Imanol Gomez - Academia.edu (original) (raw)
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Beijing Normal University-Hong Kong Baptist University United International College
Institut de Recherche et Coordination Acoustique/Musique IRCAM
Friedrich-Alexander-Universität Erlangen-Nürnberg
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Papers by Imanol Gomez
Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely... more Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely high dimensional, sparse and noisy signals which are difficult to visualize, monitor and analyze. The use of spatial music can be particularly appropriate to represent its contained patterns. The literature describes several research done on sonifying neuroimaging data as well as different techniques to use spatialization as a musical language. In this paper, we discuss an artistic approach to fMRI sonification exploiting new compositional paradigms in spatial music. Therefore, we consider the brain activity as audio base material of a the spatial musical composition. Our approach attempts to explore the aesthetic potential of brain sonification not by transforming the data beyond the recognizable, but presenting the data as direct as possible.
The study of human brain functions has dramatically increased greatly due to the advent of Functi... more The study of human brain functions has dramatically increased greatly due to the advent of Functional Magnetic Resonance Imaging (fMRI), arguably the best technique for observing human brain activity that is currently available. However, fMRI techniques produce extremely high dimensional, sparse and noisy data which is difficult to visualize, monitor and analyze. In this paper, we propose two different sonification approaches to monitor fMRI data. The goal of the resulting fMRI data sonification system is to allow the auditory identification of cognitive states produced by different stimuli. The system consists of a feature selection component and a sonification engine. We explore different feature selection methods and sonification strategies. As a case study, we apply our system to the identification of cognitive states produced by volume accented and duration accented rhythmic stimuli.
Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely... more Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely high dimensional, sparse and noisy signals which are difficult to visualize, monitor and analyze. The use of spatial music can be particularly appropriate to represent its contained patterns. The literature describes several research done on sonifying neuroimaging data as well as different techniques to use spatialization as a musical language. In this paper, we discuss an artistic approach to fMRI sonification exploiting new compositional paradigms in spatial music. Therefore, we consider the brain activity as audio base material of a the spatial musical composition. Our approach attempts to explore the aesthetic potential of brain sonification not by transforming the data beyond the recognizable, but presenting the data as direct as possible.
Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely... more Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely high dimensional, sparse and noisy signals which are difficult to visualize, monitor and analyze. The use of spatial music can be particularly appropriate to represent its contained patterns. The literature describes several research done on sonifying neuroimaging data as well as different techniques to use spatialization as a musical language. In this paper, we discuss an artistic approach to fMRI sonification exploiting new compositional paradigms in spatial music. Therefore, we consider the brain activity as audio base material of a the spatial musical composition. Our approach attempts to explore the aesthetic potential of brain sonification not by transforming the data beyond the recognizable, but presenting the data as direct as possible.
The study of human brain functions has dramatically increased greatly due to the advent of Functi... more The study of human brain functions has dramatically increased greatly due to the advent of Functional Magnetic Resonance Imaging (fMRI), arguably the best technique for observing human brain activity that is currently available. However, fMRI techniques produce extremely high dimensional, sparse and noisy data which is difficult to visualize, monitor and analyze. In this paper, we propose two different sonification approaches to monitor fMRI data. The goal of the resulting fMRI data sonification system is to allow the auditory identification of cognitive states produced by different stimuli. The system consists of a feature selection component and a sonification engine. We explore different feature selection methods and sonification strategies. As a case study, we apply our system to the identification of cognitive states produced by volume accented and duration accented rhythmic stimuli.
Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely... more Brain activity data, measured by functional Magnetic Resonance Imaging (fMRI), produces extremely high dimensional, sparse and noisy signals which are difficult to visualize, monitor and analyze. The use of spatial music can be particularly appropriate to represent its contained patterns. The literature describes several research done on sonifying neuroimaging data as well as different techniques to use spatialization as a musical language. In this paper, we discuss an artistic approach to fMRI sonification exploiting new compositional paradigms in spatial music. Therefore, we consider the brain activity as audio base material of a the spatial musical composition. Our approach attempts to explore the aesthetic potential of brain sonification not by transforming the data beyond the recognizable, but presenting the data as direct as possible.