Grid Infrastructures for Computational Neuroscience: The neuGRID Example

Abstract

Evolution of brain imaging in neurodegenerative diseasesBrain imaging was regarded as an elective examination in patients with cognitive decline 15 years ago [1]. The practice parameters for diagnosis and evaluation of dementia defined by the American Academy of Neurology regarded computed tomography (CT) and magnetic resonance (MR) as 'optional' assessments [2,3]. Over time, imaging in dementia has moved from a negative, exclusionary role to one that added positive diagnostic and prognostic information. In the late 1990s, the traditional exclusionary approach was abandoned in favor of the inclusive approach [4,5]. Rapid advances in neuroimaging technologies such as PET, single photon emission CT, MR spectroscopy, diffusion tensor imaging and functional MRI have offered new vision into the pathophysiology of Alzheimer's desease (AD) [6] and, consequently, increasingly new powerful data-analysis methods have been developed [7].Since the beginning of the 21st Century, the development of innovative techniques for region-of-interest-based volumetry, automated voxel-based morphometry, cortical thickness measurement, basal forebrain volumetry and multivariate statistics have emerged [7][8][9] and those measurements most feasible and accurate have started to be used in clinical settings. The availability to the neuroimaging community of large prospective image data repositories has led to the development of web-based interfaces to access data and online image analysis tools to assess longitudinal brain changes [10][11][12][13].With the development of novel analysis techniques, the computational complexity of neuroimaging analysis has also increased signifi cantly. Higher spatial resolution images and longer time scans are being acquired so that more voxels will need to be processed for each acquisition. The same applies to the computational resources required by algorithms, since these have become increasingly central processing Neuroscience is increasingly making use of statistical and mathematical tools to extract information from images of biological tissues. Computational neuroimaging tools require substantial computational resources and the increasing availability of large image datasets will further enhance this need. Many efforts have been directed towards creating brain image repositories including the recent US Alzheimer Disease Neuroimaging Initiative. Multisite-distributed computing infrastructures have been launched with the goal of fostering shared resources and facilitating data analysis in the study of neurodegenerative diseases. Currently, some Grid-and non-Grid-based projects are aiming to establish distributed e-infrastructures, interconnecting compatible imaging datasets and to supply neuroscientists with the most advanced information and communication technologies tools to study markers of Alzheimer's and other brain diseases, but they have so far failed to make a difference in the larger neuroscience community. NeuGRID is an Europeon comission-funded effort arising from the needs of the Alzheimer's...

Provision of an integrated data analysis platform for computational neuroscience experiments

“…al., 2005). The main body of work in this area includes for example, neuGRID (Redolfi et al, 2009), Neurolog (Wali et al, 2012), LONI (Dinov et al, 2009) and BIRN (Grethe et al, 2005). In these efforts data gathering, management and visualisation has been successfully facilitated, however the constituent data is captured and stored in large distributed databases.…”

Glueing grids and clouds together: a service-oriented approach

“…The GP uses the JavaGAT (van Nieuwpoort et al, 2007) middleware, which is a SAGA implementation, and OMII adapters to communicate with the OMII middleware. GP client applications, such as the pipeline service in the neuGrid project (Redolfi et al, 2009), allow clinicians and neuroscientists to create neuro-imaging pipelines, in a user friendly environment, for a series of automated transformations on brain images. Once the pipelines are constructed, the neuro-imaging pipeline service parallelises them.…”

Overview of Medical Data Management Solutions for Research Communities

“…A precommercial release of the Mammogrid+ software version 1.0 was planned for June 2007 to be deployed within the five hospitals collaborating in the project. Experience developed during the Mammogrid project was also exploited in more recent projects like neuGRID [7].…”