Brain mapping with transcranial magnetic stimulation using a refined correlation ratio and Kendall's tau

Transcranial magnetic stimulation mapping of the motor cortex: comparison of five estimation algorithms

Background

There are currently five different kinds of transcranial magnetic stimulation (TMS) motor mapping algorithms available, from ordinary point-based algorithms to advanced field-based algorithms. However, there have been only a limited number of comparison studies conducted, and they have not yet examined all of the currently available algorithms. This deficiency impedes the judicious selection of algorithms for application in both clinical and basic neuroscience, and hinders the potential promotion of a potential superior algorithm. Considering the influence of algorithm complexity, further investigation is needed to examine the differences between fMRI peaks and TMS cortical hotspots that were identified previously.

Methods

Twelve healthy participants underwent TMS motor mapping and a finger-tapping task during fMRI. The motor cortex TMS mapping results were estimated by five algorithms, and fMRI activation results were obtained. For each algorithm, the prediction error was defined as the distance between the measured scalp hotspot and optimized coil position, which was determined by the maximum electric field strength in the estimated motor cortex. Additionally, the study identified the minimum number of stimuli required for stable mapping. Finally, the location difference between the TMS mapping cortical hotspot and the fMRI activation peak was analyzed.

Results

The projection yielded the lowest prediction error (5.27 ± 4.24 mm) among the point-based algorithms and the association algorithm yielded the lowest (6.66 ± 3.48 mm) among field-based estimation algorithms. The projection algorithm required fewer stimuli, possibly resulting from its suitability for the grid-based mapping data collection method. The TMS cortical hotspots from all algorithms consistently deviated from the fMRI activation peak (20.52 ± 8.46 mm for five algorithms).

Conclusion

The association algorithm might be a superior choice for clinical applications and basic neuroscience research, due to its lower prediction error and higher estimation sensitivity in the deep cortical structure, especially for the sulcus. It also has potential applicability in various other TMS domains, including language area mapping and more. Otherwise, our results provide further evidence that TMS motor mapping intrinsically differs from fMRI motor mapping.

Minimum-Norm Estimation of Motor Representations in Navigated TMS Mappings

Navigated transcranial magnetic stimulation (nTMS) can be applied to locate and outline cortical motor representations. This may be important, e.g., when planning neurosurgery or focused nTMS therapy, or when assessing plastic changes during neurorehabilitation. Conventionally, a cortical location is considered to belong to the motor cortex if the maximum electric field (E-field) targeted there evokes a motor-evoked potential in a muscle. However, the cortex is affected by a broad E-field distribution, which tends to broaden estimates of representation areas by stimulating also the neighboring areas in addition to the maximum E-field location. Our aim was to improve the estimation of nTMS-based motor maps by taking into account the E-field distribution of the stimulation pulse. The effect of the E-field distribution was considered by calculating the minimum-norm estimate (MNE) of the motor representation area. We tested the method on simulated data and then applied it to recordings from six healthy volunteers and one stroke patient. We compared the motor representation areas obtained with the MNE method and a previously introduced interpolation method. The MNE hotspots and centers of gravity were close to those obtained with the interpolation method. The areas of the maps, however, depend on the thresholds used for outlining the areas. The MNE method may improve the definition of cortical motor areas, but its accuracy should be validated by comparing the results with maps obtained with direct cortical stimulation of the cortex where the E-field distribution can be better focused.

Enhancement of human cognitive performance using transcranial magnetic stimulation (TMS)

Here we review the usefulness of transcranial magnetic stimulation (TMS) in modulating cortical networks in ways that might produce performance enhancements in healthy human subjects. To date over sixty studies have reported significant improvements in speed and accuracy in a variety of tasks involving perceptual, motor, and executive processing. Two basic categories of enhancement mechanisms are suggested by this literature: direct modulation of a cortical region or network that leads to more efficient processing, and addition-by-subtraction, which is disruption of processing which competes or distracts from task performance. Potential applications of TMS cognitive enhancement, including research into cortical function, rehabilitation therapy in neurological and psychiatric illness, and accelerated skill acquisition in healthy individuals are discussed, as are methods of optimizing the magnitude and duration of TMS-induced performance enhancement, such as improvement of targeting through further integration of brain imaging with TMS. One technique, combining multiple sessions of TMS with concurrent TMS/task performance to induce Hebbian-like learning, appears to be promising for prolonging enhancement effects. While further refinements in the application of TMS to cognitive enhancement can still be made, and questions remain regarding the mechanisms underlying the observed effects, this appears to be a fruitful area of investigation that may shed light on the basic mechanisms of cognitive function and their therapeutic modulation.

Robust real-time robot-world calibration for robotized transcranial magnetic stimulation

BACKGROUND

For robotized transcranial magnetic stimulation (TMS), the magnetic coil is placed on the patient's head by a robot. As the robotized TMS system requires tracking of head movements, robot and tracking camera need to be calibrated. However, for robotized TMS in a clinical setting, such calibration is required frequently. Mounting/unmounting a marker to the end effector and moving the robot into different poses is impractical. Moreover, if either system is moved during treatment, recalibration is required.

METHODS

To overcome this limitation, we propose to directly track a marker at link three of the articulated arm. Using forward kinematics and a constant marker transform to link three, the calibration can be performed instantly.

RESULTS

Our experimental results indicate an accuracy similar to standard hand-eye calibration approaches. It also outperforms classical hand-held navigated TMS systems.

CONCLUSION

This robust online calibration greatly enhances the system's user-friendliness and safety.

Robot-assisted image-guided transcranial magnetic stimulation for somatotopic mapping of the motor cortex: a clinical pilot study

Purpose

Shape and exact location of motor cortical areas varies among individuals. The exact knowledge of these locations is crucial for planning of neurosurgical procedures. In this study, we have used robot-assisted image-guided transcranial magnetic stimulation (Ri-TMS) to elicit MEP response recorded for individual muscles and reconstruct functional motor maps of the primary motor cortex.

Methods

One healthy volunteer and five patients with intracranial tumors neighboring the precentral gyrus were selected for this pilot study. Conventional MRI and fMRI were obtained. Transcranial magnetic stimulation was performed using a MagPro X100 stimulator and a standard figure-of-eight coil positioned by an Adept Viper s850 robot. The fMRI activation/Ri-TMS response pattern were compared. In two cases, Ri-TMS was additionally compared to intraoperative direct electrical cortical stimulation.

Results

Maximal MEP response of the m. abductor digiti minimi was located in an area corresponding to the “hand knob” of the precentral gyrus for both hemispheres. Repeated Ri-TMS measurements showed a high reproducibility. Simultaneous registration of the MEP response for m. brachioradialis, m. abductor pollicis brevis, and m. abductor digiti minimi demonstrated individual peak areas of maximal MEP response for the individual muscle groups. Ri-TMS mapping was compared to the corresponding fMRI studies. The areas of maximal MEP response localized within the “finger tapping” activated areas by fMRI in all six individuals.

Conclusions

Ri-TMS is suitable for high resolution non-invasive preoperative somatotopic mapping of the motor cortex. Ri-TMS may help in the planning of neurosurgical procedures and may be directly used in navigation systems.