.neuroimage.2020.117082

Cited by 41 publications

(37 citation statements)

References 27 publications

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“…The traditional manual coil placement is time-consuming and prone to localization errors on the order of several millimetres and degrees in orientation 26–28 , being a major source of variability across sessions 27 . Our millisecond-control of stimulus orientation enables the development of automated algorithms 29 for closed-loop paradigms triggered by neurophysiological recordings, increasing the efficacy for TMS in both research and clinical applications 30,31 . It also enables novel studies on intracortical inhibition and facilitation mechanisms 5,6 ; for instance, in paired-pulse protocols changing the E-field orientation within a millisecond interval without the need for the mechanical movement of the transducer.…”

Section: Discussionmentioning

confidence: 99%

TMS with fast and accurate electronic control: measuring the orientation sensitivity of corticomotor pathways

Souza

Nieminen

Tugin

et al. 2021

Preprint

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Despite the evident benefit of transcranial magnetic stimulation (TMS) to probe human brain function and treat neurological diseases, current technology allows only a slow, mechanical adjustment of the electric filed orientation. Automated and fast control of the TMS orientation is critical to enable synchronizing the stimulation with the ongoing brain activity. We overcome these limitations with a two-coil electronically controlled TMS transducer to define precisely the pulse orientation (∼1° steps) without mechanical movement. We validated the technology by determining the dependency of motor evoked responses on the stimulus orientation and intensity with high angular resolution. The motor response was found to follow a logistic function of the stimulus orientation, which helps to disentangle the TMS neuronal effects. The electronic control of the TMS electric field is a decisive step towards automated brain stimulation protocols with enhanced accuracy of stimulus targeting and timing for better diagnostics and improved clinical efficacy.

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Section: Discussionmentioning

confidence: 99%

TMS with fast and accurate electronic control: measuring the orientation sensitivity of corticomotor pathways

Souza

Nieminen

Tugin

et al. 2021

Preprint

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“…However, exploring the effects of all tACS parameters on the performance of different individuals requires an exhausting amount of testing when considering different current (0-2 mA) and frequency (0-100 Hz) combinations. 4 One recently proposed method for selecting parameters in brain stimulation is Bayesian optimization (BO) (15,16). BO is an active machine learning technique that aims to find the global optimum of a black-box function ( ) by making a series of evaluations.…”

Section: Introductionmentioning

confidence: 99%

“…The present work was inspired by previous work that used BO in human-based research (15,16,(18)(19)(20) In these previous BO studies, all iterations of the process are run on the same individual, allowing the experimenters to achieve person-specific results.…”

Section: Introductionmentioning

confidence: 99%

“…The present work was inspired by previous work that used BO in human-based research (15, 16, 18–20) In these previous BO studies, all iterations of the process are run on the same individual, allowing the experimenters to achieve person-specific results. However, to do this, the entire BO process must be run for each individual that requires stimulation - a lengthy and costly process.…”

Section: Introductionmentioning

confidence: 99%

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Personalized Closed-Loop Brain Stimulation for Effective Neurointervention Across Participants

Bueren

Nguyen

et al. 2021

Preprint

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Accumulating evidence from human-based research has highlighted that the prevalent one-size-fits-all approach for neural and behavioral interventions is inefficient. This approach can benefit one individual, but be ineffective or even detrimental for another. Studying the efficacy of the large range of different parameters for different individuals is costly, time-consuming and requires a large sample size that makes such research impractical and hinders effective interventions. Here an active machine learning technique is presented across participants—personalized Bayesian optimization (pBO)—that searches available parameter combinations to optimize an intervention as a function of an individual’s ability. This novel technique was utilized to identify transcranial alternating current stimulation frequency and current strength combinations most likely to improve arithmetic performance, based on a subject’s baseline arithmetic abilities. The pBO was performed across all subjects tested, building a model of subject performance, capable of recommending parameters for future subjects based on their baseline arithmetic ability. pBO successfully searches, learns, and recommends parameters for an effective neurointervention as supported by behavioral, stimulation, and neural data. The application of pBO in human-based research opens up new avenues for personalized and more effective interventions, as well as discoveries of protocols for treatment and translation to other clinical and non-clinical domains.

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“…This allows for the identification of those TMS coil positions on the head surface that yield the strongest effect. Frameworks have been proposed to reduce user-dependence [19], relying on custom built TMS hardware to identify the optimal coil position in an automated way. These coil configurations can then be projected onto the cortex to estimate functionally relevant brain structures in a simplified manner [7,20].…”

Section: Introductionmentioning

confidence: 99%

Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression

Numssen

Zier

Thielscher

et al. 2021

Preprint

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Background: The precise cortical origins of the electrophysiological and behavioral effects of transcranial magnetic stimulation (TMS) remain largely unclear. Addressing this question is further impeded by substantial inter-individual response variability to TMS. Objective: We present a novel method to reliably and user-independently determine the effectively stimulated cortical site at the individual subject level. This generic approach combines physiological measurements with electric field simulations and leverages information from random coil positions, electric field estimations, and electromyography. Methods: We applied ~1000 single biphasic TMS pulses with standard TMS hardware to 13 subjects with random coil positions & orientations over the primary motor hand area. Motor evoked potentials (MEPs) of three finger muscles were recorded concurrently. We calculated the corresponding electric fields for all TMS pulses and regressed them against the elicited MEPs in each cortical element. This yields a cortical map of congruency between induced field strength and generated response. Results: We observed high congruence between the electric fields and the elicited MEPs in hotspots located primarily on the crowns and rims of the precentral gyrus. The three cortical digit representations could be distinguished at the individual subject level with a high spatial resolution. A post-hoc convergence analysis revealed a possible lower bound of only 180 pulses to obtain qualitatively identical results. Conclusions: Leveraging information from many different TMS pulses significantly reduces the number of necessary stimulations and mapping time. The protocol is easy to implement due to the realization of arbitrary coil positions & orientations and is suitable for practical and clinical use such as preoperative mapping.

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Automated search of stimulation targets with closed-loop transcranial magnetic stimulation

Cited by 41 publications

References 27 publications

TMS with fast and accurate electronic control: measuring the orientation sensitivity of corticomotor pathways

TMS with fast and accurate electronic control: measuring the orientation sensitivity of corticomotor pathways

Personalized Closed-Loop Brain Stimulation for Effective Neurointervention Across Participants

Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression

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