Article Archive
November/December 2017

Research Review: Brain Activity Affects Fall Risk
By Emmeline Ayers, MPH, and Joe Verghese, MBBS
Today's Geriatric Medicine
Vol. 10 No. 6 P. 10

Each year one-third of community-dwelling people over the age of 65 and one-half of those over the age of 80 experience falls. The consequences of falls among older adults are often devastating, resulting in disabilities, institutionalization, and premature mortality.1 Injuries from falls are among the 20 most expensive medical conditions and were estimated to be responsible for $31 billion per year in health care costs in the United States in 2015.2,3

In the United States, fatal falls increase from 17% among adults aged 65 to 74 to 47% in those over the age of 80.4 Therefore, the need to identify early markers that place individuals at high risk for falls is imperative. A further challenge is that current fall research has focused on clinical impairments in gait, balance, cognition, and other sensory functions that predict falls,5,6 and little is known about biological processes that precede the occurrence of clinical impairments that lead to falls.

Walking While Talking
The formative observation by Lundin-Olsson and colleagues, who noticed that nursing home residents who stopped walking when talking were at higher risk of falls,7 has spurred exploration of real world divided-attention tasks to identify older adults at high risk for falls. These paradigms are designed to understand fall risk by examining performance of individuals as they walk while simultaneously conducting cognitively demanding tasks such as reciting alternate letters of the alphabet or counting backward from 100 by sevens.

The walking while talking (WWT) task affords the opportunity to manipulate attention demands and measure the effect of taxing attention on gait performance. The decrement in gait speed during WWT compared with normal walking is a measure of dual task cost that occurs when two tasks interfere with each other and compete for the same brain resources.8,9

Results from previous studies conducted by the authors show that slower gait speed during WWT predicts falls in nondemented community-dwelling older adults and demonstrate the incremental validity of WWT over normal walking assessments in predicting falls.10,11

Different brain processes and substrates have been correlated with dual tasks compared with normal walking.12-14 Change in gait speed between single and dual tasks was found to be greater in participants with decreased cortical volume and metabolic activity of the primary motor cortex in adults with mild cognitive impairment.14 Cognitively impaired adults with greater severity of subcortical hyperintensities, of presumably vascular or neurodegenerative origins, perform worse in dual tasks compared with normal controls.13

Although cognitive control processes based in the prefrontal cortex are recognized as important contributors to falls, current research is primarily focused on clinical predictors of falls,5,6 leaving a gap in the understanding of the underlying neural processes that might predict falls. Evidence supports impairments in cognitive functions, specifically executive functions, as a major contributor to falls in aging.15,16 The prefrontal cortex, a key structure for performing executive and other cognitive functions, also plays a vital role in control of cognition and mobility, indicating its important role in fall risk.12 Worse performance on dual task assessments that involve executive functions, such as walking while performing an attention-demanding task, have been shown to predict falls in nondemented older adults.9-11,17,18

Functional Near Infrared Spectroscopy
Conventional neuroimaging techniques cannot image the brain during motion,19 necessitating newer approaches such as the functional Near Infrared Spectroscopy (fNIRS).20-22 Unlike traditional neuroimaging methods, such as structural or functional MRI,23,24 fNIRS has the advantage of studying participants while they actually walk.23

fNIRS is a noninvasive technology that enables continuous monitoring of changes in blood oxygenation related to brain function.25 Using fNIRS, the authors showed that WWT elicits a greater degree of brain activity in the prefrontal cortex compared with normal walking in community-dwelling older adults.25,26 While changes in brain activation patterns early in progressive neurodegenerative diseases have been described,24 whether brain activation in high-functioning healthy older adults could predict falls had not been examined.27

Study Findings
The primary goal of the study was to determine whether brain activity in the prefrontal cortex measured during walking using fNIRS technology predicts falls in high-functioning older adults. We hypothesized that increased magnitude of prefrontal cortex activation during WWT would predict falls in high-functioning community-dwelling older adults. We conducted a prospective study of 166 high-functioning older adults enrolled in the Central Control of Mobility in Aging study at Albert Einstein College of Medicine.

High-functioning status was defined as absence of dementia and disability and with normal gait diagnosed by study clinicians in participants aged 65 and older. Task-related changes in oxygen levels in the prefrontal cortex were measured using fNIRS during single task conditions, motor (normal pace walking) and cognitive (standing while reciting alternate letters of the alphabet), as well as a dual task condition (walking while reciting alternate letters of the alphabet, ie, WWT).

Incident falls were prospectively assessed every two to three months over a 50-month study period. Over the study period, 71 participants reported 116 falls, with a median time to first fall of 19.5 months.

Results showed that each standard deviation increase in brain activity levels during WWT was associated with a 32% increased risk for falls during the next four years. The association remained after accounting for multiple established clinical fall risk factors including cognitive status, slow gait, previous falls, and frailty.

Although previous studies have shown that gait speed during WWT predicts falls in older adult populations,8,10 in this high-functioning sample, neither gait speed nor the letters recited during WWT predicted falls. Similarly, brain activation during both of the single task conditions did not predict falls. These findings provide evidence that brain activity patterns during dual tasks may indicate risk of falls in high-functioning older adults before any visible signs of clinical dysfunction and may not be elicited by more simple tasks such as walking or talking alone. Additionally, these results show that dual task assessments can strain cognitive reserves in cognitively and physically healthy older adults.

Interventions and Clinical Implications
The relationship between cognitive interventions and their effect on gait, balance, and fall risk are being explored in recent studies.28-30 Dual task performance was reported to improve by training28,29 and could be studied as a novel fall prevention strategy.

After a 12-week training program in divided attention tasks, cognitively impaired participants demonstrated significant improvement in walking abilities.28 Participants with Parkinson's disease showed significantly improved gait performance during normal and dual task conditions after six weeks of a dual task treadmill training program enhanced with virtual reality.30 Cognitive remediation approaches using computerized programs demonstrated an improvement in attention and executive function as well as memory in cognitively normal older adults.29

Results from our pilot study of frail older adults, who were randomly assigned to either a computerized cognitive remediation program or a usual care group for a 12-week program, showed improvement in gait velocity during normal walking and WWT for the cognitive remediation group.29 A full-scale clinical trial to validate these results is now underway (NCT02567227).31

These preliminary studies support the feasibility and validity of cognitive-based approaches as a novel nonpharmacological means of modifying gait performance as a fall prevention strategy to improve mobility.

From a clinical perspective, findings from our study suggest that there may be changes in brain activity patterns before physical symptoms manifest in high-functioning older people who are at risk of falls. These alterations in brain activity patterns without obvious behavioral manifestations may be used to assess fall risk and implicate neural processes early in the pathogenesis of falls.

In the future, a simple brain scan assessment such as fNIRS might be used to help predict falls in high-functioning older adults. Clinicians may be able to use this information to recommend behavioral and lifestyle modifications or treatments for their patients that may reduce the risk of future falls. Future research is needed to find the underlying biological mechanisms or diseases that may be altering brain activity and how to correct them at an early stage in order to prevent future falls.

— Emmeline Ayers, MPH, is the associate for the division of cognitive and motor aging (neurology) and geriatrics (medicine) at Albert Einstein College of Medicine in New York.

— Joe Verghese, MBBS, is a professor of neurology and chief of the Integrated Divisions of Cognitive and Motor Aging (neurology) and Geriatrics (medicine) at Albert Einstein College of Medicine.

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