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Abstract Recognizing objects is a vital skill on which humans heavily rely to respond quickly and adaptively to their environment. Yet, we lack understanding on the role that visual information sampling plays in this process, and its relation to the individual's priors. To bridge this gap, the eye-movements of 18 adult participants were recorded during a free-viewing object-recognition task using Dots stimuli (Moca et al., 2011).
Abstract While animals readily adjust their behavior to adapt to relevant changes in the environment, the neural pathways enabling these changes remain largely unknown. Here, using multiphoton imaging, we investigated whether feedback from the piriform cortex to the olfactory bulb supports such behavioral flexibility. To this end, we engaged head-fixed mice in a multimodal rule-reversal task guided by olfactory and auditory cues.
Abstract We introduce Gradient-k, an upgrade of the k-means algorithm that improves clustering accuracy and reduces the number of iterations required for convergence. This is achieved by correcting the distance used in the k-means algorithm by a factor based on the angle between the density gradient and the direction to the cluster center.
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