The study compared the brain activation patterns associated with the comprehension of written and spoken Portuguese sentences. An fMRI study measured brain activity while participants read and listened to sentences about general world knowledge. Participants had to decide if the sentences were true or false. To mirror the transient nature of spoken sentences, visual input was presented in rapid serial visual presentation format. The results showed a common core of amodal left inferior frontal and middle temporal gyri activation, as well as modality specific brain activation associated with listening and reading comprehension. Reading comprehension was associated with more left-lateralized activation and with left inferior occipital cortex (including fusiform gyrus) activation. Listening comprehension was associated with extensive bilateral temporal cortex activation and more overall activation of the whole cortex. Results also showed individual differences in brain activation for reading comprehension. Readers with lower working memory capacity showed more activation of right-hemisphere areas (spillover of activation) and more activation in the prefrontal cortex, potentially associated with more demand placed on executive control processes. Readers with higher working memory capacity showed more activation in a frontal-posterior network of areas (left angular and precentral gyri, and right inferior frontal gyrus). The activation of this network may be associated with phonological rehearsal of linguistic information when reading text presented in rapid serial visual format. The study demonstrates the modality fingerprints for language comprehension and indicates how lowand high working memory capacity readers deal with reading text presented in serial format.

Table of contentsI1 Introduction to the 2015 Brainhack ProceedingsR. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. PfannmöllerA1 Distributed collaboration: the case for the enhancement of Brainspell’s interfaceAmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto ToroA2 Advancing open science through NiDataBen Cipollini, Ariel RokemA3 Integrating the Brain Imaging Data Structure (BIDS) standard into C-PACDaniel Clark, Krzysztof J. Gorgolewski, R. Cameron CraddockA4 Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNIR. Cameron Craddock, Daniel J. ClarkA5 LORIS: DICOM anonymizerSamir Das, Cécile Madjar, Ayan Sengupta, Zia MohadesA6 Automatic extraction of academic collaborations in neuroimagingSebastien DeryA7 NiftyView: a zero-footprint web application for viewing DICOM and NIfTI filesWeiran DengA8 Human Connectome Project Minimal Preprocessing Pipelines to NipypeEric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Krzysztof J. GorgolewskiA9 Generating music with resting-state fMRI dataCaroline Froehlich, Gil Dekel, Daniel S. Margulies, R. Cameron CraddockA10 Highly comparable time-series analysis in NitimeBen D. FulcherA11 Nipype interfaces in CBRAINTristan Glatard, Samir Das, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. EvansA12 DueCredit: automated collection of citations for software, methods, and dataYaroslav O. Halchenko, Matteo Visconti di Oleggio CastelloA13 Open source low-cost device to register dog’s heart rate and tail movementRaúl Hernández-Pérez, Edgar A. Morales, Laura V. CuayaA14 Calculating the Laterality Index Using FSL for Stroke Neuroimaging DataKaori L. Ito, Sook-Lei LiewA15 Wrapping FreeSurfer 6 for use in high-performance computing environmentsHans J. JohnsonA16 Facilitating big data meta-analyses for clinical neuroimaging through ENIGMA wrapper scriptsErik Kan, Julia Anglin, Michael Borich, Neda Jahanshad, Paul Thompson, Sook-Lei LiewA17 A cortical surface-based geodesic distance package for PythonDaniel S Margulies, Marcel Falkiewicz, Julia M HuntenburgA18 Sharing data in the cloudDavid O’Connor, Daniel J. Clark, Michael P. Milham, R. Cameron CraddockA19 Detecting task-based fMRI compliance using plan abandonment techniquesRamon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe MeneguzziA20 Self-organization and brain functionJörg P. Pfannmöller, Rickson Mesquita, Luis C.T. Herrera, Daniela DenticoA21 The Neuroimaging Data Model (NIDM) APIVanessa Sochat, B Nolan NicholsA22 NeuroView: a customizable browser-base utilityAnibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe MeneguzziA23 DIPY: Brain tissue classificationJulio E. Villalon-Reina, Eleftherios Garyfallidis

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ResumoEste artigo aborda o desempenho de crianças em fase de alfabetização em testes de leitura, um eixo do projeto ACERTA. O projeto busca a identificação precoce de transtornos de aprendizagem, mais especificamente, a dislexia. Neste artigo, discutimos os resultados dos testes de leitura e escrita aplicados em escolas de Porto Alegre, os quais auxiliam na identificação de crianças em risco de apresentarem dificuldade inesperada para leitura. Os objetivos específicos deste artigo são: a) verificar o desempenho das crianças em fase de alfabetização em testes de leitura e escrita e b) identificar as dificuldades persistentes que possam ser indicativas de risco de transtorno de aprendizagem. Analisamos os resultados da Provinha Brasil, do ditado ortográfico e da leitura de palavras e pseudopalavras. Os resultados são apresentados a partir de uma perspectiva ainda descritiva da amostra.Palavras-chave: avaliação de leitura; alfabetização; dislexia. The performance of children learning to read in reading and writing assessments AbstractThis paper is about the performance of children learning to read in reading tests, one of the axes of the project ACERTA (Evaluation of Children at Risk for Learning Disabilities, in Portuguese). The project aims to establish early identification of learning disabilities, more specifically, dyslexia. In this paper, we discuss the results of reading tests made in schools, which help to identify children at risk for the unexpected difficulty learning to read. The specific objectives of this study are: a) to verify the performance of children in literacy stage in reading and writing tests and b) identify the persistent difficulties that may be indicative of learning disorder risk. We analyze, specifically, the results of the tests: Provinha Brasil, spelling test and word/pseudoword reading. The test results are presented with the goal of describing the results from the first years of the project.

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Objectives: We propose and evaluate a system for assessing severity of ZikV-related microcephaly brain abnormalities called RaRe (Radiological Reading score). The system is a combination of neuroradiologist evaluation scores; we also propose and evaluate its semi-automated version, which is generated from MRI indices. Design: We carried out a cross-sectional study with retrospective data collection at birth and 13-39 months; data collection includes radiologists evaluation of MRI images and a semi-automated system for analyzing MRI images from ZikV-related microcephaly patients; we also evaluated the association of severity and RaRe scores with developmental outcomes. Setting: Brain Institute of Rio Grande do Sul and Memorial Hospital Arthur Ramos, both in Brazil. Participants: 42 infants with ZikV-related congenital microcephaly (age at second evaluation M = 24.83 months; SD = 5.82). Mothers were infected by Zika Virus during pregnancy and were symptomatic or asymptomatic. Main outcome measures: Clinical and radiological outcomes (blindly reviewed); severity classification system (semi-automated - RaRe-Auto or based on neuroradiological evaluation - RaRe-Clin) and association with developmental outcomes (Bayley-III scales). Results: RaRe-Clin positively correlated with RaRe-Auto (r = 0.892; p < 0.001). Severity negatively associated with neurodevelopment scores assessed by Bayley-III scales in all three domains: cognition, language and motor skills. There was no association between trimester of infection and head circumference at birth (r = 0.160; p = 0.338) but there was an association between trimester of infection and RaRe-Clin (r = -0.355; p = 0.029). Conclusions: The clinical and semi-automated RaRe scores predicted Bayley scores. RaRe-Clin and RaRe-Auto can predict the trimester of infection and severity of outcomes and should be investigated in their further application with other congenital and infection-related brain abnormalities.

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