Biology subjects

Suda-Hashimoto, N.

Publications and source records attributed to Suda-Hashimoto, N..

4 recordsLinked to original sources

bioRxiv2023

Three-dimensional markerless motion capture of multiple freely behaving monkeys for automated characterization of social behavior

Given their high sociality and close evolutionary distance to humans, monkeys are an essential animal model for unraveling the biological mechanisms underlying human social behavior and elucidating the pathogenesis of diseases exhibiting abnormal social behavior. However, behavioral analysis of naturally behaving monkeys requires manual counting of various behaviors, which has been a bottleneck due to problems in throughput and objectivity. Here, we developed a three-dimensional markerless motion capture system that utilized multi-view data for robust tracking of individual monkeys and accurate reconstruction of the three-dimensional poses of multiple monkeys living in groups. Validation analysis in two monkey groups revealed that the system enabled the characterization of individual social dispositions and relationships through automated detection of various social events. Analyses of social looking facilitated the investigation of adaptive behaviors in a social group. These results suggest that this motion capture system will significantly enhance our ability to analyze primate social behavior.

animal behavior and cognition↗

bioRxiv2021

Effects of short-term isolation on social animals' behavior: an experimental case study of Japanese macaque

One of the goals in animal socioecology is to understand the functions and dynamics of group living. While observations of free-ranging animals are a crucial source of information, an experimental investigation that manipulates the size or composition, or both, of animal groups in captivity can also bring complementary contributions to the research inquiry. When paired with an automatic data collection by biologging technology, experimental studies on captive animals also allow for big data analyses based on recent machine learning techniques. As an initial exploration of this research paradigm, the present study inquired to what extent isolation of captive Japanese macaques (Macaca fuscata) changed their movement patterns. Using three-dimensional location trajectories of the macaques that were systematically collected via Bluetooth Low Energy beacons and a deep neural network, we estimated the identifiability of whether a macaque was behaving in isolation or in group. We found that the neural network identified the isolation vs. in-group conditions with more than 90% accuracy from a five-minute location trajectory, suggesting that the isolation caused notable changes from the canonical group-living behaviors. In addition, the isolation made each individual more identifiable from one another based on their location trajectories.

animal behavior and cognition↗

bioRxiv2020

Non-Parametric Analysis of Inter-Individual Relations Using an Attention-Based Neural Network

O_LISocial network analysis, which has been widely adopted in animal studies over the past decade, enables the revelation of global characteristic patterns of animal social systems from pairwise inter-individual relations. Animal social networks are typically drawn based on geometric proximity and/or frequency of social behaviors (e.g., grooming), but the appropriate metric for inter-individual relationship is not clear, especially when prior knowledge on the species/data is limited. C_LIO_LIIn this study, researchers explored a non-parametric analysis of inter-individual relations using a neural network with the attention mechanism, which plays a central role in natural language processing. The high interpretability of the attention mechanism and flexibility of the entire neural network allow for automatic detection of inter-individual relations included in the raw data, without requiring prior knowledge/assumptions about what modes/types of relations are included in the data. For these case studies, three-dimensional location data collected from simulated agents and real Japanese macaques were analyzed. C_LIO_LIThe proposed method successfully recovered the latent relations behind the simulated data and discovered female-oriented relations in the real data, which are in accordance with previous generalizations about the macaque social structure. C_LIO_LIThe proposed method does not exploit any behavioral patterns that are particular to Japanese macaques, and researchers can use it for location data of other animals. The exibility of the neural network would also allow for its application to a wide variety of data with interacting components, such as vocal communication. C_LI

animal behavior and cognition↗

bioRxiv2019

Animals exhibit personality traits in their movement: a case study on location trajectories of primates

Researching individual recognition (IR) is essential to understand the life history and adaptive behavior of social animals. Investigation of personality traits may also provide insights into how social animals distinguish between different individuals. This study investigates IR behavior in Japanese macaques (Macaca fuscata), focusing on one specific trait, which is movement. Using a recently developed tracking system based on Bluetooth(R) Low Energy beacons, we collected three-dimensional (3D) location data from five Japanese macaques living in a group cage. A non-parametric, neural network-based analysis of the data revealed the existence of personality traits in extremely limited aspects of the movement data (2-min trajectory of 3D location). Our results support the validity of multimodal approaches in studying IR, beyond the typical single-frame face recognition method, both for researchers and animal agents.

animal behavior and cognition↗