FDTD-based Transcranial Magnetic Stimulation model applied to specific neurodegenerative disorders

Non-invasive treatment of neurodegenerative diseases is particularly challenging in Western countries, where the population age is increasing. In this work, magnetic propagation in human head is modelled by Finite-Difference Time-Domain (FDTD) method, taking into account specific characteristics of Transcranial Magnetic Stimulation (TMS) in neurodegenerative diseases. It uses a realistic high-resolution three-dimensional human head mesh. The numerical method is applied to the analysis of magnetic radiation distribution in the brain using two realistic magnetic source models: a circular coil and a figure-8 coil commonly employed in TMS. The complete model was applied to the study of magnetic stimulation in Alzheimer and Parkinson Diseases (AD, PD). The results show the electrical field distribution when magnetic stimulation is supplied to those brain areas of specific interest for each particular disease. Thereby the current approach entails a high potential for the establishment of the current underdeveloped TMS dosimetry in its emerging application to AD and PD

Analysis of optical neural stimulation effects on neural networks affected by neurodegenerative diseases

The number of people in risk of developing a neurodegenerative disease increases as the life expectancy grows due to medical advances. Multiple techniques have been developed to improve patient’s condition, from pharmacological to invasive electrodes approaches, but no definite cure has yet been discovered. In this work Optical Neural Stimulation (ONS) has been studied. ONS stimulates noninvasively the outer regions of the brain, mainly the neocortex. The relationship between the stimulation parameters and the therapeutic response is not totally clear. In order to find optimal ONS parameters to treat a particular neurodegenerative disease, mathematical modeling is necessary. Neural networks models have been employed to study the neural spiking activity change induced by ONS. Healthy and pathological neocortical networks have been considered to study the required stimulation to restore the normal activity. The network consisted of a group of interconnected neurons, which were assigned 2D spatial coordinates. The optical stimulation spatial profile was assumed to be Gaussian. The stimulation effects were modeled as synaptic current increases in the affected neurons, proportional to the stimulation fluence. Pathological networks were defined as the healthy ones with some neurons being inactivated, which presented no synaptic conductance. Neurons’ electrical activity was also studied in the frequency domain, focusing specially on the changes of the spectral bands corresponding to brain waves. The complete model could be used to determine the optimal ONS parameters in order to achieve the specific neural spiking patterns or the required local neural activity increase to treat particular neurodegenerative pathologies.This work has been partially supported by the project MAT2012-38664-C02-01 of the Spanish Ministery of Economy and Competitiveness and by San Cándido Foundation

Optical neural stimulation modeling on degenerative neocortical neural networks

Neurodegenerative diseases usually appear at advanced age. Medical advances make people live longer and as a consequence, the number of neurodegenerative diseases continuously grows. There is still no cure for these diseases, but several brain stimulation techniques have been proposed to improve patients’ condition. One of them is Optical Neural Stimulation (ONS), which is based on the application of optical radiation over specific brain regions. The outer cerebral zones can be noninvasively stimulated, without the common drawbacks associated to surgical procedures. This work focuses on the analysis of ONS effects in stimulated neurons to determine their influence in neuronal activity. For this purpose a neural network model has been employed. The results show the neural network behavior when the stimulation is provided by means of different optical radiation sources and constitute a first approach to adjust the optical light source parameters to stimulate specific neocortical areas.This work has been partially supported by the project MAT2012-38664-C02-01 of the Spanish Ministry of Economy and Competitiveness, and by San Cándido Foundation

Study of the optical stimulation effects on a neural network with neurodegenerative processes

RESUMEN: El riesgo de desarrollar una enfermedad neurodegenerativa aumenta con la edad. Con los avances médicos la esperanza de vida crece por lo que se hace necesario el desarrollo de técnicas de estimulación cerebral. Una de ellas es la Estimulación Neuronal Óptica (ENO) que estimula no invasivamente las regiones exteriores del cerebro. En este trabajo se realiza un estudio de la ENO y su posterior aplicación al tratamiento de dichas patologías. Con el fin de analizar sus efectos se modela una red neuronal con diferentes grados de patología. Los resultados muestran la distribución de la radiación óptica en el neocórtex y la actividad de una red neuronal patológica estimulada. El modelo completo presenta una gran versatilidad para determinar los parámetros óptimos de la ENO para alcanzar patrones de activación neuronal específicos para tratar patologías neurodegenerativas.ABSTRACT: Risk of developing a neurodegenerative disease increases at advanced age. Medical advances increase life expectancy, which is why it is necessary to develop brain stimulation techniques. One of them is Optical Neural Stimulation (ONS) that stimulates noninvasively the outer brain regions. In this work ONS and its application for treatment of these pathologies is studied. In order to analyze ONS effects, a neuronal network with different stages of neurodegenerative pathology has been modeled. The results show the optical radiation distribution in the neocortex and the activity of a stimulated pathological neural network. The complete model presents a wide functionality to determine the optimal ONS parameters in order to achieve the specific neural spiking patterns to treat particular neurodegenerative pathology

CoSimPy: An open-source python library for MRI radiofrequency Coil EM/Circuit Cosimulation

Background and objectives: The Electromagnetic/Circuit cosimulation method represents a valuable and effective strategy to address those problems where a radiative structure has to interact with external supporting circuitries. This is of particular concern for Magnetic Resonance Imaging (MRI), radiofrequency (RF) coils design, where the supporting circuitry optimisation represents, generally, a crucial aspect. This article presents CoSimPy, an open-source Python circuit simulation library for Electromagnetic/Circuit cosimulations and specifically optimised for MRI, RF coils design.Methods: CoSimPy is designed following an Object-orientated programming. In addition to the essential methods aimed to performed the Electromagnetic/Circuit cosimulations, many others are implemented both to simplify the standard workflow and to evaluate the RF coils performance. In this article, the theory which underlies the fundamental methods of CoSimPy is shown together with the basic framework of the library.Results: In the paper, the reliability of CoSimPy is successfully tested against a full-wave electromagnetic simulations involving a reference setup. The library is made available httys://github.com/umbertozanovello/CoSimpy under together with a detailed documentation providing guidelines and examples. CoSimPy is distributed under the Massachusetts Institute of Technology (MIT) license.Conclusions: CoSimPy demonstrated to be an agile tool employable for Electromagnetic/Circuit cosimulations. Its distribution is meant to fulfil the needs of several researchers also avoiding duplication of effort in writing custom implementations. CoSimPy is under constant development and aims to represent a coworking environment where scientists can implement additional methods whose sharing can represent an advantage for the community. Finally, even if CoSimPy is designed with special focus on MRI, it represents an efficient and practical tool potentially employable wherever electronic devices made of radiative and circuitry components are involved. (C) 2022 Published by Elsevier B.V

Transcranial magnetic stimulation for orofacial pain relief

Práce si klade za cíl ověření úspěšnosti stimulace deseti reálných pacientů podstupujících léčbu orofaciální bolesti pomocí rTMS. Dále se práce zaměřuje na identifikaci možných nepřesností během prováděného zákroku. Využití individuálních anatomických modelů v tak vysokém počtu je zcela unikátní. Ložisko orofaciální bolesti je identifikováno pomocí fMRI, která je následně vyhodnocena pomocí programu SPM. Během stimulace pacienta se zaznamenává pozice cívky vůči hlavě pacienta trojrozměrným skenováním senzorem KINECT. Pro pacienty jsou zpracovány individuální anatomické modely hlavy automatickou segmentací MARS. Následuje výpočet rozložení elektromagnetického pole simulátorem Sim4Life. Výsledkem výpočtů jsou nízké hodnoty indukovaného pole v aktivacích fMRI. Pouze u jednoho pacienta bylo stimulováno intenzitou vyšší než 80 V/m 20,5 % objemu aktivace. Vychýlení stimulační cívky o dva centimetry mimo souvislý úsek mozkového závitu snížilo objem stimulované aktivace na jednu desetinu. Kombinace vysoce fokální cívky a malého objemu mozkové aktivace klade vysoké nároky na přesnost umisťování stimulační cívky. Jako hlavní zdroj nepřesností byl identifikován proces nahrazování navigační a stimulační cívky.The aim of the study is verification of success rate by rTMS of ten patients suffering by orofacial pain. The thesis further aims to the identification of main inaccuracies during the process. For the first time high precision individual anatomical models for each patient are used for stimulation efficiency evaluation. The source of orofacial pain is identified by fMRI, which is evaluated by SPM software. During the stimulation relative position of stimulation coil to patient's head is recorded with three-dimensional scanning based on KINECT sensor. For all patient three-dimensional anatomical head models are created by automatic head segmentation software MARS. Then the electromagnetic field distribution is computed in Sim4Life software. The result is low electric field intensity in fMRI activations. Only one patient was stimulated with higher electric intensity than 80 V/m in 20,5 % of activation volume. Displacement of stimulation coil out of gyrus higher than two centimeters reduced volume of stimulated activation to one tenth. Combination of high focality coil and small activation volume demands high precision coil positioning. Like the main source of inaccuracies was identified the process of replacement navigation by stimulation coil