| 1. |
- Finkel, Sebastian, et al.
(författare)
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Intermittent theta burst stimulation over right somatosensory larynx cortex enhances vocal pitch‐regulation in nonsingers
- 2019
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193.
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Tidskriftsartikel (refereegranskat)abstract
- While the significance of auditory cortical regions for the development and maintenance of speech motor coordination is well established, the contribution of somatosensory brain areas to learned vocalizations such as singing is less well understood. To address these mechanisms, we applied intermittent theta burst stimulation (iTBS), a facilitatory repetitive transcranial magnetic stimulation (rTMS) protocol, over right somatosensory larynx cortex (S1) and a nonvocal dorsal S1 control area in participants without singing experience. A pitch‐matching singing task was performed before and after iTBS to assess corresponding effects on vocal pitch regulation. When participants could monitor auditory feedback from their own voice during singing (Experiment I), no difference in pitch‐matching performance was found between iTBS sessions. However, when auditory feedback was masked with noise (Experiment II), only larynx‐S1 iTBS enhanced pitch accuracy (50–250 ms after sound onset) and pitch stability (>250 ms after sound onset until the end). Results indicate that somatosensory feedback plays a dominant role in vocal pitch regulation when acoustic feedback is masked. The acoustic changes moreover suggest that right larynx‐S1 stimulation affected the preparation and involuntary regulation of vocal pitch accuracy, and that kinesthetic‐proprioceptive processes play a role in the voluntary control of pitch stability in nonsingers. Together, these data provide evidence for a causal involvement of right larynx‐S1 in vocal pitch regulation during singing.
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| 2. |
- Fu, Jingru, et al.
(författare)
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Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration
- 2023
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 44:4, s. 1289-1308
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Tidskriftsartikel (refereegranskat)abstract
- Predicting brain aging can help in the early detection and prognosis of neurodegenerative diseases. Longitudinal cohorts of healthy subjects scanned through magnetic resonance imaging (MRI) have been essential to understand the structural brain changes due to aging. However, these cohorts suffer from missing data due to logistic issues in the recruitment of subjects. This paper proposes a methodology for filling up missing data in longitudinal cohorts with anatomically plausible images that capture the subject-specific aging process. The proposed methodology is developed within the framework of diffeomorphic registration. First, two novel modules are introduced within Synthmorph, a fast, state-of-the-art deep learning-based diffeomorphic registration method, to simulate the aging process between the first and last available MRI scan for each subject in three-dimensional (3D). The use of image registration also makes the generated images plausible by construction. Second, we used six image similarity measurements to rearrange the generated images to the specific age range. Finally, we estimated the age of every generated image by using the assumption of linear brain decay in healthy subjects. The methodology was evaluated on 2662 T1-weighted MRI scans from 796 healthy participants from 3 different longitudinal cohorts: Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies-3, and Group of Neuropsychological Studies of the Canary Islands (GENIC). In total, we generated 7548 images to simulate the access of a scan per subject every 6 months in these cohorts. We evaluated the quality of the synthetic images using six quantitative measurements and a qualitative assessment by an experienced neuroradiologist with state-of-the-art results. The assumption of linear brain decay was accurate in these cohorts (R2 ∈ [.924,.940]). The experimental results show that the proposed methodology can produce anatomically plausible aging predictions that can be used to enhance longitudinal datasets. Compared to deep learning-based generative methods, diffeomorphic registration is more likely to preserve the anatomy of the different structures of the brain, which makes it more appropriate for its use in clinical applications. The proposed methodology is able to efficiently simulate anatomically plausible 3D MRI scans of brain aging of healthy subjects from two images scanned at two different time points.
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| 3. |
- Lindeberg, Tony, 1964-, et al.
(författare)
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Analysis of brain activation patterns using a 3-D scale-space primal sketch
- 1999
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Ingår i: Human Brain Mapping. - 1065-9471 .- 1097-0193. ; 7:3, s. 166-94
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Tidskriftsartikel (refereegranskat)abstract
- A fundamental problem in brain imaging concerns how to define functional areas consisting of neurons that are activated together as populations. We propose that this issue can be ideally addressed by a computer vision tool referred to as the scale-space primal sketch. This concept has the attractive properties that it allows for automatic and simultaneous extraction of the spatial extent and the significance of regions with locally high activity. In addition, a hierarchical nested tree structure of activated regions and subregions is obtained. The subject in this article is to show how the scale-space primal sketch can be used for automatic determination of the spatial extent and the significance of rCBF changes. Experiments show the result of applying this approach to functional PET data, including a preliminary comparison with two more traditional clustering techniques. Compared to previous approaches, the method overcomes the limitations of performing the analysis at a single scale or assuming specific models of the data.
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