Jumpei Matsumoto

The paper shows that social behaviors, not vocal features, predict vocal turn-taking in marmosets, highlighting multimodal coordination in primate communication.

This study examines the effects of TCB-2 on multiple physiological and behavioral measures in mice, finding distinct effects across different metrics and partial modulation by a 5-HT2A antagonist.

This study identifies diverse ultrasonic vocalizations in rats beyond the traditional high-short/low-long dichotomy, highlighting the need for broader research into complex affective states.

The paper investigates how male mice respond to different types of ultrasonic vocalizations (USVs) based on social context, finding that USVs from chased intruders elicit approach behavior.

This paper develops a 3D markerless motion capture system for tracking multiple freely behaving monkeys to automate social behavior analysis.

This paper introduces SMP, an unsupervised algorithm for decomposing primate behavior into motion motifs, outperforming existing methods and visualizing neural manipulation effects.

The paper identifies a novel dopaminergic critic signal in mice during operant tasks that predicts correct/incorrect choices before reward signals, suggesting a role in learning and strategy adjustment.

This paper develops an AI system to quantify social and pathophysiological behaviors in common marmosets using 3D pose estimation and unsupervised analysis.

This study examines rhythmic oscillations in midbrain dopaminergic nuclei of mice during task performance, finding phase-locked activity in specific frequency bands linked to behavioral events.

This paper introduces USVCAM, an acoustic camera system for faster and simpler localization of ultrasonic vocalizations in mice, demonstrating its use in analyzing social communication in a home cage.

This study uses DREADD technology in common marmosets to show that chemogenetic activation of nigrostriatal dopamine neurons induces contralateral rotation behavior.

This paper develops a monkey pose estimation system using OpenPose, achieving performance comparable to human models and running in real-time.

The paper introduces MacaquePose, a dataset for markerless motion capture of macaques, showing neural network performance comparable to human-level pose estimation.

The paper shows that reward-associated configural cues elicit theta oscillations in rat retrosplenial neurons phase-locked to LFP theta cycles during memory retrieval.

The paper uses a convolutional neural network to detect monkey features like the nose and shoulders from RGB images in their natural environment with low model loss.