A neuroethological approach to decision-making considers the effect of evolutionary pressures on neural circuits mediating choice. In this view, decision systems are expected to enhance fitness with respect to the local environment, and particularly efficient solutions to specific problems should be conserved, expanded, and repurposed to solve other problems. Here, we discuss basic prerequisites for a variety of decision systems from this viewpoint. We focus on two of the best-studied and most widely represented decision problems. First, we examine patch leaving, a prototype of environmentally based switching between action patterns. Second, we consider social information seeking, a process resembling foraging with search costs. We argue that while the specific neural solutions to these problems sometimes differ across species, both the problems themselves and the algorithms instantiated by biological hardware are repeated widely throughout nature. The behavioral and mathematical study of ubiquitous decision processes like patch leaving and social information seeking thus provides a powerful new approach to uncovering the fundamental design structure of nervous systems.
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http://dx.doi.org/10.1016/j.conb.2012.07.009 | DOI Listing |
Sci Rep
December 2024
Department of Architecture, Rafsanjan Branch, Islamic Azad University, Rafsanjan, Iran.
The advent of smart cities has brought about a paradigm shift in urban management and citizen engagement. By leveraging technological advancements, cities are now able to collect and analyze extensive data to optimize service delivery, allocate resources efficiently, and enhance the overall well-being of residents. However, as cities become increasingly interconnected and data-dependent, concerns related to data privacy and security, as well as citizen participation and representation, have surfaced.
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December 2024
Department of Computing and Information Systems, Sunway University, 47500, Petaling Jaya, Selangor Darul Ehsan, Malaysia.
Urban mobility prediction is crucial for optimizing resource allocation, managing transportation systems, and planning urban development. We propose a novel framework, GeoTemporal LSTM (GT-LSTM), designed to address the intricate spatiotemporal dynamics of urban environments. GT-LSTM integrates temporal dependencies with geographic information through a multi-modal approach that combines attention mechanisms and Recurrent Neural Networks (RNNs).
View Article and Find Full Text PDFHealth Expect
February 2025
School of Nursing, McMaster University, Hamilton, Ontario, Canada.
Introduction: The transition from paediatric to adult health care (i.e., 'health care transition') poses many challenges for youth with medical complexity (YMC) and their families.
View Article and Find Full Text PDFJ Dtsch Dermatol Ges
December 2024
Department of Dermatology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, China.
Background: Basal cell carcinoma (BCC) is a prevalent type of skin cancer in which the inherent subjectivity of dermoscopy poses diagnostic challenges. Existing AI systems, which provide mainly image-level insights, lack the interpretability that is crucial for effective clinical decisions and patient education.
Patients And Methods: Our study developed a refined BCC dataset from the Human‒Machine Adversarial Model (HAM10000), which was annotated by clinicians to identify key diagnostic features.
Front Public Health
December 2024
Department of Data Integration and Analysis, Statens Serum Institut, Copenhagen, Denmark.
Except for a few countries, comprehensive all-cause surveillance for bacteremia is not part of mandatory routine public health surveillance. We argue that time has come to include automated surveillance for bacteremia in the national surveillance systems, and explore diverse approaches and challenges in establishing bacteremia monitoring. Assessed against proposed criteria, surveillance for bacteremia should be given high priority.
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