Complexity is perhaps one of the less properly understood concepts, even within the scientific community. Recent theoretical and experimental advances, however, based on the close relationship between the complexity of the system and the presence of 1/f fluctuations in its macroscopic behavior, have opened new domains of investigation, which consider fundamental questions as well as more applied perspectives. These approaches allow a better understanding of how essential macroscopic functions could emerge from complex interactive networks. In this review we present the current state of the theoretical debate about the origins of 1/f fluctuations, with special focus on recent hypotheses that establish a direct link between complexity and fractal fluctuations. Further, we clarify some lines of opposition, especially between idiosyncratic versus nomothetic conceptions, and global versus componential approaches. Finally, we discuss the deep questioning that this approach can generate with regard to current theories of motor control and psychological processes, as well as some future developments which may be evoked, especially in the domain of physical medicine and rehabilitation.
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http://dx.doi.org/10.1615/critrevbiomedeng.2013006727 | DOI Listing |
J Neural Eng
January 2025
Center for Complex Systems and Brain Sciences, Universidad Nacional de San Martin Escuela de Ciencia Y Tecnologia, 25 de Mayo y Francia, San Martín, Buenos Aires, 1650, ARGENTINA.
Objective Magnetic resonance imaging (MRI), functional MRI (fMRI) and other neuroimaging techniques are routinely used in medical diagnosis, cognitive neuroscience or recently in brain decoding. They produce three- or four-dimensional scans reflecting the geometry of brain tissue or activity, which is highly correlated temporally and spatially. While there exist numerous theoretically guided methods for analyzing correlations in one-dimensional data, they often cannot be readily generalized to the multidimensional geometrically embedded setting.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
The field of emotion recognition from physiological signals is a growing area of research with significant implications for both mental health monitoring and human-computer interaction. This study introduces a novel approach to detecting emotional states based on fractal analysis of electrodermal activity (EDA) signals. We employed detrended fluctuation analysis (DFA), Hurst exponent estimation, and wavelet entropy calculation to extract fractal features from EDA signals obtained from the CASE dataset, which contains physiological recordings and continuous emotion annotations from 30 participants.
View Article and Find Full Text PDFSci Rep
December 2024
State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210009, China.
The diagnostic and prognostic value of quantitative electroencephalogram (qEEG) in the the onset of postoperative delirium (POD) remains an area of inquiry. We aim to determine whether qEEG could assist in the diagnosis of early POD in cardiac surgery patients. We prospectively studied a cohort of cardiac surgery patients undergoing qEEG for evaluation of altered mental status.
View Article and Find Full Text PDFCogn Neurodyn
December 2024
University Larbi Tebessi, Tebessa, Algeria.
This paper introduces a novel class of chaotic attractors by lever- aging different activation functions within neurons possessing multiple dendrites. We propose a comprehensive framework where the activation functions in neurons are varied, allowing for diverse behaviors such as amplification, fluctuation, and folding of scrolls within the resulting chaotic attractors. By employing wavelet functions and other model-specific activation functions, we demonstrate the capability to modify scroll characteristics, including size and direction.
View Article and Find Full Text PDFChaos
December 2024
Department of Systems Biomedicine, School of Basic Medical Sciences, Shandong University, Jinan, Shandong 250012, China.
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