Look into a crowd and you’ll see a patchwork of unique faces—an assortment of skin tones and hair and eye colors, and noses, lips, and chins of different shapes and sizes. Each face is recognizable as a specific and individual person. Yet, in spite of this apparent distinctiveness, each face is still just one variation on a standard theme—eyes, noses, and mouths are generally placed in the same location on each of us.

The same is true of our brains. A stereotyped map of brain organization holds true from person to person: for example, the frontal lobes for higher-order thinking and planning reside just behind the forehead, the visual cortex is positioned in the back of the brain, and the auditory cortices sit along the sides. These lobes and other major anatomical landmarks of the brain are recognizable even in a newborn. Zooming in to examine the organization of...

A parsimonious account for this standard organization is that the blueprint for brain development is orchestrated by a genetic master plan. However, many experiments have demonstrated that while genes play an important role, they must interact significantly with the environment to sculpt brain structure and function. In fact, brain development may be largely self-organizing in response to environmental cues. For some scientists, it is the deviations from the master plan in response to atypical input from the environment that reveal the really intriguing aspects of how a brain is built.

When a major sense is absent from birth, the sensory regions adapt, processing input from other intact senses.

An important scientific approach to understanding the environmental influences on brain development is to investigate the organization of the sensory cortices in people with congenital deafness or blindness. When a major sense is absent from birth, during the period of time when the brain is most plastic, the sensory regions adapt, processing input from other intact senses. But the brain is not a tabula rasa, a blank slate, with any region able to do the work of another. Instead, it appears that the adapted cortex still maintains a degree of functional specialization, even when parts of it are processing other sensory modalities in place of the missing one. A persistent question has been how likely certain cortical areas, like the highly specialized primary sensory cortices, are to be colonized by other senses when the default sense is absent. Perhaps primary cortical areas are more constrained by the genetic blueprint. But a significant complication is the fact that, while overall brain organization is fairly standard across individuals, brain reorganization in the absence of a sense apparently is not.


In the trenches of clinical work, variability and uncertainty are the rule, and it can be difficult to predict who will do well with a particular intervention. For example, a cochlear implant, a device implanted surgically into the cochlea to directly stimulate an intact auditory nerve, can, under certain conditions, introduce a sense of sound to someone who is deaf. But there is substantial variability across individuals in the extent to which they learn to process the artificial sounds generated by a microphone and computer chip. Some of this variability may be in the integrity of the auditory nerve, but importantly, the diverse experiences of deaf individuals—ranging from well-studied factors such as the age at which they lost the ability to hear, to subtle factors such as their interests, talents, and activities—have likely contributed to different reorganizations of the auditory cortex that influence patient outcome.

An important step for future research is to determine precisely how variable brain plasticity is. The study of the extent to which touch and/or vision are processed in the auditory cortex of congenitally deaf adults offers some support for variability. In a recent study (J Neuro, 32: 9626-38, 2012), my colleagues and I found that Heschl’s gyrus, the site of human primary auditory cortex, responds to both touch and vision in adults who were born profoundly deaf, significantly more so than in hearing people. It would be easy to conclude from this average response across groups that a general principle of brain reorganization holds in every deaf person.  But we were also curious whether there might be perceptual consequences of a remapped brain. We took advantage of a visual trick called the double-flash illusion to probe the way touch and vision may interact in deaf people. In hearing people, previous research has shown that two beeps or two vibrations to the fingers paired with a single flash of light create the illusion of a second flash. We reasoned that if touch is a strong influence on the deaf auditory cortex, deaf people might show a stronger double-flash illusion response to two touches than hearing people. This is precisely what we found. But not all deaf people responded to the same extent—and it was those deaf people with the strongest response to touch in Heschl’s gyrus who reported the second flash most frequently.

We don’t know what factors in one congenitally deaf individual might lead him or her to have a stronger response to the illusion than another, but this variability might be useful information for clinicians. For example, if the auditory cortex is more committed to processing touch, it may impact how receptive the auditory cortex is to new auditory input from a cochlear implant. Information about how the brain remaps with experience could also be helpful for educational programs or occupational therapies. If an individual is highly responsive to touch, perhaps a tactile rather than visual assistive device would be the best choice.

In addition to informing potential clinical applications, one wonders whether individual variability in small sample sizes may account for some of the disparate findings in the scientific literature investigating neuroplasticity in deaf or blind brains. Human case studies are not adequate to capture variability. Animal studies are also, of necessity, based on small sample sizes, and it may be that failures to replicate results, which might be viewed as technical failures, are in fact examples of individual variability. A dialogue between clinicians and scientists about the extent of individual variability observed using different methodologies would go far in determining how to make the leap from scientific discovery to clinical application.

Christina Karns is currently a research associate at the University of Oregon in the Department of Psychology’s Brain Development Lab. She uses human neuroimaging to investigate how brain development is shaped by internal and external factors. 

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