gib
So with the mind intro out of the way let us focus on a scan. No need to respond to this post because I need to tie a few things together in a simpler way.
It might seem strange to be looking at intermediate information before the simple explanations but it is the best way for me to explain it . . .
That is a great idea actually gib.
Sneak preview . . .
DTI Color Map
OK . . . this will take a few passes to get right. The mind and brain work differently - that is the truth for this pass.
In this pass let us briefly cover a few things.
The Synapse
In the brain we need to look at synaptic connections. It is widely accepted that the synapse plays a role in the formation of memory.
As neurotransmitters activate receptors across the synaptic cleft, the connection between the two neurons is strengthened when both neurons are active at the same time, as a result of the receptor’s signaling mechanisms.
fMRI
Functional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. 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.
The primary form of fMRI uses the blood-oxygen-level dependent (BOLD) contrast, discovered by Seiji Ogawa.
As we can now tell there are different forms of fMRI - we start at a low resolution:
These fMRI images are from a study showing parts of the brain lighting up on seeing houses and other
parts on seeing faces. The ‘r’ values are correlations, with higher positive or negative values
indicating a better match.
Statistics
Now we wonder how we can get higher resolution and mathematics holds the key as usual: Statistical inference uses mathematics to draw conclusions in the presence of uncertainty. There is much uncertainty in low resolution imaging.
Tensors
When using Diffusion MRI as opposed to fMRI we can apply Diffusion tensor imaging (DTI) which is an MRI technique that enables the measurement of the restricted diffusion of water in tissue in order to produce neural tract images instead of using this data solely for the purpose of assigning contrast or colors to pixels in a cross sectional image.
Lets start with low resolution DTI:
Visualization of DTI data with ellipsoids.
A more precise statement of the image acquisition process is that the image-intensities at each position are attenuated, depending on the strength (b-value) and direction of the so-called magnetic diffusion gradient, as well as on the local microstructure in which the water molecules diffuse.
The principal application is in the imaging of white matter where the location, orientation, and anisotropy of the tracts can be measured. The architecture of the axons in parallel bundles, and their myelin sheaths, facilitate the diffusion of the water molecules preferentially along their main direction. Such preferentially oriented diffusion is called anisotropic diffusion.
Tractographic reconstruction of neural connections via DTI
- Diffusion MRI relies on the mathematics and physical
interpretations of the geometric quantities known as tensors.
Only a special case of the general mathematical notion is relevant to imaging, which is based on the concept of a symmetric matrix. Diffusion itself is tensorial, but in many cases the objective is not really about trying to study brain diffusion per se, but rather just trying to take advantage of diffusion anisotropy in white matter for the purpose of finding the orientation of the axons and the magnitude or degree of anisotropy.
Matrices
The following matrix displays the components of the diffusion tensor:
Sources: Wikipedia