Transcranial focused ultrasound of the amygdala modulates fear network activation and connectivity.

BACKGROUND: Current noninvasive brain stimulation methods are incapable of directly modulating subcortical brain regions critically involved in psychiatric disorders. Transcranial Focused Ultrasound (tFUS) is a newer form of noninvasive stimulation that could modulate the amygdala, a subcortical region implicated in fear. OBJECTIVE: We investigated the effects of active and sham tFUS of the amygdala on fear circuit activation, skin conductance responses (SCR), and self-reported anxiety during a fear-inducing task. We also investigated amygdala tFUS' effects on amygdala-fear circuit resting-state functional connectivity. METHODS: Thirty healthy individuals were randomized in this double-blinded study to active or sham tFUS of the left amygdala. We collected fMRI scans, SCR, and self-reported anxiety during a fear-inducing task (participants viewed red or green circles which indicated the risk of receiving an aversive stimulus), as well as resting-state scans, before and after tFUS. RESULTS: Compared to sham tFUS, active tFUS was associated with decreased (pre to post tFUS) blood-oxygen-level-dependent fMRI activation in the amygdala (F(1,25) = 4.86, p = 0.04, η2 = 0.16) during the fear task, and lower hippocampal (F(1,27) = 4.41, p = 0.05, η2 = 0.14), and dorsal anterior cingulate cortex (F(1,27) = 6.26, p = 0.02; η2 = 0.19) activation during the post tFUS fear task. The decrease in amygdala activation was correlated with decreased subjective anxiety (r = 0.62, p = 0.03). There was no group effect in SCR changes from pre to post tFUS (F(1,23) = 0.85, p = 0.37). The active tFUS group also showed decreased amygdala-insula (F(1,28) = 4.98, p = 0.03) and amygdala-hippocampal (F(1,28) = 7.14, p = 0.01) rsFC, and increased amygdala-ventromedial prefrontal cortex (F(1,28) = 3.52, p = 0.05) resting-state functional connectivity. CONCLUSIONS: tFUS can change functional connectivity and brain region activation associated with decreased anxiety. Future studies should investigate tFUS' therapeutic potential for individuals with clinical levels of anxiety.

Network-specific metabolic and haemodynamic effects elicited by non-invasive brain stimulation.

Repetitive transcranial magnetic stimulation (TMS), when applied to the dorsolateral prefrontal cortex (dlPFC), treats depression. Therapeutic effects are hypothesized to arise from propagation of local dlPFC stimulation effects across distributed networks; however, the mechanisms of this remain unresolved. dlPFC contains representations of different networks. As such, dlPFC TMS may exert different effects depending on the network being stimulated. Here, to test this, we applied high-frequency TMS to two nearby dlPFC targets functionally embedded in distinct anti-correlated networks-the default and salience networks- in the same individuals in separate sessions. Local and distributed TMS effects were measured with combined 18fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging. Identical TMS patterns caused opposing effects on local glucose metabolism: metabolism increased at the salience target following salience TMS but decreased at the default target following default TMS. At the distributed level, both conditions increased functional connectivity between the default and salience networks, with this effect being dramatically larger following default TMS. Metabolic and haemodynamic effects were also linked: across subjects, the magnitude of local metabolic changes correlated with the degree of functional connectivity changes. These results suggest that TMS effects upon dlPFC are network specific. They also invoke putative antidepressant mechanisms of TMS: network de-coupling.

Role of articulatory motor networks in perceptual categorization of speech signals: a 7T fMRI study.

Speech and language processing involve complex interactions between cortical areas necessary for articulatory movements and auditory perception and a range of areas through which these are connected and interact. Despite their fundamental importance, the precise mechanisms underlying these processes are not fully elucidated. We measured BOLD signals from normal hearing participants using high-field 7 Tesla fMRI with 1-mm isotropic voxel resolution. The subjects performed 2 speech perception tasks (discrimination and classification) and a speech production task during the scan. By employing univariate and multivariate pattern analyses, we identified the neural signatures associated with speech production and perception. The left precentral, premotor, and inferior frontal cortex regions showed significant activations that correlated with phoneme category variability during perceptual discrimination tasks. In addition, the perceived sound categories could be decoded from signals in a region of interest defined based on activation related to production task. The results support the hypothesis that articulatory motor networks in the left hemisphere, typically associated with speech production, may also play a critical role in the perceptual categorization of syllables. The study provides valuable insights into the intricate neural mechanisms that underlie speech processing.

Software Package for Transcranial Magnetic Stimulation Coil and Coil Array Analysis and Design.

Objective: This study aims to describe a MATLAB software package for transcranial magnetic stimulation (TMS) coil analysis and design. Approach: Electric and magnetic fields of the coils as well as their self- and mutual (for coil arrays) inductances are computed, with or without a magnetic core. Solid and stranded (Litz wire) conductors are also taken into consideration. The starting point is the centerline of a coil conductor(s), which is a 3D curve defined by the user. Then, a wire mesh and a computer aided design (CAD) mesh for the volume conductor of a given cross-section (circular, elliptical, or rectangular) are automatically generated. Self- and mutual inductances of the coil(s) are computed. Given the conductor current and its time derivative, electric and magnetic fields of the coil(s) are determined anywhere in space.Computations are performed with the fast multipole method (FMM), which is the most efficient way to evaluate the fields of many elementary current elements (current dipoles) comprising the current carrying conductor at a large number of observation points. This is the major underlying mathematical operation behind both inductance and field calculations. Main Results: The wire-based approach enables precise replication of even the most complex physical conductor geometries, while the FMM acceleration quickly evaluates large quantities of elementary current filaments. Agreement to within 0.74% was obtained between the inductances computed by the FMM method and ANSYS Maxwell 3D for the same coil model. Although not provided in this study, it is possible to evaluate non-linear magnetic cores in addition to the linear core exemplified. An experimental comparison was carried out against a physical MagVenture C-B60 coil; the measured and simulated inductances differed by only 1.25%, and nearly perfect correlation was found between the measured and computed E-field values at each observation point. Significance: The developed software package is applicable to any quasistatic inductor design, not necessarily to the TMS coils only.

Role of Articulatory Motor Networks in Perceptual Categorization of Speech Signals: A 7 T fMRI Study.

BACKGROUND: The association between brain regions involved in speech production and those that play a role in speech perception is not yet fully understood. We compared speech production related brain activity with activations resulting from perceptual categorization of syllables using high field 7 Tesla functional magnetic resonance imaging (fMRI) at 1-mm isotropic voxel resolution, enabling high localization accuracy compared to previous studies. METHODS: Blood oxygenation level dependent (BOLD) signals were obtained in 20 normal hearing subjects using a simultaneous multi-slice (SMS) 7T echo-planar imaging (EPI) acquisition with whole-head coverage and 1 mm isotropic resolution. In a speech production localizer task, subjects were asked to produce a silent lip-round vowel /u/ in response to the visual cue "U" or purse their lips when they saw the cue "P". In a phoneme discrimination task, subjects were presented with pairs of syllables, which were equiprobably identical or different along an 8-step continuum between the prototypic /ba/ and /da/ sounds. After the presentation of each stimulus pair, the subjects were asked to indicate whether the two syllables they heard were identical or different by pressing one of two buttons. In a phoneme classification task, the subjects heard only one syllable and asked to indicate whether it was /ba/ or /da/. RESULTS: Univariate fMRI analyses using a parametric modulation approach suggested that left motor, premotor, and frontal cortex BOLD activations correlate with phoneme category variability in the /ba/-/da/ discrimination task. In contrast, the variability related to acoustic features of the phonemes were the highest in the right primary auditory cortex. Our multivariate pattern analysis (MVPA) suggested that left precentral/inferior frontal cortex areas, which were associated with speech production according to the localizer task, play a role also in perceptual categorization of the syllables. CONCLUSIONS: The results support the hypothesis that articulatory motor networks in the left hemisphere that are activated during speech production could also have a role in perceptual categorization of syllables. Importantly, high voxel-resolution combined with advanced coil technology allowed us to pinpoint the exact brain regions involved in both perception and production tasks.

A novel whole-head RF coil design tailored for concurrent multichannel brain stimulation and imaging at 3T.

PURPOSE: Multichannel Transcranial Magnetic Stimulation (mTMS) [1] is a novel non-invasive brain stimulation technique allowing multiple sites to be stimulated simultaneously or sequentially under electronic control without movement of the coils. To enable simultaneous mTMS and MR imaging, we have designed and constructed a whole-head 28-channel receive-only RF coil at 3T. METHODS: A helmet-shaped structure was designed considering a specific layout for a mTMS system with holes for positioning the TMS units next to the scalp. Diameter of the TMS units defined the diameter of RF loops. The placement of the preamplifiers was designed to minimize possible interactions and to allow straightforward positioning of the mTMS units around the RF coil. Interactions between TMS-MRI were analyzed for the whole-head system extending the results presented in previous publications [2]. Both SNR- and g-factors maps were obtained to compare the imaging performance of the coil with commercial head coils. RESULTS: Sensitivity losses for the RF elements containing TMS units show a well-defined spatial pattern. Simulations indicate that the losses are predominantly caused by eddy currents on the coil wire windings. The average SNR performance of the TMSMR 28-channel coil is about 66% and 86% of the SNR of the 32/20-channel head coil respectively. The g-factor values of the TMSMR 28-channel coil are similar to the 32-channel coil and significantly better than the 20-channel coil. CONCLUSION: We present the TMSMR 28-channel coil, a head RF coil array to be integrated with a multichannel 3-axisTMS coil system, a novel tool that will enable causal mapping of human brain function.

Fast Individualized High-resolution Electric Field Modeling for Computational TMS Neuronavigation.

Transcranial Magnetic Stimulation (TMS) is a non-invasive method for safe and painless activation of cortical neurons. On-line visualization of the induced Electric field (E-field) has the potential to improve quantitative targeting and dosing of stimulation, however present commercially available systems are limited by simplified approximations of the anatomy. Here, we developed a near real-time method to accurately approximate the induced E-field of a freely moving TMS coil with an individualized high-resolution head model. We use a set of magnetic dipoles around the head to approximate the total E-field of a moving TMS coil. First, we match the incident field of the dipole basis set with the incident E-field of the moving coil. Then, based on the principle of superposition and uniqueness of the solutions, we apply same basis coefficients to the total E-field of the basis set. The computed E-fields results show high similarity with an established TMS solver both in terms of the amplitude and the spatial distribution patterns. The proposed method enables rapid visualization of the E-field with ~100 ms of computation time enabling interactive planning, targeting, dosing and coil positioning tasks for TMS neuronavigation.

Rapid computation of TMS-induced E-fields using a dipole-based magnetic stimulation profile approach.

BACKGROUND: TMS neuronavigation with on-line display of the induced electric field (E-field) has the potential to improve quantitative targeting and dosing of stimulation, but present commercially available solutions are limited by simplified approximations. OBJECTIVE: Developing a near real-time method for accurate approximation of TMS induced E-fields with subject-specific high-resolution surface-based head models that can be utilized for TMS navigation. METHODS: Magnetic dipoles are placed on a closed surface enclosing an MRI-based head model of the subject to define a set of basis functions for the incident and total E-fields that define the subject's Magnetic Stimulation Profile (MSP). The near real-time speed is achieved by recognizing that the total E-field of the coil only depends on the incident E-field and the conductivity boundary geometry. The total E-field for any coil position can be obtained by matching the incident field of the stationary dipole basis set with the incident E-field of the moving coil and applying the same basis coefficients to the total E-field basis functions. RESULTS: Comparison of the MSP-based approximation with an established TMS solver shows great agreement in the E-field amplitude (relative maximum error around 5%) and the spatial distribution patterns (correlation >98%). Computation of the E-field took ~100 ms on a cortical surface mesh with 120k facets. CONCLUSION: The numerical accuracy and speed of the MSP approximation method make it well suited for a wide range of computational tasks including interactive planning, targeting, dosing, and visualization of the intracranial E-fields for near real-time guidance of coil positioning.

A 3-axis coil design for multichannel TMS arrays.

PURPOSE: Multichannel Transcranial Magnetic Stimulation (mTMS) arrays enable multiple sites to be stimulated simultaneously or sequentially under electronic control without moving the system's stimulation coils. Here, we build and characterize the performance of a novel modular 3-axis TMS coil that can be utilized as a unit element in large-scale multichannel TMS arrays. METHODS: We determined the basic physical characteristics of the 3-axis TMS coil x-, y- and z-elements using a custom 2-channel programmable stimulator prototype. We mapped the temporal rate-of-change of the induced magnetic field (dB/dt) on a 2D plane parallel to the coil surface (including an extended line for full spatial coverage) and compared those values with predictions from magnetic field simulations. Temperature measurements were carried out to assess the incorporated air-cooling method. We measured the mutual and self-inductances of the x/y/z-elements to assess coupling between them. Additionally, we measured and calculated the coupling between z-elements in the array configuration. Finally, we performed electric field simulations to evaluate the stimulation intensity and focality of the coil and compared the results to conventional TMS coils as well as demonstrated suitability of the 3-axis coil for a multichannel array configuration. RESULTS: The experimentally obtained dB/dt values validated the computational model of the 3-axis coil and therefore confirmed that both the coil and stimulator system are operating as intended. The air-cooling system was effective for brief high-frequency pulse trains and extended single- and paired-pulse TMS protocols. The electromagnetic simulations suggested that an array of the 3-axis coils would have comparable stimulation intensity to conventional TMS coils, therefore enabling clearly suprathreshold stimulation of the human brain. The recorded coil coupling between the x/y/z-elements was < 1% and the maximal coupling between z-elements in the array configuration was 1.8% and 3.4% for the measured and calculated values, respectively. CONCLUSION: We presented a 3-axis coil intended for multichannel TMS arrays. The electromagnetic measurements and simulations verified that the coil fabrication met the desired specifications and that the inductive coupling between the elements was negligible. The air-cooled 3-axis TMS coil appears suitable to be used as an element in multichannel TMS arrays.

A software toolkit for TMS electric-field modeling with boundary element fast multipole method: an efficient MATLAB implementation.

Objective: To present and disseminate our transcranial magnetic stimulation (TMS) modeling software toolkit, including several new algorithmic developments, and to apply this software to realistic TMS modeling scenarios given a high-resolution model of the human head including cortical geometry and an accurate coil model. Approach: The recently developed charge-based boundary element fast multipole method (BEM-FMM) is employed as an alternative to the 1st order finite element method (FEM) most commonly used today. The BEM-FMM approach provides high accuracy and unconstrained numerical field resolution close to and across cortical interfaces. Here, the previously proposed BEM-FMM algorithm has been improved in several novel ways. Main results: The improvements resulted in a threefold increase in computational speed while maintaining the same solution accuracy. The computational code based on the MATLAB® platform is made available to all interested researchers, along with a coil model repository and examples to create custom coils, head model repository, and supporting documentation. The presented software toolkit may be useful for post-hoc analyses of navigated TMS data using high-resolution subject-specific head models as well as accurate and fast modeling for the purposes of TMS coil/hardware development. Significance: TMS is currently the only non-invasive neurostimulation modality that enables painless and safe supra-threshold stimulation by employing electromagnetic induction to efficiently penetrate the skull. Accurate, fast, and high resolution modeling of the electric fields may significantly improve individualized targeting and dosing of TMS and therefore enhance the efficiency of existing clinical protocols as well as help establish new application domains.

Robust desynchronization of Parkinson's disease pathological oscillations by frequency modulation of delayed feedback deep brain stimulation.

The hyperkinetic symptoms of Parkinson's Disease (PD) are associated with the ensembles of interacting oscillators that cause excess or abnormal synchronous behavior within the Basal Ganglia (BG) circuitry. Delayed feedback stimulation is a closed loop technique shown to suppress this synchronous oscillatory activity. Deep Brain Stimulation (DBS) via delayed feedback is known to destabilize the complex intermittent synchronous states. Computational models of the BG network are often introduced to investigate the effect of delayed feedback high frequency stimulation on partially synchronized dynamics. In this study, we develop a reduced order model of four interacting nuclei of the BG as well as considering the Thalamo-Cortical local effects on the oscillatory dynamics. This model is able to capture the emergence of 34 Hz beta band oscillations seen in the Local Field Potential (LFP) recordings of the PD state. Train of high frequency pulses in a delayed feedback stimulation has shown deficiencies such as strengthening the synchronization in case of highly fluctuating neuronal activities, increasing the energy consumed as well as the incapability of activating all neurons in a large-scale network. To overcome these drawbacks, we propose a new feedback control variable based on the filtered and linearly delayed LFP recordings. The proposed control variable is then used to modulate the frequency of the stimulation signal rather than its amplitude. In strongly coupled networks, oscillations reoccur as soon as the amplitude of the stimulus signal declines. Therefore, we show that maintaining a fixed amplitude and modulating the frequency might ameliorate the desynchronization process, increase the battery lifespan and activate substantial regions of the administered DBS electrode. The charge balanced stimulus pulse itself is embedded with a delay period between its charges to grant robust desynchronization with lower amplitudes needed. The efficiency of the proposed Frequency Adjustment Stimulation (FAS) protocol in a delayed feedback method might contribute to further investigation of DBS modulations aspired to address a wide range of abnormal oscillatory behavior observed in neurological disorders.

Delayed Feedback Frequency Adjustment for Deep Brain Stimulation of Subthalamic Nucleus Oscillations.

Neural oscillations within the Basal Ganglia (BG) circuitry are associated with Parkinson's Disease (PD) and are observable through the Local Field Potential (LFP) of the Subthalamic Nucleus (STN) or Globus Pallidus externa (GPe) neurons. LFP amplitude modulation in a delayed feedback protocol for Deep Brain Stimulation (DBS) is shown to destabilize the complex intermittent synchronous states. However, traditional High Frequency Stimulations (HFS) often intensify the synchronization of highly fluctuating neurons, are less efficient in activating all neurons in large scale networks and consume more battery of the DBS device. Here, we investigate the partially synchronous dynamics of a STN-GPe coupling network to examine the effect of frequency adjustment in the stimulation signal. The frequency of the stimulation signal is adjusted according to the nonlinear delayed feedback LFP of the STN population. Frequency adjustment protocol with a fixed stimulation amplitude is shown to increase the desynchronization efficiency and neuronal activation by 25% and 16.2%, respectively, while reducing the energy consumption by 31.5% compared to amplitude modulation methods for stimulation of large networks (1000 neurons).

Hyperbolic Modeling of Subthalamic Nucleus Cells to Investigate the Effect of Dopamine Depletion.

To investigate how different types of neurons can produce well-known spiking patterns, a new computationally efficient model is proposed in this paper. This model can help realize the neuronal interconnection issues. The model can demonstrate various neuronal behaviors observed in vivo through simple parameter modification. The behaviors include tonic and phasic spiking, tonic and phasic bursting, class 1 and class 2 excitability, rebound spike, rebound burst, subthreshold oscillation, and accommodated spiking along with inhibition neuron responses. Here, we investigate the neuronal spiking patterns in Parkinson's disease through our proposed model. Abnormal pattern of subthalamic nucleus in Parkinson's disease can be studied through variations in the shape and frequency of firing patterns. Our proposed model introduces mathematical equations, where these patterns can be derived and clearly differentiated from one another. The irregular and arrhythmic behaviors of subthalamic nucleus firing pattern under normal conditions can easily be transformed to those caused by Parkinson's disease through simple parameter modifications in the proposed model. This model can explicitly show the change of neuronal activity patterns in Parkinson's disease, which may eventually lead to effective treatment with deep brain stimulation devices.

Computational Stimulation of the Basal Ganglia Neurons with Cost Effective Delayed Gaussian Waveforms.

Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices.