Data fusion refers to the joint analysis of multiple datasets that provide different (eg,
complementary) views of the same task. In general, it can extract more information than …

Data fusion is the joint analysis of multiple inter-related datasets that provide complementary
views of the same phenomenon. The process of correlating and fusing information from …

Objective Fusion of EEG and fMRI data provides complementary information about the brain
functions. Thus, data fusion should employ all dimensions of data to both extract the shared …

Combining various sources of information to discover hidden patterns is key in data
analysis. These sources can often be represented as matrices and/or multiway arrays, or …

Magnetoencephalography (MEG) and electroencephalography (EEG) are contemporary
methods to investigate the function and organization of the brain. Simultaneously acquired …

EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are
synchronized to interictal epileptic discharges, which can provide evidence for localizing the …

Data fusion refers to the joint analysis of multiple datasets which provide complementary
views of the same task. In this paper, the problem of jointly analyzing …

The fusion of simultaneously recorded EEG and fMRI data is of great value to neuroscience
research due to the complementary properties of the individual modalities. Traditionally …

High-dimensional and multimodal data to describe various aspects of a patient's clinical
condition have become increasingly abundant in the medical field across a variety of …

Data fusion refers to the joint analysis of multiple datasets which provide complementary
views of the same task. In this preprint, the problem of jointly analyzing …