Sentence examples for model of brain activity from inspiring English sources

The "SCARF" model of brain activity states that five experiences tend to provoke intense "fight-or-flight -style reactions.

By using the absolute value of the amplitude of the horizontal electro-ocular activity as a regressor in their model of brain activity, they showed that spontaneous electro-ocular activity elicits distributed patterns of activity in occipital and parietal cortices.

One possibility is to build a complete model map of brain activity by creating fleets of molecule-size machines to noninvasively act as sensors to measure and store brain activity at the cellular level.

In the multiple-subject model, the estimate of brain activity is directly obtained in the registered spherical space (inflated cortical surface).

In both the individual reconstructions and the random-effects model, an estimate of brain activity is obtained for both the group average and the individual subjects.

The model matched the pattern of brain activity with the correct photo 110 times out of 120 for Naselaris and 86 of 120 times for Kay.

The extensive presence of high-order chaos in a well-established physiological model of electrorhythmogenesis further emphasizes the applicability and relevance of mean field mesoscopic models in the description of brain activity at theoretical, experimental, and clinical levels.

A notable application of such network simulation approaches is to test disconnection hypotheses by simulating lesions in large-scale network models and observing alterations of brain activity as a result of these lesions.

For example, the three hypothesized symptom groups in the tripartite model reflect highly distinctive patterns of brain activity [ 59- 61].

The key feature of this model is not to necessarily reconstruct a more accurate group-level image (although we will show that this does occur), but rather to directly test the null hypothesis that two groups of subjects can be modeled by the same image of brain activity.

In this work, we describe an image reconstruction approach using a parametric Bayesian model that simultaneously reconstructs group-level images of brain activity in the context of a random-effects analysis.