Sentence examples for measured time course from inspiring English sources

However, we observed systematic differences in the magnitude of the change in the BOLD signal with significantly stronger signal changes in field A1 of the auditory cortex compared to field R. The measured time course of the signal was in good agreement with similar studies in human auditory cortex but showed considerable differences to data reported from macaque visual cortex.

Then, we measured time course of both association and dissociation of Ca2+ to and from BRAC by mixing 1 volume of BRAC in Ca2+-free buffer with 25 volume of solution containing 1.69 µM Ca2+, and 1 volume of BRAC in 1.69 µM Ca2+ solution with 25 volume of Ca2+-free buffer, respectively.

To estimate the catalytic oxidation of coelenterazine-h by Rluc8 in BRAC, we measured time course of emission intensity change after mixing BRAC with 20 µM coelenterazine-h in Ca2+-free solution, and used the obtained data as a "base line".

The measured time course of subjects' button press responses associated with auditory target hits were convolved with a hemodynamic response function (HRF) for both the sparse and continuous imaging sessions.

The measured time course of LOX2 and VSP2 transcription (Fig. 2) is in good agreement with the time course of metabolite changes in the shoots [ 28].

Thirdly, using measured time course gene expression data from microarray experiments, we compute the Pearson correlation coefficient and Euclidean distance between the observed expression pattern and the predicted expression pattern.

The initial value problems were solved numerically for cyclic and step changes in stretch using model parameters (k0 = 3.0×10−4 sec−1, k1 = 1.8×103 sec−1, and τ = 0.5 sec) previously determined by fitting measured time courses of stress fiber alignment in non-confluent BAECs [7].

Note that predicted and measured time courses are in very good agreement without rescaling the time axis of the large-particle simulation.

Using these approaches, model parameters can be well fitted to measured time courses provided from either experiment (in vivo) or simulation (in silico), i.e. high quality fits with minimal residual values can be obtained by global optimization methods.

Preliminary data analyses indicated that the measured time courses of absolute tissue blood oxygenation, determined by the light amplitudes and phases from all four source-detector separations were too noisy to determine reliable time intervals for characterizing oxygen recovery, due to the unstable phase slopes over time.

We used the above expressions (Eqns. a – d ) in nonlinear least squares fitting to determine best-fit parameter values, i.e., the values of the model parameters (P, k and c) and initial condition (V0) that allow the model to most closely reproduce a given set of measured time courses.