ArticleFrontiers in neuroscience2013
Adaptive cluster analysis approach for functional localization using magnetoencephalography.
Article in Frontiers in neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Internet Gaming Disorder Clustering Based on Personality Traits in Adolescents, and Its Relation with Comorbid Psychological Symptoms.International journal of environmental research and public health · 2020Article
- TRCMGene: A two-step referential compression method for the efficient storage of genetic data.PloS one · 2018Article
- Deep sparse multi-task learning for feature selection in Alzheimer's disease diagnosis.Brain structure & function · 2016Article
- Epileptogenic focus localization in treatment-resistant post-traumatic epilepsy.Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia · 2015Review
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Authors and funding
5 authors.
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Abstract
In this paper we propose an agglomerative hierarchical clustering Ward's algorithm in tandem with the Affinity Propagation algorithm to reliably localize active brain regions from magnetoencephalography (MEG) brain signals. Reliable localization of brain areas with MEG has been difficult due to variations in signal strength, and the spatial extent of the reconstructed activity. The proposed approach to resolve this difficulty is based on adaptive clustering on reconstructed beamformer images to find locations that are consistently active across different participants and experimental conditions with high spatial resolution. Using data from a human reaching task, we show that the method allows more accurate and reliable localization from MEG data alone without using functional magnetic resonance imaging (fMRI) or any other imaging techniques.
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