We used a computational model of rhythmic movement to analyze how the connectivity of sensory feedback affects the tuning of a closed-loop neuromechanical system to the mechanical resonant frequency (omega(r)). Our model includes a Matsuoka half-center oscillator for a central pattern generator (CPG) and a linear, one-degree-of-freedom system for a mechanical component. Using both an open-loop frequency response analysis and closed-loop simulations, we compared resonance tuning with four different feedback configurations as the mechanical resonant frequency, feedback gain, and mechanical damping varied. The feedback configurations consisted of two negative and two positive feedback connectivity schemes. We found that with negative feedback, resonance tuning predominantly occurred when omega(r) was higher than the CPG's endogenous frequency (omega(CPG)). In contrast, with the two positive feedback configurations, resonance tuning only occurred if omega(r) was lower than omega(CPG). Moreover, the differences in resonance tuning between the two positive (negative) feedback configurations increased with increasing feedback gain and with decreasing mechanical damping. Our results indicate that resonance tuning can be achieved with positive feedback. Furthermore, we have shown that the feedback configuration affects the parameter space over which the endogenous frequency of the CPG or resonant frequency the mechanical dynamics dominates the frequency of a rhythmic movement.
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http://dx.doi.org/10.1007/s00422-007-0150-8 | DOI Listing |
Sci Rep
January 2025
Department of Electronics, Information and Communication Engineering, Kangwon National University, Samcheok, Republic of Korea.
Detecting brain tumours (BT) early improves treatment possibilities and increases patient survival rates. Magnetic resonance imaging (MRI) scanning offers more comprehensive information, such as better contrast and clarity, than any alternative scanning process. Manually separating BTs from several MRI images gathered in medical practice for cancer analysis is challenging and time-consuming.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.
Fano resonance is achieved by tuning two coupled oscillators and has exceptional potential for modulating light dispersion. Here, distinct from the classical Fano resonances achieved through photonics methodologies, we introduce the Fano resonance in epsilon-near-zero (ENZ) media with novel electromagnetic properties. By adjusting the background permeability of the ENZ host, the transmission spectrum exhibits various dispersive line shapes and covers the full range of Fano parameter q morphologies, from negative to positive infinity.
View Article and Find Full Text PDFBackground: Early detection and accurate forecasting of AD progression are crucial for timely intervention and management. This study leverages multi-modal data, including MRI scans, brain volumetrics, and clinical notes, utilizing Machine Learning (ML), Deep Learning (DL) and a range of ensemble methods to enhance the forecasting accuracy of Alzheimer's disease.
Method: We utilize the OASIS-3 longitudinal dataset, tracking 1,098 patients over 30 years.
Background: Connected speech has been explored as a possible marker for Alzheimer's disease (AD) by employing language models based on machine learning. However, most previous approaches are based on scene description tasks, and it is unclear how different types of connected speech and differences across subjects' speech relate to changes in their brains.
Method: We analyzed transcripts of Flemish Dutch connected speech from interviews from 74 cognitively healthy elderly adults (mean MMSE = 28.
Nano Lett
January 2025
State Key Laboratory of Solidification Processing, Center of Advanced Lubrication and Seal Materials, School of Materials Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, P.R. China.
Plasmonic superlattices enable the precise manipulation of electromagnetic fields at the nanoscale. However, the optical properties of static lattices are dictated by their geometry and cannot be reconfigured. Here, we present a surface-interface engineered plasmonic superlattice with confined polyelectrolyte-functionalized metal-organic framework (MOF) hybrid layers to tune plasmon resonance for ultrafast chemical sensing.
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