Behavioral entrainment to rhythmic auditory stimulation can be modulated by tACS depending on the electrical stimulation field properties.

Synchronization between auditory stimuli and brain rhythms is beneficial for perception. In principle, auditory perception could be improved by facilitating neural entrainment to sounds via brain stimulation. However, high inter-individual variability of brain stimulation effects questions the usefulness of this approach. Here we aimed to modulate auditory perception by modulating neural entrainment to frequency modulated (FM) sounds using transcranial alternating current stimulation (tACS). In addition, we evaluated the advantage of using tACS montages spatially optimized for each individual's anatomy and functional data compared to a standard montage applied to all participants. Across two different sessions, 2 Hz tACS was applied targeting auditory brain regions. Concurrent with tACS, participants listened to FM stimuli with modulation rate matching the tACS frequency but with different phase lags relative to the tACS, and detected silent gaps embedded in the FM sound. We observed that tACS modulated the strength of behavioral entrainment to the FM sound in a phase-lag specific manner. Both the optimal tACS lag and the magnitude of the tACS effect were variable across participants and sessions. Inter-individual variability of tACS effects was best explained by the strength of the inward electric field, depending on the field focality and proximity to the target brain region. Although additional evidence is necessary, our results also provided suggestive insights that spatially optimizing the electrode montage could be a promising tool to reduce inter-individual variability of tACS effects. This work demonstrates that tACS effectively modulates entrainment to sounds depending on the optimality of the electric field. However, the lack of reliability on optimal tACS lags calls for caution when planning tACS experiments based on separate sessions.

tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel.

BACKGROUND AND OBJECTIVE: Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. METHODS: Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. RESULTS: In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = -3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. CONCLUSIONS: Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects.

Interindividual variability of electric fields during transcranial temporal interference stimulation (tTIS).

Transcranial temporal interference stimulation (tTIS) is a novel non-invasive brain stimulation technique for electrical stimulation of neurons at depth. Deep brain regions are generally small in size, making precise targeting a necessity. The variability of electric fields across individual subjects resulting from the same tTIS montages is unknown so far and may be of major concern for precise tTIS targeting. Therefore, the aim of the current study is to investigate the variability of the electric fields due to tTIS across 25 subjects. To this end, the electric fields of different electrode montages consisting of two electrode pairs with different center frequencies were simulated in order to target selected regions-of-interest (ROIs) with tTIS. Moreover, we set out to compare the electric fields of tTIS with the electric fields of conventional tACS. The latter were also based on two electrode pairs, which, however, were driven in phase at a common frequency. Our results showed that the electric field strengths inside the ROIs (left hippocampus, left motor area and thalamus) during tTIS are variable on single subject level. In addition, tTIS stimulates more focally as compared to tACS with much weaker co-stimulation of cortical areas close to the stimulation electrodes. Electric fields inside the ROI were, however, comparable for both methods. Overall, our results emphasize the potential benefits of tTIS for the stimulation of deep targets, over conventional tACS. However, they also indicate a need for individualized stimulation montages to leverage the method to its fullest potential.

[Tumor treating fields in cancer treatment in Denmark].

Tumor treating fields (TTFields) is a new non-invasive approach to cancer treatment. TTFields is low-intensity (1-5 V/m), intermediate frequency (150-200 kHz) alternating electric fields delivered locally to the tumour to selectively kill dividing cells and disrupt cancer growth. TTFields has proven safe and effective for newly diagnosed glioblastoma and is currently being tried for multiple other tumours. This review presents an introduction to TTFields, covering the main indications, the application method, the mechanism of action, the clinical results and the perspectives for implementation in Danish cancer treatment.

[Tumor treating fields in cancer treatment in Denmark].

Tumor treating fields (TTFields) is a new non-invasive approach to cancer treatment. TTFields are low-intensity (1-5 V/m), intermediate frequency (150-200 kHz) alternating electric fields delivered locally to the tumour to selectively kill dividing cells and disrupt cancer growth. TTFields has proven safe and effective for newly diagnosed glioblastoma and is currently being tried for multiple other tumours. This review presents an introduction to TTFields, covering the main indications, the application method, the mechanism of action, the clinical results and the perspectives for implementation in Danish cancer treatment.

Optimization of tumor treating fields using singular value decomposition and minimization of field anisotropy.

Tumor treating fields (TTFields) are increasingly used to treat newly diagnosed and recurrent glioblastoma (GBM). Recently, the authors proposed a new and comprehensive method for efficacy estimation based on singular value decomposition of the sequential field distributions. The method accounts for all efficacy parameters known to affect anti-cancer efficacy of TTFields, i.e. intensity, exposure time, and spatial field correlation. In this paper, we describe a further development, which enables individual optimization of the TTFields activation cycle. The method calculates the optimal device settings to obtain a desired average field intensity in the tumor, while minimizing unwanted field correlation. Finite element (FE) methods were used to estimate the electrical field distribution in the head. The computational head model was based on MRI data from a GBM patient. Sequential field vectors were post-processed using singular value decomposition. A linear transformation was applied to the resulting field matrix to reduce fractional anisotropy (FA) of the principal field components in the tumor. Results were computed for four realistic transducer array layouts. The optimization method significantly reduced FA and maintained the average field intensity in the tumor. The algorithm produced linear gain factors to be applied to the transducer array pairs producing the sequential fields. FA minimization was associated with an increase in total current delivered through the head during a activation cycle. Minimized FA can be obtained for an unchanged total current level, albeit with a reduction in average field intensity. We present an algorithm for optimization of the TTFields activation cycle settings. The method can be used to minimize the spatial correlation between sequential TTFields, while adjusting the total current level and mean field intensity to a desired level. Future studies are needed to validate clinical impact and assess sensitivity towards model parameters.

Importance of electrode position for the distribution of tumor treating fields (TTFields) in a human brain. Identification of effective layouts through systematic analysis of array positions for multiple tumor locations.

Tumor treating fields (TTFields) is a new modality used for the treatment of glioblastoma. It is based on antineoplastic low-intensity electric fields induced by two pairs of electrode arrays placed on the patient's scalp. The layout of the arrays greatly impacts the intensity (dose) of TTFields in the pathology. The present study systematically characterizes the impact of array position on the TTFields distribution calculated in a realistic human head model using finite element methods. We investigate systematic rotations of arrays around a central craniocaudal axis of the head and identify optimal layouts for a large range of (nineteen) different frontoparietal tumor positions. In addition, we present comprehensive graphical representations and animations to support the users' understanding of TTFields. For most tumors, we identified two optimal array positions. These positions varied with the translation of the tumor in the anterior-posterior direction but not in the left-right direction. The two optimal directions were oriented approximately orthogonally and when combining two pairs of orthogonal arrays, equivalent to clinical TTFields therapy, we correspondingly found a single optimum position. In most cases, an oblique layout with the fields oriented at forty-five degrees to the sagittal plane was superior to the commonly used anterior-posterior and left-right combinations of arrays. The oblique configuration may be used as an effective and viable configuration for most frontoparietal tumors. Our results may be applied to assist clinical decision-making in various challenging situations associated with TTFields. This includes situations in which circumstances, such as therapy-induced skin rash, scar tissue or shunt therapy, etc., require layouts alternative to the prescribed. More accurate distributions should, however, be based on patient-specific models. Future work is needed to assess the robustness of the presented results towards variations in conductivity.

A Review on Tumor-Treating Fields (TTFields): Clinical Implications Inferred From Computational Modeling.

Tumor-treating fields (TTFields) are a cancer treatment modality that uses alternating electric fields of intermediate frequency (∼100-500 kHz) and low intensity (1-3 V/cm) to disrupt cell division. TTFields are delivered by transducer arrays placed on the skin close to the tumor and act regionally and noninvasively to inhibit tumor growth. TTFields therapy is U.S. Food and Drug Administration approved for the treatment of glioblastoma multiforme, the most common and aggressive primary human brain cancer. Clinical trials testing the safety and efficacy of TTFields for other solid tumor types are underway. The objective of this paper is to review computational approaches used to characterize TTFields. The review covers studies of the macroscopic spatial distribution of TTFields generated in the human head, and of the microscopic field distribution in tumor cells. In addition, preclinical and clinical findings related to TTFields and principles of its operation are summarized. Particular emphasis is put on outlining the potential clinical value inferred from computational modeling.

Impact of tumor position, conductivity distribution and tissue homogeneity on the distribution of tumor treating fields in a human brain: A computer modeling study.

BACKGROUND: Tumor treating fields (TTFields) are increasingly used in the treatment of glioblastoma. TTFields inhibit cancer growth through induction of alternating electrical fields. To optimize TTFields efficacy, it is necessary to understand the factors determining the strength and distribution of TTFields. In this study, we provide simple guiding principles for clinicians to assess the distribution and the local efficacy of TTFields in various clinical scenarios. METHODS: We calculated the TTFields distribution using finite element methods applied to a realistic head model. Dielectric property estimates were taken from the literature. Twentyfour tumors were virtually introduced at locations systematically varied relative to the applied field. In addition, we investigated the impact of central tumor necrosis on the induced field. RESULTS: Local field "hot spots" occurred at the sulcal fundi and in deep tumors embedded in white matter. The field strength was not higher for tumors close to the active electrode. Left/right field directions were generally superior to anterior/posterior directions. Central necrosis focally enhanced the field near tumor boundaries perpendicular to the applied field and introduced significant field non-uniformity within the tumor. CONCLUSIONS: The TTFields distribution is largely determined by local conductivity differences. The well conducting tumor tissue creates a preferred pathway for current flow, which increases the field intensity in the tumor boundaries and surrounding regions perpendicular to the applied field. The cerebrospinal fluid plays a significant role in shaping the current pathways and funnels currents through the ventricles and sulci towards deeper regions, which thereby experience higher fields. Clinicians may apply these principles to better understand how TTFields will affect individual patients and possibly predict where local recurrence may occur. Accurate predictions should, however, be based on patient specific models. Future work is needed to assess the robustness of the presented results towards variations in conductivity.

Combining non-invasive transcranial brain stimulation with neuroimaging and electrophysiology: Current approaches and future perspectives.

Non-invasive transcranial brain stimulation (NTBS) techniques such as transcranial magnetic stimulation (TMS) and transcranial current stimulation (TCS) are important tools in human systems and cognitive neuroscience because they are able to reveal the relevance of certain brain structures or neuronal activity patterns for a given brain function. It is nowadays feasible to combine NTBS, either consecutively or concurrently, with a variety of neuroimaging and electrophysiological techniques. Here we discuss what kind of information can be gained from combined approaches, which often are technically demanding. We argue that the benefit from this combination is twofold. Firstly, neuroimaging and electrophysiology can inform subsequent NTBS, providing the required information to optimize where, when, and how to stimulate the brain. Information can be achieved both before and during the NTBS experiment, requiring consecutive and concurrent applications, respectively. Secondly, neuroimaging and electrophysiology can provide the readout for neural changes induced by NTBS. Again, using either concurrent or consecutive applications, both "online" NTBS effects immediately following the stimulation and "offline" NTBS effects outlasting plasticity-inducing NTBS protocols can be assessed. Finally, both strategies can be combined to close the loop between measuring and modulating brain activity by means of closed-loop brain state-dependent NTBS. In this paper, we will provide a conceptual framework, emphasizing principal strategies and highlighting promising future directions to exploit the benefits of combining NTBS with neuroimaging or electrophysiology.

Effects of parietal TMS on visual and auditory processing at the primary cortical level -- a concurrent TMS-fMRI study.

Accumulating evidence suggests that multisensory interactions emerge already at the primary cortical level. Specifically, auditory inputs were shown to suppress activations in visual cortices when presented alone but amplify the blood oxygen level-dependent (BOLD) responses to concurrent visual inputs (and vice versa). This concurrent transcranial magnetic stimulation-functional magnetic resonance imaging (TMS-fMRI) study applied repetitive TMS trains at no, low, and high intensity over right intraparietal sulcus (IPS) and vertex to investigate top-down influences on visual and auditory cortices under 3 sensory contexts: visual, auditory, and no stimulation. IPS-TMS increased activations in auditory cortices irrespective of sensory context as a result of direct and nonspecific auditory TMS side effects. In contrast, IPS-TMS modulated activations in the visual cortex in a state-dependent fashion: it deactivated the visual cortex under no and auditory stimulation but amplified the BOLD response to visual stimulation. However, only the response amplification to visual stimulation was selective for IPS-TMS, while the deactivations observed for IPS- and Vertex-TMS resulted from crossmodal deactivations induced by auditory activity to TMS sounds. TMS to IPS may increase the responses in visual (or auditory) cortices to visual (or auditory) stimulation via a gain control mechanism or crossmodal interactions. Collectively, our results demonstrate that understanding TMS effects on (uni)sensory processing requires a multisensory perspective.