Detailed analysis of the functional connectivity of an individual brain

In a new paper just out in Neuron, researchers Timothy Laumann and colleagues present an in-depth look at a single human brain.

The brain in question belongs to neuroscientist Russ Poldrack, and he’s one of the authors of the paper. Poldrack was fMRI scanned a total of 84 times over a period of 532 days. The goal of this intense scanning schedule was to provide a detailed analysis of the functional connectivity of an individual brain...

On the other hand, to understand an individual brain, one scan is not enough, because “an observed pattern of functional brain organization in an individual may reflect persistent traits shaped by development and genetics, but may also relate to current state or environmental effects.”  Hence this study.

So what did they find? One important result was that the degree of session-to-session (within subject) variability in connectivity was higher in some brain regions than in others:

Within-subject variability was non-uniformly distributed across systems, with higher variability observed in correlations within and between somatomotor and visual regions. Relatively less variability was observed between frontoparietal, default mode, ventral attention, and medial parietal regions.

It’s notable that while visual cortex connectivity is one of the most variable networks in Poldrack’s brain, it’s one of the most stable across individuals.,,

We don’t know whether this pattern of variability is, itself, invariant across subjects, or whether Poldrack’s visual cortex is just unusually variable.

Laumann et al. performed several other analyses, on Poldrack’s data and also on data from Nico Dosenbach (another of the authors, who was scanned ten times). However, they refrain from reading too much into the results, concluding that

Any study reporting observations in one or two subjects has necessarily limited generality… Therefore, we do not assign specific meaning to the detailed features observed here. However, we believe that the reliable presence of these detailed features in each individual must motivate further studies of this type…
In particular, we believe that the subject-specific approach outlined here may be essential for understanding the functional brain organization of unique or rare subjects (e.g., cognitive savants, rare disease populations, or brain-injured subjects like H.M.).

Then again, convincing these patients to undergo dozens of MRI scans might be tricky, though, and so would finding money to pay for them.

http://blogs.discovermagazine.com/neuroskeptic/2015/08/02/a-close-look-at-the-connectivity-of-a-single-brain/#.VcC79GRVikp
Courtesy of:  http://www.medpagetoday.com/Neurology/GeneralNeurology/52922?xid=nl_mpt_DHE_2015-08-05&eun=g906366d0r

Laumann TO, Gordon EM, Adeyemo B, Snyder AZ, Joo SJ, Chen MY, Gilmore AW,
McDermott KB, Nelson SM, Dosenbach NU, Schlaggar BL, Mumford JA, Poldrack RA,
Petersen SE. Functional System and Areal Organization of a Highly Sampled
Individual Human Brain. Neuron. 2015 Jul 22. pii: S0896-6273(15)00600-5. doi:
10.1016/j.neuron.2015.06.037. [Epub ahead of print]

Abstract

Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected-considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individual's systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals.