Titlebook: Brain Informatics; 15th International C Mufti Mahmud,Jing He,Ning Zhong Conference proceedings 2022 Springer Nature Switzerland AG 2022 art

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Root-Cause Analysis of?Activation Cascade Differences in?Brain Networks probably the simplest way to study the dynamics of macro-scale brain activity is to compute the “activation cascade” that follows the artificial stimulation of a source region. Such cascades can be computed using the Linear Threshold model on a weighted graph representation of the connectome. The q

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Unstructured Categorization with Probabilistic Feedback: Learning Accuracy Versus Response TimeWhen an effect is observed, the performance is better for a lower number of categories. We aimed to investigate the effect of the category number on the performance in the unstructured category learning tasks with probabilistic feedback. We conducted four experiments. The stimuli consisted of dot mo

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Optimizing Measures of?Information Encoding in?Astrocytic Calcium Signalsn-neural cells in the brain, can add information about key cognitive variables that is not found in the activity of nearby neurons. This raises the question of what could be the contribution of astrocytes in information processing, and calls for analysis tools to characterize this contribution. Here

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Introducing the Rank-Biased Overlap as Similarity Measure for Feature Importance in Explainable Mach training sets could produce different rankings of predictive features. Thus, the quantification of differences between feature importance is crucial for assessing model trustworthiness. Rank-biased Overlap (RBO) is a similarity measure between ., . and . rankings, which are all characteristics of f

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Prediction of?Neuropsychological Scores from?Functional Connectivity Matrices Using Deep Autoencoderm large-scale datasets of patient’s records. However, in many cases data scarcity has forced the adoption of simpler (linear) feature extraction methods, which are less prone to overfitting. In this work, we exploit data augmentation and transfer learning techniques to show that deep, non-linear aut

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Brain Source Reconstruction Solution Quality Assessment with?Spatial Graph Frequency Featuresreover, we found the locations of active sources also have an impact on the performance of ESI algorithms. For the real EEG/MEG source reconstruction, as the ground true activation is unknown, it is hard to validate which algorithm performs better. In this paper, we proposed to use statistical featu