Mouse characteristics in early training stage.

<p>Mouse characteristics in early training stage.</p

Misclassification matrix in 6-class model.

<p>Misclassification matrix in 6-class model.</p

Misclassification matrix in 6-class model.

<p>Misclassification matrix in 6-class model.</p

Model performance according to the picture sizes.

<p>Model performance according to the picture sizes.</p

Mouse characteristics in early training stage.

<p>Mouse characteristics in early training stage.</p

Representative trajectories in swim path classification and converted images.

<p>Swim path trajectories were classified into the following six classes: A) Thigmotaxis, B) Rotating, C) Focal search, D) Scanning, E) Circling, and F) Direct swim. Class labeling was conducted by a human researcher before use in the neural network model. Converted grayscale images are shown just below the original images.</p

Schema of convolutional neural network model for 48x48.

<p>The two left layers are for the convolution process and the two right layers are for linear connections. Values in parentheses are input and output data size in each layer. ReLU: rectified linear unit.</p

Transition of cognitive scores and its relation to the early stage swim strategy.

<p>Average cognitive score increased as the training proceeds in both control and BCAS groups (A). The existence of thigmotaxis in early training stage significantly affected the cognitive score in day 5 (B). *p<0.05 vs control group.</p

Mouse characteristics in late training stage.

<p>Mouse characteristics in late training stage.</p

Accuracy, sensitivity and specificity of recognition model.

<p>Accuracy, sensitivity and specificity of recognition model.</p