Sanzleon P.,Institute Of Neurosciences Des Systemes |
Knock S.A.,Charite University of Medicine |
Woodman M.M.,Institute Of Neurosciences Des Systemes |
Domide L.,Codemart |
And 3 more authors.
Frontiers in Neuroinformatics | Year: 2013
We present TheVirtualBrain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. © 2013 Sanz_leon, Knock, Woodman, Domide, Mersmann, Mcintosh and Jirsa.
Kumar P.,Inter University Accelerator Center |
Ahmad A.,Aix - Marseille University |
Ahmad A.,CNRS Jean Lamour Institute |
Carrere M.,Institute Of Neurosciences Des Systemes
Radiation Effects and Defects in Solids | Year: 2015
In this paper, we report an analytical model to estimate the variation of the yield (and hence the pressure) from sputtering, elastic collisions, and backscattering on a surface exposed to International Thermonuclear Experimental Reactor-relevant plasmas. To study the yield and the pressure exerted on the surfaces of carbon (C), silicon (Si) and tungsten (W) due to plasma exposure, the irradiation of H, Ar and Xe ions at normal incidence was considered. Transport and range of ions in matter simulations were done to calculate the backscattering/sputtering yields and the energies on the surfaces. The calculations are significant for the optimization of material facing the plasma in future fusion reactors where erosion and long term operation are key issues. The results show that yield increases with the increase of ion energy. The carbon surface is the least affected to exposure of the plasma. In the chosen ion energy range (0–1 keV), the simulations/calculations (for Ar ion incident on Si and W) are in good agreement with published experimental results. © 2015 Taylor & Francis
Aram P.,Institute Of Neurosciences Des Systemes |
Aram P.,University of Sheffield |
Freestone D.R.,University of Melbourne |
Freestone D.R.,The Bionics Institute |
And 6 more authors.
NeuroImage | Year: 2013
Neural fields are spatially continuous state variables described by integro-differential equations, which are well suited to describe the spatiotemporal evolution of cortical activations on multiple scales. Here we develop a multi-resolution approximation (MRA) framework for the integro-difference equation (IDE) neural field model based on semi-orthogonal cardinal B-spline wavelets. In this way, a flexible framework is created, whereby both macroscopic and microscopic behavior of the system can be represented simultaneously. State and parameter estimation is performed using the expectation maximization (EM) algorithm. A synthetic example is provided to demonstrate the framework. © 2012 Elsevier Inc.
PubMed | University of Sheffield, Bitly Inc, University of Malta, Institute Of Neurosciences Des Systemes and University of Melbourne
Type: | Journal: NeuroImage | Year: 2014
Neural fields are spatially continuous state variables described by integro-differential equations, which are well suited to describe the spatiotemporal evolution of cortical activations on multiple scales. Here we develop a multi-resolution approximation (MRA) framework for the integro-difference equation (IDE) neural field model based on semi-orthogonal cardinal B-spline wavelets. In this way, a flexible framework is created, whereby both macroscopic and microscopic behavior of the system can be represented simultaneously. State and parameter estimation is performed using the expectation maximization (EM) algorithm. A synthetic example is provided to demonstrate the framework.
McGonigal A.,Aix - Marseille University |
McGonigal A.,Institute Of Neurosciences Des Systemes |
Bartolomei F.,Aix - Marseille University |
Bartolomei F.,Institute Of Neurosciences Des Systemes |
And 5 more authors.
Stereotactic and Functional Neurosurgery | Year: 2014
Background: In pharmacoresistant focal epilepsies involving the central region, risk of motor deficit generally contraindicates cortical resection. Gamma knife radiosurgery (GK) is an established treatment for mesial temporal epilepsy and epilepsy associated with hypothalamic hamartoma. Objectives: To explore the safety profile and efficacy of GK in motor cortex epilepsies. Methods: Four patients (18-31 years) with intractable focal sensorimotor epilepsy seizures arising from the paracentral lobule, demonstrated by stereoelectroencephalography, in whom conventional surgery was contraindicated because of motor deficit risk underwent GK. A marginal dose of 24 Gy was delivered to a focal zone involving the paracentral lobule. Results Volume of treatment ranged from 1.6 to 3.18 cm3 (median: 2.34). No motor deficit or other adverse effect occurred. Follow-up was available for at least 3 years (range: 36-78 months; median: 49). No complication of GK, including motor deficit, occurred. Two patients achieved an Engel class 1B outcome and 2 were unchanged. Both of the patients who improved had gradual disappearance of objective motor ictal semiology (6-12 months after GK), preceding reduced seizure frequency (12-18 months onwards). Cerebral MRI showed no change. Conclusions: GK is a potentially useful treatment for focal paracentral epilepsies where conventional surgery would carry an unacceptable risk of motor deficit. © 2014 S. Karger AG, Basel.