Big Data on Healthy Brain Aging – Dana Foundation

Big Data on Healthy Brain Aging – Dana Foundation

Some people are resilient to the ravages of age, while others are particularly susceptible, developing Alzheimer’s disease or another form of dementia. For most of us, however, getting older involves a gradual reduction in brain volume, accompanied by an apparently inexorable decline in mental functions.

Exactly how the brain changes with age, and why some people are affected more by aging than others, is still unclear. Researchers discussed recent developments in the field and described new ways of investigating how the brain changes during healthy aging during a symposium at the annual meeting of the Society for Neuroscience, held in San Diego last month. 

Psychologist Carol Barnes of the University of Arizona discussed the cellular changes that occur with healthy aging, and how they are related to mental function and behavior. Until recently, scientists assumed that age-related cognitive declines in wayfinding and distinguishing similar objects occurred because neurons were dying in the hippocampus and other parts of the brain such as the prefrontal cortex.

That view has now changed; researchers are now explaining these changes in terms of alterations in neuronal networks, not cell death. In this view, forming a memory involves strengthening synaptic connections within sparsely distributed networks of hippocampal neurons via a mechanism called long-term potentiation; memory recall likely requires the reactivation of the same network that encoded the memory in the first place. [See: Probing the Workings of Human Brain Cells]

“We now know that we keep the same number of hippocampal cells across our entire lifespan, and that the cells remain healthy,” says Barnes, a member of the Dana Alliance for Brain Initiatives. “But there’s a substantial loss of functional synapses, and data from my lab suggests that there’s also some axonal pruning going on.”

Barnes explained that there is remarkable consistency in cognitive aging across species. Many of the other species examined—including rodents, dogs, and monkeys—experience the same age-related problems as we do, and this gives researchers the opportunity to generate animal models to learn more about brain changes underlying cognitive decline.

Barnes’s research has shown long-term potentiation is impaired in aged rats, and that this is associated with worsened memory performance. Others have reported that hippocampal neurons from old rats are more susceptible to long-term depression—another form of plasticity in which connections are weakened—than are cells from younger ones.

Barnes and her colleagues have also published evidence that reactivation of hippocampal networks gradually weakens with age in rats, and that this is closely linked to worsened performance on spatial memory tests. They also have found that aged mice exhibit deficits in pattern separation, the process by which the brain distinguishes between activity patterns generated by overlapping but distinct networks of hippocampal neurons. Equivalent changes in the human brain could explain why older people often have trouble navigating and distinguishing between similar objects or events.

As well as being central to normal age-related cognitive decline, the hippocampus is also the first brain region to degenerate in Alzheimer’s disease. Yet, our knowledge of how networks of hippocampal neurons encode and retrieve memories, and contribute to processes such as spatial navigation and pattern separation, is still rudimentary.

Giorgio Ascoli, George Mason University in Fairfax, VA, described his approach of using neuroinformatics to gain a better understanding of how the structure and function of the hippocampus changes during healthy aging brain.

 “The nervous system is spectacularly diverse and complex in both structure and function,” says Ascoli, “and one of our key goals is to describe the function of the hippocampus at the level of neurons and synapses.”

Ascoli aims to characterize the diversity of cell types in the hippocampus and map how they connect to each other. He and his colleagues have compiled a comprehensive database of hippocampal neurons, which characterizes each type of cell on the basis of approximately 20,000 different parameters derived from their anatomical structure, functional properties, and other measures.

“We collated all the published data about cell types in the hippocampus and their connections, and put them into a large table that took years to assemble,” said Ascoli. The data, available online for free at, reveal just how diverse and complex the brain really is.

The hippocampus is traditionally divided into 5 or 6 subfields, each containing the same repertoire of perhaps a dozen basic cell types. But according to Ascoli’s database, the rodent hippocampus can be subdivided into 26 smaller sub-regions, and contains well over 100 different types of neurons.    

 “We’re still quality controlling the entries so you can’t run it yourself yet,” says Ascoli, “but there’s already a tremendous amount of information in there, and we’re planning a beta release within the coming year.” Eventually, the database should provide detailed information about how networks of hippocampal neurons are altered with age.

Apostolos Georgopoulos of the University of Minnesota, who chaired the symposium, offered another bioinformatics-based approach—the Brain Health Index, a test battery that produces a set of measurements that provide information about the state of health of the brain.

The Brain Health Index was developed as part of the University of Minnesota’s Healthy Brain Project, a large-scale, long-term study that aims to advance our understanding of how the brain changes across the lifespan. Each participant undergoes various procedures, including brain imaging with multiple techniques, DNA testing for genetic assessment, and memory and language tests. The data sets are integrated with information about lifestyle obtained from medical records, and then analyzed to derive a measure of brain health.

 “The Brain Index is a simple measure calculated by statistical analysis of multimodal imaging data,” explained Georgopoulos, also a member of the Dana Alliance for Brain Initiatives. “Larger population sizes and the number of modalities assessed will help validate the Index in various groups and different conditions.” The project is now in its third year, and so far Georgopoulos and his colleagues have tested 200 healthy people, 20 of whom have undergone the same tests for three consecutive years.

The Healthy Brain Project and are just two examples of the recent shift towards such big data projects, which aim to amass large amounts of information about various aspects of brain structure and function. But as Ascoli says, data collection is just the first step. “The real challenge will come when we collect all the data and then have to interpret them.”





Big Data on Healthy Brain Aging – Dana Foundation

Share this post