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111
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Dataset results
111 results for “cognitive modeling”
Risk Warning Model of Postoperative Delirium and Long-term Cognitive Dysfunction in Elderly Patients
ClinicalTrials.gov study NCT06423547. IPD Sharing: NO. Countries: 1. Publications: 2.
Testing a Cognitive Behavioral Model for Reducing Dyspnea in Patients With Lung Cancer
ClinicalTrials.gov study NCT05304793. IPD Sharing: NO. Countries: 1. Publications: 1.
Risk Model of Cognitive Impairment in Diabetes
ClinicalTrials.gov study NCT05590442. IPD Sharing: NO. Countries: 1. Publications: 3.
A Treatment for Depression Via a Gamified Mobile Phone Application Based on a New Cognitive Model
ClinicalTrials.gov study NCT05685758. IPD Sharing: NO. Countries: 1. Publications: 10.
Internet-delivered Cognitive Behaviour Therapy for Chronic Conditions: Comparing Low Intensity Delivery Models
ClinicalTrials.gov study NCT03500237. IPD Sharing: NO. Countries: 1. Publications: 1.
A Care Model for Elderly Hip-fractured Persons With Cognitive Impairment and Their Family Caregivers
ClinicalTrials.gov study NCT03894709. IPD Sharing: NO. Countries: 1. Publications: 3.
Developing Risk Prediction Model and Testing the Effect of Dual Task Walking on Improving Cognitive Function in Patients With Colorectal Cancer
ClinicalTrials.gov study NCT04490733. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
An Inpatient Rehabilitation Model of Care Targeting Patients With Cognitive Impairment
ClinicalTrials.gov study NCT01566136. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Stepped Care Model for the Wider Dissemination of Cognitive-Behavioural Therapy for Insomnia Among Cancer Patients
ClinicalTrials.gov study NCT01864720. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Data and R Code for publication: Should dispersers be fast learners? Modelling the role of cognition in dispersal
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CT data and 3D models associated with: Palaeoneurology of the Early Cretaceous iguanodont Proa valdearinnoensis and its bearing on the parallel developments of cognitive abilities in theropod and ornithopod dinosaurs
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Data from: Modeling the internet of things, self-organizing and other complex adaptive communication networks: a cognitive agent-based computing approach
Background: Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose: It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method: We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results: The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.
Data from: Overexpression of Dyrk1A is implicated in several cognitive, electrophysiological and neuromorphological alterations found in a mouse model of Down syndrome
Down syndrome (DS) phenotypes result from the overexpression of several dosage-sensitive genes. The DYRK1A (dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A) gene, which has been implicated in the behavioral and neuronal alterations that are characteristic of DS, plays a role in neuronal progenitor proliferation, neuronal differentiation and long-term potentiation (LTP) mechanisms that contribute to the cognitive deficits found in DS. The purpose of this study was to evaluate the effect of Dyrk1A overexpression on the behavioral and cognitive alterations in the Ts65Dn (TS) mouse model, which is the most commonly utilized mouse model of DS, as well as on several neuromorphological and electrophysiological properties proposed to underlie these deficits. In this study, we analyzed the phenotypic differences in the progeny obtained from crosses of TS females and heterozygous Dyrk1A (+/−) male mice. Our results revealed that normalization of the Dyrk1A copy number in TS mice improved working and reference memory based on the Morris water maze and contextual conditioning based on the fear conditioning test and rescued hippocampal LTP. Concomitant with these functional improvements, normalization of the Dyrk1A expression level in TS mice restored the proliferation and differentiation of hippocampal cells in the adult dentate gyrus (DG) and the density of GABAergic and glutamatergic synapse markers in the molecular layer of the hippocampus. However, normalization of the Dyrk1A gene dosage did not affect other structural (e.g., the density of mature hippocampal granule cells, the DG volume and the subgranular zone area) or behavioral (i.e., hyperactivity/attention) alterations found in the TS mouse. These results suggest that Dyrk1A overexpression is involved in some of the cognitive, electrophysiological and neuromorphological alterations, but not in the structural alterations found in DS, and suggest that pharmacological strategies targeting this gene may improve the treatment of DS-associated learning disabilities.
Data from: Space-use behavior of woodland caribou based on a cognitive movement model
1. Movement patterns offer a rich source of information on animal behaviour and the ecological significance of landscape attributes. This is especially useful for species occupying remote landscapes where direct behavioural observations are limited. In this study, we fit a mechanistic model of animal cognition and movement to GPS positional data of woodland caribou (Rangifer tarandus caribou; Gmelin 1788) collected over a wide range of ecological conditions. 2. The model explicitly tracks individual animal informational state over space and time, with resulting parameter estimates that have direct cognitive and ecological meaning. Three biotic landscape attributes were hypothesized to motivate caribou movement: forage abundance (dietary digestible biomass), wolf (Canis lupus; Linnaeus, 1758) density and moose (Alces alces; Linnaeus, 1758) habitat. Wolves are the main predator of caribou in this system and moose are their primary prey. 3. Resulting parameter estimates clearly indicated that forage abundance is an important driver of caribou movement patterns, with predator and moose avoidance often having a strong effect, but not for all individuals. From the cognitive perspective, our results support the notion that caribou rely on limited sensory inputs from their surroundings, as well as on long-term spatial memory, to make informed movement decisions. Our study demonstrates how sensory, memory and motion capacities may interact with ecological fitness covariates to influence movement decisions by free-ranging animals.
Dataset: Model-based Cognitive Communications for Low-power Wireless Networks
<p>Dataset: Model-based Cognitive Communications for Low-power Wireless Networks</p>
Code and data for: A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task
<p>A source code and data dump for analyses of the article "A computational model for driver’s cognitive state, visual perception and intermittent attention in a distracted car following task"</p> <p>Code is under GNU AGPL-v3. Data under CC-BY-4.0</p> <p>Versioned code is available at https://gitlab.com/mulsimco/follow17 and https://gitlab.com/mulsimco/cfmodels</p> <p>See README.md in follow17 for usage.</p>
Phenotypes of painful TMD in discordant monozygotic twins according to a cognitive-behavioral-emotional model: a case-control study
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Cognitive Model for Behavioral Interventions as a Personalized Intervention for Patients With Serious Mental Illness
ClinicalTrials.gov study NCT05820360. IPD Sharing: NO. Countries: 0. Publications: 8.
Interleaved TMS-fMRI for Hippocampal Stimulation: Modeling Dose-Response Relationship in Amnestic Mild Cognitive Impairment
ClinicalTrials.gov study NCT05515952. IPD Sharing: NO. Countries: 1. Publications: 0.
A Scalable Model for Promoting Functioning and Well-Being Among Older Adults With Mild Cognitive Impairment Via Meaningful Social Interactions: Project SPEAK!
ClinicalTrials.gov study NCT04717479. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.