Towards a theory of individual differences in statistical learning

Published 21 November 2016http://rstb.royalsocietypublishing.org/content/372/1711/20160059In recent years, statistical learning (SL) research has seen a growing interest in tracking individual performance in SL tasks, mainly as a predictor of linguistic abilities. We review studies from this line of research and outline three presuppositions underlying the experimental approach they employ: (i) that SL is a unified theoretical construct; (ii) that current SL tasks are interchangeable, and equally valid for assessing SL ability; and (iii) that performance in the standard forced-choice test in the task is a good proxy of SL ability. We argue that these three critical presuppositions are subject to a number of theoretical and empirical issues. First, SL shows patterns of modality- and informational-specificity, suggesting that SL cannot be treated as a unified construct. Second, different SL tasks may tap into separate sub-components of SL that are not necessarily interchangeable. Third, the commonly used forced-choice tests in most SL tasks are subject to inherent limitations and confounds. As a first step, we offer a methodological approach that explicitly spells out a potential set of different SL dimensions, allowing for better transparency in choosing a specific SL task as a predictor of a given linguistic outcome. We then offer possible methodological solutions for better tracking and measuring SL ability. Taken together, these discussions provide a novel theoretical and methodological approach for assessing individual differences in SL, with clear testable predictions. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’.This article was supported by the Israel Science Foundation (Grant No. 217/14, awarded to R.F.), by the National Institute of Child Health and Human Development (Grant Nos. RO1 HD 067364, awarded to Ken Pugh and R.F., and PO1-HD 01994, awarded to Haskins Laboratories), and by the ERC (project 692502, awarded to R.F.). L.B. is a research fellow of the Fyssen Foundation

Is there such a thing as a ‘good statistical learner’?

Available online 19 November 2021A growing body of research investigates individual differences in the learning of statistical structure, tying them to variability in cognitive (dis)abilities. This approach views statistical learning (SL) as a general individual ability that underlies performance across a range of cognitive domains. But is there a general SL capacity that can sort individuals from ‘bad’ to ‘good’ statistical learners? Explicating the suppositions underlying this approach, we suggest that current evidence supporting it is meager. We outline an alternative perspective that considers the variability of statistical environments within different cognitive domains. Once we focus on learning that is tuned to the statistics of real-world sensory inputs, an alternative view of SL computations emerges with a radically different outlook for SL research.This article was supported by the European Research Council (ERC) Advanced Grant Project 692502-L2STAT and the Israel Science Foundation (ISF) Grant Project 705/20, awarded to R.F. L.B. received funding from the ERC Advanced Grant Project 833029-LEARNATTEND. N.S. received funding from the ISF, grant number 48/2

Cooperative Carbon Dioxide Adsorption in Alcoholamine- and Alkoxyalkylamine-Functionalized Metal-Organic Frameworks.

A series of structurally diverse alcoholamine- and alkoxyalkylamine-functionalized variants of the metal-organic framework Mg2 (dobpdc) are shown to adsorb CO2 selectively via cooperative chain-forming mechanisms. Solid-state NMR spectra and optimized structures obtained from van der Waals-corrected density functional theory calculations indicate that the adsorption profiles can be attributed to the formation of carbamic acid or ammonium carbamate chains that are stabilized by hydrogen bonding interactions within the framework pores. These findings significantly expand the scope of chemical functionalities that can be utilized to design cooperative CO2 adsorbents, providing further means of optimizing these powerful materials for energy-efficient CO2 separations

Extraction methods for phycocyanin determination in freshwater filamentous cyanobacteria and their application in a shallow lake

Phycocyanin (PC) is one of the water-soluble accessory pigments of cyanobacteria species, and its concentration in aquatic systems is used to estimate the presence and relative abundance of blue-green algae. PC concentration and the PC/Chl-a ratio of four N2-fixing filamentous cyanobacteria strains (Cylindrospermopsis raciborskii, Anabaena spiroides, Aphanizomenon flos-aquae and Aphanizomenon issatschenkoi) common to Lake Balaton (Hungary) were determined using repeated freezing and thawing. A strong linear correlation was found between the extracted PC and Chl-a concentrations for all strains at high Chl-a concentrations (almost stable PC/Chl-a ratio in the range of 20−100 µg l−1 Chl-a). Extraction of PC and Chl-a from samples with low biomass of cyanobacteria (less than 20 µg l−1 Chl-a) proved to be unreliable using the standard protocol of freeze–thaw cycles (coefficients of variation exceeding 10–15%). In order to find an extraction method that is robust in fresh waters characterized by low algae biomass (e.g. Lake Balaton), the effectiveness of four extraction methods (repeated freeze–thaw method and homogenization with mortar and pestle, Ultrasonic, and Polytron homogenizer) were compared using C. raciborskii. It was found that the efficiency of extraction of phycocyanin was highest when a single freeze–thaw cycle was followed by sonication (25% additional yield compared with using the freeze–thaw method alone). Applying this combined method to surface water samples of Lake Balaton, a strong correlation was found between PC concentration and cyanobacterial biomass (R 2 = 0.9436), whilst the repeated freezing–thawing method found no detectable PC content. Here we show that the combined sonication/freeze–thaw method could be suitable for measuring filamentous cyanobacteria PC content, even at low concentrations; as well as for the estimation of cyanobacterial contribution to total biomass in fresh waters

Ubiquitin, a central component of selective cytoplasmic proteolysis, is linked to proteins residing at the locus of non-selective proteolysis, the vacuole

Ubiquitin, an evolutionary highly conserved protein, is known to be involved in selective proteolysis in the cytoplasm. Here we show that ubiquitin-protein conjugates are also found in the yeast vacuole. Mutants defective in the major vacuolar endopeptidases, proteinase yscA and yscB, lead to accumulation of ubiquitin-protein conjugates in this cellular organelle.

CT evaluation of the equivocal pulmonary nodule

In the setting of a questionable pulmonary nodule demonstrated by conventional radiographs, the place of CT in the diagnostic algorithm is not well established. We reviewed our experience in 50 consecutive patients referred to CT for a "possible pulmonary nodule." From the chest radiographs we noted nodule location, maximum dimension, presence on one or both views, and presence on a previous radiograph (> 1 year old), and nodules were categorized as "likely" or "unlikely" to be real parenchymal lesions based on radiographic appearance. Of a total of 56 questionable nodules, CT demonstrated no abnormality in 21 cases, parenchymal nodules in 16, scarring, atelectasis, or infiltrate in 11, and normal structural variants in 8. True pulmonary nodules were statistically significantly more frequently categorized as "likely" lesions than normal variants or no disease, but this was not of a magnitude to be clinically useful. Based on analysis of various radiographic features of equivocal nodules and their subsequent outcomes, we suggest a radiologic approach to the equivocal pulmonary nodule.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26780/1/0000336.pd