scholarly journals An oscillator model better predicts cortical entrainment to music

2019 ◽  
Vol 116 (20) ◽  
pp. 10113-10121 ◽  
Author(s):  
Keith B. Doelling ◽  
M. Florencia Assaneo ◽  
Dana Bevilacqua ◽  
Bijan Pesaran ◽  
David Poeppel

A body of research demonstrates convincingly a role for synchronization of auditory cortex to rhythmic structure in sounds including speech and music. Some studies hypothesize that an oscillator in auditory cortex could underlie important temporal processes such as segmentation and prediction. An important critique of these findings raises the plausible concern that what is measured is perhaps not an oscillator but is instead a sequence of evoked responses. The two distinct mechanisms could look very similar in the case of rhythmic input, but an oscillator might better provide the computational roles mentioned above (i.e., segmentation and prediction). We advance an approach to adjudicate between the two models: analyzing the phase lag between stimulus and neural signal across different stimulation rates. We ran numerical simulations of evoked and oscillatory computational models, showing that in the evoked case,phase lag is heavily rate-dependent, while the oscillatory model displays marked phase concentration across stimulation rates. Next, we compared these model predictions with magnetoencephalography data recorded while participants listened to music of varying note rates. Our results show that the phase concentration of the experimental data is more in line with the oscillatory model than with the evoked model. This finding supports an auditory cortical signal that (i) contains components of both bottom-up evoked responses and internal oscillatory synchronization whose strengths are weighted by their appropriateness for particular stimulus types and (ii) cannot be explained by evoked responses alone.

Author(s):  
Eugenia Stanisauskis ◽  
Paul Miles ◽  
William Oates

Auxetic foams exhibit novel mechanical properties due to their unique microstructure for improved energy-absorption and cavity expansion applications that have fascinated the scientific community since their inception. Given the advancements in material processing and performance of polymer open cell auxetic foams, there is a strong desire to fully understand the nonlinear rate-dependent deformation of these materials. The influence of nonlinear compressibility is introduced here along with relaxation effects to improve model predictions for different stretch rates and finite deformation regimes. The viscoelastic behavior of the material is analyzed by comparing fractional order and integer order calculus models. All results are statistically validated using maximum entropy methods to obtain Bayesian posterior densities for the hyperelastic, auxetic, and viscoelastic parameters. It is shown that fractional order viscoelasticity provides [Formula: see text]–[Formula: see text] improvement in prediction over integer order viscoelastic models when the model is calibrated at higher stretch rates where viscoelasticity is more significant.


Neuroscience ◽  
2021 ◽  
Vol 453 ◽  
pp. 1-16
Author(s):  
Juliette Royer ◽  
Chloé Huetz ◽  
Florian Occelli ◽  
José-Manuel Cancela ◽  
Jean-Marc Edeline

2020 ◽  
Vol 6 (25) ◽  
pp. eaba0616 ◽  
Author(s):  
S. Janbaz ◽  
K. Narooei ◽  
T. van Manen ◽  
A. A. Zadpoor

Mechanical metamaterials are usually designed to exhibit novel properties and functionalities that are rare or even unprecedented. What is common among most previous designs is the quasi-static nature of their mechanical behavior. Here, we introduce a previously unidentified class of strain rate-dependent mechanical metamaterials. The principal idea is to laterally attach two beams with very different levels of strain rate-dependencies to make them act as a single bi-beam. We use an analytical model and multiple computational models to explore the instability modes of such a bi-beam construct, demonstrating how different combinations of hyperelastic and viscoelastic properties of both beams, as well as purposefully introduced geometric imperfections, could be used to create robust and highly predictable strain rate-dependent behaviors of bi-beams. We then use the bi-beams to design and experimentally realize lattice structures with unique strain rate-dependent properties including switching between auxetic and conventional behaviors and negative viscoelasticity.


2019 ◽  
Vol 317 (1) ◽  
pp. L39-L48
Author(s):  
Thien-Khoi N. Phung ◽  
Scott E. Sinclair ◽  
Patrudu Makena ◽  
Robert C. Molthen ◽  
Christopher M. Waters

Airway narrowing due to hyperresponsiveness severely limits gas exchange in patients with asthma. Imaging studies in humans and animals have shown that bronchoconstriction causes patchy patterns of ventilation defects throughout the lungs, and several computational models have predicted that these regions are due to constriction of smaller airways. However, these imaging approaches are often limited in their ability to capture dynamic changes in small airways, and the patterns of constriction are heterogeneous. To directly investigate regional variations in airway narrowing and the response to deep inspirations (DIs), we utilized tantalum dust and microfocal X-ray imaging of rat lungs to obtain dynamic images of airways in an intact animal model. Airway resistance was simultaneously measured using the flexiVent system. Custom-developed software was used to track changes in airway diameters up to generation 19 (~0.3–3 mm). Changes in diameter during bronchoconstriction were then measured in response to methacholine (MCh) challenge. In contrast with the model predictions, we observed significantly greater percent constriction in larger airways in response to MCh challenge. Although there was a dose-dependent increase in total respiratory resistance with MCh, the percent change in airway diameters was similar for increasing doses. A single DI following MCh caused a significant reduction in resistance but did not cause a significant increase in airway diameters. Multiple DIs did, however, cause significant increases in airway diameters. These measurements allowed us to directly quantify dynamic changes in airways during bronchoconstriction and demonstrated greater constriction in larger airways.


NANO ◽  
2016 ◽  
Vol 11 (07) ◽  
pp. 1650083 ◽  
Author(s):  
Sachin O. Gajbhiye ◽  
S. P. Singh

A unique atomic structure of carbon nanotube unveils outstanding properties. This makes it potentially highly valued reinforcing material to strengthen composite materials. The methodology is established in this research paper to investigate the static and dynamic characteristics of the nanocomposites. Repol polypropylene H110MA is used as a matrix material along with the different percentages of single-walled carbon nanotubes (SWCNTs). A concept of representative volume element (RVE) is considered to study the various properties of the nanocomposite material. The carbon–carbon bond of nanotube is modeled using Tersoff–Brenner potential and represented by space frame element. The matrix material properties are tested in the laboratory which are further used to model it and represented by three-dimensional continuum elements. The interaction between nanotube and polymer matrix is modeled using “Lennard–Jones 6-12” potential represented by nonlinear spring elements. The effect of reinforcement, chirality, % volume of SWCNT, atomic vacancy defect and Stone–Wales defect on the properties of nanocomposite are investigated. To see the effect of reinforcement, the eigenvalues of the RVE are extracted for different boundary conditions. The viscoplastic behavior of the matrix material is considered and the rate-dependent characteristics of the nanocomposite are studied. The damping property of the nanocomposite material is also investigated based on the phase lag between stress and strain field by applying harmonic strain at different frequencies.


1995 ◽  
Vol 117 (2) ◽  
pp. 91-99 ◽  
Author(s):  
M. Krarti ◽  
C. Lopez-Alonzo ◽  
D. E. Claridge ◽  
J. F. Kreider

An analytical model is developed to predict the annual variation of soil surface temperature from readily available weather data and soil thermal properties. The time variation is approximated by a first harmonic function characterized by an average, an amplitude, and a phase lag. A parametric analysis is presented to determine the effect of various factors such as evaporation, soil absorptivity, and soil convective properties on soil surface temperature. A comparison of the model predictions with experimental data is presented. The comparative analysis indicates that the simplified model predicts soil surface temperatures within ten percent of measured data for five locations.


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