Multimodality brain imaging
Section snippets
Background: neuroimaging of self-paced movement
To introduce the methodology, the findings with self-paced movements will be reviewed. Functional neuroimaging studies with positron emission tomography (PET) and fMRI show increased metabolism mainly in three cortical areas with simple self-paced movements [1], [2]. PET using O-15 water measures regional cerebral blood flow; this is a reasonable measure since synaptic activity increases local metabolism and stimulates changes in perfusion. fMRI most commonly uses the BOLD technique which
Example 1: brain activity associated with movements at different frequencies
Work by Kunesch et al. [9] has demonstrated that manipulative serial hand movements show a clear distribution of their temporal characteristics into two distinct groups. When the hand was used as a sense organ during active touch, the finger movements across objects were restricted to a slow performance range below 2 Hz. In contrast, manual skills not associated with the collection of sensory information like handwriting, typing or pencil shading, were performed rapidly at frequencies close to
Example 2: motor cortex activity in a no-go task
The go/no-go task is a popular experimental design, for the study of reaction time and studies of cognitive function and the motor system. It is basically a two-choice reaction time experiment. Subjects wait for one of two stimuli and then either move or do not move depending on which it is. The issue to be discussed here is what happens in the motor cortex in the no-go situation. There are several possibilities, but the two most likely are that the cortex does just nothing, or that it is
Conclusion
These examples demonstrate that multimodal brain imaging is much better than the use of only a single modality. In fact, a single modality might be actively misleading. Regions of the brain can be active and not show with PET or fMRI. EEG findings can be similar for excitation and inhibition. Putting all the methods together is not easy, and further methodological development is required, but it is already apparent that the multimodal approach will be very helpful in understanding human brain
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