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      Integrated number sense tutoring remediates aberrant neural representations in children with mathematical disabilities

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Number sense is essential for early mathematical development but it is compromised in children with mathematical disabilities (MD). Here we investigate the impact of a personalized 4-week Integrated Number Sense (INS) tutoring program aimed at improving the connection between nonsymbolic (sets of objects) and symbolic (Arabic numerals) representations in children with MD. Utilizing neural pattern analysis, we found that INS tutoring not only improved cross-format mapping but also significantly boosted arithmetic fluency in children with MD. Critically, the tutoring normalized previously low levels of cross-format neural representations in these children to pre-tutoring levels observed in typically developing, especially in key brain regions associated with numerical cognition. Moreover, we identified distinct, ‘inverted U-shaped’ neurodevelopmental changes in the MD group, suggesting unique neural plasticity during mathematical skill development. Our findings highlight the effectiveness of targeted INS tutoring for remediating numerical deficits in MD, and offer a foundation for developing evidence-based educational interventions.

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          Information-based functional brain mapping.

          Nikolaus Kriegeskorte, Rainer Goebel, Peter A. Bandettini (2006)
          The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data. The complexity of the data creates a need for statistical summary, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest. In neuroimaging, for example, brain mapping analysis has focused on the discovery of activation, i.e., of extended brain regions whose average activity changes across experimental conditions. Here we propose to ask a more general question of the data: Where in the brain does the activity pattern contain information about the experimental condition? To address this question, we propose scanning the imaged volume with a "searchlight," whose contents are analyzed multivariately at each location in the brain.
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            Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

            Nikolaus Kriegeskorte, Marieke Mur, Peter A. Bandettini (2009)
            A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g., single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement (e.g., fMRI and invasive or scalp electrophysiology), and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices (RDMs), which characterize the information carried by a given representation in a brain or model. Building on a rich psychological and mathematical literature on similarity analysis, we propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing RDMs. We demonstrate RSA by relating representations of visual objects as measured with fMRI in early visual cortex and the fusiform face area to computational models spanning a wide range of complexities. The RDMs are simultaneously related via second-level application of multidimensional scaling and tested using randomization and bootstrap techniques. We discuss the broad potential of RSA, including novel approaches to experimental design, and argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience.
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              Hippocampus: cognitive processes and neural representations that underlie declarative memory.

              Howard Eichenbaum (2004)
              The hippocampus serves a critical role in declarative memory--our capacity to recall everyday facts and events. Recent studies using functional brain imaging in humans and neuropsychological analyses of humans and animals with hippocampal damage have revealed some of the elemental cognitive processes mediated by the hippocampus. In addition, recent characterizations of neuronal firing patterns in behaving animals and humans have suggested how neural representations in the hippocampus underlie those elemental cognitive processes in the service of declarative memory.
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                Author and article information

                Journal
                Journal ID (nlm-ta): bioRxiv
                Journal ID (publisher-id): BIORXIV
                Title: bioRxiv
                Publisher: Cold Spring Harbor Laboratory
                Publication date (Electronic): 12 April 2024
                Electronic Location Identifier: 2024.04.09.587577
                Affiliations
                [1 ]Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, 94305
                [2 ]Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305
                [3 ]Stanford Neuroscience Institute, Stanford University, Stanford, California, CA, 94305
                [4 ]Symbolic Systems Program, Stanford University, Stanford, California, CA, 94305
                [5 ]Centre National de la Recherche Scientifique & Université Paris Sorbonne, Paris 75016, France
                Author notes
                [¶]

                These authors contributed equally to this work.

                Author Contributions: Y.P., H.C., and V.M. designed research; F.S. and T.I. performed research; Y.P. and Y.Z. analyzed data; Y.P., Y.Z., F.S., H.C., and V.M. wrote the paper.

                Address for Correspondence: Yunji Park, Ph.D. and Vinod Menon, Ph.D., 401 Quarry Rd, Stanford University School of Medicine, Stanford, CA 94305, yunjip@ 123456stanford.edu ; menon@ 123456stanford.edu
                Author information
                http://orcid.org/0000-0003-2904-9505
                http://orcid.org/0000-0001-9157-5544
                http://orcid.org/0000-0002-9516-4213
                http://orcid.org/0000-0002-8573-3662
                http://orcid.org/0000-0002-2231-1112
                Article
                DOI: 10.1101/2024.04.09.587577
                PMC ID: 11030345
                PubMed ID: 38645139
                SO-VID: adeec57a-d56f-48b0-a5eb-6e51baef1bd0
                License:

                This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

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                Subject: Article

                Keywords: neural plasticity,intervention,mathematical disabilities,number sense,multivariate neural pattern analysis
                Data availability:
                Keywords: neural plasticity, intervention, mathematical disabilities, number sense, multivariate neural pattern analysis

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