Adaptive network modeling for joint action and memory recall for elderly by detecting interpersonal synchrony

This paper explores the potential of adaptive network modeling for joint action and memory recall among elderly through detecting interpersonal synchrony. With the aging population increasing, there is a crucial need to focus on the health and social interaction of older adults. Based on research of the significance of social interaction and memory use for the elderly, as well as the role of interpersonal synchrony in joint action, this paper aims to analyse computationally how to enhance positive effects of social interactions among older individuals by applying an adaptive network model. The research examines the concept of interpersonal synchrony and its impact on joint action, memory, and emotional well-being in elderly populations. Through simulation experiments and analysis, the study demonstrates the potential benefits for music in memory recall for older adults with cognitive decline, highlighting the importance of social interaction and emotional resonance. This study offers a valuable contribution to understanding and improving social interactions and memory recall among the elderly.

Authors

Institutions

Publication Details

Journal
Cognitive Systems Research
Published
2024-08-30
DOI
https://doi.org/10.1016/j.cogsys.2024.101280
Citations
4
Primary Topic
Action Observation and Synchronization
Type
article
Field-Weighted Citation Impact
2.57
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive network modeling for joint action and memory recall for elderly by detecting interpersonal synchrony

Yijie Xu, Peter H. M. P. Roelofsma, Sophie C. F. Hendrikse, Jan Treur
4 citations
Cognitive Systems Research
Action Observation and Synchronization
2.57
article

Adaptive network modeling for joint action and memory recall for elderly by detecting interpersonal synchrony

Yijie Xu, Peter H. M. P. Roelofsma, Sophie C. F. Hendrikse, Jan Treur
article en
4 citations

Abstract

This paper explores the potential of adaptive network modeling for joint action and memory recall among elderly through detecting interpersonal synchrony. With the aging population increasing, there is a crucial need to focus on the health and social interaction of older adults. Based on research of the significance of social interaction and memory use for the elderly, as well as the role of interpersonal synchrony in joint action, this paper aims to analyse computationally how to enhance positive effects of social interactions among older individuals by applying an adaptive network model. The research examines the concept of interpersonal synchrony and its impact on joint action, memory, and emotional well-being in elderly populations. Through simulation experiments and analysis, the study demonstrates the potential benefits for music in memory recall for older adults with cognitive decline, highlighting the importance of social interaction and emotional resonance. This study offers a valuable contribution to understanding and improving social interactions and memory recall among the elderly.

Cognitive Systems ResearchVol. 88
Vrije Universiteit Amsterdam (NL), Hologic (Germany) (DE), The Hague University of Applied Sciences (NL)
Gender equality
Openalex Percentile: Top 11%
Action Observation and Synchronization
2.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Adaptive network modeling for joint action and memory recall for elderly by detecting interpersonal synchrony — Yijie Xu, Peter H. M. P. Roelofsma, et al. · Cognitive Systems Research (2024) | TGRS Research Map | TGRS