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Minati, Ludovico, Nigri, Anna, Cercignani, Mara and Chan, Dennis (2013) Detection of scale-freeness in brain connectivity by functional MRI: signal processing aspects and implementation of an open hardware co-processor. Medical Engineering & Physics, 35 (10). pp. 1525-1531. ISSN 1350-4533
Full text not available from this repository.Abstract
An outstanding issue in graph-theoretical studies of brain functional connectivity is the lack of formal criteria for choosing parcellation granularity and correlation threshold. Here, we propose detectability of scale-freeness as a benchmark to evaluate time-series extraction settings. Scale-freeness, i.e., power-law distribution of node connections, is a fundamental topological property that is highly conserved across biological networks, and as such needs to be manifest within plausible reconstructions of brain connectivity. We demonstrate that scale-free network topology only emerges when adequately fine cortical parcellations are adopted alongside an appropriate correlation threshold, and provide the full design of the first open-source hardware platform to accelerate the calculation of large linear regression arrays.
| Item Type: | Article |
|---|---|
| Keywords: | Functional connectivity Graph-based analysis Network topology Scale freeness Functional magnetic resonance imaging (fMRI) Parallel processing |
| Schools and Departments: | Brighton and Sussex Medical School > Clinical and Experimental Medicine Brighton and Sussex Medical School > Neuroscience |
| Subjects: | R Medicine |
| Related URLs: | |
| Depositing User: | Patricia Butler |
| Date Deposited: | 24 Jul 2013 08:50 |
| Last Modified: | 09 Jan 2020 16:12 |
| URI: | http://sro.sussex.ac.uk/id/eprint/45748 |