Our ability to read is a must to navigate our current society, and despite the large variability in skill within the general population, it is often taken for granted. This project aims to help elucidate the mechanisms from genes to reading behaviour, by identifying anatomical brain imaging markers correlated to reading ability using an automated pipeline that can be used in the context of large imaging genetic datasets. We need to systematically characterise how reading expertise is reflected in the brain in order to be able to ask questions about its genetics underpinnings in large datasets without behavioural reading measures. We need to identify small genetic effects that additively contribute to the ready-to-read brain because it will pinpoint to relevant biological pathways that are the substrate of reading ability. We need to understand the extend to which the same genetic markers influence reading and its brain correlates, and whether genetic influences on reading performance are mediated through brain morphology, to help discern between different risk profiles for reading difficulties. BIG READING integrates behavioural, brain imaging and genome-wide data in automated scalable pipelines to gain a deeper understanding of the link between genes and reading behaviour. I will analyse structural imaging markers correlated to reading-related traits in deeply phenotyped datasets of the general population to systematically characterise how reading expertise is reflected in the brain. I will perform heritability and genome-wide association scans in datasets with tens of thousands of participants to identify small genetic effects that additively contribute to the ready-to-read brain. I will perform genetic overlap analyses to define the extend of shared influence of genes on reading and its brain correlates and use genes as instruments to make causal inferences between brain markers and reading ability. This project will provide a foundation for future studies on how

The overarching goal of L2STAT is to understand L2 literacy acquisition by bringing together, for the first time, recent advances in the neurobiology of statistical learning (SL), a detailed statistical characterization of the world’s writing systems, and neurally-plausible general principles of learning, representation, and processing. L2STAT aims to provide a new theoretical framework that considers L2 learning and SL a two-way street: SL, on the one hand, tunes learners to the regularities of a new linguistic environment, and on the other hand, L2 environment shapes learners’ sensitivity to its specific types of statistical properties. The project will focus on the assimilation of reading skills in four novel linguistic environments, and investigate how exposure to their distinct writing systems shape, in turn, SL. L2STAT is an interdisciplinary project that launches in parallel five mutually informative research axes: 1) we employ advanced methods from computational linguistics and machine learning to precisely characterize the statistics of four highly contrasting writing systems (English, Spanish, Hebrew, Chinese). 2) We study the learning that results from biologically-inspired computational models that are exposed to these statistics, to generate a priori predictions regarding what statistical properties can (or cannot) be learned, and how neural mechanisms constrain the representations learned during L2 literacy acquisition. 3) We develop psychometrically reliable behavioral tests of individuals’ capacities to extract regularities in the visual and auditory modalities. 4) We use state of the art neuroimaging techniques including EEG, MEG, fMRI to probe the neurobiological underpinning for detecting regularities in the visual and auditory modalities. 5) We conduct behavioral experimentation in four sites (Israel, Spain, Taiwan to track literacy acquisition longitudinally in the four different languages.

Locating events on a timeline allows us to keep track of the past, live the present and plan the future. Some individuals can lose this fundamental aspect of human existence: aphasic patients. Aphasia is a language disorder typically caused by a stroke or a head injury that affects the ability to read, write and speak coherently. The source of the temporal impairment in aphasia is still unknown. Previous accounts focused on the linguistic aspect of this deficit, but data coming from clinical case reports and experimental studies suggest that this temporal impairment may not be exclusively linguistic. The main aim of this project is to carry out a systematic investigation of time processing in aphasic patients across different domains and, for the first time, through the use of structural magnetic resonance imaging. Three questions will be addressed: which aspects of time processing are impaired in aphasic patients? Is this impairment language-specific? What is the neurobiological basis of time processing? Behavioral (neurolinguistics/cognitive science) paradigms testing different aspects of non-/linguistic time processing will be combined with a voxel-based lesion-symptom mapping (VLSM) analysis and diffusion magnetic resonance imaging (dMRI). VLSM allows to analyze the relationship between lesioned grey matter and patients’ performance on a voxel-by-voxel basis, without the need of grouping patients based on lesion site or behavioral cut-off scores, while dMRI allows to explore which white matter pathways are also affected. Diffusion indexes will be also used to analyze the relationship between white matter fiber tract integrity and patients' performance. This proposal will provide answers to long-standing questions concerning the nature of the temporal impairment in aphasic patients and the neural underpinnings of time processing. This work will also lay the foundations for the development of new clinical tools for aphasic patients suffering temporal impairment.

Successful communication in humans critically depends on two aspects of language development: how many words we know (vocabulary growth) and whether we know how to combine them to understand and express meaningful ideas (semantic organization). This fellowship is designed to examine the role of early language environment in shaping these two aspects of language development. This aim will be addressed by conducting a longitudinal investigation of lexical development between 9 and 18 months of age. This will make it possible to map the structure of individual parents’ speech to the individual language development of their children. The focus on individual development promises not only to advance our theoretical understanding of typical development, but also to inform theory-based enrichment programs for atypical lexico-semantic development. To achieve these aims, the proposed research will strengthen connections between two fields in infant research, language acquisition and semantic development. Additionally, it will use a combination of complementary methods: analyses of naturalistic language input, parental reports, experimental paradigms, and cognitive modeling. Bridging the two research fields through a multi-method approach places this fellowship at the intersection of the fellow’s current expertise and the research lines currently active at the host institution (BCBL). Specifically, the semantic development aspect builds on the fellow’s strong background in category learning and lexico-semantic organization, while the language acquisition part aligns closely with the BCBL’s research lines. On the methodological side, the fellow will bring expertise in experimental designs, while skills related to the longitudinal approach, infant research, and cognitive modeling are those that the fellow will develop by training during this fellowship. Hence, this fellowship will strongly support the development of the prospective fellow’s independent line of research.