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- Bakken, TE, et al.
(författare)
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Comparative cellular analysis of motor cortex in human, marmoset and mouse
- 2021
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 598:7879, s. 111-
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Tidskriftsartikel (refereegranskat)abstract
- The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.
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- Scheuermann, F., et al.
(författare)
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Designing collaborative activities in virtual environments for learning
- 2004
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Ingår i: Proc. Fifth Int. Conf. Inf. Technol. Based High. Educ. Train. ITHET. - 0780385969 ; , s. 641-643
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Konferensbidrag (refereegranskat)abstract
- This paper demonstrates the connection between organisation, collaboration and learning in virtual learning environments (VLEs). Our main focus is the investigation of the extent to which course developers and course instructors need to consider organisational measures and design in order to trigger (self-guided) learning and collaboration of participants within online learning environments. The design of these virtual learning environments involves an intricate balance between the following elements: the organisation of the content; how the instructional activities are sequenced; how the interactions between students, tasks, and materials are structured; and how the learning process is evaluated. Mentorship must be present throughout this process. Aspects of mentorship can manifest themselves in a variety of ways including: asking an expert, true mentoring, tutoring, and peer to peer support.
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- Conroy, Melanie, et al.
(författare)
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Uncertainty in humanities network visualization
- 2024
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Ingår i: Frontiers in Communication. - : Frontiers Media S.A.. - 2297-900X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Network visualization is one of the most widely used tools in digital humanities research. The idea of uncertain or “fuzzy” data is also a core notion in digital humanities research. Yet network visualizations in digital humanities do not always prominently represent uncertainty. In this article, we present a mathematical and logical model of uncertainty as a range of values which can be used in network visualizations. We review some of the principles for visualizing uncertainty of different kinds, visual variables that can be used for representing uncertainty, and how these variables have been used to represent different data types in visualizations drawn from a range of non-humanities fields like climate science and bioinformatics. We then provide examples of two diagrams: one in which the variables displaying degrees of uncertainty are integrated into the graph and one in which glyphs are added to represent data certainty and uncertainty. Finally, we discuss how probabilistic data and what-if scenarios could be used to expand the representation of uncertainty in humanities network visualizations.
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