Older adults encode-but do not always use-perceptual details: intentional versus unintentional effects of detail on memory judgments

Investigations of memory deficits in older individuals have concentrated on their increased likelihood of forgetting events or details of events that were actually encountered (errors of omission). However mounting evidence demonstrates that normal cognitive aging also is associated with an increased propensity for errors of commission-shown in false alarms or false recognition. The present study examined the origins of this age difference. Older and younger adults each performed three types of memory tasks in which details of encountered items might influence performance. Although older adults showed greater false recognition of related lures on a standard (identical) old/new episodic recognition task, older and younger adults showed parallel effects of detail on repetition priming and meaning-based episodic recognition (decreased priming and decreased meaning-based recognition for different relative to same exemplars). The results suggest that the older adults encoded details but used them less effectively than the younger adults in the recognition context requiring their deliberate, controlled use.

Talent in autism: hyper-systemising, hyper-attention to detail and sensory hypersensitivity

We argue that hyper-systemizing predisposes individuals to show talent, and review evidence that hyper-systemizing is part of the cognitive style of people with autism spectrum conditions (ASC). We then clarify the hyper-systemizing theory, contrasting it to the weak central coherence (WCC) and executive dysfunction (ED) theories. The ED theory has difficulty explaining the existence of talent in ASC. While both hyper-systemizing and WCC theories postulate excellent attention to detail, by itself excellent attention to detail will not produce talent. By contrast, the hyper-systemizing theory argues that the excellent attention to detail is directed towards detecting 'if p, then q' rules (or [input-operation-output] reasoning). Such law-based pattern recognition systems can produce talent in systemizable domains. Finally, we argue that the excellent attention to detail in ASC is itself a consequence of sensory hypersensitivity. We review an experiment from our laboratory demonstrating sensory hypersensitivity detection thresholds in vision. We conclude that the origins of the association between autism and talent begin at the sensory level, include excellent attention to detail and end with hyper-systemizing.

Effect of phonetic complexity on word reading and repetition in deep dyslexia

This investigation moves beyond the traditional studies of word reading to identify how the production complexity of words affects reading accuracy in an individual with deep dyslexia (JO). We examined JO’s ability to read words aloud while manipulating both the production complexity of the words and the semantic context. The classification of words as either phonetically simple or complex was based on the Index of Phonetic Complexity. The semantic context was varied using a semantic blocking paradigm (i.e., semantically blocked and unblocked conditions). In the semantically blocked condition words were grouped by semantic categories (e.g., table, sit, seat, couch,), whereas in the unblocked condition the same words were presented in a random order. JO’s performance on reading aloud was also compared to her performance on a repetition task using the same items. Results revealed a strong interaction between word complexity and semantic blocking for reading aloud but not for repetition. JO produced the greatest number of errors for phonetically complex words in semantically blocked condition. This interaction suggests that semantic processes are constrained by output production processes which are exaggerated when derived from visual rather than auditory targets. This complex relationship between orthographic, semantic, and phonetic processes highlights the need for word recognition models to explicitly account for production processes.

Global snow mass measurements and the effect of stratigraphic detail on inversion of microwave brightness temperatures

Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method then it is equivalent to ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model.

Green infrastructure and ecosystem services - is the devil in the detail?

Background - Green infrastructure is a strategic network of green spaces designed to deliver ecosystem services to human communities. Green infrastructure is a convenient concept for urban policy makers, but the term is used too-generically and with limited understanding of the relative values or benefits of different types of green space and how these complement one another. At a finer scale/more practical level– little consideration is given to the composition of the plant-communities, yet this is what ultimately defines extent of service provision. This paper calls for greater attention to be paid to urban plantings with respect to ecosystem service delivery and for plant science to engage more-fully in identifying those plants that promote various services. Scope - Many urban plantings are designed based on aesthetics alone, with limited thought on how plant choice/composition provides other ecosystem services. Research is beginning to demonstrate, however, that landscape plants provide a range of important services, such as helping mitigate floods and alleviating heat islands, but that not all species are equally effective. The paper reviews a number of important services and demonstrates how genotype choice radically affects service delivery. Conclusions – Although research is in its infancy, data is being generated that relates plant traits to specific services; thereby helping identify genotypes that optimise service delivery. The urban environment, however, will become exceedingly bland if future planting is simply restricted to monocultures of a few ‘functional’ genotypes. Therefore, further information is required on how to design plant communities where the plants identified:- a/ provide more than a single benefit (multi-functionality) b/ complement each other in maximising the range of benefits that can be delivered in one location and c/ continue to maintain public acceptance through diversity. The identification/development of functional landscape plants is an exciting and potentially high impact arena for plant science.