Dataset Information

Effect of Attentional Bias on the 3D Rotated Objects Recognition Ability of Dogs.

ABSTRACT: The ability to recognize rotated objects has been widely reported in the animal kingdom. Studies on animal and human spatial cognition highlighted the importance of visuo-spatial cognitive capability for surviving in a dynamic world. Although domestic animals are frequently involved in activities requiring a high level of visuo-spatial ability, currently, little is known about their visuo-spatial skills. To investigate this issue, we trained six dogs to discriminate between 3D objects (using a modified version of the Shepard-Metzler task) that were then reproduced digitally on a computer. We found that the dogs recognized three-dimensional objects and their rotated versions (45° and 180°) more easily when presented on the left side of the screen, suggesting right hemisphere superiority in the control of visuo-spatial functions. Moreover, we report inter-individual variability in their performance in the visuo-spatial task. Our preliminary results suggest that dogs could use a rotational invariance process for the discrimination of 3D rotated shapes that deserves further investigation.

SUBMITTER: Siniscalchi M

PROVIDER: S-EPMC10215826 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effect of Attentional Bias on the 3D Rotated Objects Recognition Ability of Dogs.

Siniscalchi Marcello M d'Ingeo Serenella S Quaranta Angelo A

Animals : an open access journal from MDPI 20230517 10

The ability to recognize rotated objects has been widely reported in the animal kingdom. Studies on animal and human spatial cognition highlighted the importance of visuo-spatial cognitive capability for surviving in a dynamic world. Although domestic animals are frequently involved in activities requiring a high level of visuo-spatial ability, currently, little is known about their visuo-spatial skills. To investigate this issue, we trained six dogs to discriminate between 3D objects (using a m ...[more]

PMID: 37238104

Similar Datasets

Project description:We propose a brain inspired attentional search model for target search in a 3D environment, which has two separate channels—one for the object classification, analogous to the “what” pathway in the human visual system, and the other for prediction of the next location of the camera, analogous to the “where” pathway. To evaluate the proposed model, we generated 3D Cluttered Cube datasets that consist of an image on one vertical face, and clutter or background images on the other faces. The camera goes around each cube on a circular orbit and determines the identity of the image pasted on the face. The images pasted on the cube faces were drawn from: MNIST handwriting digit, QuickDraw, and RGB MNIST handwriting digit datasets. The attentional input of three concentric cropped windows resembling the high-resolution central fovea and low-resolution periphery of the retina, flows through a Classifier Network and a Camera Motion Network. The Classifier Network classifies the current view into one of the target classes or the clutter. The Camera Motion Network predicts the camera's next position on the orbit (varying the azimuthal angle or “θ”). Here the camera performs one of three actions: move right, move left, or do not move. The Camera-Position Network adds the camera's current position (θ) into the higher features level of the Classifier Network and the Camera Motion Network. The Camera Motion Network is trained using Q-learning where the reward is 1 if the classifier network gives the correct classification, otherwise 0. Total loss is computed by adding the mean square loss of temporal difference and cross entropy loss. Then the model is trained end-to-end by backpropagating the total loss using Adam optimizer. Results on two grayscale image datasets and one RGB image dataset show that the proposed model is successfully able to discover the desired search pattern to find the target face on the cube, and also classify the target face accurately.

Dataset Information

Effect of Attentional Bias on the 3D Rotated Objects Recognition Ability of Dogs.

Publications

Effect of Attentional Bias on the 3D Rotated Objects Recognition Ability of Dogs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets