<p>(<i>A</i>) Predictive log-likelihood for each model, on prediction trials, relative to the stationary KF model. Larger values indicate superior performance on held-out data from prediction trials. (<i>B</i>) Predictive log-likelihood for each model, on the reconstruction data, relative to the stationary KF model. Error bars represent within-subject standard error of the mean.</p
<p>Likelihoods are normalized to bits/spike to account for different population size as well as firi...
<p>*** >0.001, NS (not significant), NE (Not estimated)</p><p>The log likelihood values are presente...
<p><b>AB</b> The log-likelihood differences between the models, using the Difference model as a base...
Comparisons of the prediction performance of Catboost model and logistic regression model.</p
<p>LL = log likelihood (higher is better). MSE = mean squared error (lower is better). The best valu...
<p>Bars indicate the prediction accuracy (mean ± SEM, N = 5) for the five models in both the 3T and ...
<p>The relative measure of model performance, i.e. the per-bin log-likelihood Δ<i>p</i> (see <a href...
Research that seeks to compare two predictive models requires a thorough statistical approach to dra...
(A) Log-likelihood ratio of model against the null random baseline model based on predicting histori...
<p>(A) Euclidean distance between participants' reconstructions and the observed (true) first and la...
<p><b>a</b>: Each column represents a subject, divided by test group (all datasets include a Gaussia...
(A) Geometric average likelihood per trial for each model (i.e., average total log likelihood divide...
A multi-level model allows the possibility of marginalization across levels in different ways, yield...
Columns show different versions of the task. Rows show model fits for (A) the distance model (unscal...
<p>(A) We compared the ‘Reward T’ model to all the other models by examining the paired differences ...
<p>Likelihoods are normalized to bits/spike to account for different population size as well as firi...
<p>*** >0.001, NS (not significant), NE (Not estimated)</p><p>The log likelihood values are presente...
<p><b>AB</b> The log-likelihood differences between the models, using the Difference model as a base...
Comparisons of the prediction performance of Catboost model and logistic regression model.</p
<p>LL = log likelihood (higher is better). MSE = mean squared error (lower is better). The best valu...
<p>Bars indicate the prediction accuracy (mean ± SEM, N = 5) for the five models in both the 3T and ...
<p>The relative measure of model performance, i.e. the per-bin log-likelihood Δ<i>p</i> (see <a href...
Research that seeks to compare two predictive models requires a thorough statistical approach to dra...
(A) Log-likelihood ratio of model against the null random baseline model based on predicting histori...
<p>(A) Euclidean distance between participants' reconstructions and the observed (true) first and la...
<p><b>a</b>: Each column represents a subject, divided by test group (all datasets include a Gaussia...
(A) Geometric average likelihood per trial for each model (i.e., average total log likelihood divide...
A multi-level model allows the possibility of marginalization across levels in different ways, yield...
Columns show different versions of the task. Rows show model fits for (A) the distance model (unscal...
<p>(A) We compared the ‘Reward T’ model to all the other models by examining the paired differences ...
<p>Likelihoods are normalized to bits/spike to account for different population size as well as firi...
<p>*** >0.001, NS (not significant), NE (Not estimated)</p><p>The log likelihood values are presente...
<p><b>AB</b> The log-likelihood differences between the models, using the Difference model as a base...