Bibliographic record
Abstract
Declining memory abilities are reported by virtually all older adults and give rise to the greatest number of complaints about aging in older people. The important questions that arise clinically concern the differences between the so-called benign memory losses of healthy aging and the pathological losses associated with Alzheimer disease and other dementias. Also arising are questions such as to what extent can memory loss be used as a diagnostic tool, and (crucially) can anything be done about it? The 2 In Review articles survey what is known about age-related memory changes: first from the point of view of cognitive psychologists Dr Lin Luo and myself,1 and second from the perspective of a clinical neuropsychologist Dr Lars Backman.2 When does memory decline begin? A rather general answer could be that most people report some problems from their early sixties; however, a study by Park et al3 showed that some memory functions decline as early as the thirties. Two important points in this connection are first that memory is not one monolithic entity, and second that (paradoxically perhaps) memory is also intimately related to other cognitive functions. On the first point, the article by Dr Luo and myself1 describes ideas and evidence from cognitive psychology suggesting that there are at least 5 major memory systems, and that these systems show very different rates of decline in the course of aging. Episodic memory (for specific events) and working memory (for information held and manipulated in conscious awareness) typically fall off relatively rapidly, whereas memory for perceptual information, for highly practiced habits and procedures, and for general knowledge (semantic memory) hold up relatively well. The reasons behind these differential patterns of age-related losses are still under active debate; however, 2 suggestions at the cognitive level of analysis are that age-related problems are found especially in situations requiring large amounts of self-initiated processing and where access to highly specific information is required. The notion of self-initiated processing4 describes cognitive operations that are neither habitual nor well supported by the environmental context; rather, they must be initiated and performed in a conscious, effortful manner, often using new processing operations directed at the specific task. Such operations are typically considered to be frontal lobe functions, and the frontal lobes are known to decline in efficiency in the course of aging.5 Older people are also penalized when the information sought from memory is highly specific in nature-proper names are an obvious example, but specific episodes from the individual's autobiographical past are another. Older people are relatively unimpaired when retrieving general information about a topic, but do less well when specifics are required. One suggestion here is that knowledge is represented and organized hierarchically, with general commonalities easily accessible at the top, and increasingly specific pieces of information that are less easy to access at the bottom of the hierarchy.6 The point that memory is related to other cognitive functions is in line with Dr Backman's2 observation that other cognitive abilities such as attention, executive control, learning, and problem-solving also decline in the course of both normal and pathological aging. To some extent this general cognitive decline may reflect the growing inefficiency of general neurophysiological systems-blood supply, neural connectivity, dopamine depletion, poor glucose metabolism, and so forth-but it is also the case that memory integrity both affects and is affected by other cognitive abilities. Brief examples include: attention-paying attention, especially to the meaning and implication of perceived events, is an obvious prerequisite for subsequent memory performance; memory operations involving elaboration and organization are also crucial for good long-term learning; finally, good working memory abilities reflect good executive control functions (frontal lobes again) and affect such higher-level cognitive activities as problem-solving and planning. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".