{"title":"Biologically inspired computational models of Visuospatial Working Memory: A systematic review","authors":"Viviana Dueñas, Sonia López, José-Antonio Cervantes, Gerardo Ortiz-Torres","doi":"10.1016/j.cogsys.2025.101410","DOIUrl":null,"url":null,"abstract":"<div><div>Visuospatial working memory is a fundamental cognitive component that enables humans to explore and interact with their visual environment. This paper presents a systematic review of bio-inspired computational models of visuospatial working memory developed over the past 14 years. The review identifies the main bio-inspired and algorithmic approaches used, examines the cognitive functions and brain areas considered in these models, and discusses the strategies employed to evaluate them. Furthermore, it outlines the current challenges in enhancing the design and implementation of such models. The findings from this meta-review are intended to support and guide future research on developing bio-inspired computational models of visuospatial working memory to enhance the cognitive abilities of bio-inspired artificial agents.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"94 ","pages":"Article 101410"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Systems Research","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389041725000907","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Visuospatial working memory is a fundamental cognitive component that enables humans to explore and interact with their visual environment. This paper presents a systematic review of bio-inspired computational models of visuospatial working memory developed over the past 14 years. The review identifies the main bio-inspired and algorithmic approaches used, examines the cognitive functions and brain areas considered in these models, and discusses the strategies employed to evaluate them. Furthermore, it outlines the current challenges in enhancing the design and implementation of such models. The findings from this meta-review are intended to support and guide future research on developing bio-inspired computational models of visuospatial working memory to enhance the cognitive abilities of bio-inspired artificial agents.
期刊介绍:
Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.
The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.
Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.