Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity

Rimpiläinen, Ville; Koulouri, Alexandra; Lucka, Felix; Kaipio, Jari P.; Wolters, Carsten H.

doi:10.1016/j.neuroimage.2018.11.058

Cited by 14 publications

(14 citation statements)

References 62 publications

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“…However, even the state-of-the-art head-modeling approaches are only an approximation of the true individual anatomy. Known sources of inaccuracy include segmentation errors 41 , a limited number of tissue types 42 , and the use of standard, but possibly incorrect, conductivity values 43,44 . Despite these limitations, we remain convinced that computational models are invaluable for prospectively adjusting the stimulation intensities for rTMS.…”

Section: Discussionmentioning

confidence: 99%

Weak rTMS-induced electric fields produce neural entrainment in humans

Zmeykina

Mittner

Paulus

et al. 2020

Sci Rep

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Repetitive transcranial magnetic stimulation (rTMS) is a potent tool for modulating endogenous oscillations in humans. The current standard method for rTMS defines the stimulation intensity based on the evoked liminal response in the visual or motor system (e.g., resting motor threshold). The key limitation of the current approach is that the magnitude of the resulting electric field remains elusive. A better characterization of the electric field strength induced by a given rTMS protocol is necessary in order to improve the understanding of the neural mechanisms of rTMS. In this study we used a novel approach, in which individualized prospective computational modeling of the induced electric field guided the choice of stimulation intensity. We consistently found that rhythmic rTMS protocols increased neural synchronization in the posterior alpha frequency band when measured simultaneously with scalp electroencephalography. We observed this effect already at electric field strengths of roughly half the lowest conventional field strength, which is 80% of the resting motor threshold. We conclude that rTMS can induce immediate electrophysiological effects at much weaker electric field strengths than previously thought. Neurons and neural assemblies in the mammalian brain temporally synchronize their activity leading to the emergence of macroscopic network oscillations 1. Network oscillations are rhythmic patterns of neural activity that are maintained in all physiologically occurring brain states 2. They are crucial for intact neuropsychological functioning and are frequently disrupted in neurological or psychiatric diseases 3. However, neurons also respond to both endogenous and exogenous electric fields 4. Non-invasive electrical brain stimulation (NIBS) methods, such as repetitive transcranial magnetic stimulation (rTMS), are promising techniques for modulating endogenous oscillations 5. Many NIBS studies employ oscillating electric fields because it is believed that these exogenous oscillations can modulate the phase or the power of endogenous oscillations 6. The two crucial properties of rTMS-generated periodic electric fields are its frequency and its magnitude. Whereas the frequency of the electric field is clearly defined, its magnitude in the brain is defined only indirectly. Most studies choose to set the stimulation intensity using the near threshold approach. This approach defines the stimulation intensity as a percentage of the threshold intensity required to induce a liminal response in the motor or visual cortex 7. Although the near threshold approach utilizes individualized stimulation intensities, the properties of the rTMS-induced electric field, including its strength, can differ substantially within and across individuals. For example, this approach cannot account for differences in the cortical folding pattern and the cortex-scalp distance between motor and non-motor areas 8. However, it is crucial to account for these known anatomical effects because the induced electric field strength plays an...

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Section: Discussionmentioning

confidence: 99%

Weak rTMS-induced electric fields produce neural entrainment in humans

Zmeykina

Mittner

Paulus

et al. 2020

Sci Rep

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“…Of note is that the skull conductivity and, therefore, the correct modeling is a pivotal point, which, due to head abnormalities or insufficient imaging tools, can be challenging to approximate [35]. To address this issue, Bayesian Approximation Error (BAE) approaches displayed high efficiency in reducing the source localization error by several millimeters, enhancing spatial accuracy, which is crucial in clinical applications [36].…”

Section: Forward Problemmentioning

confidence: 99%

“…On this premise, anatomical MRI could contribute to the correct solution of the forward (and as a result the inverse) problem, since the information concerning the thickness and conductivities of each head tissue is needed for the source localization computation [40]. For this reason, it is optimal to use subject-specific MRI in order to reconstruct the individual head model, additionally incorporating the anisotropic properties of the skull and white matter [36,98]. However, in several cases, individual MRI is unavailable or the head model cannot be created, due to brain abnormalities and impairments, such as brain malformation or tumors.…”

Section: Esi Challenges and Limitationsmentioning

confidence: 99%

Advances in Electrical Source Imaging: A Review of the Current Approaches, Applications and Challenges

Zorzos

Kakkos

Ventouras

et al. 2021

Signals

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Brain source localization has been consistently implemented over the recent years to elucidate complex brain operations, pairing the high temporal resolution of the EEG with the high spatial estimation of the estimated sources. This review paper aims to present the basic principles of Electrical source imaging (ESI) in the context of the recent progress for solving the forward and the inverse problems, and highlight the advantages and limitations of the different approaches. As such, a synthesis of the current state-of-the-art methodological aspects is provided, offering a complete overview of the present advances with regard to the ESI solutions. Moreover, the new dimensions for the analysis of the brain processes are indicated in terms of clinical and cognitive ESI applications, while the prevailing challenges and limitations are thoroughly discussed, providing insights for future approaches that could help to alleviate methodological and technical shortcomings.

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“…Known sources of inaccuracy include segmentation errors [42], a limited number of compartments, i.e. tissue types [43], and the use of standard, but possibly incorrect, conductivity values for these compartments [44,45]. Practical constraints on the implementation of the stimulation can further contribute to inaccuracies in the electric field calculations.…”

Section: Towards a Better Understanding Of The Neural Mechanisms Of Rtmsmentioning

confidence: 99%

Weak rTMS-induced electric fields produce neural entrainment in humans

Zmeykina¹,

Mittner²,

Paulus³

et al. 2019

Preprint

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Repetitive transcranial magnetic stimulation (rTMS) is a potent tool for modulating endogenous oscillations in humans. The current standard dosing method for rTMS defines the electric field strength only indirectly. A better characterization of the electric field strength induced by a given rTMS protocol is necessary in order to improve the understanding of the neural mechanisms of rTMS. In this study we used a novel approach, in which individualized prospective computational modeling of the induced electric field guided the choice of stimulation intensity. We consistently found that rhythmic rTMS protocols increased neural synchronization in the posterior alpha frequency band when measured simultaneously with scalp electroencephalography. We observed this effect already at electric field strengths of roughly half the lowest conventional dose, which is 80% of the resting motor threshold. We conclude that rTMS can induce immediate electrophysiological effects at much weaker electric field strengths than previously thought.

show abstract

Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity

Cited by 14 publications

References 62 publications

Weak rTMS-induced electric fields produce neural entrainment in humans

Weak rTMS-induced electric fields produce neural entrainment in humans

Advances in Electrical Source Imaging: A Review of the Current Approaches, Applications and Challenges

Weak rTMS-induced electric fields produce neural entrainment in humans

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