Search results
Results From The WOW.Com Content Network
Functional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. [1] [2] This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases. [3]
Main limitations of fMRS are related to signal sensitivity and the fact that many metabolites of potential interest can not be detected with current fMRS techniques. Because of limited spatial and temporal resolution fMRS can not provide information about metabolites in different cell types, for example, whether lactate is used by neurons or by ...
"afni_proc.py" is a pre-made script that will run fMRI data from a single subject through a series of pre-processing steps, starting with the raw data. The default settings will perform the following pre-processing steps and finish with a basic regression analysis: [8] Slice timing: [9] Each 3D brain image is composed of multiple 2D images ...
Functional magnetic resonance imaging data. Functional neuroimaging is the use of neuroimaging technology to measure an aspect of brain function, often with a view to understanding the relationship between activity in certain brain areas and specific mental functions.
When fMRI was developed one of its major limitations was the inability to randomize trials, but the event related fMRI fixed this problem. [2] Cognitive subtraction was also an issue, which tried to correlate cognitive-behavioral differences between tasks with brain activity by pairing two tasks that are assumed to be matched perfectly for ...
A model of interacting neural populations is specified, with a level of biological detail dependent on the hypotheses and available data. This is coupled with a forward model describing how neural activity gives rise to measured responses. Estimating the generative model identifies the parameters (e.g. connection strengths) from the observed data.
Parametric statistical models are assumed at each voxel, using the general linear model to describe the data variability in terms of experimental and confounding effects, with residual variability. Hypotheses expressed in terms of the model parameters are assessed at each voxel with univariate statistics.
As "Prospects of fMRI as a Lie Detector" [9] states, fMRIs use electromagnets to create pulse sequences in the cells of the brain. The fMRI scanner then detects the different pulses and fields that are used to distinguish tissue structures and the distinction between layers of the brain, matter type, and the ability to see growths.