Integrated Analysis of EEG and fMRI Using Sparsity of Spatial Maps

International audienceIntegration of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is an open problem, which has motivated many researches. The most important challenge in EEG-fMRI integration is the unknown relationship between these two modalities. In this paper, we extract the same features (spatial map of neural activity) from both modality. Therefore, the proposed integration method does not need any assumption about the relationship of EEG and fMRI. We present a source localization method from scalp EEG signal using jointly fMRI analysis results as prior spatial information and source separation for providing temporal courses of sources of interest. The performance of the proposed method is evaluated quantitatively along with multiple sparse priors method and sparse Bayesian learning with the fMRI results as prior information. Localization bias and source distribution index are used to measure the performance of different localization approaches with or without a variety of fMRI-EEG mismatches on simulated realistic data. The method is also applied to experimental data of face perception of 16 subjects. Simulation results show that the proposed method is significantly stable against the noise with low localization bias. Although the existence of an extra region in the fMRI data enlarges localization bias, the proposed method outperforms the other methods. Conversely, a missed region in the fMRI data does not affect the localization bias of the common sources in the EEG-fMRI data. Results on experimental data are congruent with previous studies and produce clusters in the fusiform and occipital face areas (FFA and OFA, respectively). Moreover, it shows high stability in source localization against variations in different subjects

Visual skills in elite athletes

In order to perform at the highest level, athletes will acquire information from all of their sensory systems. It would be intuitive to assume that the most vital information for the majority of sports-related tasks will be gathered via the visual system and that this visual input. tends to override information from other sensory sources. Research is beginning to highlight the links between the ability to quickly and accurately pick up visual information and quality of performance in a range of sports (Erickson, 2007). The purpose of this thesis is to investigate the visual skills of elite athletes and the effect of these visual skills on performance at the highest level of sport. The first experimental chapter aims to assess the current level of visual skills present in athletes of the highest level and compare these to lower level athletes, as well as by gender and sport. The thesis then goes on to develop a tool to use in order to assess the visual demands of a particular sport. In Chapters Four and Five visual training programmes are used with the aim of improving visual skills of elite athletes. In one study improvements are measured by playing position and the next applies different methods of vision training and improvements are measured not only in visual skill but also in sport-specific skill. Finally Chapter Six uses fMRI to compare the different brain function of expert athlete with novices. This thesis has shown that athletes from different sports, genders and abilities show assorted visual skills. It has also developed a tool to uncover which visual skills an expert considers most important for their sport. The training studies have proved successful in improving not only the visual skills of elite athletes but also their sport specific skills. Finally, it has been shown that experts use different areas of their brain when making sporting judgements, regardless of whether the decision is in the sport in which they excel or in an unfamiliar sport.EThOS - Electronic Theses Online ServiceGBUnited Kingdo