The body of work on aging and information processing has consistently indicated that, generally, cognitive performance deteriorates with age (Park & Minear 2004). Measures of speed, reasoning, and working memory all indicate a negative trend for age. Although these findings may seem bleak, there are some domains that remain intact. For instance, knowledge seems to continue to accumulate well into old age.
One distinction that must be drawn when examining the effects of aging on cognitive processing is that between primary and secondary aging. Primary or normal aging is the inevitable process of deterioration that occurs as we move through the life-span and when a diagnosis of dementia has been eliminated. Secondary aging results from effects of the environment and disease. There is clear evidence that pathologies (e.g., dementia, loss of cardiovascular functioning, etc.) associated with aging are also associated with less efficient cognitive processes or abilities. Related to primary aging, three areas warrant attention: the relationship between aging and commonly assessed processing variables, the theoretical and methodological issues associated with this area, and finally, recent developments in the field of cognitive aging.
Age-Related Changes In Cognitive Processing
As we age, the speed with which we perform certain mental operations declines. More specifically, scores for processing speed show negative age trends and are obvious before the age of 50, but probably begin in the early 20s. One large-scale national study indicated that the average performance on measures of processing speed for young adults in their early twenties was near the 75th percentile while adults in their early seventies performed near the 20th percentile (Salthouse 2004). Processing speed is often measured by how rapidly an individual can make same/different judgments about pairs of symbols, patterns, or letters.
The relationship between age and processing speed is extremely strong and linear. However, it is also important to note that these age-related declines are not associated with increases in between-person variability. Instead, the trend is for increased age to be associated with a smaller range in scores.
Speed of processing has received a large amount of attention and has been hypothesized as the major underlying mechanism for all cognitive deterioration. Although there are competing theories proposed in the literature, the processing-speed theory has been well developed and has received a considerable amount of empirical support (Salthouse 2004).
There are two underlying mechanisms regarding processing-speed theory. First, the limited time mechanism asserts that the time to perform later operations is hampered when a large portion of the available time is expended on earlier operations. The second mechanism proposed is the simultaneity mechanism, which is based on the idea that the products of earlier processing may be lost by the time later processing is completed, thereby making relevant information no longer accessible when it is needed.
Findings related to memory and aging are less straightforward than processing speed and can be best understood by examining different types of memory. Memory can be conceptualized as a set of systems rather than a single entity. These include short-term and long-term memory, and both are comprised of various subsystems.
Short-term memory is composed of both primary and working memory. Primary memory is the ability to store a small amount of information that has been recently experienced. Working memory is the integration of processing and storing information in a transient short-term system. Tasks involving working memory include encoding and decoding messages, understanding text while reading, or mentally performing a math problem. Given that working memory is intergal to everyday functioning, it has been examined extensively in investigations of aging and cognition.
Working memory is measured using complex span tasks. For example, the backward digit span from the Wechsler Memory Scale Letter–Number Sequencing task is one commonly used measure. In this test, individuals are presented with a string of intermingled letters and numbers (e.g., M83GH6). They are then asked to repeat the string back in alphanumeric order (e.g., GHM368). Another popular measure is the Reading Span task. This asks individuals to read a sentence and answer a question about it while remembering the last word of that sentence.
As with processing speed, older adults experience a decline in working memory capacity as they age (Park 2002). Working memory begins to decrease in the twenties and a gradual decline is evident with each passing decade. However, with the appropriate environmental support some of these age differences can be mitigated. For example, teaching older adults to write down items that they may forget later has been shown to enhance working memory.
Long-term memory is comprised of two components: implicit or nondeclarative memory and explicit or declarative memory. Implicit memory is measured by tests that rely on prior experience or learning but do not require deliberate recollection (e.g., accuracy and reaction time). Explicit memory is measured by invoking stored information and is a purposeful or intentional process. In tests of explicit memory, participants are instructed to engage in conscious recollection such as recall or recognition tasks.
Explicit memory can be further differentiated into semantic and episodic memory, and this particular sub-division becomes particularly important in regard to aging. Semantic memory contains facts and knowledge about the world and the meanings of words or concepts. Semantic memory is relatively preserved across the adult life-span as measured through vocabulary and general knowledge tests. Semantic memory performance increases through the early sixties followed by a gradual decline (Zacks & Hasher 2006).
In contrast, episodic memory contains information associated with one’s experiences. It is the ability to recall the specific features of the spatial and temporal contexts in which events occur. Episodic memory can be measured by prospective memory, face recognition, name recognition, action memory, sentence memory, word recall with or without a distractor task, source memory, and memory for activities. The data clearly indicate agerelated deficits related to episodic memory.
Procedural memory, a type of implicit memory, refers to skills that have been highly rehearsed such as motor skills or cognitive skills. Findings indicate that procedural memory is minimally affected by age.
In the context of aging, repetition priming is often utilized to examine implicit memory. Examinations of repetition priming involve two phases. First, subjects are oriented to the task and exposed to some experimental materials. This is followed by a sentence completion or perceptual identification test that requires participants to use some of the earlier experimental materials and some new materials. The goal in these studies is to determine whether subjects benefit from previous exposure to experimental materials. Age differences with regard to repetition priming have been found to be quite small relative to changes in episodic memory.
Inhibition is the process by which we are able to selectively process information. It allows us to stay focused on the most relevant issues or stimuli and ignore extraneous information or thoughts (Hasher & Zacks 1988). As we age we have more difficulty focusing on target information and thus our attention is spread across both irrelevant and relevant information, making us less efficient.
The findings in general indicate that our ability to inhibit irrelevant material does decline with age. Some of the most significant findings related to inhibition involve the ability to process discourse.
It is overly simplistic to view cognitive aging only in terms of processing mechanisms or capabilities. Older adults bring knowledge and experience to situations and these resources remain stable even while processing capabilities may be diminishing. One issue of importance in cognitive aging is to understand the relationship between simultaneous growth in knowledge and decreases in processing abilities. While both longitudinal and cross-sectional studies have found marked declines in abilities such as encoding of new memories for episodes or facts, working memory, and processing speed, areas such as autobiographical memory, semantic knowledge, and emotional processing remain relatively stable across the life-span. Vocabulary test abilities increase until around age 50, after which they tend to level off or slightly decline (Salthouse 2003).
In order to fully understand the findings related to intelligence, it is important to distinguish between fluid and crystallized intelligence. Fluid intelligence can be conceptualized as a broad set of abilities related to information-processing skills involved in reasoning, abstracting, and problem-solving. Fluid intelligence is unique to an individual and is not imparted through systematic influences such as culture. Crystallized intelligence refers to knowledge that is acquired through experience and education and is demonstrated through verbal comprehension and concept formation. It reflects the cultural knowledge component of intelligence.
It is widely accepted that with age comes greater knowledge and experience and that this accumulated wisdom may offset or compensate for other age-related declines. This effect has been documented in some laboratory experiments, although some data suggest that when completing the same task, young adults depend on processing efficiency whereas older adults depend more on accumulated knowledge (Salthouse 2004).
Although there is a tendency to overlook the relationship between physical health and mental acuity, sensory changes may be good indicators of cognitive efficiency. Changes in sensory abilities such as visual and auditory acuity may increase the cognitive load necessary to function in a given situation and this increase in effort may be distracting, thereby making it more difficult to remember or make associations with what was heard or seen. Declines in vision, auditory acuity, balance, and muscle strength are all good indicators of changes in cognitive ability because they probably are concomitant with changes in the brain.
One of the biggest issues facing researchers in the area of cognition and aging is whether the focus should be upon age-related effects on a single variable or process, or whether the focus should include several domains examined simultaneously. The former, referred to as micro-approaches, are often used with small samples from divergent groups (e.g., young vs old). The benefit of these approaches is that they can identify specific processes at both the behavioral and possibly the neuropsychological level, which may enhance our understanding of aging and cognition. The limitation of these methods is that the examination of a process in isolation may hinder our understanding by obscuring the interactions among various processes, which may be important.
In contrast, macro-approaches to cognitive aging utilize large samples of 100 or more adults across a wide age range. These approaches are correlational in nature and examine the patterns in relationships among variables. Supporters of this paradigm argue that agerelated effects on particular cognitive tasks may be symptoms of broader phenomena. Therefore, independent examination of these variables fails to provide a complete understanding of cognitive processing in the aging context.
A second methodological issue concerns the fact that true experimental investigations are not possible because age cannot be manipulated by the experimenter. Some scholars argue that the focus should be on comparing pre-existing groups that share various lifestyle characteristics. Other researchers argue that the best method to overcome this limitation is to make some type of intervention that will then alter an individual’s cognitive performance, making it possible to determine which manipulations influence the relationship between age and performance on a particular cognitive task.
A third methodological concern involves proximal versus distal factors. The former refer to individual differences between age groups at the time of assessment. In contrast, distal factors involve differences occurring much earlier in the life-span. The question becomes one of whether we should try to explain differences in performances based on information gleaned at the time of assessment, or whether differences should be explained in terms of earlier life experiences.
Finally, one of the biggest issues for research regarding aging concerns the nature of the cross-sectional design. Are cross-sectional differences informative about the age-related changes in processing, or should all conclusions be based on longitudinal trends? Conclusions drawn from static cross-sectional designs may reflect cohort effects and other confounds, and may fail to capture all of the effects of the aging process.
Recent developments in neuroimaging techniques, such as positron emission tomography (PET) and functional magnetic imaging (fMRI), have brought new data to bear on theories of age-related changes in processing speed, inhibition, and working memory. Some of the most promising data show that older adults and younger adults recruit different areas of the brain to perform the same task. This has led researchers to question why this bilateral recruitment occurs. It has been hypothesized that bilateral recruitment may be a compensatory mechanism for older adults or it may be related to an inability to suppress activation (Park & Gutchess 2006).
Much of the knowledge regarding cognitive aging has been derived under highly constrained laboratory conditions. While such conditions have been necessary to control for a variety of confounds, it is also important to determine whether information processing differs on the basis of the cultural, social, or environmental conditions in which it occurs. Park and Gutchess (2006) argue that many of the declines in cognitive aging experienced in western cultures are also experienced in other cultures. However, it appears that culture does impact neurocognitive aging. Park and Gutchess (2006) found that older adults from Asian and western countries experience differences in activation of processing areas when completing the same behavioral task. This developing area of cultural psychology promises to inform us about the adaptability of the neurocognitive system and the biological imperatives that are unrelated to culture.
Real-world investigations, as opposed to laboratory investigations of information processing, are important in determining how age-related declines affect our day-to-day functioning. This research has established that environment does affect information processing, especially in the case of memory. For example, research indicates older adults remember to take medications more reliably than middle-aged adults. These results have been explained in terms of environmental demands. Older adults typically operate in an environment with very different demands than middle-aged adults. Middle-aged adults are normally required to balance competing demands from work and family. Therefore the chaotic characteristics of the environment may impact memory performance more than does underlying cognitive ability. Other studies (Chasteen et al. 2001) have also determined that context does play an important role in everyday behavior and may ameliorate the effects of decline in information processing in our everyday lives. A complete theory of cognitive aging should integrate context.
While we know a great deal about what happens to information processing as we age, we know less about the underlying mechanisms of why we experience these declines. However, new research in the areas of neuroimaging may be able to answer some of these questions. Naturalistic studies are extending what we know about information processing and how we cope with age-related declines. These studies may uncover intervention strategies that will enable us to maintain healthy minds across the life-span.
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