ArticleFrontiers in neuroinformatics2014
BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs.
Article in Frontiers in neuroinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- Optogenetic activation of dorsal raphe serotonin neurons induces brain-wide activation.Nature communications · 2024Article
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- aXonica: A support package for MRI based Neuroimaging.Biotechnology notes (Amsterdam, Netherlands) · 2024Article
- Digital 3D Brain MRI Arterial Territories Atlas.Scientific data · 2023Article
- Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.Human brain mapping · 2022Review
- 3T sodium MR imaging in Alzheimer's disease shows stage-dependent sodium increase influenced by age and local brain volume.NeuroImage. Clinical · 2022Article
- Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on "Frontiers in Neuroinformatics".Frontiers in neuroinformatics · 2022Review
- Neuroplasticity in post-stroke aphasia: A systematic review and meta-analysis of functional imaging studies of reorganization of language processing.Neurobiology of language (Cambridge, Mass.) · 2021Article
- Cingulo-opercular adaptive control for younger and older adults during a challenging gap detection task.Journal of neuroscience research · 2020Article
- Functional Neuroimaging in the New Era of Big Data.Genomics, proteomics & bioinformatics · 2019Review
- Cluster failure revisited: Impact of first level design and physiological noise on cluster false positive rates.Human brain mapping · 2019Article
- Using GPUs to accelerate computational diffusion MRI: From microstructure estimation to tractography and connectomes.NeuroImage · 2019Article
- No effect of attentional bias modification training in methamphetamine users receiving residential treatment.Psychopharmacology · 2019Article
- Using the Wild Bootstrap to Quantify Uncertainty in Mean Apparent Propagator MRI.Frontiers in neuroinformatics · 2019Article
- AutoVOI: real-time automatic prescription of volume-of-interest for single voxel spectroscopy.Magnetic resonance in medicine · 2018Article
- Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.Magnetic resonance imaging · 2018Article
- Orthographic influence on spoken word identification: Behavioral and fMRI evidence.Neuropsychologia · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Analysis of functional magnetic resonance imaging (fMRI) data is becoming ever more computationally demanding as temporal and spatial resolutions improve, and large, publicly available data sets proliferate. Moreover, methodological improvements in the neuroimaging pipeline, such as non-linear spatial normalization, non-parametric permutation tests and Bayesian Markov Chain Monte Carlo approaches, can dramatically increase the computational burden. Despite these challenges, there do not yet exist any fMRI software packages which leverage inexpensive and powerful graphics processing units (GPUs) to perform these analyses. Here, we therefore present BROCCOLI, a free software package written in OpenCL (Open Computing Language) that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. BROCCOLI has, for example, been tested with an Intel CPU, an Nvidia GPU, and an AMD GPU. These tests show that parallel processing of fMRI data can lead to significantly faster analysis pipelines. This speedup can be achieved on relatively standard hardware, but further, dramatic speed improvements require only a modest investment in GPU hardware. BROCCOLI (running on a GPU) can perform non-linear spatial normalization to a 1 mm(3) brain template in 4-6 s, and run a second level permutation test with 10,000 permutations in about a minute. These non-parametric tests are generally more robust than their parametric counterparts, and can also enable more sophisticated analyses by estimating complicated null distributions. Additionally, BROCCOLI includes support for Bayesian first-level fMRI analysis using a Gibbs sampler. The new software is freely available under GNU GPL3 and can be downloaded from github (https://github.com/wanderine/BROCCOLI/).
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