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- Benjaminsson, Simon, 1982-, et al.
(author)
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A Novel Model-Free Data Analysis Technique Based on Clustering in a Mutual Information Space : Application to Resting-State fMRI
- 2010
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In: Frontiers in Systems Neuroscience. - : Frontiers Media SA. - 1662-5137. ; 4, s. 34:1-34:8
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Journal article (peer-reviewed)abstract
- Non-parametric data-driven analysis techniques can be used to study datasets with few assumptions about the data and underlying experiment. Variations of independent component analysis (ICA) have been the methods mostly used on fMRI data, e.g., in finding resting-state networks thought to reflect the connectivity of the brain. Here we present a novel data analysis technique and demonstrate it on resting-state fMRI data. It is a generic method with few underlying assumptions about the data. The results are built from the statistical relations between all input voxels, resulting in a whole-brain analysis on a voxel level. It has good scalability properties and the parallel implementation is capable of handling large datasets and databases. From the mutual information between the activities of the voxels over time, a distance matrix is created for all voxels in the input space. Multidimensional scaling is used to put the voxels in a lower-dimensional space reflecting the dependency relations based on the distance matrix. By performing clustering in this space we can find the strong statistical regularities in the data, which for the resting-state data turns out to be the resting-state networks. The decomposition is performed in the last step of the algorithm and is computationally simple. This opens up for rapid analysis and visualization of the data on different spatial levels, as well as automatically finding a suitable number of decomposition components.
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- Benjaminsson, Simon, 1982-, et al.
(author)
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Nexa : A scalable neural simulator with integrated analysis
- 2012
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In: Network. - 0954-898X .- 1361-6536. ; 23:4, s. 254-271
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Journal article (peer-reviewed)abstract
- Large-scale neural simulations encompass challenges in simulator design, data handling and understanding of simulation output. As the computational power of supercomputers and the size of network models increase, these challenges become even more pronounced. Here we introduce the experimental scalable neural simulator Nexa, for parallel simulation of large-scale neural network models at a high level of biological abstraction and for exploration of the simulation methods involved. It includes firing-rate models and capabilities to build networks using machine learning inspired methods for e. g. self-organization of network architecture and for structural plasticity. We show scalability up to the size of the largest machines currently available for a number of model scenarios. We further demonstrate simulator integration with online analysis and real-time visualization as scalable solutions for the data handling challenges.
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- Benjaminsson, Simon, 1982-
(author)
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On large-scale neural simulations and applications in neuroinformatics
- 2013
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Doctoral thesis (other academic/artistic)abstract
- This thesis consists of three parts related to the in silico study of the brain: technologies for large-scale neural simulations, neural algorithms and models and applications in large-scale data analysis in neuroinformatics. All parts rely on the use of supercomputers.A large-scale neural simulator is developed where techniques are explored for the simulation, analysis and visualization of neural systems on a high biological abstraction level. The performance of the simulator is investigated on some of the largest supercomputers available.Neural algorithms and models on a high biological abstraction level are presented and simulated. Firstly, an algorithm for structural plasticity is suggested which can set up connectivity and response properties of neural units from the statistics of the incoming sensory data. This can be used to construct biologically inspired hierarchical sensory pathways. Secondly, a model of the mammalian olfactory system is presented where we suggest a mechanism for mixture segmentation based on adaptation in the olfactory cortex. Thirdly, a hierarchical model is presented which uses top-down activity to shape sensory representations and which can encode temporal history in the spatial representations of populations.Brain-inspired algorithms and methods are applied to two neuroinformatics applications involving large-scale data analysis. In the first application, we present a way to extract resting-state networks from functional magnetic resonance imaging (fMRI) resting-state data where the final extraction step is computationally inexpensive, allowing for rapid exploration of the statistics in large datasets and their visualization on different spatial scales. In the second application, a method to estimate the radioactivity level in arterial plasma from segmented blood vessels from positron emission tomography (PET) images is presented. The method outperforms previously reported methods to a degree where it can partly remove the need for invasive arterial cannulation and continuous sampling of arterial blood during PET imaging.In conclusion, this thesis provides insights into technologies for the simulation of large-scale neural models on supercomputers, their use to study mechanisms for the formation of neural representations and functions in hierarchical sensory pathways using models on a high biological abstraction level and the use of large-scale, fine-grained data analysis in neuroinformatics applications.
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| 6. |
- Hrastinski, Stefan, 1980-, et al.
(author)
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Identifying and exploring the effects of different types of tutor questions in individual online synchronous tutoring in mathematics
- 2019
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In: Interactive Learning Environments. - : Informa UK Limited. - 1049-4820 .- 1744-5191. ; , s. 1-13
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Journal article (peer-reviewed)abstract
- Although we know that asking questions is an essential aspect of onlinetutoring, there is limited research on this topic. The aim of this paperwas to identify commonly used direct question types and explore theeffects of using these question types on conversation intensity, approachto tutoring, perceived satisfaction and perceived learning. The researchsetting was individual online synchronous tutoring in mathematics. Theempirical data was based on 13,317 logged conversations and aquestionnaire. The tutors used a mix of open, more student-centredquestions, and closed, more teacher-centred questions. In contrast toprevious research, this study provides a more positive account indicatingthat it is indeed possible to train tutors to focus on asking questions,rather than delivering content. Frequent use of many of the questiontypes contributed to increased conversation intensity. However, therewere few question types that were associated with statisticallysignificant effects on perceived satisfaction or learning. There are nosilver bullet question types that by themselves led to positive effects onperceived satisfaction and learning. The question types could be used byteachers and teacher students when reflecting on what types ofquestions they are asking, and what kind of questions they could be asking.
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| 8. |
- Schain, Martin, et al.
(author)
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Arterial input function derived from pairwise correlations between PET-image voxels
- 2013
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In: Journal of Cerebral Blood Flow and Metabolism. - : Nature Publishing Group. - 0271-678X .- 1559-7016. ; 33:7, s. 1058-1065
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Journal article (peer-reviewed)abstract
- A metabolite corrected arterial input function is a prerequisite for quantification of positron emission tomography (PET) data by compartmental analysis. This quantitative approach is also necessary for radioligands without suitable reference regions in brain. The measurement is laborious and requires cannulation of a peripheral artery, a procedure that can be associated with patient discomfort and potential adverse events. A non invasive procedure for obtaining the arterial input function is thus preferable. In this study, we present a novel method to obtain image-derived input functions (IDIFs). The method is based on calculation of the Pearson correlation coefficient between the time-activity curves of voxel pairs in the PET image to localize voxels displaying blood-like behavior. The method was evaluated using data obtained in human studies with the radioligands [11C]flumazenil and [11C]AZ10419369, and its performance was compared with three previously published methods. The distribution volumes (VT) obtained using IDIFs were compared with those obtained using traditional arterial measurements. Overall, the agreement in VT was good (~3% difference) for input functions obtained using the pairwise correlation approach. This approach performed similarly or even better than the other methods, and could be considered in applied clinical studies. Applications to other radioligands are needed for further verification.
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- Stenbom, Stefan, 1982-, et al.
(author)
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Digital badges for in-service training of online tutors
- 2016
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Conference paper (peer-reviewed)abstract
- In this presentation, an application where digital badges are used for continuing training of online tutors is reviewed. First, we present how digital badges are used in a math tutoring service for K–12 students. Then, we discuss benefits and challenges of digital badges for development of in-service online tutors.
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