Dataset Information

Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization.

ABSTRACT:

Background

Selecting optimal stimulation parameters from numerous possibilities is a major obstacle for assessing the efficacy of non-invasive brain stimulation.

Objective

We demonstrate that Bayesian optimization can rapidly search through large parameter spaces and identify subject-level stimulation parameters in real-time.

Methods

To validate the method, Bayesian optimization was employed using participants' binary judgements about the intensity of phosphenes elicited through tACS.

Results

We demonstrate the efficiency of Bayesian optimization in identifying parameters that maximize phosphene intensity in a short timeframe (5?min for >190 possibilities). Our results replicate frequency-dependent effects across three montages and show phase-dependent effects of phosphene perception. Computational modelling explains that these phase effects result from constructive/destructive interference of the current reaching the retinas. Simulation analyses demonstrate the method's versatility for complex response functions, even when accounting for noisy observations.

Conclusion

Alongside subjective ratings, this method can be used to optimize tACS parameters based on behavioral and neural measures and has the potential to be used for tailoring stimulation protocols to individuals.

SUBMITTER: Lorenz R

PROVIDER: S-EPMC6879005 | biostudies-literature | 2019 Nov - Dec

REPOSITORIES: biostudies-literature

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Publications

Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization.

Lorenz Romy R Simmons Laura E LE Monti Ricardo P RP Arthur Joy L JL Limal Severin S Laakso Ilkka I Leech Robert R Violante Ines R IR

Brain stimulation 20190704 6

<h4>Background</h4>Selecting optimal stimulation parameters from numerous possibilities is a major obstacle for assessing the efficacy of non-invasive brain stimulation.<h4>Objective</h4>We demonstrate that Bayesian optimization can rapidly search through large parameter spaces and identify subject-level stimulation parameters in real-time.<h4>Methods</h4>To validate the method, Bayesian optimization was employed using participants' binary judgements about the intensity of phosphenes elicited th ...[more]

PMID: 31289013

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Project description:Non-invasive brain stimulation (NIBS) techniques such as transcranial alternating current stimulation (tACS) have recently become extensively utilized due to their potential to modulate ongoing neuronal oscillatory activity and consequently to induce cortical plasticity relevant for various cognitive functions. However, the neurophysiological basis for stimulation effects as well as their inter-individual differences is not yet understood. In the present study, we used a closed-loop electroencephalography-tACS(EEG-tACS) protocol to examine the modulation of alpha oscillations generated in occipito-parietal areas. In particular, we investigated the effects of a repeated short-time intermittent stimulation protocol (1 s in every trial) applied over the visual cortex (Cz and Oz) and adjusted according to the phase and frequency of visual alpha oscillations on the amplitude of these oscillations. Based on previous findings, we expected higher increases in alpha amplitudes for tACS applied in-phase with ongoing oscillations as compared to an application in anti-phase and this modulation to be present in low-alpha amplitude states of the visual system (eyes opened, EO) but not high (eyes closed, EC). Contrary to our expectations, we found a transient suppression of alpha power in inter-individually derived spatially specific parieto-occipital components obtained via the estimation of spatial filters by using the common spatial patterns approach. The amplitude modulation was independent of the phase relationship between the tACS signal and alpha oscillations, and the state of the visual system manipulated via closed- and open-eye conditions. It was also absent in conventionally analyzed single-channel and multi-channel data from an average parieto-occipital region. The fact that the tACS modulation of oscillations was phase-independent suggests that mechanisms driving the effects of tACS may not be explained by entrainment alone, but rather require neuroplastic changes or transient disruption of neural oscillations. Our study also supports the notion that the response to tACS is subject-specific, where the modulatory effects are shaped by the interplay between the stimulation and different alpha generators. This favors stimulation protocols as well as analysis regimes exploiting inter-individual differences, such as spatial filters to reveal otherwise hidden stimulation effects and, thereby, comprehensively induce and study the effects and underlying mechanisms of tACS.

Dataset Information

Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization.

Background

Objective

Methods

Results

Conclusion

Publications

Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization.

Similar Datasets

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