NIH Blueprint: The Human Connectome Project

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Recommended Reading | September 14, 2010

Using fMRI to Predict Brain Maturity

One of the key missions of the study of brain imaging data is to be able to read into the landscape of the brain itself, and literally see whether or not it has fundamental weaknesses that might lead to brain diseases. A new article published in Science Magazine and co-authored by several HCP Investigators — Steve Petersen, Deanna Barch, Jonathan Power, Gagan Wig, and led by Brad Schlaggar — tries to advance this field by asking: can a single fMRI scan give us enough information to classify and make predictions about that individual?

The work described here had two major objectives. The first aim was to develop an approach for making accurate predictions about individuals on the basis of single fMRI scans. The second aim, building on the first, was to further illuminate typical brain development, a prerequisite for studying developmental disorders and pediatric-onset neuropsychiatric diseases (2, 3).

These researchers used multivariate pattern analysis tools (MVPA), a successfully established method of parsing brain activity during task-based activities: mapping the process of memory retrieval, or understanding how the mind associates meaning with nouns.

Fig 1: Functional Brain Maturation Curve

However, they faced an interesting challenge when working with a pre-adolescent subject group — the unpredictablity of task performance — and are pushing the envelope of MVPA by applying it to resting-state functional connectivity MRI (rs-fcMRI), which can be gathered quickly and easily during times of rest.

The visual results of this pattern analysis are both striking and informative, as the researchers use functional connectivity data to determine measure the subject’s “brain age,” and to chart the maturation process from birth to full adulthood (age 30). This type of data visualization (Fig 1) allows researchers to characterize the typical trajectory of maturation as a biological growth curve.

However, a new view of brain activity emerges if we map the functional connectivity MVPA data over the actual landscape of the brain itself (Fig 2), and we get to see first-hand how the brain changes functionally as we mature.

Fig 2: fcMVPA connection and region weights.

Read the full article: Science Magazine: Prediction of Individual Brain Maturity Using fMRI

Science 10 September 2010:
Vol. 329. no. 5997, pp. 1358 – 1361
DOI: 10.1126/science.1194144