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Topic: dyslexia

Seminar
4 seminars
ePoster
1 ePoster
Podcast episode
1 podcast episode

In Cognition and Neuroscience

Seminar · Cognition

How Dynamics of Statistical Learning Affects Skill Acquisition: the Cases of Dyslexia and Autism

Merav Ahissar · Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem

Fri, Sep 25, 2026 · 19:00 UTC

Merav Ahissar examines how expertise emerges through learning the statistics of task-relevant stimuli. Slow learning builds familiarity with stable regularities, such as syllable patterns in language, while fast adaptation supports flexible responses to changing situations, including surprising social interactions. The talk considers atypical learning dynamics in dyslexia and autism and how these may explain difficulties in linguistic and social skill acquisition, respectively. The discussion draws on Gertsovski and Ahissar, Trends in Cognitive Sciences, 2026. Speaker: Merav Ahissar, Edmond a

Podcast episode · Artificial Intelligence

AI boost for people with dyslexia and how algorithms shape what we read

The Science Show

Sep 12, 2026

The Science Show reviews a new approach to detecting and measuring concussion, a repurposed satellite for mapping the Universe, intervention to conserve a potentially sterile native plant, AI support for people with dyslexia, and how recommendation algorithms influence reading choices.

Seminar · Brain Imaging

Functional Plasticity in the Language Network – evidence from Neuroimaging and Neurostimulation

Gesa Hartwigsen · University of Leipzig, Germany

Tue, May 20, 2025 · 12:15 UTC

Efficient cognition requires flexible interactions between distributed neural networks in the human brain. These networks adapt to challenges by flexibly recruiting different regions and connections. In this talk, I will discuss how we study functional network plasticity and reorganization with combined neurostimulation and neuroimaging across the adult life span. I will argue that short-term plasticity enables flexible adaptation to challenges, via functional reorganization. My key hypothesis is that disruption of higher-level cognitive functions such as language can be compensated for by the

Seminar · Neuroscience

Dyslexia, Rhythm, Language and the Developing Brain

Usha Goswami CBE · University of Cambridge

Thu, Feb 22, 2024 · 12:00 UTC

Recent insights from auditory neuroscience provide a new perspective on how the brain encodes speech. Using these recent insights, I will provide an overview of key factors underpinning individual differences in children’s development of language and phonology, providing a context for exploring atypical reading development (dyslexia). Children with dyslexia are relatively insensitive to acoustic cues related to speech rhythm patterns. This lack of rhythmic sensitivity is related to the atypical neural encoding of rhythm patterns in speech by the brain. I will describe our recent data from infa

Seminar · Cognition

Learning-to-read and dyslexia: a cross-language computational perspective

Johannes Ziegler · Aix-Marseille University & CNRS

Tue, Sep 27, 2022 · 12:15 UTC

How do children learn to read in different countries? How do deficits in various components of the reading network affect learning outcomes? What are the consequences of such deficits in different languages? In this talk, I will present a full-blown developmentally plausible computational model of reading acquisition that has been implemented in English, French, Italian and German. The model can simulate individual learning trajectories and intervention outcomes on the basis of three component skills: orthography, phonology, and vocabulary. I will use the model to show how cross-language diffe

ePoster · Neuroscience

Neurophysiological correlates of cognitive load in online learning for neurotypical and neurodivergent students

Anne-Laure Le Cunff, Eleanor Dommett, Vincent Giampietro · FENS Forum 2024

Working memory is inherently limited in capacity and duration, which may hamper learning, including in online learning environments. Because working memory capacity varies among individuals, cognitive load in online learning may not have the same impact for neurotypical and neurodivergent students. This study investigated the relationship between neurodivergent traits and cognitive load during online learning. Seventy participants, including 35 neurotypical students and 35 neurodivergent students with a diagnosis of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD