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This is illustrated in Fig. 12 bottom, in which the responses of a view-tuned neuron (selected as the neuron with most selectivity between faces, and a response to exemplar 1 of one of the non-scrambled faces) were with similarly high firing rates to the scrambled versions of the same set of exemplars.
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We reconstruct the evolution of the subfamily Formicinae based upon a next-generation, pan-genomic data set of UCEs, and provide a direct comparison of this targeted-enrichment phylogenomic approach to a much smaller traditional phylogenetic data set assembled by Sanger-sequencing methods using the same set of 82 exemplar species.
The procedure was to train on the set of unscrambled faces and then to test how the neurons that responded best to each face then responded when the scrambled versions of the faces were shown, using randomly scrambled versions of the same eight faces each with the same set of 5 view exemplars.
There were also two control groups who made either recognition or categorization decisions about the same sets of items but who saw no exemplars in the study period.
An ID shift (IDS) occurs when a subject trained to respond to a particular stimulus dimension, such as colour or shape, is required to transfer that rule to a novel set of exemplars of that same stimulus dimension.
When using LDA-transformed concatenated features, a new equally large set of exemplars was created by selecting sequences of 29 consecutive frames, using the same procedures as for selecting single-frame exemplars.
Such judgments will typically be based on comparison with selected features of a limited set of exemplars.
The potential downside of relying on a single set of exemplars to estimate state probabilities is that it may yield overly sparse state probability vectors.
In the experimental design, we used a small set of exemplars, which were presented repeatedly throughout a session.
Real-valued messages are exchanged between data points until a high-quality set of exemplars and corresponding clusters gradually emerges.
For the testing (untrained, cross validation) set of exemplars, one of the neurons responded with a high rate to 8 of the 10 untrained exemplars of one class (hats) and to 1 of the exemplars of the other class (beer mugs).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com