New neural-redundancy metric accurately detects mild cognitive impairment

Redundant brain pathways can serve as pre-symptomatic indicators of mild cognitive impairment (MCI) in aging individuals, allowing care teams to design first-line neuropsychological exercises for slowing the possible approach of Alzheimer’s disease.

The phenomenon of neural redundancy is established but has been newly confirmed by radiology researchers with the University of North Carolina at Chapel Hill.

Publishing their findings in Human Brain Mapping March 10, the team describes their use of a novel metric for showing when and where neural redundancy is activated on functional MRI.

The term “neural redundancy,” or “network redundancy,” refers to the brain’s substitution of a healthy region for transmitting signals when the region that normally handles the task slows or stalls.  

In the present study, Pew-Thian Yap, PhD, and colleagues set out to “overcome the limitations of previous studies and offer a more comprehensive account of redundancy.”

Toward that end the team steered clear of previous approaches that cast a wide net over all possible connections between nodes. Instead, they considered only redundant connections without common nodes.

“As removing a node shared by multiple connections causes the loss of all connections, our metric therefore accounts for truly redundant connections, partial removal of which will still ensure network integrity,” the authors explain.

Using the term 2-connected network to define a network with at least two redundant connections between each pair of activated regions, Yap and co-researchers examined changes in global redundancy associated with the progression of Alzheimer’s disease.

Upon doing so, the team observed that the whole-brain networks of MCI individuals are more likely to be 2-connected than the networks of normal controls and individuals with Alzheimer’s disease.

The data Yap and colleagues used in the research was resting-state fMRI data in the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

They drew from the records of 49 MCI patients, 49 Alzheimer’s patients and 49 healthy controls.

Yap et al. suggest their key contribution to the science was demonstrating the utility of their novel redundancy metric in differentiating the stages of Alzheimer’s disease as it visibly progresses on imaging:

To delineate the redundancy profile during Alzheimer’s disease progression and enable better MCI diagnosis, we define a metric that reflects redundant disjoint connections between brain regions and extract redundancy features in three high-order brain networks—medial frontal, frontoparietal, and default mode networks—based on dynamic functional connectivity (dFC) captured by resting-state functional magnetic resonance imaging (rs-fMRI).”

The team emphasizes their results’ support of brain-wiring redundancy as a neuroprotective mechanism in aging-related cognitive decline.

“Since MCI subjects are at high risk of converting to Alzheimer’s disease, identifying MCI individuals is essential for early intervention,” they write. “By taking advantage of the high sensitivity of our metric, we showed that MCI can be detected with high accuracy.”

The study is available in full for free.

Dave Pearson

Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.

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