Recent progress in network sciences has made it possible to apply key findings from control theory to the study of networks. Referred to as network control theory, this framework describes how the interactions between interconnected system elements and external energy sources, potentially constrained by different optimality criteria, result in complex network behavior. A typical example is the quantification of the functional role certain brain regions or symptoms play in shaping the temporal dynamics of brain activity or the clinical course of a disease, a property that is quantified in terms of the so-called controllability metrics. Critically though, contrary to the engineering context in which control theory was originally developed, a mathematical understanding of the network nodes and connections in neurosciences cannot be assumed. For instance, in the case of psychological systems such as those studied to understand psychiatric disorders, a potentially large set of related variables are unknown. As such, while the measures offered by network control theory would be mathematically correct, in that they can be calculated with high precision, they could have little translational values with respect to their putative role suggested by controllability metrics. It is therefore critical to understand if and how the controllability metrics estimated over subnetworks would deviate, if access to the complete set of variables, as is common in neurosciences, cannot be taken for granted.In this paper, we use a host of simulations based on synthetic as well as structural magnetic resonance imaging (MRI) data to study the potential deviation of controllability metrics in sub- compared to the full networks. Specifically, we estimate average- and modal-controllability, two of the most widely used controllability measures in neurosciences, in a large number of settings where we systematically vary network type, network size, and edge density.We find out, across all network types we test, that average and modal controllability are systematically, over- or underestimated depending on the number of nodes in the sub- and full network and the edge density.Finally, we provide formal theoretical proof that our observations generalize to any network type and discuss the ramifications of this systematic bias and potential solutions to alleviate the problem.
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http://dx.doi.org/10.1088/1741-2552/acb256 | DOI Listing |
Sci Rep
January 2025
College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
Multiple active mining faces and extensive excavations under thick-hard strata in deep coal mines result in frequent strong mine earthquakes, often accompanied by significant surface subsidence deformation. Understanding the specific law of surface movement and the spatiotemporal distribution response to intense mine earthquakes is crucial for effectively preventing and mitigating dynamic disasters in deep mines. Utilizing the key layer theory, the intricate strata of the Yingpanhao Coal Mine are systematically delineated, drawing upon the engineering context of working faces 2201 and 2202 within the Ordos Chemical Co.
View Article and Find Full Text PDFIntensive Crit Care Nurs
January 2025
School of Nursing, Taipei Medical University, Taipei, Taiwan; Department of Nursing, Taipei Medical University Hospital, Taipei, Taiwan; Research Center of Sleep Medicine, Taipei Medical University Hospital, Taipei, Taiwan; Research Center of Sleep Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan. Electronic address:
Objective: To evaluate the effects of a 4-week Delirium Introduction and Maintenance programme based on the knowledge-to-action framework on nurses' knowledge, self-confidence, attitudes, and screening accuracy for delirium in the paediatric intensive care unit (PICU).
Research Methodology/design: A quasi-experimental study with a pretest-posttest design.
Setting: This study was conducted between January and February 2024 with nurses in two Indonesian PICUs.
Psychoneuroendocrinology
December 2024
Department of Psychological Science, University of Arkansas, Fayetteville, USA.
How does stress influence our decision-making? Although numerous studies have attempted to answer this question, their results have been inconsistent-presumably due to methodological heterogeneity. Drawing on cumulative prospect theory, we examined how acute stress influenced risky decision-making. To this end, we randomly assigned 147 participants to an acute stress induction or control condition and subsequently assessed participants' risky decision-making.
View Article and Find Full Text PDFWater Res
December 2024
MOE Key Laboratory of Pollution Processes and Environmental Criteria/Tianjin Engineering Center of Environmental Diagnosis and Contamination Remediation, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, PR China. Electronic address:
In aqueous environments, microplastics (MPs) undergo photoaging, releasing dissolved organic matter (DOM). Disinfection byproducts (DBPs) formation from natural organic matter (NOM) phototransformation has been reported. However, the impact of NOM on the photoaging of MPs (especially nitrogen-containing MPs) and subsequent nitrogenous DBPs (N-DBPs) formation remains unknown.
View Article and Find Full Text PDFPsychiatry Res
December 2024
Department of Psychiatry, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, PR China. Electronic address:
Background: Auditory verbal hallucinations (AVHs) in schizophrenia (SCZ) are linked to brain network abnormalities. Resting-state fMRI studies often assume stable networks during scans, yet dynamic changes related to AVHs are not well understood.
Methods: We analyzed resting-state fMRI data from 60 SCZ patients with persistent AVHs (p-AVHs), 39 SCZ patients without AVHs (n-AVHs), and 59 healthy controls (HCs), matched for demographics.
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