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An embedded network approach for scale-up of fluctuation-driven systems with preservation of spike information.

ABSTRACT: To address computational "scale-up" issues in modeling large regions of the cortex, many coarse-graining procedures have been invoked to obtain effective descriptions of neuronal network dynamics. However, because of local averaging in space and time, these methods do not contain detailed spike information and, thus, cannot be used to investigate, e.g., cortical mechanisms that are encoded through detailed spike-timing statistics. To retain high-order statistical information of spikes, we develop a hybrid theoretical framework that embeds a subnetwork of point neurons within, and fully interacting with, a coarse-grained network of dynamical background. We use a newly developed kinetic theory for the description of the coarse-grained background, in combination with a Poisson spike reconstruction procedure to ensure that our method applies to the fluctuation-driven regime as well as to the mean-driven regime. This embedded-network approach is verified to be dynamically accurate and numerically efficient. As an example, we use this embedded representation to construct "reverse-time correlations" as spiked-triggered averages in a ring model of orientation-tuning dynamics.

SUBMITTER: Cai D

PROVIDER: S-EPMC521148 | biostudies-literature | 2004 Sep

REPOSITORIES: biostudies-literature

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An embedded network approach for scale-up of fluctuation-driven systems with preservation of spike information.

Cai David D Tao Louis L McLaughlin David W DW

Proceedings of the National Academy of Sciences of the United States of America 20040920 39

To address computational "scale-up" issues in modeling large regions of the cortex, many coarse-graining procedures have been invoked to obtain effective descriptions of neuronal network dynamics. However, because of local averaging in space and time, these methods do not contain detailed spike information and, thus, cannot be used to investigate, e.g., cortical mechanisms that are encoded through detailed spike-timing statistics. To retain high-order statistical information of spikes, we develo ...[more]

PMID: 15381777

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Project description:BackgroundWith the increasing sophistication of the medical industry, various advanced medical services such as medical artificial intelligence, telemedicine, and personalized health care services have emerged. The demand for medical data is also rapidly increasing today because advanced medical services use medical data such as user data and electronic medical records (EMRs) to provide services. As a result, health care institutions and medical practitioners are researching various mechanisms and tools to feed medical data into their systems seamlessly. However, medical data contain sensitive personal information of patients. Therefore, ensuring security while meeting the demand for medical data is a very important problem in the information age for which a solution is required.ObjectiveOur goal is to design a blockchain-based decentralized patient information exchange (PIE) system that can safely and efficiently share EMRs. The proposed system preserves patients' privacy in the EMRs through a medical information exchange process that includes data encryption and access control.MethodsWe propose a blockchain-based EMR-sharing system that allows patients to manage their EMRs scattered across multiple hospitals and share them with other users. Our PIE system protects the patient's EMR from security threats such as counterfeiting and privacy attacks during data sharing. In addition, it provides scalability by using distributed data-sharing methods to quickly share an EMR, regardless of its size or type. We implemented simulation models using Hyperledger Fabric, an open source blockchain framework.ResultsWe performed a simulation of the EMR-sharing process and compared it with previous works on blockchain-based medical systems to check the proposed system's performance. During the simulation, we found that it takes an average of 0.01014 (SD 0.0028) seconds to download 1 MB of EMR in our proposed PIE system. Moreover, it has been confirmed that data can be freely shared with other users regardless of the size or format of the data to be transmitted through the distributed data-sharing technique using the InterPlanetary File System. We conducted a security analysis to check whether the proposed security mechanism can effectively protect users of the EMR-sharing system from security threats such as data forgery or unauthorized access, and we found that the distributed ledger structure and re-encryption-based data encryption method can effectively protect users' EMRs from forgery and privacy leak threats and provide data integrity.ConclusionsBlockchain is a distributed ledger technology that provides data integrity to enable patient-centered health information exchange and access control. PIE systems integrate and manage fragmented patient EMRs through blockchain and protect users from security threats during the data exchange process among users. To increase safety and efficiency in the EMR-sharing process, we used access control using security levels, data encryption based on re-encryption, and a distributed data-sharing scheme.

Project description:BackgroundThe introduction of self-administered injectable contraception presents an opportunity to address the unmet need for family planning. As ministries of health scale up self-administered injectable contraception, there is a scarcity of knowledge on the implementation practices and contextual conditions that help and hinder these efforts. The World Health Organization has launched the "enhancing self-administered family planning through embedded research project" (EASIER) to address this challenge.ObjectiveEASIER's objectives are to: (1) assess the coverage of self-injectable contraception, and the readiness of health systems to integrate it into the contraceptive method mix; (2) document strategies used to introduce and scale up self-injectable contraception and understand practices that have led to success and challenges; (3) identify the contextual factors that affect the adoption and implementation of self-injectable contraception throughout health systems; (4) understand whether implementation addresses users' preferences and needs; (5) strengthen collaboration between decision makers, researchers, and implementers; support and build capacity to use evidence.MethodsEASIER developed a global protocol that implementation research (IR) teams in Burkina Faso, Ghana, and Kenya adapted into country-level embedded IR projects. In all countries (1) at the national level, IR teams evaluate the policy environment for scaling up by conducting a desk review and in-depth interviews; (2) at the local level, IR teams implement quantitative questionnaires on structural and organizational readiness to integrate self-injection into the method mix; (3) in "case study" localities, IR teams conduct in-depth interviews and focus group discussions with implementers, method users, and community members; and (4) IR teams use participatory action research to elicit stakeholder participation and translate findings into programmatic decisions.ResultsEASIER has been launched in all 3 countries. Preliminary findings are available from Burkina Faso and Kenya. In Burkina Faso, IR teams identified the need to strengthen health worker training approaches to ensure that family planning providers at primary health care facilities are adequately oriented to depo-medroxyprogesterone acetate subcutaneous (DMPA-SC) and self-injection and capacitated to initiate women to the method. In addition, they report the need for service communication strategies that reach potential users of the method with knowledge about self-injection and how to initiate the practice. In Kenya, the findings illuminate the need for practice guidelines that county health teams can use to coordinate the rollout of self-administered DMPA-SC. In addition, Kenya's findings underscore the importance of addressing logistical bottlenecks to help avoid stock-outs.ConclusionsEASIER presents a strategy to embed IR in contraceptive method introduction and scale-up, address local knowledge needs, devise ways to maximize the impact of new technologies in health systems, and build capacity for using evidence in programmatic decisions. Adaptation and implementation of country-level IR studies will advance the use of IR to strengthen family planning programs.Trial registrationAustralia New Zealand Clinical Trials Registry ACTRN12622001228774; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384534&isReview=true.International registered report identifier (irrid)DERR1-10.2196/44222.

Dataset Information

An embedded network approach for scale-up of fluctuation-driven systems with preservation of spike information.

Publications

An embedded network approach for scale-up of fluctuation-driven systems with preservation of spike information.

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