It’s no secret that cognitive functions tend to diminish in old age, but a new study from Washington University in St. Louis has identified at least one mental task that older adults seem to perform as well, if not better, than their younger counterparts.
Ironically, it is the older adults’ diminished ability to hold important contextual clues in working memory that seems to explain their superior performance on a simple test requiring them to quickly identify a specific sequence of letters on a computer screen.
“Our new findings are startling because researchers had previously found it nearly impossible to identify a task involving attention or memory that older adults perform as well as young people,” said Todd Braver, Ph.D., an assistant professor of psychology in Arts & Sciences. “In this experiment, older adults not only completed the task with fewer errors, but amazingly, their reaction times were as fast as the younger adults, and that’s pretty much unheard of.” Perhaps more important to science’s broader effort to unravel the mechanisms of human thought, is the fact that a sophisticated new “context-driven” computer model of the human brain predicted the quirk and led researchers to test for its existence.
The model, developed by Washington University researchers in collaboration with Jonathan Cohen, M.D., Ph.D., professor of psychology at Princeton University, uses computer-simulated context-processing skills as a single operational mechanism – a sort of neural operating system – to tie together and explain the workings of several cognitive processes, functions that generally had been thought to operate independently.
Known as a “connectionist neural network model,” the system relies on a complex, interconnected set of computer algorithms to mimic various human thought processes. The connectionist model is based on the theory that there is no single physical area of the brain that controls the thought process. Rather cognition is carried out in an intricate web of interlocking and interacting brain regions, which together spur our thoughts and actions. “Our model predicted specific effects of aging on brain function and these effects were confirmed through empirical studies of actual human behavior,” Braver said.
The research was presented at the Nov. 19, 1999, meeting of the Psychonomic Society. Other members of the research team are Deanna Barch, Ph.D., an assistant professor of psychology, and Beth A. Keys, a psychology doctoral student at Washington University.
The computer model’s success, coupled with other recent breakthroughs in cognitive research, has led the Washington University team to propose a novel theory of brain function – that our ability to retrieve, hold onto and evaluate important contextual clues is the primary driving force behind a range of critical executive-level mental functions.
It’s clear that a number of complex cognitive functions depend heavily on our ability to grasp context. In language, for instance, a single word, such as “pen,” may have several distinct meanings depending on its use in a sentence. A thesaurus may list hundreds of different words for the same broad concept, each word conveying a subtle but important difference in context.
In this study, researchers suggest that context-processing also plays an important underlying role in the execution of cognitive processes, such as short-term memory, attention and inhibition. Each process, they argue, can be understood as being supported by a chemical neurotransmitter system that continually rewards the brain for holding onto informational tidbits relevant to the task at hand. In healthy young adults, the reward system for contextually important information is so strong that sensory distractions and other non-essential information are blocked out of working memory, effectively maintaining attention and goal-orientation.
“We suggest that a wide range of age-related impairments in cognitive control may, in fact, be due to a single fundamental deficit in the mind’s ability to properly represent and maintain task-relevant context,” Barch said. “We further suggest that these cognitive declines might be due to disturbances in the functional interactions between the prefrontal cortex and the dopamine neurotransmitter system, which serve as the neural mechanisms underlying context
representation and maintenance.” The new theory meshes well with a flurry of recent clinical, experimental and neuroimaging studies that establish the brain’s prefrontal cortex as a critical player in high-level cognitive processes. The prefrontal cortex, a lobe of brain tissue located just behind the forehead, is the brain’s executive command center, the region where we sort out our behaviors, our emotions, our most abstract intellectual thoughts.
A number of recent studies also suggest that dopamine, a key chemical neurotransmitter of the brain, plays a significant role in facilitating and moderating executive-level cognitive processes in the prefrontal cortex. Breakdowns in the prefrontal cortex and/or dopamine system have been strongly related to the diminished cognitive functions associated with normal aging and with a variety of brain-based diseases, such as schizophrenia, Alzheimer’s and Parkinson’s. Dopamine also is thought to play a powerful role in human addiction to commonly abused psychoactive drugs, such as alcohol, cocaine and heroin.
Although science now understands a great deal about the specific functions of various brain regions and how these functions are affected by dopamine and other chemical neurotransmitters, very little is understood about how these functions interact and what central operational mechanics govern the intricate workings of human thought. In recent years, computer modeling has emerged as a viable option for developing new paradigms for understanding the underlying forces that shape cognition.
In this study, the computer model helped researchers recognize that the sheer power and agility of young people’s contextual processing skills might leave them vulnerable to errors in certain context-related decision-making situations. More interesting, the model also produced the very counterintuitive suggestion that the diminished cognitive skills of older adults might leave them less susceptible to making some of those same mistakes.
To test the computer’s hypothesis, the researchers analyzed data from an experiment involving two large groups of younger and older adults, all of whom had completed a test used to assess context-related cognitive skills. Each was instructed to observe a series of letters flashed across a computer screen and to push one button if the letter “X” appeared immediately following the letter “A” or another button for any other combination of letters. To test how each group responded under various conditions, researchers varied the frequency of A-X letter presentations and the times between delivery of the cue and target letters.
As expected, older adults performed much worse than the younger ones in situations where the first letter presented was not an “A” and the second letter was an “X” – young people quickly realized that without an initial “A” in the sequence, the two letters being presented would never meet the A-X target guidelines. Older adults made more errors in this situation, apparently taken in by the appearance of the “X” and losing track of the context (the fact that it was not preceded by an “A”).
Interestingly, as the computer model had predicted, researchers were able to lull young minds into a trap by front-end-loading the test with an abnormally high percentage of positive A-X combinations. Young minds, easily capable of keeping context information in working memory, apparently jumped to the conclusion that any “A” presentation was statistically likely to be followed by the target letter “X.” Older minds, struggling to keep context in working memory, were less primed to expect an “X” as the next letter.
In situations where the next letter was, in fact, not an X, healthy older adults actually give the youngsters a run for their money – performing with fewer errors and with reaction times that are as good, if not better, than those of their younger counterparts.
Identifying pieces of the puzzle
In studies such as this one, and in others using sophisticated advances in functional neuroimaging techniques, researchers have begun to identify important pieces of the puzzle of human cognition. Now, researchers such as Barch and Braver are hoping that computer brain modeling may help science to begin fitting these pieces together. “Computer models of the brain are becoming more sophisticated in their ability to accurately represent specific functions of various regions of the brain and how information is exchanged between these regions,” Braver said.
“Compared to the human brain, which has billions and billions of neurons, our models are quite simple, but they hold the potential to be very powerful in predicting and understanding the basic mechanisms of brain function. By systematically ‘damaging’ cognitive functions in computer models of the healthy brain, we hope to unlock secrets about what goes awry with normal aging and brain diseases.”
Source: Washington University in St. Louis Press Release. January 19, 2000.