Brain Development and Aging

Summary: According to researchers, brain signals in specific brain areas change during a lifespan in ways that could be vital for maintaining flexibility.

Source: University of Miami.

New study by UM psychologists reveals that brain signals in specific regions change over a lifespan in ways that might be important for maintaining flexibility.

The brain is a complex organ–a network of nerve cells, or neurons, producing thought, memory, action, and feeling. How does this complex system change from childhood to adulthood to late life in order to maintain optimal behavioral responses?

These questions were put to the test by a group of University of Miami psychologists who studied hundreds of fMRI brain scans, from two separate datasets, to see how the variability of brain signals changes or remains the same during a human lifespan.

The UM team analyzed hundreds of brain scans of participants, ranging in age from 6 to 86, who were all in a “resting state,” which means they were not engaged in any particular task while in the fMRI scanner. The publicly available data, which is freely available to neuroimaging researchers, was acquired from the Nathan-Kline institute.

“Resting state is a misnomer because intrinsically your brain is always doing something. There is always something happening in the brain,” said postdoctoral fellow Jason Nomi. “The scans we are looking at represent the baseline variability of ongoing activity in the brain at any given time. No one has really characterized this baseline across the lifespan.”

Lucina Uddin, an associate professor of psychology in the UM College of Arts and Sciences, explains that studying the brain when it’s in a resting state allows researchers to “basically look at the organization of the brain as it is without any extra stressors or stimuli. What we are looking at is the intrinsic organization of the brain and how it changes across the lifespan.”

By analyzing the resting-state fMRI data, the researchers were able to see how regions of the brain change from moment to moment and how those changes show a pattern across age and participants.

Their results demonstrated that, instead of an overall decrease in variability with aging, as earlier studies showed, the brain displayed regional differences, with some areas of the brain showing increases in variability across age while other areas showed a decrease.

“As certain areas of the brain become more variable, it seems to compensate in some ways for the other parts of the brain that are decreasing,” said Aaron Heller, an assistant professor in the Psychology Department and senior author of the paper.

Image shows a brain scan.

“These patterns of variability that we notice in the brain signals are what we think relates to the ability to respond to new challenges in the environment,” added Nomi.

Heller says that the next step is to test whether these patterns of variability have an impact on behavior in ways that are important to understanding lifespan, aging, emotional regulation, and developmental disorders such as autism.


Funding: The study, made possible with the help of a University of Miami Convergence Research Grant, is a collaborative effort of independent labs within the University of Miami Neuroimaging Facility within the Neuroscience Building on the Coral Gables campus.

Additional authors of the study include Taylor S. Bolt and Chiemeka Ezie in the Department of Psychology.

Source: Penny Smith – University of Miami
Image Source: image is adapted from the University of Miami news release.
Original Research: Abstract for “Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan” by Jason S. Nomi, Taylor S. Bolt, C.E. Chiemeka Ezie, Lucina Q. Uddin and Aaron S. Heller in Journal of Neuroscience. Published online May 31 2017 doi:10.1523/JNEUROSCI.3408-16.2017

University of Miami “Brain Development and Aging.” NeuroscienceNews. NeuroscienceNews, 5 June 2017.


Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan

Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study used resting-state fMRI data from a large sample of male and female human participants covering a wide age range (6–85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 s). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation.

SIGNIFICANCE STATEMENT Although brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan.

“Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan” by Jason S. Nomi, Taylor S. Bolt, C.E. Chiemeka Ezie, Lucina Q. Uddin and Aaron S. Heller in Journal of Neuroscience. Published online May 31 2017 doi:10.1523/JNEUROSCI.3408-16.2017

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