scholarly journals “Online” modulation of brain hemodynamics despite stereotyped running

2020 ◽  
Author(s):  
Antoine Bergel ◽  
Elodie Tiran ◽  
Thomas Deffieux ◽  
Charlie Demené ◽  
Mickaël Tanter ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Metabolic Cost ◽  
Large Cell ◽  
Stereotyped Behavior ◽  
Running Speed ◽  
Strongly Coupled ◽  
Neurovascular Interactions ◽  
Multiple Structures ◽  
Brain Hemodynamics ◽  
Adaptation Processes

AbstractTheta and gamma rhythms coordinate large cell assemblies during locomotion. Their spread across temporal and spatial scales makes them challenging to observe. Additionally, the metabolic cost of these oscillations and their contribution to neuroimaging signals remains elusive. To finely characterize neurovascular interactions in running rats, we monitored brain hemodynamics with functional ultrasound and hippocampal local field potentials in running rats. Theta rhythm and running speed were strongly coupled to brain hemodynamics in multiple structures, with delays ranging from 0.8 seconds to 1.8 seconds. Surprisingly, hemodynamics was also strongly modulated across trials within the same recording session: cortical hemodynamics sharply decreased after 5-10 runs, while hippocampal hemodynamics strongly and linearly potentiated, particularly in the CA regions. This effect occurred while running speed and theta activity remained constant, and was accompanied by increased power in hippocampal high-frequency oscillations (100-150 Hz). Our findings reveal distinct vascular subnetworks modulated across fast and slow timescales and suggest strong adaptation processes despite stereotyped behavior.

scholarly journals Adaptive modulation of brain hemodynamics across stereotyped running episodes

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Antoine Bergel ◽  
Elodie Tiran ◽  
Thomas Deffieux ◽  
Charlie Demené ◽  
Mickaël Tanter ◽  
...  
Keyword(s):  
Blood Flow ◽  
Primary Motor Cortex ◽  
Adaptive Modulation ◽  
Metabolic Cost ◽  
Brain Structures ◽  
Stereotyped Behavior ◽  
Retrosplenial Cortex ◽  
Dorsal Thalamus ◽  
Neurovascular Interactions ◽  
Brain Hemodynamics

AbstractDuring locomotion, theta and gamma rhythms are essential to ensure timely communication between brain structures. However, their metabolic cost and contribution to neuroimaging signals remain elusive. To finely characterize neurovascular interactions during locomotion, we simultaneously recorded mesoscale brain hemodynamics using functional ultrasound (fUS) and local field potentials (LFP) in numerous brain structures of freely-running overtrained rats. Locomotion events were reliably followed by a surge in blood flow in a sequence involving the retrosplenial cortex, dorsal thalamus, dentate gyrus and CA regions successively, with delays ranging from 0.8 to 1.6 seconds after peak speed. Conversely, primary motor cortex was suppressed and subsequently recruited during reward uptake. Surprisingly, brain hemodynamics were strongly modulated across trials within the same recording session; cortical blood flow sharply decreased after 10–20 runs, while hippocampal responses strongly and linearly increased, particularly in the CA regions. This effect occurred while running speed and theta activity remained constant and was accompanied by an increase in the power of hippocampal, but not cortical, high-frequency oscillations (100–150 Hz). Our findings reveal distinct vascular subnetworks modulated across fast and slow timescales and suggest strong hemodynamic adaptation, despite the repetition of a stereotyped behavior.

scholarly journals Brain pathology recapitulates physiology: A network meta-analysis

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Thomas J. Vanasse ◽  
Peter T. Fox ◽  
P. Mickle Fox ◽  
Franco Cauda ◽  
Tommaso Costa ◽  
...  
Keyword(s):  
Network Architecture ◽  
Spatial Scales ◽  
Meta Analysis ◽  
Metabolic Cost ◽  
Common Mechanism ◽  
Brain Disorders ◽  
Brain Pathology ◽  
Structural Network ◽  
Meta Analyses ◽  
Function Network

AbstractNetwork architecture is a brain-organizational motif present across spatial scales from cell assemblies to distributed systems. Structural pathology in some neurodegenerative disorders selectively afflicts a subset of functional networks, motivating the network degeneration hypothesis (NDH). Recent evidence suggests that structural pathology recapitulating physiology may be a general property of neuropsychiatric disorders. To test this possibility, we compared functional and structural network meta-analyses drawing upon the BrainMap database. The functional meta-analysis included results from >7,000 experiments of subjects performing >100 task paradigms; the structural meta-analysis included >2,000 experiments of patients with >40 brain disorders. Structure-function network concordance was high: 68% of networks matched (pFWE < 0.01), confirming the broader scope of NDH. This correspondence persisted across higher model orders. A positive linear association between disease and behavioral entropy (p = 0.0006;R2 = 0.53) suggests nodal stress as a common mechanism. Corroborating this interpretation with independent data, we show that metabolic ‘cost’ significantly differs along this transdiagnostic/multimodal gradient.

scholarly journals PREDICTING RETRO WALKING/RUNNING SPEED FROM METABOLIC COST OF FORWARD RUNNING.

1998 ◽  
Vol 30 (Supplement) ◽  
pp. 59
Author(s):  
S. Ready ◽  
J. Lahr ◽  
D. Bacharach
Keyword(s):  
Metabolic Cost ◽  
Running Speed

scholarly journals Multivariate localization functions for strongly coupled data assimilation in the bivariate Lorenz ’96 system

2021 ◽  
Author(s):  
Zofia Stanley ◽  
Ian Grooms ◽  
William Kleiber
Keyword(s):  
Data Assimilation ◽  
Spatial Scales ◽  
Background Error ◽  
Strongly Coupled ◽  
Localization Function ◽  
Background Error Covariance ◽  
Error Covariance ◽  
Coupled Data Assimilation ◽  
Lorenz 96 ◽  
The Impact

Abstract. Localization is widely used in data assimilation schemes to mitigate the impact of sampling errors on ensemble-derived background error covariance matrices. Strongly coupled data assimilation allows observations in one component of a coupled model to directly impact another component through inclusion of cross-domain terms in the background error covariance matrix. When different components have disparate dominant spatial scales, localization between model domains must properly account for the multiple length scales at play. In this work we develop two new multivariate localization functions, one of which is a multivariate extension of the fifth-order piecewise rational Gaspari-Cohn localization function; the within-component localization functions are standard Gaspari-Cohn with different localization radii while the cross-localization function is newly constructed. The functions produce non-negative definite localization matrices, which are suitable for use in variational data assimilation schemes. We compare the performance of our two new multivariate localization functions to two other multivariate localization functions and to the univariate analogs of all four functions in a simple experiment with the bivariate Lorenz '96 system. In our experiment the multivariate Gaspari-Cohn function leads to better performance than any of the other localization functions.

scholarly journals Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution

2016 ◽  
Author(s):  
Xueling Liu ◽  
Arthur P. Mizzi ◽  
Jeffrey L. Anderson ◽  
Inez Fung ◽  
Ronald C. Cohen
Keyword(s):  
Data Assimilation ◽  
Spatial Resolution ◽  
Spatial Scales ◽  
Weather Forecast ◽  
Point Sources ◽  
Short Time Scale ◽  
Strongly Coupled ◽  
Meteorological Observations ◽  
High Space ◽  
Short Time

Abstract. Observations of trace gases from space based instruments offer the opportunity to constrain chemical and weather forecast and reanalysis models using the tools of data assimilation. To date, attempts at assimilation of nitrogen dioxide (NO2) satellite remote sensing have focused on updating emissions and concentrations. These initial efforts evaluated updates at length scales of ~ 100 km using once a day measurements from satellites with ground pixels of 13 km × 24 km or larger. In the boundary layer, NO2 has a lifetime on the order of five hours and corresponding 1/e concentration variations near urban and point sources occur on spatial scales on the order of 50–75 km. Accurate observations and modeling of these variations require spatial resolution of order 4 km. In addition, because of the short lifetime, NO2 variations are more strongly coupled to short time scale meteorological parameters than longer lived chemicals such as CO or CO2. In the next few years, we anticipate the launch of several instruments with ~ 3 km spatial resolution. In addition, some of these instruments will be in geostationary orbits and thus have hourly revisit times. In anticipation of these instruments, we investigate the potential of high space and time resolution column measurements to serve as constraints on urban NOx emissions using a geostationary observation simulator coupled to a data assimilation system. We find that constraints on emissions are strongest in regions with high emissions and are most effective when coupled to hourly assimilation of meteorological observations. We find that errors in the meteorological fields result in unrecoverable biases in the updated emissions confirming a conjecture that simultaneous meteorology and chemical assimilation is essential to accurate description of the emissions and chemistry.

scholarly journals Multivariate localization functions for strongly coupled data assimilation in the bivariate Lorenz 96 system

2021 ◽  
Vol 28 (4) ◽  
pp. 565-583
Author(s):  
Zofia Stanley ◽  
Ian Grooms ◽  
William Kleiber
Keyword(s):  
Data Assimilation ◽  
Spatial Scales ◽  
Background Error ◽  
Strongly Coupled ◽  
Localization Function ◽  
Background Error Covariance ◽  
Error Covariance ◽  
Coupled Data Assimilation ◽  
Lorenz 96 ◽  
The Impact

Abstract. Localization is widely used in data assimilation schemes to mitigate the impact of sampling errors on ensemble-derived background error covariance matrices. Strongly coupled data assimilation allows observations in one component of a coupled model to directly impact another component through the inclusion of cross-domain terms in the background error covariance matrix. When different components have disparate dominant spatial scales, localization between model domains must properly account for the multiple length scales at play. In this work, we develop two new multivariate localization functions, one of which is a multivariate extension of the fifth-order piecewise rational Gaspari–Cohn localization function; the within-component localization functions are standard Gaspari–Cohn with different localization radii, while the cross-localization function is newly constructed. The functions produce positive semidefinite localization matrices which are suitable for use in both Kalman filters and variational data assimilation schemes. We compare the performance of our two new multivariate localization functions to two other multivariate localization functions and to the univariate and weakly coupled analogs of all four functions in a simple experiment with the bivariate Lorenz 96 system. In our experiments, the multivariate Gaspari–Cohn function leads to better performance than any of the other multivariate localization functions.

Metabolic energy and muscular activity required for leg swing in running

2005 ◽  
Vol 98 (6) ◽  
pp. 2126-2131 ◽  
Author(s):  
Jesse R. Modica ◽  
Rodger Kram
Keyword(s):  
Stance Phase ◽  
Muscular Activity ◽  
Metabolic Cost ◽  
Rectus Femoris ◽  
Swing Phase ◽  
Metabolic Energy ◽  
Medial Gastrocnemius ◽  
Running Speed ◽  
Pulling Forces ◽  
The Cost

The metabolic cost of leg swing in running is highly controversial. We investigated the cost of initiating and propagating leg swing at a moderate running speed and some of the muscular actions involved. We constructed an external swing assist (ESA) device that applied small anterior pulling forces to each foot during the first part of the swing phase. Subjects ran on a treadmill at 3.0 m/s normally and with ESA forces up to 4% body weight. With the greatest ESA force, net metabolic rate was 20.5% less than during normal running. Thus we infer that the metabolic cost of initiating and propagating leg swing comprises ∼20% of the net cost of normal running. Even with the greatest ESA, mean electromyograph (mEMG) of the medial gastrocnemius and soleus muscles during later portions of stance phase did not change significantly compared with normal running, indicating that these muscles are not responsible for the initiation of leg swing. However, with ESA, rectus femoris mEMG during the early portions of swing phase was as much as 74% less than during normal running, confirming that it is responsible for the propagation of leg swing.

High spatial resolution x-ray microanalysis of interfaces

1995 ◽  
Vol 53 ◽  
pp. 284-285
Author(s):  
J. R. Michael
Keyword(s):  
Spatial Resolution ◽  
Electron Probe ◽  
Solid Angle ◽  
Collection Efficiency ◽  
Spatial Scales ◽  
Energy Dispersive Spectrometer ◽  
X Rays ◽  
X Ray ◽  
Probe Size ◽  
Brightness Field

X-ray microanalysis in the analytical electron microscope (AEM) refers to a technique by which chemical composition can be determined on spatial scales of less than 10 nm. There are many factors that influence the quality of x-ray microanalysis. The minimum probe size with sufficient current for microanalysis that can be generated determines the ultimate spatial resolution of each individual microanalysis. However, it is also necessary to collect efficiently the x-rays generated. Modern high brightness field emission gun equipped AEMs can now generate probes that are less than 1 nm in diameter with high probe currents. Improving the x-ray collection solid angle of the solid state energy dispersive spectrometer (EDS) results in more efficient collection of x-ray generated by the interaction of the electron probe with the specimen, thus reducing the minimum detectability limit. The combination of decreased interaction volume due to smaller electron probe size and the increased collection efficiency due to larger solid angle of x-ray collection should enhance our ability to study interfacial segregation.

Laser scanning confocal microscopic analysis of cytoskeletal and nuclear reorganization in live Drosophila embryos

1993 ◽  
Vol 51 ◽  
pp. 174-175
Author(s):  
William Theurkauf
Keyword(s):  
Laser Scanning ◽  
Microscopic Analysis ◽  
Large Cell ◽  
Early Embryo ◽  
Drosophila Embryo ◽  
Cortical Actin ◽  
Nuclear Reorganization ◽  
Cytoskeletal Elements ◽  
Microtubule Structure ◽  
Drosophila Embryos

Cell division in eucaryotes depends on coordinated changes in nuclear and cytoskeletal components. In Drosophila melanogaster embryos, the first 13 nuclear divisions occur without cytokinesis. During the final four divisions, nuclei divide in a uniform monolayer at the surface of the embryo. These surface divisions are accompanied by dramatic changes in cortical actin and microtubule structure (Karr and Alberts, 1986), and inhibitor studies indicate that these changes are essential to orderly mitosis (Zalokar and Erk, 1976). Because the early embryo is syncytial, fluorescent probes introduced by microinjection are incorporated in structures associated with all of the nuclei in the blastoderm. In addition, the nuclei divide synchronously every 10 to 20 min. These characteristics make the syncytial blastoderm embryo an excellent system for the analysis of mitotic reorganization of both nuclear and cytoskeletal elements. However, the Drosophila embryo is a large cell, and resolution of cytoskeletal filaments and nuclear structure is hampered by out-of focus signal.

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