Already this imaging capability has led to fundamental insights about normal and abnormal brains. For example, biologists have known for a long time that the human brain starts out with little myelin, and that the axons gradually myelinate over childhood and adolescence. The myelination process seems to be associated with learning. With diffusion tensor imaging, researchers can now see this process in living humans. For example, they can see which parts of the brain are associated with reading and language acquisition. People with higher IQs in general tend to have longer, skinnier diffusion ellipsoids, suggesting greater fiber integrity or a greater amount of myelination. The fiber integrity (or “fractional anisotropy”) seems to peak in the early 30s and gradually decreases thereafter; this may explain why memory and other cognitive processes decline gradually with age.

Likewise, diffusion tensor imaging points out areas of the white matter that are compromised in particular diseases. In schizophrenic patients, the fiber integrity is reduced in the part of the brain called the cingulate (responsible for error detection), the corpus callosum (responsible for communication between the brain hemispheres), and the frontal lobe. In autism, the deficits in fractional anisotropy occur in regions that are associated with processing social cues. Attention deficit hyperactivity disorder seems to be an exceptional case where the fractional anisotropy is too high rather than too low. And in concussion injuries, the fiber integrity is reduced near the site of the injury. This finding could be useful as both an objective criterion for diagnosis and a way of predicting which patients will suffer more serious long-term symptoms.

In the decade of the 2000s, research on diffusion tensor imaging took off, with the number of research papers doubling roughly every 2 years. Probably the most fundamental problem that remains is to distinguish when two fibers cross within a single cube (or “voxel,” the three-dimensional analogue of a pixel) of the image. It has been estimated that as many as 30 percent of the voxels in a diffusion tensor imaging scan have more than one fiber passing through them. Unfortunately, the standard diffusion tensor cannot detect this fact. An ellipsoid has only one longest axis, and it cannot have two separate “bumps.” If there are actually two fibers, diffusion tensor imaging will produce not two ellipsoids but a single, rounder ellipsoid. It will thus underestimate the fractional anisotropy in that voxel, and it may also draw the fiber pathways incorrectly.

One way to address the problem of crossing fibers would be to improve the resolution of the scans, so that each voxel is smaller. This would require MRI scanners with stronger magnetic fields—a trend that has continued throughout the past decade. But a less expensive alternative is to develop mathematical methods that would replace ellipsoids with more complicated diffusion surfaces. For example, a method called high angular resolution diffusion imaging (as shown in Figure 10 on page 28) combines magnetic resonance data with the principles of tomography, and it produces

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