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Brain simulation techniques have demonstrated undisputable therapeutic effects on neural diseases. Invasive stimulation techniques like deep brain stimulation (DBS) and noninvasive techniques like transcranial magnetic stimulation (TMS) have been approved by FDA as treatments for many drug resist neural disorders and diseases. Developing noninvasive, deep, and targeted brain stimulation techniques is currently one of the important tasks in brain researches. Transcranial direct current stimulation (tDCS) and transcranial alternative current stimulation (tACS) techniques have the advantages of low cost and portability. However, neither of them can produce targeted stimulation due to lacking of electrical field focusing mechanism. Recently, Grossman et al. reported using the down beating signals of two tACS signals to accomplish focused stimulation. By sending two sine waves running at slightly different high frequencies (~2kHz), they demonstrated that they can modulate a “localized” neuron group at the difference frequency of the two sine waves and at the same time avoid excitation of neurons at other locations. As a result, equivalent focusing effect was accomplished by such beating mechanism. In this work, we show neither theoretically nor experimentally the beating mechanism can produce “focusing effect” and the beating signal spread globally across the full brain. The localized modulation effect likely happened right at the electrode contact sites when the electrode contact area is small and the current is concentrated. We conclude that to accomplish noninvasive and focused stimulation at current stage the only available tool is the focused TMS system we recently demonstrated.
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Towards tDCS Digital Twins Using Deep Learning-Based Direct Estimation of Personalized Electrical Field Maps from T1-Weighted MRI
Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation method that applies neuromodulatory effects to the brain via low-intensity, direct current. It has shown possible positive effects in areas such as depression, substance use disorder, anxiety, and pain. Unfortunately, mixed trial results have delayed the field’s progress. Electrical current field approximation provides a way for tDCS researchers to estimate how an individual will respond to specific tDCS parameters. Publicly available physics-based stimulators have led to much progress; however, they can be error-prone, susceptible to quality issues (e.g., poor segmentation), and take multiple hours to run. Digital functional twins provide a method of estimating brain function in response to stimuli using computational methods. We seek to implement this idea for individualized tDCS. Hence, this work provides a proof-of-concept for generating electrical field maps for tDCS directly from T1-weighted magnetic resonance images (MRIs). Our deep learning method employs special loss regularizations to improve the model’s generalizability and calibration across individual scans and electrode montages. Users may enter a desired electrode montage in addition to the unique MRI for a custom output. Our dataset includes 442 unique individual heads from individuals across the adult lifespan. The pipeline can generate results on the scale of minutes, unlike physics-based systems that can take 1–3 hours. Overall, our methods will help streamline the process of individual current dose estimations for improved tDCS interventions. To support open science, the code that is associated with this paper is available at: https://github.com/lab-smile/tDCS-DT.
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- PAR ID:
- 10579446
- Publisher / Repository:
- Springer Nature Switzerland
- Date Published:
- ISBN:
- 978-3-031-72069-7
- Page Range / eLocation ID:
- 465 to 475
- Subject(s) / Keyword(s):
- transcranial direct current stimulation (tDCS) deep learning digital twin
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Study Objectives Synchronization of neural activity within local networks and between brain regions is a major contributor to rhythmic field potentials such as the EEG. On the other hand, dynamic changes in microstructure and activity are reflected in the EEG, for instance slow oscillation (SO) slope can reflect synaptic strength. SO-spindle coupling is a measure for neural communication. It was previously associated with memory consolidation, but also shown to reveal strong interindividual differences. In studies, weak electric current stimulation has modulated brain rhythms and memory retention. Here, we investigate whether SO-spindle coupling and SO slope during baseline sleep are associated with (predictive of) stimulation efficacy on retention performance. Methods Twenty-five healthy subjects participated in three experimental sessions. Sleep-associated memory consolidation was measured in two sessions, in one anodal transcranial direct current stimulation oscillating at subjects individual SO frequency (so-tDCS) was applied during nocturnal sleep. The third session was without a learning task (baseline sleep). The dependence on SO-spindle coupling and SO-slope during baseline sleep of so-tDCS efficacy on retention performance were investigated. Results Stimulation efficacy on overnight retention of declarative memories was associated with nesting of slow spindles to SO trough in deep nonrapid eye movement baseline sleep. Steepness and direction of SO slope in baseline sleep were features indicative for stimulation efficacy. Conclusions Findings underscore a functional relevance of activity during the SO up-to-down state transition for memory consolidation and provide support for distinct consolidation mechanisms for types of declarative memories.more » « less
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Abstract Working memory (WM) is a fundamental cognitive ability that supports complex thought but is limited in capacity. Thus, WM training interventions have become very popular as a means of potentially improving WM-related skills. Another promising intervention that has gained increasing traction in recent years is transcranial direct current stimulation (tDCS), a noninvasive form of brain stimulation that can modulate cortical excitability and temporarily increase brain plasticity. As such, it has the potential to boost learning and enhance performance on cognitive tasks. This study assessed the efficacy of tDCS to supplement WM training. Sixty-two participants were randomized to receive either right prefrontal, left prefrontal, or sham stimulation with concurrent visuospatial WM training over the course of seven training sessions. Results showed that tDCS enhanced training performance, which was strikingly preserved several months after training completion. Furthermore, we observed stronger effects when tDCS was spaced over a weekend break relative to consecutive daily training, and we also demonstrated selective transfer in the right prefrontal group to nontrained tasks of visual and spatial WM. These findings shed light on how tDCS may be leveraged as a tool to enhance performance on WM-intensive learning tasks.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Book Chapter:
- https://doi.org/10.1007/978-3-031-72069-7_44
