The Developmental Trajectory of the Operational Momentum Effect

Mental calculation is thought to be tightly related to visuospatial abilities. One of the strongest evidence for this link is the widely replicated operational momentum (OM) effect: the tendency to overestimate the result of additions and to underestimate the result of subtractions. Although the OM effect has been found in both infants and adults, no study has directly investigated its developmental trajectory until now. However, to fully understand the cognitive mechanisms lying at the core of the OM effect it is important to investigate its developmental dynamics. In the present study, we investigated the development of the OM effect in a group of 162 children from 8 to 12 years old. Participants had to select among five response alternatives the correct result of approximate addition and subtraction problems. Response alternatives were simultaneously presented on the screen at different locations. While no effect was observed for the youngest age group, children aged 9 and older showed a clear OM effect. Interestingly, the OM effect monotonically increased with age. The increase of the OM effect was accompanied by an increase in overall accuracy. That is, while younger children made more and non-systematic errors, older children made less but systematic errors. This monotonous increase of the OM effect with age is not predicted by the compression account (i.e., linear calculation performed on a compressed code). The attentional shift account, however, provides a possible explanation of these results based on the functional relationship between visuospatial attention and mental calculation and on the influence of formal schooling. We propose that the acquisition of arithmetical skills could reinforce the systematic reliance on the spatial mental number line and attentional mechanisms that control the displacement along this metric. Our results provide a step in the understanding of the mechanisms underlying approximate calculation and an important empirical constraint for current accounts on the origin of the OM effect

Probing the Dual-Route Model of the SNARC Effect by Orthogonalizing Processing Speed and Depth

The dual-route model explains the SNARC (Spatial-Numerical Association of Response Codes) effect assuming two routes of parallel information processing: the unconditional route (automatic activation of pre-existing links) and the conditional route (activation of task-specific links). To test predictions derived from this model, we evaluated whether response latency in superficial number processing modulates the SNARC effect in a color task (participants judged the color of a number). In Experiment 1, participants performed a parity task, an easy color task (short RTs), and a difficult color task (RTs similar to those of the parity task). A SNARC effect emerged only in the parity task. In Experiment 2, participants performed a color task and a secondary task under four conditions chosen to orthogonally manipulate response latency (short vs. long) and processing depth (semantic vs. perceptual). Only the long-latency perceptual-processing condition elicited a SNARC effect. To explain these results, we suggest that the cognitive resources required by a secondary task might dilute the SNARC effect. Our results indicate that the dual-route model should be modified to take into account additional factors (e.g., working memory load) that influence the level of activation of the unconditional route.Peer Reviewe

Phase transitions in a frustrated XY model with zig-zag couplings

We study a new generalized version of the square-lattice frustrated XY model where unequal ferromagnetic and antiferromagnetic couplings are arranged in a zig-zag pattern. The ratio between the couplings $\rho$ can be used to tune the system, continuously, from the isotropic square-lattice to the triangular-lattice frustrated XY model. The model can be physically realized as a Josephson-junction array with two different couplings, in a magnetic field corresponding to half-flux quanta per plaquette. Mean-field approximation, Ginzburg-Landau expansion and finite-size scaling of Monte Carlo simulations are used to study the phase diagram and critical behavior. Depending on the value of $\rho$, two separate transitions or a transition line in the universality class of the XY-Ising model, with combined $Z_2$ and U(1) symmetries, takes place. In particular, the phase transitions of the standard square-lattice and triangular-lattice frustrated XY models correspond to two different cuts through the same transition line. Estimates of the chiral ($Z_2$) critical exponents on this transition line deviate significantly from the pure Ising values, consistent with that along the critical line of the XY-Ising model. This suggests that a frustrated XY model or Josephson-junction array with a zig-zag coupling modulation can provide a physical realization of the XY-Ising model critical line.Comment: 11 pages, 9 figures, RevTex, to appear in Phys. Rev.

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Neurocognitive evidence for cultural recycling of cortical maps in numerical cognition

Das Kernsystem zur approximativen Verarbeitung numerischer Informationen - das approximative Mengensystem (AMS) - ist, ebenso wie Systeme zur Verarbeitung räumlicher Informationen, im parietalen Cortex (PC) implementiert. Hier integriere ich 9 experimentelle Studien in vier Teilen und zeige, wie abstrakte mathematische Fähigkeiten mit dem AMS zusammenhängen. Die Hypothese ist, dass die mathematischen Leistungen des Menschen auf grundlegenden Konzepten (Raum, Zahl) aufbauen indem sie kortikale Areale ko-optieren, deren ursprüngliche Organisation für die neuen kulturellen Bedürfnisse geeignet erscheinen. Teil eins zeigt mittels des Operationalen Momentum Effekts, dass (nicht-)symbolisches Rechnen auf das AMS zurückgreift und Kopfrechnen evolutionär alte Strukturen im PC ko-optiert: Durch Anwendung multivariater Lernalgorithmen auf funktionelle Gehirnaktivierungen im posterioren PC während basaler perzeptueller Aufgaben (Sakkaden) konnte ich später ausgeführter Additionen von Subtraktionen unterscheiden. Dies ist ein Hinweis auf das kulturelle Recycling kortikaler Karten für kulturell bedingte kognitive Funktionen. Teil zwei untersucht die Folgen der Implementierung numerischer Informationen im PC. Die Verarbeitung numerischer Informationen konnte auch unter Crowding-Bedingungen nachgewiesen werden, was auf einen bevorzugten, nicht-bewusst vermittelten Zugang numerischer Informationen zum kognitiven System deuten könnte, wie sie bereits für andere visuelle Informationen, die im PC verarbeitet werden gezeigt wurde. Auch die Interferenz zwischen räumlichen und numerischen Informationen kann als Konsequenz der kortikalen und repräsentationalen Überlappung verstanden werden. In Teil drei und vier argumentiere ich, dass Kopfrechenfähigkeiten durch die Befähigung, Ordinalität zu verarbeiten, im AMS verankert sind und zeige technische, Stimulus-inhärente Faktoren auf, die problematisch bei der Unterscheidung zwischen approximativem und exaktem Rechnen sein können.A plethora of evidence supports the idea of a core system in the parietal cortex (PC) of the human brain that enables us to approximately process numerical information, the approximate number system (ANS). By synthesizing nine experimental studies in four parts, I argue how abstract mathematical competencies are linked to the ANS and PC. The hypothesis is that human mathematics builds from foundational concepts (space, number) by progressively co-opting cortical areas whose prior organization fits with the cultural need. In part one the operational momentum effect demonstrates that (non-)symbolic approximate calculation partly relies on the ANS, and that mental arithmetic co-opts evolutionarily older cortical systems in PC. Low-level perceptual processes such as saccades lead to spatial patterns of activation in posterior parts of PC that are predictive of patterns during abstract approximate calculation processes. This is interpreted in terms of cultural recycling of cortical maps for cognitive purposes that go beyond the evolutionary scope of a given region. Part two investigates the consequences of the parietal implementation of numerical magnitude information. Akin to other visual properties that are processed in PC this may favour a privileged, non-conscious access of numerical information to the cognitive system even under a crowding regime. Also, the interference between spatial and numerical information can be interpreted as a consequence of a representational and cortical overlap. Part three elucidates the grounding of mental arithmetic abilities in the ANS and argues for a mediation of the association between ANS and symbolic arithmetic via numerical ordering abilities, which in turn rely on neural circuits in right-hemispheric prefrontal cortex. In part four I will argue that the involvement of approximate calculation in high-level symbolic calculation remains elusive due to a number of technical issues with stimulus-inherent numerical features

Understanding mathematical thinking: The key for improving mathematical performance and a test case for exploring the human mind

International audienceUnderstanding mathematical thinking-the key for improving mathematical performance and a test case for exploring the human mind How well you do in mathematics is often taken as a direct index for general intelligence. People who struggle with mathematics fear being intellectually insufficient. Even worse, understanding of mathematics is also perceived as a stable and persistent trait-irremediable. While it is true that deficiencies in mathematical understanding do have a negative impact on career success, medical decision making and even personal health, it only represents one cognitive domain that does not represent an index of general intelligence. Also, various intervention studies have demonstrated that mathematical understanding is malleable. The key for changing these (and other) misbeliefs lies in a better understanding of the cognitive mechanisms that underlie mathematical cognition. The increasing awareness of the fact that many individuals struggle with mathematics was the motivation for writing An Introduction to Mathematical Cognition, the new book by Gilmore, Göbel and Inglis. The book starts out with a definition of what mathematical cognition is: an interdisciplinary endeavour that sets out to explain how mathematical understanding develops and what factors define individual differences in performance. The second chapter provides a brief and well-structured overview of the perception of non-symbolic numerical information. Understanding the number of items in a set (i.e., its numerosity), is a capacity that provides many species with an evolutionary and vital advantage. The authors empirically motivate the differentiation between core mechanisms that serve perceiving smaller (< 5) numerosities on one hand and larger numerosities on the other. They describe the developmental trajectories of both mechanisms as well as the existing theoretical models and the underlying neural correlates. The chapter finishes with a critical evaluation of the cognitive system for perceiving larger numerosities and features alternative explanation for a multitude of related findings. In the third chapter, the authors focus on symbols that represent numerical magnitudes (e.g. Arabic digits, number words, etc.). Since nothing relates these symbols to the quantity they describe (Why do "three" and "3" describe the number of lines depicted hereafter? |||), the authors discuss how children acquire a conceptual understanding of this relation (the symbol grounding problem). Two theoretical alternatives are introduced that explain this process either as a refinement of an innate system that allows for approximate numerical estimates or a bootstrapping process in which an initially void placeholder system (i.e., number words) is successively filled with meaning, starting from the mapping between small number words (one-four) and capacity limited object representations. The chapter then delineates the development of digit writing and multi-digit number processing before ending on a description of the relationship between symbolic number knowledge and mathematical performance. Chapters 4 to 6 cover the development of arithmetic skill, the understanding of arithmetic concepts and mathematical difficulties. The authors describe that different problem representations can hav

Editorial 2021

No abstract available