Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression

Transcranial magnetic stimulation (TMS) is a powerful tool to investigate causal structure-function relationships in the human brain. However, a precise delineation of the effectively stimulated neuronal populations is notoriously impeded by the widespread and complex distribution of the induced electric field. Here, we propose a method that allows rapid and feasible cortical localization at the individual subject level. The functional relationship between electric field and behavioral effect is quantified by combining experimental data with numerically modeled fields to identify the cortical origin of the modulated effect. Motor evoked potentials (MEPs) from three finger muscles were recorded for a set of random stimulations around the primary motor area. All induced electric fields were nonlinearly regressed against the elicited MEPs to identify their cortical origin. We could distinguish cortical muscle representation with high spatial resolution and localized them primarily on the crowns and rims of the precentral gyrus. A post-hoc analysis revealed exponential convergence of the method with the number of stimulations, yielding a minimum of about 180 random stimulations to obtain stable results. Establishing a functional link between the modulated effect and the underlying mode of action, the induced electric field, is a fundamental step to fully exploit the potential of TMS. In contrast to previous approaches, the presented protocol is particularly easy to implement, fast to apply, and very robust due to the random coil positioning and therefore is suitable for practical and clinical applications

New Insights into Alzheimer's Disease Progression: A Combined TMS and Structural MRI Study

BACKGROUND: Combination of structural and functional data of the human brain can provide detailed information of neurodegenerative diseases and the influence of the disease on various local cortical areas. METHODOLOGY AND PRINCIPAL FINDINGS: To examine the relationship between structure and function of the brain the cortical thickness based on structural magnetic resonance images and motor cortex excitability assessed with transcranial magnetic stimulation were correlated in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients as well as in age-matched healthy controls. Motor cortex excitability correlated negatively with cortical thickness on the sensorimotor cortex, the precuneus and the cuneus but the strength of the correlation varied between the study groups. On the sensorimotor cortex the correlation was significant only in MCI subjects. On the precuneus and cuneus the correlation was significant both in AD and MCI subjects. In healthy controls the motor cortex excitability did not correlate with the cortical thickness. CONCLUSIONS: In healthy subjects the motor cortex excitability is not dependent on the cortical thickness, whereas in neurodegenerative diseases the cortical thinning is related to weaker cortical excitability, especially on the precuneus and cuneus. However, in AD subjects there seems to be a protective mechanism of hyperexcitability on the sensorimotor cortex counteracting the prominent loss of cortical volume since the motor cortex excitability did not correlate with the cortical thickness. Such protective mechanism was not found on the precuneus or cuneus nor in the MCI subjects. Therefore, our results indicate that the progression of the disease proceeds with different dynamics in the structure and function of neuronal circuits from normal conditions via MCI to AD

Identification of proprioceptive thalamocortical tracts in children : comparison of fMRI, MEG, and manual seeding of probabilistic tractography

Studying white matter connections with tractography is a promising approach to understand the development of different brain processes, such as proprioception. An emerging method is to use functional brain imaging to select the cortical seed points for tractography, which is considered to improve the functional relevance and validity of the studied connections. However, it is unknown whether different functional seeding methods affect the spatial and microstructural properties of the given white matter connection. Here, we compared functional magnetic resonance imaging, magnetoencephalography, and manual seeding of thalamocortical proprioceptive tracts for finger and ankle joints separately. We showed that all three seeding approaches resulted in robust thalamocortical tracts, even though there were significant differences in localization of the respective proprioceptive seed areas in the sensorimotor cortex, and in the microstructural properties of the obtained tracts. Our study shows that the selected functional or manual seeding approach might cause systematic biases to the studied thalamocortical tracts. This result may indicate that the obtained tracts represent different portions and features of the somatosensory system. Our findings highlight the challenges of studying proprioception in the developing brain and illustrate the need for using multimodal imaging to obtain a comprehensive view of the studied brain process.Peer reviewe

The role of neuronavigation in TMS-EEG studies : Current applications and future perspectives

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) allows measuring noninvasively the electrical response of the human cerebral cortex to a direct perturbation. Complementing TMSEEG with a structural neuronavigation tool (nTMS-EEG) is key for accurately selecting cortical areas, targeting them, and adjusting the stimulation parameters based on some relevant anatomical priors. This step, together with the employment of visualization tools designed to perform a quality check of TMS-evoked potentials (TEPs) in real-time during TMS-EEG data acquisition, is pivotal for maximizing the impact of the TMS pulse on the cortex and in ensuring highly reproducible measurements within sessions and across subjects. Moreover, storing stimulation parameters in the neumnavigation system can help in replicating the stimulation parameters within and across experimental sessions and sharing them across research centers. Finally, the systematic employment of neumnavigation in TMS-EEG studies is also critical to standardize measurements in clinical populations in search for reliable diagnostic and prognostic TMS-EEG-based biomarkers for neurological and psychiatric disorders.Peer reviewe

Brain stimulation reveals neural mechanisms of stereopsis

Stereopsis is critical for interaction with our environment. However, binocular disparity in natural images is often ambiguous and this makes it difficult to establish a binocular correspondence solution. In my thesis, I focus on both the challenges of this problem and solutions that the brain applies. To study brain function, I use Transcranial Magnetic Stimulation (TMS) which allows me to causally relate induced changes in neural activity with changes in depth perception. This way I can map out neural mechanisms of stereopsis within the visual cortex. As a first step, I conducted a proof of concept study to confirm where in the visual cortex TMS can be used to study perception. I systematically mapped out where in the visual cortex TMS triggers self-propagating, perceptually noticeable neural activation. I related this to the retinotopic organisation and the location of object- and motion-selective areas, identified by functional Magnetic Resonance Imaging. My work confirms that TMS can trigger perceptually significant neural activation in early and dorsal visual areas. In my second chapter, I investigated how incoherent binocular disparity challenges stereopsis. As disparity coherence is reduced it becomes increasingly challenging to establish global correspondence and consequently observers struggle to perceive depth. Interestingly, this problem is less severe when images contain a mixture of bright and dark features (mixed contrast polarity). By locating where in the brain disparity processing benefits from mixed contrast polarity, I can infer where incoherent disparity might challenge mechanisms of stereopsis. I applied TMS during discrimination of incoherent disparity in images with mixed or single contrast polarity. I found that stimulation over V1 differentially affects perception of mixed and single polarity stimuli. My findings show that mechanisms of stereopsis in early visual cortex process mixed and single polarity differently and suggest these mechanisms are challenged by incoherent disparity. In my final chapter, I investigated the role of parietal cortex in the processing of incoherent disparity information. Findings in both macaque monkeys and human observers suggest that the dorsal visual cortex is particularly involved in the processing of incoherent disparity signals. Here, I tested the role of the posterior parietal cortex in human observers. I used brain stimulation to suppress synaptic transmission in parietal cortex and recorded electroencephalography during incoherent disparity processing. Disrupting parietal cortex caused changes in early, disparity responses in visual cortex. This suggests that parietal cortex provides top-down influence to the visual cortex relevant to incoherent disparity processing.European Commission (FP7, PRISM), Wellcome Trus

Advanced Statistical Machine Learning Methods for the Analysis of Neurophysiologic Data with Medical Application

Transcranial magnetic stimulation procedures use a magnetic field to carry a short-lasting electrical current pulse into the brain, where it stimulates neurons, particularly in superficial regions of the cerebral cortex. It is a powerfull tool to calculate several parameters related to the intracortical excitability and inhibition of the motor cortex. The cortical silent period (CSP), evoked by magnetic stimulation, corresponds to the suppression of muscle activity for a short period after a muscle response to a magnetic stimulation. The duration of the CSP is paramount to assess intracortical inhibition, and it is known to be correlated with the prognosis of stroke patients’ motor ability. Current mechanisms to estimate the duration of the CSP are mostly based on the analysis of raw electromyographical (EMG) signal and they are very sensitive to the presence of noise. This master thesis is devoted to the analysis of the EMG signal of stroke patients under rehabilitation. The use of advanced statistical machine learning techniques that behave robustly in the presence of noise for this analysis allows us to accurately estimate signal parameters such as the CSP. The research reported in this thesis provides us with a first evidence about their applicability in other areas of neuroscience