There are declines with age in speed of processing, working memory, inhibitory function, and long-term memory, as well as decreases in brain structure size and white matter integrity. In the face of these decreases, functional imaging studies have demonstrated, somewhat surprisingly, reliable increases in prefrontal activation. To account for these joint phenomena, we propose the scaffolding theory of aging and cognition (STAC). STAC provides an integrative view of the aging mind, suggesting that pervasive increased frontal activation with age is a marker of an adaptive brain that engages in compensatory scaffolding in response to the challenges posed by declining neural structures and function. Scaffolding is a normal process present across the lifespan that involves use and development of complementary, alternative neural circuits to achieve a particular cognitive goal. Scaffolding is protective of cognitive function in the aging brain, and available evidence suggests that the ability to use this mechanism is strengthened by cognitive engagement, exercise, and low levels of default network engagement.

/pdf/the-adaptive-brain-aging-and-neurocognitive-scaffolding-3igyn72710.pdf

The Adaptive Brain: Aging and Neurocognitive Scaffolding

Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications

Text documents often contain valuable structured data that is hidden Yin regular English sentences. This data is best exploited infavailable as arelational table that we could use for answering precise queries or running data mining tasks.We explore a technique for extracting such tables from document collections that requires only a handful of training examples from users. These examples are used to generate extraction patterns, that in turn result in new tuples being extracted from the document collection.We build on this idea and present our Snowball system. Snowball introduces novel strategies for generating patterns and extracting tuples from plain-text documents.At each iteration of the extraction process, Snowball evaluates the quality of these patterns and tuples without human intervention,and keeps only the most reliable ones for the next iteration. In this paper we also develop a scalable evaluation methodology and metrics for our task, and present a thorough experimental evaluation of Snowball and comparable techniques over a collection of more than 300,000 newspaper documents.

/pdf/snowball-extracting-relations-from-large-plain-text-4non5e8y6h.pdf

Snowball: extracting relations from large plain-text collections

This paper presents a meta-analysis of the data from 6,179 participants in 77 studies that investigated the association between working-memory capacity and language comprehension ability. A primary goal of the meta-analysis was to compare the predictive power of the measures of working memory developed by Daneman and Carpenter (1980) with the predictive power of other measures of working memory. The results of the meta-analysis support Daneman and Carpenter’s (1980) claim that measures that tap the combined processing and storage capacity of working memory (e.g., reading span, listening span) are better predictors of comprehension than are measures that tap only the storage capacity (e.g., word span, digit span). The meta-analysis also showed that math process plus storage measures of working memory are good predictors of comprehension. Thus, the superior predictive power of the process plus storage measures is not limited to measures that involve the manipulation of words and sentences.

https://link.springer.com/content/pdf/10.3758/BF03214546.pdf

Working memory and language comprehension: A meta-analysis.

Two studies, involving a total of 460 adults between 18 and 87 years of age, were conducted to determine which of several hypothesized processing components was most responsible for age-related declines in working memory functioning. Significant negative correlations between age and measures of working memory (i.e., from -.39 to -.52) were found in both studies, and these relations were substantially attenuated by partialing measures hypothesized to reflect storage capacity, processing efficiency, coordination effectiveness, and simple comparison speed. Because the greatest attenuation of the age relations occurred with measures of simple processing speed, it was suggested that many of the age differences in working memory may be mediated by age-related reductions in the speed of executing elementary operations. Working memory is generally defined as the preservation of information while simultaneously processing the same or other information. It is distinguished from other forms of memory because the assumption that it reflects both processing and storage implies that it plays an important role in many cognitive tasks (e.g., Baddeley, 1986; Carpenter & Just, 1989; Salthouse, 1990). An illustration of the hypothesized functioning of working memory in one cognitive task, mental arithmetic, is presented in Figure 1. The left column in this figure indicates the operations to be performed, and the right column represents the intermediate products that must be temporarily stored while carrying out those operations. This figure is useful because it graphically illustrates both the importance and the complexity of working memory. That is, it is clear from this example that effective storage of information is essential in order for the successful performance of certain cognitive tasks. Figure 1 also suggests that it may be fruitful to think of working memory not as a single discrete structure, but rather as a dynamic interchange among three conceptually distinct aspects or components-processing efficiency, storage capacity, and coordination effectiveness. Processing is represented by the series of operations in the left column, storage is represented by the entries in the right column, and coordination can be assumed to correspond both to the sequencing of operations and to the arrows portraying the exchange of information between processing and storage. A primary purpose of this article was to investigate the contribution of these three hypothesized components to age-related differences in measures of working memory. Each of the components has been hypothesized to be an important source of adult age differences by one or more researchers, but few definitive conclusions have been possible because the currently available evidence is both weak and inconsistent. To illustrate,

/pdf/decomposing-adult-age-differences-in-working-memory-435y0smlg8.pdf

Decomposing adult age differences in working memory.

This note describes a scoring scheme for the coreference task in MUC6 It improves on the original approach by: (1) grounding the scoring scheme in terms of a model; (2) producing more intuitive recall and precision scores; and (3) not requiring explicit computation of the transitive closure of coreference The principal conceptual difference is that we have moved from a syntactic scoring model based on following coreference links to an approach defined by the model theory of those links

/pdf/a-model-theoretic-coreference-scoring-scheme-3hgvjapslc.pdf

A model-theoretic coreference scoring scheme

Young and elderly adults were compared for recall performance on simple digit and word spans (traditional tests of primary memory), versus a “loaded” auditory word span test designed to emphasize working memory capacity. Although digit spans were identical for the two age groups, there were small but significant age differences in word span, and even larger differences in working memory performance. An analysis of correlations between span measures and verbal ability scores supported the position that working memory loading represents a special problem for the elderly.

Does the capacity of working memory change with age

Historically, tailoring language processing systems to specific domains and languages for which they were not originally built has required a great deal of effort. Recent advances in corpus-based manual and automatic training methods have shown promise in reducing the time and cost of this porting process. These developments have focused even greater attention on the bottleneck of acquiring reliable, manually tagged training data. This paper describes a new set of integrated tools, collectively called the Alembic Workbench, that uses a mixed-initiative approach to "bootstrapping" the manual tagging process, with the goal of reducing the overhead associated with corpus development. Initial empirical studies using the Alembic Workbench to annotate "named entities" demonstrates that this approach can approximately double the production rate. As an added benefit, the combined efforts of machine and user produce domain specific annotation rules that can be used to annotate similar texts automatically through the Alembic-NLP system. The ultimate goal of this project is to enable end users to generate a practical domain-specific information extraction system within a single session.

/pdf/mixed-initiative-development-of-language-processing-systems-27u06a8zxi.pdf

Mixed-Initiative Development of Language Processing Systems

The MITRE Identification Scrubber Toolkit: Design, training, and assessment

As with several other veteran MUC participants, MITRE's Alembic system has undergone a major transformation in the past two years. The genesis of this transformation occurred during a dinner conversation at the last MUC conference, MUC-5. At that time, several of us reluctantly admitted that our major impediment towards improved performance was reliance on then-standard linguistic models of syntax. We knew we would need an alternative to traditional linguistic grammars, even to the somewhat non-traditional categorial pseudo-parser we had in place at the time. The problem was, which alternative?

John S. Aberdeen

Papers

A model-theoretic coreference scoring scheme

Does the capacity of working memory change with age

Mixed-Initiative Development of Language Processing Systems

The MITRE Identification Scrubber Toolkit: Design, training, and assessment

MITRE: description of the Alembic system used for MUC-6