RESUMEN
Little is known about the perception of artificial spatial hearing by hearing-impaired subjects. The purpose of this study was to investigate how listeners with hearing disorders perceived the effect of a spatialization feature designed for wireless microphone systems. Forty listeners took part in the experiments. They were arranged in four groups: normal-hearing, moderate, severe, and profound hearing loss. Their performance in terms of speech understanding and speaker localization was assessed with diotic and binaural stimuli. The results of the speech intelligibility experiment revealed that the subjects presenting a moderate or severe hearing impairment better understood speech with the spatialization feature. Thus, it was demonstrated that the conventional diotic binaural summation operated by current wireless systems can be transformed to reproduce the spatial cues required to localize the speaker, without any loss of intelligibility. The speaker localization experiment showed that a majority of the hearing-impaired listeners had similar performance with natural and artificial spatial hearing, contrary to the normal-hearing listeners. This suggests that certain subjects with hearing impairment preserve their localization abilities with approximated generic head-related transfer functions in the frontal horizontal plane.
Asunto(s)
Audífonos , Pérdida Auditiva Sensorineural , Percepción del Habla , Adulto , Anciano , Audición , Pruebas Auditivas , Humanos , Persona de Mediana Edad , Ruido , Localización de Sonidos , Adulto JovenRESUMEN
Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.
Asunto(s)
Encéfalo/anatomía & histología , Conectoma , Imagen de Difusión por Resonancia Magnética/métodos , Imagen de Difusión Tensora/métodos , Fibras Nerviosas/fisiología , Vías Nerviosas , Adulto , Algoritmos , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador , Adulto JovenRESUMEN
Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.
Asunto(s)
Conectoma , Procesamiento de Imagen Asistido por Computador/métodos , Imagen por Resonancia Magnética/métodos , Algoritmos , Encéfalo/fisiología , Mapeo Encefálico/métodos , Gráficos por Computador , Computadores , Interpretación Estadística de Datos , Imagen de Difusión por Resonancia Magnética/métodos , Humanos , Internet , Modelos Estadísticos , Lenguajes de Programación , Programas Informáticos , Interfaz Usuario-ComputadorRESUMEN
The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.
Asunto(s)
Mapeo Encefálico/métodos , Imagen de Difusión Tensora/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Vías Nerviosas/citología , Adulto , Encéfalo/citología , Encéfalo/fisiología , Humanos , Masculino , Vías Nerviosas/fisiología , Adulto JovenRESUMEN
MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.
Asunto(s)
Imagen de Difusión por Resonancia Magnética/métodos , Vías Nerviosas/anatomía & histología , Animales , Encéfalo/anatomía & histología , Mapeo Encefálico , Imagen de Difusión Tensora , Humanos , Imagen por Resonancia Magnética , Red Nerviosa/anatomía & histologíaRESUMEN
BACKGROUND: Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we propose a method to estimate the respective contributions of diffusion coherence versus other effects to a tractography result by comparing data sets with and without diffusion coherence contrast. We use this methodology to assign a confidence level to every gray matter to gray matter connection and add this new information directly in the connectivity matrix. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that whereas we can have a strong confidence in mid- and long-range connections obtained by a tractography experiment, it is difficult to distinguish between short connections traced due to diffusion coherence contrast from those produced by chance due to the other uncontrolled factors of the tractography methodology.
Asunto(s)
Encéfalo/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética/métodos , Vías Nerviosas/diagnóstico por imagen , Encéfalo/anatomía & histología , Encéfalo/fisiología , Mapeo Encefálico/métodos , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Modelos Biológicos , Vías Nerviosas/anatomía & histología , Vías Nerviosas/fisiología , Radiografía , Sensibilidad y EspecificidadRESUMEN
Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.
Asunto(s)
Mapeo Encefálico , Corteza Cerebral/anatomía & histología , Corteza Cerebral/fisiología , Modelos Neurológicos , Red Nerviosa/fisiología , Adulto , Imagen de Difusión por Resonancia Magnética , Humanos , Imagenología Tridimensional , MasculinoRESUMEN
Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.