Cognitive Maps Research Articles

Partially dissociable roles of the orbitofrontal cortex and dorsal hippocampus in context-dependent hierarchical associations

Reward cues are often ambiguous; what is good in one context is not necessarily good in another. To solve this ambiguity, animals form hierarchical associations in which the context gates the retrieval of appropriate cue-evoked memories. These hierarchical associations regulate cue-elicited behavior and influence subsequent learning, promoting the inference of context-dependency. The orbitofrontal cortex (OFC) and dorsal hippocampus (DH) are both proposed to encode a "cognitive map" encompassing hierarchical, context-dependent associations. However, OFC- and DH-specific contributions to the different functional properties of hierarchical associations remain controversial. Using chemogenetic inactivation in rats, we show that the OFC is essential to both properties of hierarchical associations (performance regulation and learning bias). In contrast, DH's role appears limited to the contextual learning bias conferred by hierarchical associations. This work establishes the OFC as a critical orchestrator of hierarchical associations and provides insights into the extended circuits mediating the functional properties of these associations.

Cognitive Map of Perceptions of Social Networks as a Means of Justice in Sexual Offenses

The decision to share deeply personal experiences of sexual violence publicly is complex and multifaceted. This study provides valuable insights into this phenomenon. Interviews conducted with fifteen victims of sexual assault in Israel provide insights into the decision-making pathways of victims. The existing literature on sexual victims of sexual assault in Israel offers insights into their decision-making pathways but often lacks integration between theoretical concepts and practical outcomes. This article contributes to this field by proposing a detailed cognitive map that illuminates the specific decisions made by victims in choosing where to disclose their assault. The cognitive map presented in this study provides a comprehensive view of victims’ decision-making pathways. This study is part of a larger research project that involves interviewing communication consultants and analyzing posts from the social network platform Instagram to better understand the perceptions and behaviors of sexual assault victims. The interviews brought up four main themes: the existence of communicative justice and its importance as an arena for achieving justice; social media is critical for achieving justice, sometimes even more than the institutional arena; procedural justice is more important than outcome justice; voice is a leading principle in procedural justice principles.

Using fuzzy cognitive maps to evaluate the innovation in micro, small and medium-sized enterprises

PurposeThis article presents a fuzzy cognitive map for the evaluation of innovation in organizations.Design/methodology/approachThe purpose of this paper is to develop a model to evaluate the innovative capacity of organizations based on fuzzy cognitive maps (FCM), particularly for micro, small and medium-sized enterprises (MSMEs). The specification of the innovation evaluation model based on FCM was carried out with the “Intelligent Decision Support System” methodology. It is a six-step methodology: selection of experts, definition of concepts and relationships, model design, inference, interpretation and decision.FindingsOur approach yielded good results in three case studies, effectively determining the level of innovation in an organization. The fuzzy cognitive maps demonstrated a high level of accuracy, with an accuracy of 82% in the Colombian case studies and 92% in the global case studies. These results highlight the effectiveness of the model for quantitatively assessing levels of innovation within organizations. Furthermore, the study revealed the most influential and essential innovative activities/variables within organizations, contributing significantly to the improvement of their operations and competitiveness.Research limitations/implicationsIt is important to automate the definition of the relationships between the concepts of the context and of our FCM. It is also possible to improve the behavior of the FCM by analyzing the variables with a greater impact on the level of innovation and very dynamic in the context since they are the variables to be observed in real-time to follow the evolution of the innovative behavior of an organization.Practical implicationsThe study found that innovative activities emerged as an influential factor in organizations, essential to improving their operations and competitiveness. Our model can help in identifying areas that require improvement to impact positively organizations. By improving innovation assessment through the FCM model, organizations can anticipate higher profitability because innovations are often closely tied to revenue generation and cost savings. The tool can determine the necessity of new products or services, improve operational processes or enter new markets.Originality/valueThe previous results in the literature show that although there are relevant advances on this topic, there is not enough knowledge to provide clear guidelines for evaluating innovation and improving performance in an organization using intelligent systems. Also, previous works have not defined a framework for evaluating innovation in MSMEs based on FCMs. They also do not use the data of an organization to assess the key characteristics related to innovation. This work applies FCM to automate the evaluation of the process and the capacity for innovation in an organization. These are the main differences between our approach and previous studies.

Factors Influencing Domestic Human Trafficking in Africa: Protocol for a Scoping Review.

Human trafficking is a human rights violation in every region of the world. The African continent is not spared. Every year, millions of people experience significant health and social consequences. International organizations and governments combating human trafficking are hindered by a lack of knowledge about what factors influence domestic (within-country) human trafficking. This study aims to conduct a scoping review to collate and synthesize literature on factors influencing domestic trafficking in Africa. We will follow Arksey and O'Malley's framework to answer the question about reported influences on domestic human trafficking and their relative weight. The search strategy will explore PubMed, CINAHL, Web of Science, and Scopus. A total of 2 independent researchers will select quantitative, qualitative, or mixed methods studies that examine relationships influencing domestic human trafficking. We will document our results by following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. We will extract a list of all reported relationships between identified factors influencing domestic human trafficking in each study. Based on a discourse analysis approach, we will weigh the strengths of the relationships based on how frequently they are reported across the included studies. We will summarize the findings as fuzzy cognitive maps depicting the relationships reported in the literature. The maps represent the influences between concepts (nodes) linked by arrows (edges) going from each cause to its outcomes. These maps are helpful visual summaries of the factors associated with domestic human trafficking, allowing a comparison with maps to be created by stakeholder groups. This project received financial support in March 2023. We expect to start the project in March 2024. We recruited 2 research staff members to conduct the scoping review and expect to publish the results in March 2025. The review will provide a comprehensive understanding of factors influencing domestic human trafficking in Africa. The overlap of human trafficking with other forms of exploitation, the limited literature on domestic human trafficking, and the likely diversity of factors are challenges for the review. We propose strategies to address these challenges. PRR1-10.2196/56392.

A hierarchical active inference model of spatial alternation tasks and the hippocampal-prefrontal circuit

Cognitive problem-solving benefits from cognitive maps aiding navigation and planning. Physical space navigation involves hippocampal (HC) allocentric codes, while abstract task space engages medial prefrontal cortex (mPFC) task-specific codes. Previous studies show that challenging tasks, like spatial alternation, require integrating these two types of maps. The disruption of the HC-mPFC circuit impairs performance. We propose a hierarchical active inference model clarifying how this circuit solves spatial interaction tasks by bridging physical and task-space maps. Simulations demonstrate that the model’s dual layers develop effective cognitive maps for physical and task space. The model solves spatial alternation tasks through reciprocal interactions between the two layers. Disrupting its communication impairs decision-making, which is consistent with empirical evidence. Additionally, the model adapts to switching between multiple alternation rules, providing a mechanistic explanation of how the HC-mPFC circuit supports spatial alternation tasks and the effects of disruption.

Double Decomposition and Fuzzy Cognitive Graph-Based Prediction of Non-Stationary Time Series.

Deep learning models, such as recurrent neural network (RNN) models, are suitable for modeling and forecasting non-stationary time series but are not interpretable. A prediction model with interpretability and high accuracy can improve decision makers' trust in the model and provide a basis for decision making. This paper proposes a double decomposition strategy based on wavelet decomposition (WD) and empirical mode decomposition (EMD). We construct a prediction model of high-order fuzzy cognitive maps (HFCM), called the WE-HFCM model, which considers interpretability and strong reasoning ability. Specifically, we use the WD and EDM algorithms to decompose the time sequence signal and realize the depth extraction of the signal's high-frequency, low-frequency, time-domain, and frequency domain features. Then, the ridge regression algorithm is used to learn the HFCM weight vector to achieve modeling prediction. Finally, we apply the proposed WE-HFCM model to stationary and non-stationary datasets in simulation experiments. We compare the predicted results with the autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) models.For stationary time series, the prediction accuracy of the WE-HFCM model is about 45% higher than that of the ARIMA, about 35% higher than that of the SARIMA model, and about 16% higher than that of the LSTM model. For non-stationary time series, the prediction accuracy of the WE-HFCM model is 69% higher than that of the ARIMA and SARIMA models.

Shortcutting from self-motion signals reveals a cognitive map in mice.

Animals navigate by learning the spatial layout of their environment. We investigated spatial learning of mice in an open maze where food was hidden in one of a hundred holes. Mice leaving from a stable entrance learned to efficiently navigate to the food without the need for landmarks. We developed a quantitative framework to reveal how the mice estimate the food location based on analyses of trajectories and active hole checks. After learning, the computed 'target estimation vector' (TEV) closely approximated the mice's route and its hole check distribution. The TEV required learning both the direction and distance of the start to food vector, and our data suggests that different learning dynamics underlie these estimates. We propose that the TEV can be precisely connected to the properties of hippocampal place cells. Finally, we provide the first demonstration that, after learning the location of two food sites, the mice took a shortcut between the sites, demonstrating that they had generated a cognitive map.

Shortcutting from self-motion signals reveals a cognitive map in mice

Animals navigate by learning the spatial layout of their environment. We investigated spatial learning of mice in an open maze where food was hidden in one of a hundred holes. Mice leaving from a stable entrance learned to efficiently navigate to the food without the need for landmarks. We developed a quantitative framework to reveal how the mice estimate the food location based on analyses of trajectories and active hole checks. After learning, the computed ‘target estimation vector’ (TEV) closely approximated the mice’s route and its hole check distribution. The TEV required learning both the direction and distance of the start to food vector, and our data suggests that different learning dynamics underlie these estimates. We propose that the TEV can be precisely connected to the properties of hippocampal place cells. Finally, we provide the first demonstration that, after learning the location of two food sites, the mice took a shortcut between the sites, demonstrating that they had generated a cognitive map.

Transferable lessons for care provided to children with intellectual and developmental disabilities based on an analysis of facilitators and barriers to SARS-CoV-2 testing.

The purpose of this article is to report on the lessons learned from parents and caregivers of school-age children with intellectual and developmental disabilities (IDD) in Missouri and Maryland regarding the facilitators and barriers to SARS-COV-2 testing. Parents participated in interview sessions that employed fuzzy cognitive mapping (FCM), a reliable knowledge-based method that facilitates democratic discourse to understand how stakeholders make decisions. A total of 94 parents from Missouri (58) and Maryland (36) participated in the FCM sessions. Eight primary barriers and eight primary facilitating factors were identified that influence a successful SARS-COV-2 test. Analyzing the connections between these factors provided valuable information about not only which ideas were most central to the goal of a successful test, but also which factors could be modified to improve the likelihood of success. Results indicate that the physical environment and child preparedness play a central role in successful SARS-COV-2 testing for children with IDD; however, these factors within the context of other invasive procedures should be studied further. It is likely that the findings from this study are transferable to other diagnostic procedures such as influenza, respiratory syncytial virus (RSV), and methicillin-resistant Staphylococcus aureas (MRSA), which require similar testing techniques using a nasopharyngeal swab.

RETRACTION: Supply Chain Operation Evaluation and Management Decision by Fuzzy Cognitive Map Model

Retraction: P. Zheng, “,” Expert Systems 41, no. (2024): . https://doi.org/10.1111/exsy.13022. The above article, published online on 15 May 2022, in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor‐in‐Chief, David Camacho; and John Wiley & Sons Ltd. The article was submitted as part of a guest‐edited special issue. Following publication, it has come to the attention of the journal that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors did not respond to the notice of retraction.

Dynamic security in cloud computing based on fuzzy cognitive maps

Cloud Computing is a new paradigm that provides software and hardware resources based on customers’ needs. However, data security remains a significant concern, acting as a major barrier to its widespread adoption. The objective of this work is to propose a process for assessing data risks in Cloud Computing. The process is based on fuzzy cognitive maps (FCMs) for qualitative reasoning. Risk assessment is a crucial aspect of Cloud Computing. Our proposed system involves three main steps based on expert knowledge. In the first step, a global FCM was built and validated to identify threats at the Cloud Computing level. Then the second step was devoted to calculate the consequences by inference using FCM Expert. The obtained results show that the FCM has a remarkable capacity to deal with the uncertainty of the data; by doing so, it becomes possible to model the real system more accurately. The last step is to simulate, analyze the results of the second step in Matlab Simulink and also develop recommendations to reduce the risks in order to improve and increase the security of Cloud data.

Co-designing Culturally Safe Indigenous Birth in High-Risk Obstetrics: Implementing Joyce's Principle with Inuit and Cree Families and Their Medical Providers.

Introduction. Maternal evacuation-the transfer of women from remote communities to urban hospitals for childbirth-negatively affects many Indigenous Peoples in Canada. A working group of perinatal service providers in Montreal sought to enhance cultural safety in a high-risk obstetrical unit serving evacuee Indigenous families. This article describes co-design, implementation, and evaluation of short-term cultural safety interventions with Indigenous stakeholders. Methods. Indigenous families and their non-Indigenous service providers displayed their recommendations for culturally safe birth using fuzzy cognitive mapping (FCMs). Joyce's Principle-a framework for securing culturally safe healthcare for Indigenous Peoples-guided their implementation. Results. Four high-priority FCM recommendations included an Indigenous-led cultural safety training for hospital staff. Third party evaluation showed a positive influence on cultural safety knowledge and actions. Discussion. Health services designed with Indigenous stakeholders in accordance with Joyce's Principle have the potential to enhance cultural safety of maternal evacuation.

Hazards Prioritization With Cognitive Attention Maps for Supporting Driving Decision-Making

Hazards Prioritization With Cognitive Attention Maps for Supporting Driving Decision-Making

Complex Dynamic Slow Independent Symbol Aggregation Approximation for Multimodal Temporal Fuzzy Cognitive Map

Complex Dynamic Slow Independent Symbol Aggregation Approximation for Multimodal Temporal Fuzzy Cognitive Map

A Neutrosophic Cognitive Maps Approach For TheSymptoms-Disease Model In Maternal Healthcare

for maternal health conditions using neutrosphic cognitive maps (NCM). This approach develops a NCM model to analyze the nine symptoms associated with the six disorders that affect expectant mothers. A numerical example of the diagnosis model is also provided to demonstrate the applicability of the proposed NCM approach

Integrated Fuzzy Cognitive Map and Chaotic Particle Swarm Optimization for Risk Assessment of Ischemic Stroke

Integrated Fuzzy Cognitive Map and Chaotic Particle Swarm Optimization for Risk Assessment of Ischemic Stroke

Keeping birth at home: Community and service provider visions for perinatal wellness and continued Inuit childbirth in Nunavik

ProblemChildbirth on traditional territories is unattainable for many Indigenous peoples living in remote communities in Canada. BackgroundIn Nunavik, Inuit territory in northern Quebec, rapid population growth risks exceeding local midwifery capacity. This poses challenges to community-based childbirth in a region recognized for reclaiming Inuit midwifery and local birthing. AimTo explore community views on protective factors of maternal and family perinatal wellness and continued local birthing. MethodsIn ten communities, Inuit families and perinatal service providers created a total of 54 fuzzy cognitive maps on protective factors for (1) birth in a good way in Nunavik, (2) maternal and family perinatal wellness, and (3) community-based birthing in Nunavik. We used fuzzy transitive closure to examine direct and indirect connections and collated individual factors into categories using inductive thematic analysis. FindingsWell-equipped local medical facilities and services, community birthing centres run by Inuit midwives, and Inuit perinatal traditions had the strongest influence on experiencing birth in a good way in Nunavik. Inuit youth perspectives featured instrumental and emotional support for mothers and families, along with health and self-care in pregnancy as the most influential factors on maternal and family perinatal wellness. Prominent protective factors for community birth in Nunavik included maternal-infant health and wellness, local Inuit midwifery services, and well-resourced medical facilities. DiscussionFuzzy cognitive mapping was helpful in informing community visioning of local childbirth and maternal and family perinatal wellness in Nunavik. ConclusionInuit-led midwifery services are essential to continued local childbirth in the region.

Devising a project risk management method under scrum conditions based on cognitive approach

Any project implemented using Scrum is characterized by the impact of risks, including negative changes in the environment and crisis circumstances. Therefore, the processes related to risk management, which is the object of this paper, become important. The problem solved in this study is to improve the efficiency of projects through the construction of a long-term strategy for reducing the level of risk and avoiding negative consequences for projects in the context of Scrum. The proposed method of risk management has been developed on the basis of the application of the synthesis of management of intelligent decision-making technologies and formalized methods. Difficult external circumstances are characterized by a high degree of uncertainty and do not always contribute to the successful implementation of the project. Therefore, this method of project risk management under Scrum conditions based on a cognitive approach is characterized by a combined combination of cognitive analysis, mathematical modeling, and expert methods. As part of the method, a model of project risk management under Scrum conditions has been built in the form of a fuzzy cognitive map, which could ensure determining the optimal strategic decision in dynamics, taking into account the effects of various factors. The result of applying this method is compliance with time limits, reduction of overspending of resources and losses in the project, as well as adaptation to rapidly changing circumstances and adequate response. The method of project risk management is characterized by solving the problem of formalizing management decision-making procedures and their information support, taking into account the availability of both quantitative and qualitative data. Within the framework of this method, a project risk management procedure under Scrum conditions has been proposed, which contributes to the systematization, monitoring, and control of risks under the conditions of complex, rapidly changing crisis circumstances

Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes.

Many animals learn cognitive maps of their environment - a simultaneous representation of context, experience, and position. Place cells in the hippocampus, named for their explicit encoding of position, are believed to be a neural substrate of these maps, with place cell "remapping" explaining how this system can represent different contexts. Briefly, place cells alter their firing properties, or "remap", in response to changes in experiential or sensory cues. Substantial sensory changes, produced, e.g., by moving between environments, cause large subpopulations of place cells to change their tuning entirely. While many studies have looked at the physiological basis of remapping, we lack explicit calculations of how the contextual capacity of the place cell system changes as a function of place field firing properties. Here, we propose a geometric approach to understanding population level activity of place cells. Using known firing field statistics, we investigate how changes to place cell firing properties affect the distances between representations of different environments within firing rate space. Using this approach, we find that the number of contexts storable by the hippocampus grows exponentially with the number of place cells, and calculate this exponent for environments of different sizes. We identify a fundamental trade-off between high resolution encoding of position and the number of storable contexts. This trade-off is tuned by place cell width, which might explain the change in firing field scale along the dorsal-ventral axis of the hippocampus. We demonstrate that clustering of place cells near likely points of confusion, such as boundaries, increases the contextual capacity of the place system within our framework and conclude by discussing how our geometric approach could be extended to include other cell types and abstract spaces.

Cognitive Maps for a Non-Euclidean Environment: Path Integration and Spatial Memory on a Sphere

Humans build mental models of the world and utilize them for various cognitive tasks. The exact form of cognitive maps is not fully understood, especially for novel and complex environments beyond the flat Euclidean environment. To address this gap, we investigated path integration—a critical process underlying cognitive mapping—and spatial-memory capacity on the spherical (non-Euclidean) and planar (Euclidean) environments in young healthy adults (N = 20) using immersive virtual reality. We observed a strong Euclidean bias during the path-integration task on the spherical surface, even among participants who possessed knowledge of non-Euclidean geometry. Notably, despite this bias, participants demonstrated reasonable navigation ability on the sphere. This observation and simulation suggest that humans navigate nonflat surfaces by constructing locally confined Euclidean maps and flexibly combining them. This insight sheds light on potential neural mechanisms and behavioral strategies for solving complex cognitive tasks.