bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.06.07.447429

How perception and attention participate in reading skill?

Gudwani, S.·Mehta, M.·Sagar, R.·Behari, M.·Narang, V.·Dwivedi, S.·Jagannathan, N. R.·Kumaran, S. S.
View original source ↗Export metadata ↓

Abstract

Reading creates accessibility to the outer world information and is an integral skill for academic achievement. It involves visual perception, reasoning at symbolic level (text reading) and phonological processing. But does perception, visuospatial processing at pre-symbolic level affect reading skill? To understand and untangle the mechanism fifty children with reading problem (developmental dyslexia, DDC) and twentyfive age-matched typical readers (healthy controls, HC) were studied. In DDC, the variable-performance of non-symbolic visual search (pictorial-level) was associated with bilateral brain activity (functional MRI) of ventral stream (inferior occipital and fusiform) and greater involvement of frontal-prefrontal regions, suggesting the modified dorsal route-gating for figure-ground filtering. Performance variability in picture-concept reasoning (71.9% and significant group mean difference) and visuospatial-organization (51.3%) of DDC children indicate attentional or executive differences at nonsymbolic level. In symbolic discrimination performance, no significant difference observed for single alphabet or number (digit) reading but significant differences at word level for visual and phonological performance (considering orthographic differences), attributes to distractor-inhibition problems. Nonsymbolic to symbolic coding/decoding speed and writing error (copying) differences are suggestive of execution variability rather than motor coordination in DDC. In HC, the top-down dorsal route gating and hypoactivity induced in right frontal-anterior cingulate cortices, play a major role in reading by allocating spatial attention and inhibiting distractors. It has been elaborated in the "neurobiological model". How perception and attention participate in reading skill?O_ST_ABSResearch HighlightsC_ST_ABSO_LIVisuospatial attention, executive control (nonsymbolic level) and visual discrimination (symbolic level) performance contribute to reading. C_LIO_LIIn children with reading problems (dyslexia) pictorial visual processing task (fMRI) recruited higher activation in right hemispheric frontal, inferior parietal and anterior cingulate regions. C_LIO_LIBilateral activation of occipital-striate, extra-striate, fusiform for nonsymbolic is associated with significantly more errors at bigger-symbol-string, in dyslexia. C_LIO_LIAuditory discrimination differences in shallow-deep orthography. C_LIO_LICorrelation of non-symbolic executive and symbolic performances. C_LIO_LIRole of the prelexical visual perception and dorsal-route gating in reading skill explained as neurobiological model. C_LI

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gudwani, S., Mehta, M., Sagar, R., Behari, M., Narang, V., Dwivedi, S., Jagannathan, N. R., Kumaran, S. S.. 2021-06-08. How perception and attention participate in reading skill?. https://doi.org/10.1101/2021.06.07.447429

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗
bioRxiv2026

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗
bioRxiv2026

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗