Individual differences in white matter microstructure reflect variation in functional connectivity during action choice.

The relation between brain structure and function is of fundamental importance in neuroscience. Comparisons between behavioral and brain imaging measures suggest that variation in brain structure correlates with the presence of specific skills[1-3]. Behavioral measures, however, reflect the integrated function of multiple brain regions. Rather than behavior, a physiological index of function could be a more sensitive and informative measure with which to compare structural measures. Here, we test for a relationship between a physiological measure of functional connectivity between two brain areas during a simple decision making task and a measure of structural connectivity. Paired-pulse transcranial magnetic stimulation indexed functional connectivity between two regions important for action choices: premotor and motor cortex. Fractional anisotropy (FA), a marker of microstructural integrity, indexed structural connectivity. Individual differences in functional connectivity during action selection show highly specific correlations with FA in localised regions of white matter interconnecting regions including the premotor and motor cortex. Probabilistic tractography[4, 5], a technique for identifying fibre pathways from diffusion-weighted imaging (DWI), reconstructed the anatomical networks linking the component brain regions involved in making decisions. These findings demonstrate a relationship between individual differences in functional and structural connectivity within human brain networks central to action choice

Variation in Reported Human Head Tissue Electrical Conductivity Values

Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors. Of 3121 identified publications spanning three databases, 56 papers were included in data extraction. Conductivity values were categorised according to tissue type, and recorded alongside methodology, measurement condition, current frequency, tissue temperature, participant pathology and age. We found variation in electrical conductivity of the whole-skull, the spongiform layer of the skull, isotropic, perpendicularly- and parallelly-oriented white matter (WM) and the brain-to-skull-conductivity ratio (BSCR) could be significantly attributed to a combination of differences in methodology and demographics. This large variation should be acknowledged, and care should be taken when creating volume conductor models, ideally constructing them on an individual basis, rather than assuming them from the literature. When personalised models are unavailable, it is suggested weighted average means from the current meta-analysis are used. Assigning conductivity as: 0.41 S/m for the scalp, 0.02 S/m for the whole skull, or when better modelled as a three-layer skull 0.048 S/m for the spongiform layer, 0.007 S/m for the inner compact and 0.005 S/m for the outer compact, as well as 1.71 S/m for the CSF, 0.47 S/m for the grey matter, 0.22 S/m for WM and 50.4 for the BSCR

Numerical investigation of transcranial direct current stimulation on cortical modulation

Transcranial direct current stimulation (tDCS) is a non-invasive and sub-convulsive functional stimulation technique with applications in both clinical therapy and neuro-science research. The technique provides researchers and clinicians with a unique tool capable of modulating the neural excitability in both the central and peripheral nervous system. On a clinical level, the procedure has been used quite extensively for its potential therapeutic applications in a number of neurological disorders. Despite the advantages of being safe, low cost and easy to administer, our limited under-standing on interaction mechanisms between the stimulation parameters and biologi-cal materials has impeded the development and optimisation of tDCS based therapies. The focus of this thesis is to develop a realistic finite element based human head model to address the problems involved in the forward modelling of transcranial direct current stimulation. The study explores the effects of model complexities and anisotropic material properties on field estimations. The sensitivity of electric field and current density on accurate modelling of cortical and non-cortical structures, and the influence of heterogeneously defined anisotropic electric conductivity on field parameters were analysed in an incremental manner. Using the averaged and the subject specific Magnetic Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI) data, the head models with detailed anatomical features and realistic tissue conductive properties, were developed and employed to specifically address the role of stimulation parameters, such as: morphological variations, structural details, tissue behaviour, inter-subject variations, electrode montages and neural fibre pathways for defining the site and strength of modulation/stimulation. This thesis demonstrates the importance of human head modelling in elucidating the complex electric field and current density profiles instigated by the non-invasive electric stimulation. The results of this study strongly support the initial hypothesis that model complexity and accurate conductivity estimation play a crucial role in determining the accurate predictions of field variables. The study also highlighted the inadequacy of scalar field maps to decipher the complex brain current flow patterns and axonal/neural polarization. With the proposed refinements, model based strategies can be employed to optimally select the required stimulation strength and electrode montage specific to individual dose requirements. Therefore, the work con-ducted in this study will bridge the gap between the current clinical practices and the subject specific treatments by providing accurate physiologically representative simulation

Validation of Transcranial Electrical Stimulation (TES) Finite Element Modeling Against MREIT Current Density Imaging in Human Subjects

abstract: Transcranial electrical stimulation (tES) is a non-invasive brain stimulation therapy that has shown potential in improving motor, physiological and cognitive functions in healthy and diseased population. Typical tES procedures involve application of weak current (< 2 mA) to the brain via a pair of large electrodes placed on the scalp. While the therapeutic benefits of tES are promising, the efficacy of tES treatments is limited by the knowledge of how current travels in the brain. It has been assumed that the current density and electric fields are the largest, and thus have the most effect, in brain structures nearby the electrodes. Recent studies using finite element modeling (FEM) have suggested that current patterns in the brain are diffuse and not concentrated in any particular brain structure. Although current flow modeling is useful means of informing tES target optimization, few studies have validated tES FEM models against experimental measurements. MREIT-CDI can be used to recover magnetic flux density caused by current flow in a conducting object. This dissertation reports the first comparisons between experimental data from in-vivo human MREIT-CDI during tES and results from tES FEM using head models derived from the same subjects. First, tES FEM pipelines were verified by confirming FEM predictions agreed with analytic results at the mesh sizes used and that a sufficiently large head extent was modeled to approximate results on human subjects. Second, models were used to predict magnetic flux density, and predicted and MREIT-CDI results were compared to validate and refine modeling outcomes. Finally, models were used to investigate inter-subject variability and biological side effects reported by tES subjects. The study demonstrated good agreements in patterns between magnetic flux distributions from experimental and simulation data. However, the discrepancy in scales between simulation and experimental data suggested that tissue conductivities typically used in tES FEM might be incorrect, and thus performing in-vivo conductivity measurements in humans is desirable. Overall, in-vivo MREIT-CDI in human heads has been established as a validation tool for tES predictions and to study the underlying mechanisms of tES therapies.Dissertation/ThesisDoctoral Dissertation Biomedical Engineering 201

Noninvasive Neuromodulation: Modeling and Analysis of Transcranial Brain Stimulation with Applications to Electric and Magnetic Seizure Therapy

Bridging the fields of engineering and psychiatry, this dissertation proposes a novel framework for the rational dosing of electric and magnetic seizure therapy, including electroconvulsive therapy (ECT) and magnetic seizure therapy (MST), for the treatment of psychiatric disorders such as medication resistant major depression and schizophrenia. The objective of this dissertation is to develop computational modeling tools that allow ECT and MST stimulation paradigms to be biophysically optimized ex vivo, prior to testing safety and efficacy in preclinical and clinical trials. Despite therapeutic advances, treatment resistant depression (TRD) remains a largely unmet clinical need. ECT is highly effective for TRD, but its side effects limit its real-world clinical utility. Modifications of treatment technique (e.g., electrode placement, stimulus parameters, novel paradigms such as MST) significantly improve the tolerability of convulsive therapy. However, we know relatively little about the distribution of the electric field (E-field) induced in the brain to inform spatial targeting of ECT and MST. Lacking an understanding of biophysical and physiological mechanisms, refinements in ECT/MST technique rely exclusively on time-consuming and costly clinical trials. Consequently, key questions remain unanswered about how to position the ECT electrodes or MST coil for targeted brain stimulation. Addressing this knowledge gap, this dissertation proposes a new platform that will inform an improved spatial targeting of ECT and MST through state-of-the-art computer simulations of the E-field distribution in human and nonhuman primate (NHP) brain. Part I of this dissertation aims to develop anatomically realistic finite element models of transcranial electric and magnetic stimulation in human and NHPs incorporating tissue heterogeneity and anisotropy derived from structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data. The NHP models of ECT and MST are created alongside the human model since NHPs are used in preclinical studies on the mechanisms of seizure therapy. Part II of this dissertation aims to apply the model developed in Part I to electric and magnetic seizure therapy. We compute the strength and spatial distributions of the E-field induced in the brain by various ECT and MST paradigms. The relative E-field strength among various regions of interest (ROIs) is examined to select electrode/coil configurations that produce most focal stimulation of target ROIs that are considered to mediate the therapeutic action of ECT and MST. Since E-field alone is insufficient to account for individual differences in neurophysiological response, we calibrate the E-field maps relative to the neural activation threshold via in vivo measurements of the corticospinal tract response to single pulses (motor threshold, MT). We derive an empirical estimate of the neural activation threshold by coupling simulated E-field strength with individually measured MT. The E-field strength relative to an empirical neural activation threshold and corresponding volume of suprathreshold stimulation (focality) is examined to inform the selection of ECT and MST stimulus pulse amplitude that will result in focal ROI stimulation. We contrast the ECT/MST stimulation strength and focality with conventional fixed and individually titrated pulse amplitude necessary to induce a seizure (seizure threshold, ST) to study pulse amplitude adjustment as a novel means of controlling stimulation strength and focality. This work provides a basis for rational dosing of seizure therapies that could help improve their risk/benefit ratio and guide the development of safer alternatives for patients with severe psychiatric disorders

White Matter Integrity as a Biomarker for Stroke Recovery: Implications for TMS Treatment

White matter consists of myelinated axons which integrate information across remote brain regions. Following stroke white matter integrity is often compromised leading to functional impairment and disability. Despite its prevalence among stroke patients the role of white matter in development of post-stroke rehabilitation has been largely ignored. Rehabilitation interventions like repetitive transcranial magnetic stimulation (rTMS) are promising but reports on its efficacy have been conflicting. By understanding the role of white matter integrity in post-stroke motor recovery, brain reorganization and TMS efficacy we may be able to improve the development of future interventions. In this dissertation we set out answer these questions by investigating the relationship between white matter integrity and 1) bimanual motor performance following stroke, 2) cortical laterality following stroke and 3) TMS signal propagation (in a group of cocaine users without stroke). We identified white matter integrity of the corpus callosum as a key structure influencing bimanual performance using kinematic measures of hand symmetry (Chapter 2). Second, we found that reduced white matter integrity of corpus callosum was correlated with loss of functional laterality of the primary motor cortex during movement of the affected hand (Chapter 3). Lastly, we found that reduced white matter tract integrity from the site of stimulation to a downstream subcortical target, was correlated to the ability to modulate that target (Chapter 4). Taken together these studies support white matter integrity as a valuable biomarker for future rTMS trials in stroke. To emphasize the implications of these findings, we provide an example of how to incorporate white matter integrity at multiple levels of rTMS study design

White matter changes following chronic restraint stress and neuromodulation: A diffusion magnetic resonance imaging study in young male rats

Background Repetitive transcranial magnetic stimulation (rTMS), a noninvasive neuromodulation technique, is an effective treatment for depression. However, few studies have used diffusion magnetic resonance imaging to investigate the longitudinal effects of rTMS on the abnormal brain white matter (WM) described in depression. Methods In this study, we acquired diffusion magnetic resonance imaging from young adult male Sprague Dawley rats to investigate 1) the longitudinal effects of 10- and 1-Hz low-intensity rTMS (LI-rTMS) in healthy animals; 2) the effect of chronic restraint stress (CRS), an animal model of depression; and 3) the effect of 10 Hz LI-rTMS in CRS animals. Diffusion magnetic resonance imaging data were analyzed using tract-based spatial statistics and fixel-based analysis. Results Similar changes in diffusion and kurtosis fractional anisotropy were induced by 10- and 1-Hz stimulation in healthy animals, although changes induced by 10-Hz stimulation were detected earlier than those following 1-Hz stimulation. Additionally, 10-Hz stimulation increased axial and mean kurtosis within the external capsule, suggesting that the two protocols may act via different underlying mechanisms. Brain maturation–related changes in WM, such as increased corpus callosum, fimbria, and external and internal capsule fiber cross-section, were compromised in CRS animals compared with healthy control animals and were rescued by 10-Hz LI-rTMS. Immunohistochemistry revealed increased myelination within the corpus callosum in LI-rTMS–treated CRS animals compared with those that received sham or no stimulation. Conclusions Overall, decreased WM connectivity and integrity in the CRS model corroborate findings in patients experiencing depression with high anxiety, and the observed LI-rTMS–induced effects on WM structure suggest that LI-rTMS might rescue abnormal WM by increasing myelination