How numbers mean : Comparing random walk models of numerical cognition varying both encoding processes and underlying quantity representations

How do people derive meaning from numbers? Here, we instantiate the primary theories of numerical representation in computational models and compare simulated performance to human data. Specifically, we fit simulated data to the distributions for correct and incorrect responses, as well as the pattern of errors made, in a traditional “relative quantity” task. The results reveal that no current theory of numerical representation can adequately account for the data without additional assumptions. However, when we introduce repeated, error-prone sampling of the stimulus (e.g., Cohen, 2009) superior fits are achieved when the underlying representation of integers reflects linear spacing with constant variance. These results provide new insights into (i) the detailed nature of mental numerical representation, and, (ii) general perceptual processes implemented by the human visual system

Limited-capacity identity processing of multiple integers

The architecture of the numerical cognition system is currently not well understood, but at a general level, assumptions are made about two core components: a quantity processor and an identity processor. The quantity processor is concerned with accessing and using the stored magnitude denoted by a given digit. The identity processor is concerned with the recovery of the corresponding digit’s identity. Blanc-Goldhammer and Cohen (2014) established that the recovery and use of quantity information operates in an unlimited capacity fashion. Here, we assess whether the identity processor operates in a similar fashion. We present two experiments that are digit identity variations of Blanc-Goldhammer and Cohen’s (2014) magnitude estimation paradigm. The data across both experiments reveal a limited capacity identity processor whose operation reflects cross-talk with the quantity processor. Such findings provide useful evidence that is used to adjudicate between competing models of the human number processing system

The nature of shape constancy mechanisms as revealed by shape priming

Five shape priming experiments are reported in which the target was either a five- or six-sided line-drawn figure and participants made a speeded 2AFC judgment about the target’s number of sides. On priming trials, the target was preceded by a briefly presented smaller line figure (the prime) and performance on these trials was gauged relative to a no prime condition. In the first two experiments, primes were rendered invisible by the presentation of a backwards visual noise mask, respectively for a short (~40 ms) or long duration (~93 ms). No reliable priming effects arose under masked conditions. When these experiments were repeated without the mask, participants were speeded when the prime and target were related by a rigid through-the-plane rotation but not when the prime was a non-rigid, stretched version of the target. The same pattern of priming effects arose when, in a final experiment, novel irregular shapes were used. Collectively, the data reveal the operation of shape constancy mechanisms that are particularly sensitive to shape rigidity. The findings suggest that the visual system attempts to secure a correspondence between the rapid and successive presentations of the prime and the target by matching shapes according to a rigidity constraint

The COVID - Curated and Open aNalysis aNd rEsearCh plaTform (CO-CONNECT)

Objectives CO-CONNECT is making UK COVID-19 data Findable, Accessible, Interoperable and Reusable (FAIR) through a federated platform, which supports secure, anonymised research at scale and pace. This interdisciplinary project, spanning 22 organisations, is connecting data from >50 large research cohorts and data collected through routine healthcare provision across the UK. Approach Across the UK, data has been collected that can help us answer key questions about COVID-19. As the data are in many places with many different processes it is difficult and complex for public health groups, researchers, policymakers, and government to find and access lots of high-quality data quickly and efficiently to make decisions. In collaboration with Health Data Research UK, CO-CONNECT is streamlining processes of accessing data for research. Results 1) Discovering data and meta-analysis: CO-CONNECT enables researchers to determine how many people meet their research criteria within the various datasets across the UK through the Health Data Research Innovation Gateway Cohort Discovery tool e.g. “How many people in each dataset have had a PCR test which was positive and were under the age of 40?” Only summary level, anonymous data are provided so researchers can answer such questions rapidly without requiring multiple data governance permissions and directly contacting each data source. The tool also supports aggregate level meta-analysis of the data. 2) Detailed analysis: With data governance approvals, researchers can analyse detailed level, standardised, linked, pseudonymised data in a Trusted Research Environment. The common format reduces the effort on each research project, supporting rapid research. Conclusion Providing data in this de-identifiable, safe way enables rapid, robust research e.g., COVID-19 results from a test centre can be linked to hospital records along with prescriptions from pharmacies enabling researchers to understand whether people with different existing health conditions are more or less susceptible to COVID-19. If you want to know more visit https://co-connect.ac.uk

An experimental comparison between rival theories of rapid automatized naming performance and its relationship to reading

Two studies investigated the degree to which the relationship between Rapid Automatized Naming (RAN) performance and reading development is driven by shared phonological processes. Study 1 assessed RAN, phonological awareness and reading performance in 1010 children aged 7-10 years. Results showed that RAN deficits occurred in the absence of phonological awareness deficits. These were accompanied by modest reading delays. In structural equation modeling, solutions where RAN was subsumed within a phonological processing factor did not provide a good fit to the data, suggesting that processes outside phonology may drive RAN performance and its association with reading. Study 2 investigated Kail's (1991) proposal that speed of processing underlies this relationship. Children with single RAN deficits showed slower speed of processing than closely matched controls performing normally on RAN. However, regression analysis revealed that RAN made a unique contribution to reading even after accounting for processing speed. Theoretical implications are discussed

The log-linear response function of the bounded number-line task is unrelated to the psychological representation of quantity

The bounded number-line task has been used extensively to assess the numerical competence of both children and adults. One consistent finding is that young children display a logarithmic response function, whereas older children and adults display a more linear response function. Traditionally, these log-linear functions have been interpreted as providing a transparent window onto the nature of the participants’ psychological representation of quantity (termed here a direct response strategy). Here we show that the direct response strategy produces the log-linear response function regardless of whether the psychological representation of quantity is compressive or expansive. Simply put, the log-linear response function results from task constraints rather than the psychological representation of quantities. We also demonstrate that a proportion/subtraction response strategy produces response patterns that almost perfectly correlate with the psychological representation of quantity. We therefore urge researchers not to interpret the log-linear response pattern in terms of numerical representation

CaRROT-CDM:An Open-Source Tool for Transforming Data for Federated Discovery in Health Research

Health Data are collected or repurposed for research in many organisations across the UK. These data are held in many formats and at many scales. Such data can contain information on biometric measurements, medical conditions, medical procedures, demographics, and prescribed medications with several coding systems in use. For GDPR compliance, data are stored securely and de-identified prior to use in research making sharing and standardisation more difficult. The Observational Health Data Sciences and Informatics (OHDSI) program’s Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) provides standard data objects and coding for health data.   CaRROT-CDM  Open-Source tools were developed to define mappings and transform data from numerous disparate organisations (the Data Partners) to the OMOP standard to allow federated data queries via the Health Data Research UK (HDR-UK) gateway. These tools are CaRROT-Mapper and CaRROT-CDM, with the latter being the focus here.  CaRROT-CDM takes mapping information from the CaRROT-Mapper and source data as input. It produces OMOP CDM format data as output. The tool was designed to run in Data Partners’ compute environments, reducing the governance burden for transforming data to the common standard. Sensitive, identifiable data are never seen by the development team.  Conclusions and Current Work  The CaRROT-CDM tool is in use at Data Partner sites and has transformed over 20 COVID-19 and Pain data sets, so far, which are available for aggregated query via the HDR UK innovation gateway. Current work is focussed on re-engineering and testing the software for scaling to population-level health data.

Five Safes RO-Crate: FAIR Digital Objects for Trusted Research Environments

Trusted Research Environments (TREs) are secure locations in which data are placed for researchers to analyse. TREs can be set up to host administrative data, hospital data or any other data that needs to remain securely isolated. It is hard for a researcher to perform an analysis across multiple TREs, requesting and gathering the data needed from each one. Federated analysis widens the scope of research and makes more effective use of data, but that data needs to be analysed across geographical or governance boundaries, for example in devolved healthcare in the UK and across national borders in Europe.A federated infrastructure makes it much easier for analysis tools to access multiple TREs. Health Data Research UK (HDR UK) is developing a blueprint for TRE federation and tools for federated data discovery. There are different ways of implementing the well-established TREs, and many popular analysis tools already in widespread use, so solutions need to be readily adoptable by existing systems. Moreover, the infrastructure needs to work within the “Five Safes” framework that aims to protect data and enable data services to provide safe research access to data. RO-Crate is a community effort to establish a lightweight, native approach to packaging research data with their metadata. It has become a widely adopted framework for inter-service exchange, resource archiving, and reproducible reporting, used by digital research infrastructures and their services. It is an implementation of the FDO Forum’s FAIR Digital Objects.The HDR UK, through TRE-FX project, has developed the “Five Safes RO-Crate” as a new way of packaging up the digital objects needed for research requests and results with the information needed for the tools and TRE providers. Five Safes RO-Crates enable the exchange of query requests and results between analysis clients and TREs while ensuring that the access is safe and the process transparent. Included within its specification are eight steps that ensure that the RO-Crate’s metadata for safe data, safe people, safe projects, safe settings and safe outputs are reviewed according to Five Safes principles. The Five Safes RO-Crate Profile builds on the Workflow-Run-RO-Crate, first developed in the EU EOSC-Life project, effectively making them a representation of trusted workflow provenance.The approach has been piloted with TREs from Scotland, Wales and England and implemented by two widely used analysis toolkits (DataSHIELD, BitFount). Five Safes RO-Crates will be a pillar of HDR UK’s ongoing Federated Analytics development

The processing of images of biological threats in visual short-term memory

The idea that there is enhanced memory for negatively, emotionally charged pictures was examined. Performance was measured under rapid, serial visual presentation (RSVP) conditions in which, on every trial, a sequence of six photo-images was presented. Briefly after the offset of the sequence, two alternative images (a target and a foil) were presented and participants attempted to choose which image had occurred in the sequence. Images were of threatening and non-threatening cats and dogs. The target depicted either an animal expressing an emotion distinct from the other images, or the sequences contained only images depicting the same emotional valence. Enhanced memory was found for targets that differed in emotional valence from the other sequence images, compared to targets that expressed the same emotional valence. Further controls in stimulus selection were then introduced and the same emotional distinctiveness effect obtained. In ruling out possible visual and attentional accounts of the data, an informal dual route topic model is discussed. This places emphasis on how visual short-term memory reveals a sensitivity to the emotional content of the input as it unfolds over time. Items that present with a distinctive emotional content stand out in memory

A mathematical model of how people solve most variants of the number-line task

Current understanding of the development of quantity representations is based primarily on performance in the number line task. We posit that the data from number line tasks reflect the observer’s underlying representation of quantity, together with the cognitive strategies and skills required to equate line length and quantity. Here, we specify a unified theory linking the underlying psychological representation of quantity and the associated strategies in four variations of the number-line task: the production and estimation variations of the bounded and unbounded number-line tasks. Comparison of performance in the bounded and unbounded number-line tasks provides a unique and direct way to assess the role of strategy in number-line completion. Each task produces a distinct pattern of data, yet each pattern is hypothesized to arise, at least in part, from the same underlying psychological representation of quantity. Our model predicts that the estimated biases from each task should be equivalent if the different completion strategies are modelled appropriately and no other influences are at play. We test this equivalence hypothesis in two experiments. The data reveal all variations of the number-line task produce equivalent biases except for one: the estimation variation of the bounded number-line task. We discuss the important implications of these findings