Biology subjects

Nishimaru, H.

Publications and source records attributed to Nishimaru, H..

2 recordsLinked to original sources

bioRxiv2020

Reward-associated configural cues elicit theta oscillations of rat retrosplenial neurons phase-locked to LFP theta cycle

Previous behavioral studies implicated the retrosplenial cortex (RSC) in stimulus-stimulus associations, and also in retrieval of remote associative memory based on EEG theta oscillations. To investigate the neural mechanisms underlying these processes, RSC neurons and local field potentials (LFPs) were simultaneously recorded from well-trained rats performing a cue-reward association task. In the task, simultaneous presentation of two multimodal conditioned stimuli (configural CSs) predicted a reward outcome opposite to that associated with individual presentation of each elemental CS. Here, we show neurophysiological evidence that the RSC is involved in stimulus-stimulus association where configural CSs are discriminated from each elementary CS that is a constituent of the configural CSs, and that memory retrieval of rewarding CSs is associated with theta oscillation of RSC neurons during CS presentation, which is phase-locked to LFP theta cycles.

neuroscience↗

bioRxiv2020

MacaquePose: A novel 'in the wild' macaque monkey pose dataset for markerless motion capture

Video-based markerless motion capture permits quantification of an animals pose and motion, with a high spatiotemporal resolution in a naturalistic context, and is a powerful tool for analyzing the relationship between the animals behaviors and its brain functions. Macaque monkeys are excellent non-human primate models, especially for studying neuroscience. Due to the lack of a dataset allowing training of a deep neural network for the macaques markerless motion capture in the naturalistic context, it has been challenging to apply this technology for macaques-based studies. In this study, we created MacaquePose, a novel open dataset with manually labeled body part positions for macaques in naturalistic scenes, consisting of >13,000 images, refined by researchers. We show that the pose estimation performance of an artificial neural network trained with the dataset is close to that of a human-level. The MacaquePose will provide a platform for innovative behavior analysis for non-human primate.

neuroscience↗