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Monitoring morphometric drift in lifelong learning segmentation of the spinal cord
No full textMorphometric measures derived from spinal cord segmentations can serve as diagnostic and prognostic biomarkers in neurological diseases and injuries affecting the spinal cord. For instance, the spinal cord cross-sectional area can be used to monitor cord atrophy in multiple sclerosis and to characterize compression in degenerative cervical myelopathy. While robust, automatic segmentation methods to a wide variety of contrasts and pathologies have been developed over the past few years, whether their predictions are stable as the model is updated using new datasets has not been assessed. This is particularly important for deriving normative values from healthy participants. In this study, we present a spinal cord segmentation model trained on a multisite (n = 75 sites, 1,631 participants) dataset, including 9 different MRI contrasts and several spinal cord pathologies. We also introduce a lifelong learning framework to automatically monitor the morphometric drift as the model is updated using additional datasets. The framework is triggered by an automatic GitHub Actions workflow every time a new model is created, recording the morphometric values derived from the model's predictions over time. As a real-world application of the proposed framework, we employed the spinal cord segmentation model to update a recently introduced normative database of healthy participants containing commonly used measures of spinal cord morphometry. Results showed that (i) our model performs well compared with its previous versions and existing pathology-specific models on the lumbar spinal cord, images with severe compression, and in the presence of intramedullary lesions and/or atrophy achieving an average Dice score of 0.95 ± 0.03; (ii) the automatic workflow for monitoring morphometric drift provides a quick feedback loop for developing future segmentation models; and (iii) the scaling factor required to update the database of morphometric measures is nearly constant among slices across the given vertebral levels, showing minimum drift between the current and previous versions of the model monitored by the framework. The code and model are open source and accessible via Spinal Cord Toolbox v7.0
Iconicity in the evolution of language: Computational models and laboratory experiments
No full textThe emergence of human language is a complex process, and to investigate the role of iconicity in this, researchers have combined insights from computational models with empirical observations from laboratory experiments. This chapter provides an overview of the most important insights on the interaction between iconicity and other linguistic properties such as combinatoriality and systematicity. In the experimental and computational work reported, it is shown how iconicity can affect the way in which emerging languages are learned and used. The chapter also discusses how computational methods can help to better understand the gradient and subjective nature of iconicity
NASA Global Fire Map
No full textABSTRACT OF THE BOOKThroughout the history of the Americas, sentiments toward the environment have been problematized and aestheticized through visual representations in various formats. In this volume of the Handbook »The Anthropocene as Multiple Crisis«, sixty entries examine the crises of mining, energy, land use, biodiversity, water, and climate change in the major macro-regions of Latin America from the colonial period to the contemporary era of the Anthropocene, featuring iconic images from this context
Hemispheric transfer and dyslexia: Testing the deficit hypothesis for word and symmetry recognition using visual half-field tasks
No full textBackground: The interhemispheric transfer deficit theory proposes that individuals with dyslexia have impaired interhemispheric transfer, particularly affecting the integration of visual information from the left and right visual fields. This study aimed to evaluate this hypothesis by examining interhemispheric transfer in dyslexia using visual half-field tasks targeting both linguistic and visuospatial processing.Methods: We examined interhemispheric transfer in dyslexia using two visual half-field tasks: a lexical decision task to assess written word processing, and a symmetry decision task to examine visuospatial processing. We compared reaction times and accuracy in 90 Dutch-speaking participants (45 with dyslexia, 45 controls) across left, right, and bilateral stimulus presentations.Results: While both tasks successfully captured expected visual half-field differences in the control group, favoring the right visual field in the lexical decision task and the left visual field in the symmetry detection task, we did not observe that the dyslexia group showed increased differences between the two fields, as predicted by the interhemispheric transfer deficit theory. Furthermore, the dyslexia group benefited just as much as controls from stimuli presented simultaneously to both visual fields. Thus, no evidence of interhemispheric transfer deficits related to dyslexia was found in either task.Conclusions: These findings challenge the broad applicability of the interhemispheric transfer deficit theory in dyslexia, suggesting that such impairments may be task-dependent rather than domain-general. Future studies should further explore the conditions under which interhemispheric transfer deficits might occur in dyslexia
Disadvantaged yet optimistic: Migrants’ paradoxical perceptions of meritocracy and equality of opportunity
No full textInfluential drivers in the occupancy and activity of the last megaherbivore from the Northwestern Andean cloud forest of Colombia
No full textLongitudinal whole-human-brain quantitative MRI study on autolysis, fixation, rehydration, and shrinkage effects
No full textPost mortem MRI studies of formalin-fixed brain tissue are essential for linking in vivo MRI contrast to underlying microstructure measured with ex vivo histology, yet formalin not only preserves tissue but also systematically alters MRI-relevant physical properties. To systematically quantify and model these effects, we longitudinally characterized multi-parametric mapping (MPM) measures - longitudinal (R1) and effective transverse (R2*) relaxation rates, proton density proxy (NA), and magnetization transfer saturation ratio (MTsat) - across the different post mortem processes, i.e. autolysis, fixation, and hydration. Five whole-human brains were scanned longitudinally during fixation (and in situ-after rehydration, when available), and compared with an independent in vivo cohort of 25 younger healthy participants. Each MPM parameter followed a distinct trajectory across different post mortem processes. The largest changes were found for R1 during fixation relative to in situ values (more than 250%), followed by R2* with an almost 60% increase, and MTsat with a 26% reduction from in vivo to in situ. NA showed no detectable change during fixation. We developed models describing fixation-induced changes and tissue shrinkage. The R1 changes and tissue shrinkage were closely aligned, reflecting a likely common mechanism. MTsat largely preserved tissue contrast during fixation and rehydration, supporting its use for spatial alignment between in vivo MRI, fixed-tissue MRI, and histology. With our quantitative assessment of post mortem process-dependent changes we provide a unique resource for future studies to better link in vivo to fixed post mortem MRI data and thereby bridge the gap to ex vivo histology
Chronometric interleaved TMS-fMRI shows state-dependent network effects underlying speech production
No full textIntroduction: Speech production engages a distributed network of cortical regions, but the causal dynamics within this system remain incompletely understood. Transcranial magnetic stimulation (TMS) offers a unique opportunity to modulate brain activity and assess functional contributions to behavior. However, the temporal specificity of these effects and how stimulation timing during speech impacts behavior and neural activity remains unclear.Materials and methods: We developed a novel chronometric interleaved TMS-fMRI paradigm to deliver TMS during an overt object naming task while simultaneously recording whole-brain BOLD responses. Stimulation was applied to the left superior temporal gyrus (STG) at two task-relevant stages: during early conceptual processing and during subsequent linguistic processing. Task-related BOLD activation patterns were analyzed across conditions.Results: TMS delivered during linguistic processing consistently induced speech arrest outside of the scanner environment and was associated with increased activation in key language areas, including the inferior frontal gyrus (IFG) and STG. In contrast, stimulation during early conceptual processing had minimal effects on neural activation. These findings suggest that stimulation-induced disruption of speech is mediated by task-state-dependent overactivation rather than suppression.Conclusion: Our results challenge the classic "virtual lesion" view of TMS by demonstrating that stimulation can amplify neural activity in a state-dependent manner. This work establishes a novel methodological framework for temporally precise causal mapping of speech networks and emphasizes the critical role of cognitive state in shaping brain responses to stimulation