The postdictive effect of choice reflects the modulation of attention on choice

No Common Factor Underlying Decline of Visual Abilities in Mild Cognitive Impairment

INTRODUCTION

Recent work has shown an association between cognitive and visual impairments and two main theories were advanced, namely the sensory deprivation and the common cause theories. Most studies considered only basic visual functions such as visual acuity or visual field size and evaluated the association with dementia.

OBJECTIVES

To reconcile between these theories and to test the link between visual and cognitive decline in mildly cognitive impaired people.

METHODS

We employed a battery of 19 visual tasks on 39 older adults with mild cognitive impairment and 91 without any evidence of cognitive decline, as measured by the Montreal Cognitive Assessment.

RESULTS

Our results show a strong association between visual impairment and mild cognitive impairment. In agreement with previous results with younger and healthy older adults, we found also only weak correlations between most tests in older adults with mild cognitive impairment.

CONCLUSION

Our results suggest that visual and cognitive abilities decline simultaneously, but they do so independently across visual and cognitive functions and across participants.

COVID-19 Open-Data a global-scale spatially granular meta-dataset for coronavirus disease

This paper introduces the COVID-19 Open Dataset (COD), available at goo.gle/covid-19-open-data. A static copy is of the dataset is also available at 10.6084/m9.figshare.c.5399355. This is a very large “meta-dataset” of COVID-related data, containing epidemiological information, from 22,579 unique locations within 232 different countries and independent territories. For 62 of these countries we have state-level data, and for 23 of these countries we have county-level data. For 15 countries, COD includes cases and deaths stratified by age or sex. COD also contains information on hospitalizations, vaccinations, and other relevant factors such as mobility, non-pharmaceutical interventions and static demographic attributes. Each location is tagged with a unique identifier so that these different types of information can be easily combined. The data is automatically extracted from 121 different authoritative sources, using scalable open source software. This paper describes the format and construction of the dataset, and includes a preliminary statistical analysis of its content, revealing some interesting patterns.

Measurement(s)	Epidemiology
Technology Type(s)	Python
Factor Type(s)	cases • deaths • vaccinations
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	anthropogenic environment
Sample Characteristic - Location	North America • Central America • South America • Eurasia • Oceania • Antarctica • Africa