Stanford Advisors

All Publications

  • The transition from vision to language: distinct patterns of functional connectivity for sub-regions of the visual word form area. bioRxiv : the preprint server for biology Yablonski, M., Karipidis, I. I., Kubota, E., Yeatman, J. D. 2023


    Reading entails transforming visual symbols to sound and meaning. This process depends on specialized circuitry in the visual cortex, the Visual Word Form Area (VWFA). Recent findings suggest that this word-selective cortex comprises at least two distinct subregions: the more posterior VWFA-1 is sensitive to visual features, while the more anterior VWFA-2 processes higher level language information. Here, we explore whether these two subregions exhibit different patterns of functional connectivity, and whether these patterns have relevance for reading development. We address these questions using two complementary datasets: Using the Natural Scenes Datasets (NSD; Allen et al, 2022) we identify word-selective responses in high-quality 7T individual adult data (N=8; 6 females), and investigate functional connectivity patterns of VWFA-1 and VWFA-2 at the individual level. We then turn to the Healthy Brain Network (HBN; Alexander et al., 2017) database to assess whether these patterns a) replicate in a large developmental sample (N=224; 98 females, age 5-21y), and b) are related to reading development. In both datasets, we find that VWFA-1 is more strongly correlated with bilateral visual regions including ventral occipitotemporal cortex and posterior parietal cortex. In contrast, VWFA-2 is more strongly correlated with language regions in the frontal and lateral parietal lobes, particularly bilateral inferior frontal gyrus (IFG). Critically, these patterns do not generalize to adjacent face-selective regions, suggesting a unique relationship between VWFA-2 and the frontal language network. While connectivity patterns increased with age, no correlations were observed between functional connectivity and reading ability. Together, our findings support the distinction between subregions of the VWFA, and portray the functional connectivity patterns of the reading circuitry as an intrinsic stable property of the brain.

    View details for DOI 10.1101/2023.04.18.537397

    View details for PubMedID 37131630

    View details for PubMedCentralID PMC10153222

  • Anatomy and physiology of word-selective visual cortex: from visual features to lexical processing. Brain structure & function Caffarra, S., Karipidis, I. I., Yablonski, M., Yeatman, J. D. 2021


    Over the past 2decades, researchers have tried to uncover how the human brain can extract linguistic information from a sequence of visual symbols. The description of how the brain's visual system processes words and enables reading has improved with the progressive refinement of experimental methodologies and neuroimaging techniques. This review provides a brief overview of this research journey. We start by describing classical models of object recognition in non-human primates, which represent the foundation for many of the early models of visual word recognition in humans. We then review functional neuroimaging studies investigating the word-selective regions in visual cortex. This research led to the differentiation of highly specialized areas, which are involved in the analysis of different aspects of written language. We then consider the corresponding anatomical measurements and provide a description of the main white matter pathways carrying neural signals crucial to word recognition. Finally, in an attempt to integrate structural, functional, and electrophysiological findings, we propose a view of visual word recognition, accounting for spatial and temporal facets of word-selective neural processes. This multi-modal perspective on the neural circuitry of literacy highlights the relevance of a posterior-anterior differentiation in ventral occipitotemporal cortex for visual processing of written language and lexical features. It also highlights unanswered questions that can guide us towards future research directions. Bridging measures of brain structure and function will help us reach a more precise understanding of the transformation from vision to language.

    View details for DOI 10.1007/s00429-021-02384-8

    View details for PubMedID 34636985

  • Rapid online assessment of reading ability. Scientific reports Yeatman, J. D., Tang, K. A., Donnelly, P. M., Yablonski, M., Ramamurthy, M., Karipidis, I. I., Caffarra, S., Takada, M. E., Kanopka, K., Ben-Shachar, M., Domingue, B. W. 2021; 11 (1): 6396


    An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the web-browser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test (r=0.91, disattenuated r=0.94). Importantly, the LDT reading ability measure is highly reliable (r=0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 76 trials (2-3min) provides a reliable (r=0.95) measure of reading ability. Thus, the self-administered, Rapid Online Assessment of Reading ability (ROAR) developed here overcomes the constraints of resource-intensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability.

    View details for DOI 10.1038/s41598-021-85907-x

    View details for PubMedID 33737729

  • A general role for ventral white matter pathways in morphological processing: Going beyond reading. NeuroImage Yablonski, M., Menashe, B., Ben-Shachar, M. 2020; 226: 117577


    The ability to recognize the structural components of words, known as morphological processing, was recently associated with the bilateral ventral white matter pathways, across different writing systems. However, it remains unclear whether these associations are specific to the context of reading. To shed light on this question, in the current study we investigated whether the ventral pathways are associated with morphological processing in an oral word production task that does not involve reading. Forty-five participants completed a morpheme-based fluency task in Hebrew, as well as diffusion MRI (dMRI) scans. We used probabilistic tractography to segment the major ventral and dorsal white matter pathways, and assessed the correlations between their microstructural properties and performance on the morpheme-based fluency task. We found significant correlations between morpheme-based fluency and properties of the bilateral ventral tracts, suggesting that the involvement of these tracts in morphological processing extends beyond the reading modality. In addition, significant correlations were found in the frontal aslant tract (FAT), a dorsal tract associated with oral fluency and speech production. Together, our findings emphasize that neurocognitive associations reflect both the cognitive construct under investigation as well as the task used for its assessment. Lastly, to elucidate the biological factors underlying these correlations, we incorporated the composite hindered and restricted model of diffusion (CHARMED) framework, measured in independent scans. We found that only some of our findings could be attributed to variation in a CHARMED-based estimate of fiber density. Further, we were able to uncover additional correlations that could not be detected using traditional dMRI indices. In sum, our results show that the involvement of the ventral tracts in morphological processing extends to the production domain, and demonstrate the added value of including sensitive structural measurements in neurocognitive investigations.

    View details for DOI 10.1016/j.neuroimage.2020.117577

    View details for PubMedID 33221439

  • Age-Dependent White Matter Characteristics of the Cerebellar Peduncles from Infancy Through Adolescence CEREBELLUM Bruckert, L., Shpanskaya, K., McKenna, E. S., Borchers, L. R., Yablonski, M., Blecher, T., Ben-Shachar, M., Travis, K. E., Feldman, H. M., Yeom, K. W. 2019; 18 (3): 372–87
  • Separate parts of occipito-temporal white matter fibers are associated with recognition of faces and places NEUROIMAGE Tavor, I., Yablonski, M., Mezer, A., Rom, S., Assaf, Y., Yovel, G. 2014; 86: 123–30


    A central finding of functional MRI studies is the highly selective response of distinct brain areas in the occipital temporal cortex to faces and places. However, little is known about the association of white matter fibers with the processing of these object categories. In the current study we used DTI-based tractography to reconstruct two main fibers that connect the occipital lobe with the anterior temporal lobe (inferior longitudinal fasciculus-ILF) and with the frontal lobe (inferior fronto-occipital fasciculus-IFOF) in normal individuals. In addition to MRI scans subjects performed face, scene and body recognition tasks outside the scanner. Results show that recognition of faces and scenes were selectively associated with separate parts of the ILF. In particular, face recognition was highly associated with the fractional anisotropy (FA) of the anterior part of the ILF in the right hemisphere. In contrast, scene recognition was strongly correlated with the FA of the posterior and middle but not the anterior part of the ILF bilaterally. Our findings provide the first demonstration that faces and places are not only associated with distinct brain areas but also with separate parts of white matter fibers.

    View details for DOI 10.1016/j.neuroimage.2013.07.085

    View details for Web of Science ID 000330335300014

    View details for PubMedID 23933304