Figure 4 - available via license: Creative Commons Attribution 4.0 International
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Principal components analysis of hippocampal and cortical feature vectors. Each column represents principal components analysis of the 11-dimensional feature vectors of all recordings at a given age (days in vitro). In the scatter plot, each point represents one recording projected down into the two dimensions that account for maximal variance and is coloured according to its cell type. Each graph shows the cumulative fraction of variance accounted for by the principal components.
Source publication
Background: Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or...
Context in source publication
Context 1
... such dimensionality-reduction techniques are available; we chose to use the best-known method, principal components analysis. Figure 4 shows the projection of the feature vectors at three different ages down into two-dimensional space. At 7 DIV there is significant overlap between the hippocampal and cortical recordings, which might suggest that is hard to discriminate between the two types of recordings; however at 14 and 21 DIV the recordings from the same cell type cluster and there is significant separation of the hippocampal and cortical recordings. ...
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