Suggestions(2)
Exact(2)
Especially, subjects take roughly double the number of trials for learning the random mapping compared to an ideal learner (compare Fig. 6. lower panels).
Animals were considered visually impaired if they failed to find the platform within the allotted 60 s on 2 out of 3 trials on day 1 (cue learning), and on 3 out of 3 trials for learning days 3 and 4. Using this criterion, 6 aged animals, 3 AC and 3 AP, were excluded from the behavioral analysis.
Similar(58)
Although this model does not require trial-by-trial feedback for learning to occur, it precludes learning when the internal and external feedback are uncorrelated because changes to weights cancel out over time due to the randomness of the feedback evaluation that results.
We also computed for each subject the ratio between the trials required for learning the random mapping and the trials required for learning the first shift and the first mirror mapping (Figure 3A).
This study aimed to investigate whether, from the application of the teaching procedure used by Langsdorff et al. (2015) with participants with autism and Down syndrome and different educational histories, it would be possible to establish a mean number of exclusion trials necessary for learning these relations.
Consistent with performances observed in spatial learning during spaced or massed training [35], we found that less trials were required for learning acquisition during a spaced versus a massed paradigm.
She is a Faculty Affiliate of the Jameel Poverty Action Lab at MIT, dedicated to the use of randomized trials as a tool for learning what works in international development, and a Fellow of the National Bureau of Economic Research.
The pink shading shows the analysis interval for trial-over-trial learning.
We used generalized linear mixed models (GLMMs) with dog identity included as a random effect to test for differences between conditions or sessions and for learning across trials (using R package lme4, Bates et al. 2012).
There was some evidence for learning across trials, reflected in a significant condition-by-trial interaction (GLMM with likelihood ratio test: χ(3)2 = 11.2, p = 0.01).
When learning was not observed, the aim was to quantify the number of exclusion trial repetitions that were necessary for learning to occur.
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