Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

Tervo, Anne; Nieminen, Jaakko O.; Lioumis, Pantelis; Metsomaa, Johanna; Souza, Victor H.; Sinisalo, Heikki; Stenroos, Matti; Sarvas, Jukka; Ilmoniemi, Risto J.

doi:10.1016/j.brs.2022.01.016

Cited by 45 publications

(29 citation statements)

References 54 publications

(76 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The left dlPFC site (MNI‐38, MNI‐22, MNI‐38) was used to target the fronto‐parietal control network (Chen et al, 2013 ). TMS coil angle was placed at the angle between 0° and 90° (Brasil‐Neto et al, 1992 ; Janssen et al, 2015 ; Laakso et al, 2014 ; Mills et al, 1992 ; Tervo et al, 2021 ) that most minimized discomfort and pain for each subject ( M = 52°, SD = 27). Table S1 includes the optimal angle for each subject.…”

Section: Methodsmentioning

confidence: 99%

Experimental suppression of transcranial magnetic stimulation‐electroencephalography sensory potentials

Ross

Sarkar

Keller

2022

Human Brain Mapping

View full text Add to dashboard Cite

The sensory experience of transcranial magnetic stimulation (TMS) evokes cortical responses measured in electroencephalography (EEG) that confound interpretation of TMS-evoked potentials (TEPs). Methods for sensory masking have been proposed to minimize sensory contributions to the TEP, but the most effective combination for suprathreshold TMS to dorsolateral prefrontal cortex (dlPFC) is unknown. We applied sensory suppression techniques and quantified electrophysiology and perception from suprathreshold dlPFC TMS to identify the best combination to minimize the sensory TEP. In 21 healthy adults, we applied single pulse TMS at 120% resting motor threshold (rMT) to the left dlPFC and compared EEG vertex N100-P200 and perception. Conditions included three protocols: No masking (no auditory masking, no foam, and jittered interstimulus interval [ISI]), Standard masking (auditory noise, foam, and jittered ISI), and our ATTENUATE protocol (auditory noise, foam, over-the-ear protection, and unjittered ISI). ATTENUATE reduced vertex N100-P200 by 56%, "click" loudness perception by 50%, and scalp sensation by 36%. We show that sensory prediction, induced with predictable ISI, has a suppressive effect on vertex N100-P200, and that combining standard suppression protocols with sensory prediction provides the best N100-P200 suppression. ATTENUATE was more effective than Standard masking, which only reduced vertex N100-P200 by 22%, loudness by 27%, and scalp sensation by 24%. We introduce a sensory suppression protocol superior to Standard masking and demonstrate that using an unjittered ISI can contribute to minimizing sensory confounds. ATTENUATE provides superior sensory suppression to increase TEP signal-to-noise and contributes to a growing understanding of TMS-EEG sensory neuroscience.

show abstract

Section: Methodsmentioning

confidence: 99%

Experimental suppression of transcranial magnetic stimulation‐electroencephalography sensory potentials

Ross

Sarkar

Keller

2022

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…Interestingly, ongoing EEG features are now used to provide feedback to determine, for instance, the exact timing of rTMS pulses. Known as closed-loop stimulation, these approaches aim to enhance the neuroplastic capacity of rTMS by coupling the TMS parameters to real-time EEG biomarkers [ 83 , 84 ].…”

Section: Transcranial Magnetic Stimulation (Tms)mentioning

confidence: 99%

Evidence of Neuroplastic Changes after Transcranial Magnetic, Electric, and Deep Brain Stimulation

et al. 2022

View full text Add to dashboard Cite

Electric and magnetic stimulation of the human brain can be used to excite or inhibit neurons. Numerous methods have been designed over the years for this purpose with various advantages and disadvantages that are the topic of this review. Deep brain stimulation (DBS) is the most direct and focal application of electric impulses to brain tissue. Electrodes are placed in the brain in order to modulate neural activity and to correct parameters of pathological oscillation in brain circuits such as their amplitude or frequency. Transcranial magnetic stimulation (TMS) is a non-invasive alternative with the stimulator generating a magnetic field in a coil over the scalp that induces an electric field in the brain which, in turn, interacts with ongoing brain activity. Depending upon stimulation parameters, excitation and inhibition can be achieved. Transcranial electric stimulation (tES) applies electric fields to the scalp that spread along the skull in order to reach the brain, thus, limiting current strength to avoid skin sensations and cranial muscle pain. Therefore, tES can only modulate brain activity and is considered subthreshold, i.e., it does not directly elicit neuronal action potentials. In this review, we collect hints for neuroplastic changes such as modulation of behavior, the electric activity of the brain, or the evolution of clinical signs and symptoms in response to stimulation. Possible mechanisms are discussed, and future paradigms are suggested.

show abstract

“…Most of the existing closed loop controllers of TMS are based on feedback from surface measurements like EEG, EMG (Kraus et al, 2016;Tervo et al, 2020Tervo et al, , 2022 or imaging modes like functional magnetic resonance imaging (fMRI) (Hernández-Ribas et al, 2013;Jung et al, 2020). Some of the earliest studies of neural response to TMS are based on the changes in the motor evoked potentials (MEPs) (Pascual-Leone et al, 1998;Peterchev et al, 2013).…”

Section: Stimulus-response Modelsmentioning

confidence: 99%

Brain modeling for control: A review

Acharya

Ruf

Nozari

2022

Front. Control Eng.

View full text Add to dashboard Cite

Neurostimulation technologies have seen a recent surge in interest from the neuroscience and controls communities alike due to their proven potential to treat conditions such as epilepsy, Parkinson’s Disease, and depression. The provided stimulation can be of different types, such as electric, magnetic, and optogenetic, and is generally applied to a specific region of the brain in order to drive the local and/or global neural dynamics to a desired state of (in)activity. For most neurostimulation techniques, however, an underlying theoretical understanding of their efficacy is still lacking. From a control-theoretic perspective, it is important to understand how each stimulus modality interacts with the inherent complex network dynamics of the brain in order to assess the controllability of the system and develop neurophysiologically relevant computational models that can be used to design the stimulation profile systematically and in closed loop. In this paper, we review the computational modeling studies of 1) deep brain stimulation, 2) transcranial magnetic stimulation, 3) direct current stimulation, 4) transcranial electrical stimulation, and 5) optogenetics as five of the most popular and commonly used neurostimulation technologies in research and clinical settings. For each technology, we split the reviewed studies into 1) theory-driven biophysical models capturing the low-level physics of the interactions between the stimulation source and neuronal tissue, 2) data-driven stimulus-response models which capture the end-to-end effects of stimulation on various biomarkers of interest, and 3) data-driven dynamical system models that extract the precise dynamics of the brain’s response to neurostimulation from neural data. While our focus is particularly on the latter category due to their greater utility in control design, we review key works in the former two categories as the basis and context in which dynamical system models have been and will be developed. In all cases, we highlight the strength and weaknesses of the reviewed works and conclude the review with discussions on outstanding challenges and critical avenues for future work.

show abstract

Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

Cited by 45 publications

References 54 publications

Experimental suppression of transcranial magnetic stimulation‐electroencephalography sensory potentials

Experimental suppression of transcranial magnetic stimulation‐electroencephalography sensory potentials

Evidence of Neuroplastic Changes after Transcranial Magnetic, Electric, and Deep Brain Stimulation

Brain modeling for control: A review

Contact Info

Product

Resources

About