The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Monica Gori - One of the best experts on this subject based on the ideXlab platform.
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Spatial Localization of sound elicits early responses from occipital visual cortex in humans
Scientific Reports, 2017Co-Authors: Claudio Campus, Giulio Sandini, Maria Concetta Morrone, Monica GoriAbstract:Much evidence points to an interaction between vision and audition at early cortical sites. However, the functional role of these interactions is not yet understood. Here we show an early response of the occipital cortex to sound that it is strongly linked to the Spatial Localization task performed by the observer. The early occipital response to a sound, usually absent, increased by more than 10-fold when presented during a space Localization task, but not during a time Localization task. The response amplification was not only specific to the task, but surprisingly also to the position of the stimulus in the two hemifields. We suggest that early occipital processing of sound is linked to the construction of an audio Spatial map that may utilize the visual map of the occipital cortex.
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Auditory Spatial Localization: Developmental delay in children with visual impairments.
Research in developmental disabilities, 2016Co-Authors: Giulia Cappagli, Monica GoriAbstract:For individuals with visual impairments, auditory Spatial Localization is one of the most important features to navigate in the environment. Many works suggest that blind adults show similar or even enhanced performance for Localization of auditory cues compared to sighted adults (Collignon, Voss, Lassonde, & Lepore, 2009). To date, the investigation of auditory Spatial Localization in children with visual impairments has provided contrasting results. Here we report, for the first time, that contrary to visually impaired adults, children with low vision or total blindness show a significant impairment in the Localization of static sounds. These results suggest that simple auditory Spatial tasks are compromised in children, and that this capacity recovers over time.
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enhanced auditory Spatial Localization in blind echolocators
Neuropsychologia, 2015Co-Authors: Tiziana Vercillo, Monica Gori, Jennifer L Milne, Melvyn A GoodaleAbstract:Echolocation is the extraordinary ability to represent the external environment by using reflected sound waves from self-generated auditory pulses. Blind human expert echolocators show extremely precise Spatial acuity and high accuracy in determining the shape and motion of objects by using echoes. In the current study, we investigated whether or not the use of echolocation would improve the representation of auditory space, which is severely compromised in congenitally blind individuals (Gori et al., 2014). The performance of three blind expert echolocators was compared to that of 6 blind non-echolocators and 11 sighted participants. Two tasks were performed: (1) a space bisection task in which participants judged whether the second of a sequence of three sounds was closer in space to the first or the third sound and (2) a minimum audible angle task in which participants reported which of two sounds presented successively was located more to the right. The blind non-echolocating group showed a severe impairment only in the space bisection task compared to the sighted group. Remarkably, the three blind expert echolocators performed both Spatial tasks with similar or even better precision and accuracy than the sighted group. These results suggest that echolocation may improve the general sense of auditory space, most likely through a process of sensory calibration.
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Impairment of auditory Spatial Localization in congenitally blind human subjects.
Brain : a journal of neurology, 2013Co-Authors: Monica Gori, Cristina Martinoli, Giulio Sandini, David C BurrAbstract:Several studies have demonstrated enhanced auditory processing in the blind, suggesting that they compensate their visual impairment in part with greater sensitivity of the other senses. However, several physiological studies show that early visual deprivation can impact negatively on auditory Spatial Localization. Here we report for the first time severely impaired auditory Localization in the congenitally blind: thresholds for Spatially bisecting three consecutive, Spatially-distributed sound sources were seriously compromised, on average 4.2-fold typical thresholds, and half performing at random. In agreement with previous studies, these subjects showed no deficits on simpler auditory Spatial tasks or with auditory temporal bisection, suggesting that the encoding of Euclidean auditory relationships is specifically compromised in the congenitally blind. It points to the importance of visual experience in the construction and calibration of auditory Spatial maps, with implications for rehabilitation strategies for the congenitally blind.
Matthew F. Glasser - One of the best experts on this subject based on the ideXlab platform.
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The impact of traditional neuroimaging methods on the Spatial Localization of cortical areas
Proceedings of the National Academy of Sciences of the United States of America, 2018Co-Authors: Timothy S. Coalson, David C. Van Essen, Matthew F. GlasserAbstract:Localizing human brain functions is a long-standing goal in systems neuroscience. Toward this goal, neuroimaging studies have traditionally used volume-based smoothing, registered data to volume-based standard spaces, and reported results relative to volume-based parcellations. A novel 360-area surface-based cortical parcellation was recently generated using multimodal data from the Human Connectome Project, and a volume-based version of this parcellation has frequently been requested for use with traditional volume-based analyses. However, given the major methodological differences between traditional volumetric and Human Connectome Project-style processing, the utility and interpretability of such an altered parcellation must first be established. By starting from automatically generated individual-subject parcellations and processing them with different methodological approaches, we show that traditional processing steps, especially volume-based smoothing and registration, substantially degrade cortical area Localization compared with surface-based approaches. We also show that surface-based registration using features closely tied to cortical areas, rather than to folding patterns alone, improves the alignment of areas, and that the benefits of high-resolution acquisitions are largely unexploited by traditional volume-based methods. Quantitatively, we show that the most common version of the traditional approach has Spatial Localization that is only 35% as good as the best surface-based method as assessed using two objective measures (peak areal probabilities and “captured area fraction” for maximum probability maps). Finally, we demonstrate that substantial challenges exist when attempting to accurately represent volume-based group analysis results on the surface, which has important implications for the interpretability of studies, both past and future, that use these volume-based methods.
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Lost in Space: The Impact of Traditional Neuroimaging Methods on the Spatial Localization of Cortical Areas
2018Co-Authors: Timothy S. Coalson, David C. Van Essen, Matthew F. GlasserAbstract:Localizing human brain functions is a long-standing goal in systems neuroscience. Towards this goal, neuroimaging studies have traditionally used volume-based smoothing, registration to volume-based standard spaces, and have reported results relative to volume-based parcellations. A novel 360-area surface-based cortical parcellation was recently generated using multimodal data from the Human Connectome Project (HCP), and a volume-based version of this parcellation has been frequently requested for use with traditional volume-based analyses. However, given the major methodological differences between traditional volumetric and HCP-style processing, the utility and interpretability of such a parcellation must first be established. By starting from automatically generated individual-subject parcellations and processing them with different methodological approaches, we show that traditional processing steps, especially volume-based smoothing and registration, substantially degrade cortical area Localization when compared to surface-based approaches. We also show that surface-based registration using features closely tied to cortical areas, rather than to folding patterns, improves the alignment of areas, and that the benefits of high resolution acquisitions are largely unexploited by traditional volume-based methods. Quantitatively, we show that the most common version of the traditional approach has Spatial Localization that is only 35% as good as the best surface-based method as assessed with two objective measures (peak areal probabilities and 9captured area fraction9 for maximum probability maps). Finally, we demonstrate that substantial challenges exist when attempting to accurately represent volume-based group analysis results on the surface, which has important implications for the interpretability of studies that use these volume-based methods, both past and future.
Christine Dickinson - One of the best experts on this subject based on the ideXlab platform.
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Spatial Localization in visual impairment.
Investigative ophthalmology & visual science, 2006Co-Authors: Ahalya Subramanian, Christine DickinsonAbstract:PURPOSE: To investigate self-reported difficulties experienced by visually impaired subjects in real-world tasks requiring judgment of space and distance and to determine whether laboratory measures of Spatial Localization predict self-reported difficulty with Spatial tasks better than traditional measures of visual function, such as visual acuity and contrast sensitivity. METHODS: Forty-two subjects with visual impairment participated. The Spatial Localization Questionnaire (SLQ) was developed to investigate self-reported Spatial Localization difficulties, and subjects answered the questionnaire as part of the study. Subjects also completed a variety of clinical vision tests (visual acuity, contrast sensitivity, stereo acuity, and reading speed) and laboratory vision tests (vernier acuity, bisection acuity, and visual direction). RESULTS: The SLQ was found to have good validity. Several significant correlations were found between the Rasch analysis ability scores for the questionnaire and the clinical and laboratory vision tests. Using stepwise regression analysis, we found that vernier acuity and contrast sensitivity accounted for 42% of the variance in the Rasch scores (P < 0.001). CONCLUSIONS: The findings indicate that certain subjects with visual impairment have difficulty with real-world Spatial tasks, as indicated by the SLQ. Of note, these difficulties were better predicted by vernier acuity (a resolution test) and contrast sensitivity, rather than vernier or bisection bias, which measure Localization.
Martin Charron - One of the best experts on this subject based on the ideXlab platform.
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spectral and Spatial Localization of background error correlations for data assimilation
Quarterly Journal of the Royal Meteorological Society, 2007Co-Authors: Mark Buehner, Martin CharronAbstract:In this study, the Localization of background-error correlations in both the spectral and the Spatial domains is examined. While Spatial Localization has become a standard approach for reducing the sampling error of background-error correlations, Localization of spectral correlations has not yet been fully explored. It is shown that spectral Localization results in a Spatial smoothing of the correlation functions in grid-point space. The use of correlations that are diagonal in spectral space, resulting in globally homogeneous correlations, has been frequently employed with data assimilation applications for numerical weather prediction (NWP). More recently, correlations that are diagonal in the space defined by an expansion of wavelet functions have been used to implicitly localize the correlations in a particular way in both spectral and grid-point spaces simultaneously. In this study, the explicit Localization of correlations by varying amounts in both the Spatial and the spectral domains is applied, to evaluate their complementary ability to reduce sampling error. Spectral and Spatial Localization are first applied to an idealized one-dimensional problem where the true correlations are known. In this context it is found that there is an optimal combination of spectral and Spatial Localization that minimizes the sampling error for a given ensemble of error realizations. Then the implementation of spectral Localization is demonstrated in both a realistic three-dimensional variational assimilation system for NWP and an ensemble-based data assimilation system applied to an idealized model of the atmosphere's mesoscale dynamics. Two very different practical approaches are used to implement spectral Localization for these two types of data assimilation systems. For the application to the ensemble-based data assimilation system, spectral Localization is shown to systematically reduce analysis error without requiring additional model forecasts to be performed. Copyright © 2007 Crown in the right of Canada. Published by John Wiley & Sons, Ltd
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Spectral and Spatial Localization of background‐error correlations for data assimilation
Quarterly Journal of the Royal Meteorological Society, 2007Co-Authors: Mark Buehner, Martin CharronAbstract:In this study, the Localization of background-error correlations in both the spectral and the Spatial domains is examined. While Spatial Localization has become a standard approach for reducing the sampling error of background-error correlations, Localization of spectral correlations has not yet been fully explored. It is shown that spectral Localization results in a Spatial smoothing of the correlation functions in grid-point space. The use of correlations that are diagonal in spectral space, resulting in globally homogeneous correlations, has been frequently employed with data assimilation applications for numerical weather prediction (NWP). More recently, correlations that are diagonal in the space defined by an expansion of wavelet functions have been used to implicitly localize the correlations in a particular way in both spectral and grid-point spaces simultaneously. In this study, the explicit Localization of correlations by varying amounts in both the Spatial and the spectral domains is applied, to evaluate their complementary ability to reduce sampling error. Spectral and Spatial Localization are first applied to an idealized one-dimensional problem where the true correlations are known. In this context it is found that there is an optimal combination of spectral and Spatial Localization that minimizes the sampling error for a given ensemble of error realizations. Then the implementation of spectral Localization is demonstrated in both a realistic three-dimensional variational assimilation system for NWP and an ensemble-based data assimilation system applied to an idealized model of the atmosphere's mesoscale dynamics. Two very different practical approaches are used to implement spectral Localization for these two types of data assimilation systems. For the application to the ensemble-based data assimilation system, spectral Localization is shown to systematically reduce analysis error without requiring additional model forecasts to be performed. Copyright © 2007 Crown in the right of Canada. Published by John Wiley & Sons, Ltd
Timothy S. Coalson - One of the best experts on this subject based on the ideXlab platform.
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The impact of traditional neuroimaging methods on the Spatial Localization of cortical areas
Proceedings of the National Academy of Sciences of the United States of America, 2018Co-Authors: Timothy S. Coalson, David C. Van Essen, Matthew F. GlasserAbstract:Localizing human brain functions is a long-standing goal in systems neuroscience. Toward this goal, neuroimaging studies have traditionally used volume-based smoothing, registered data to volume-based standard spaces, and reported results relative to volume-based parcellations. A novel 360-area surface-based cortical parcellation was recently generated using multimodal data from the Human Connectome Project, and a volume-based version of this parcellation has frequently been requested for use with traditional volume-based analyses. However, given the major methodological differences between traditional volumetric and Human Connectome Project-style processing, the utility and interpretability of such an altered parcellation must first be established. By starting from automatically generated individual-subject parcellations and processing them with different methodological approaches, we show that traditional processing steps, especially volume-based smoothing and registration, substantially degrade cortical area Localization compared with surface-based approaches. We also show that surface-based registration using features closely tied to cortical areas, rather than to folding patterns alone, improves the alignment of areas, and that the benefits of high-resolution acquisitions are largely unexploited by traditional volume-based methods. Quantitatively, we show that the most common version of the traditional approach has Spatial Localization that is only 35% as good as the best surface-based method as assessed using two objective measures (peak areal probabilities and “captured area fraction” for maximum probability maps). Finally, we demonstrate that substantial challenges exist when attempting to accurately represent volume-based group analysis results on the surface, which has important implications for the interpretability of studies, both past and future, that use these volume-based methods.
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Lost in Space: The Impact of Traditional Neuroimaging Methods on the Spatial Localization of Cortical Areas
2018Co-Authors: Timothy S. Coalson, David C. Van Essen, Matthew F. GlasserAbstract:Localizing human brain functions is a long-standing goal in systems neuroscience. Towards this goal, neuroimaging studies have traditionally used volume-based smoothing, registration to volume-based standard spaces, and have reported results relative to volume-based parcellations. A novel 360-area surface-based cortical parcellation was recently generated using multimodal data from the Human Connectome Project (HCP), and a volume-based version of this parcellation has been frequently requested for use with traditional volume-based analyses. However, given the major methodological differences between traditional volumetric and HCP-style processing, the utility and interpretability of such a parcellation must first be established. By starting from automatically generated individual-subject parcellations and processing them with different methodological approaches, we show that traditional processing steps, especially volume-based smoothing and registration, substantially degrade cortical area Localization when compared to surface-based approaches. We also show that surface-based registration using features closely tied to cortical areas, rather than to folding patterns, improves the alignment of areas, and that the benefits of high resolution acquisitions are largely unexploited by traditional volume-based methods. Quantitatively, we show that the most common version of the traditional approach has Spatial Localization that is only 35% as good as the best surface-based method as assessed with two objective measures (peak areal probabilities and 9captured area fraction9 for maximum probability maps). Finally, we demonstrate that substantial challenges exist when attempting to accurately represent volume-based group analysis results on the surface, which has important implications for the interpretability of studies that use these volume-based methods, both past and future.