Invited Symposium 4 - How the Brain Creates Language: Insights from Genes, Neural Pathways, Neuroprosthetics, and Computational Models

Tuesday, March 10, 2026, 10:00 am – 12:00 pm PDT, Salon EF

Chair: Tamara Swaab^1,2; ¹University of Birmingham, UK, ²University of California, Davis, USA
Presenters: Reyna Gordon, Stephanie Forkel, Edward Chang, Jean-Remi King

Understanding how the human brain creates language requires explanations that span from our genetic blueprint to the neural circuits and computational principles that support communication. This invited symposium brings together four internationally recognized leaders whose research provides complementary insights into the biological and computational foundations of human speech and language. Reyna Gordon will open the session by revealing how large-scale genomic studies identify the genetic variants and neurogenomic pathways that shape language development and vulnerability to communication disorders. Stephanie Forkel will then demonstrate how individual differences in white-matter pathways and large-scale network organization give rise to diverse language profiles. In the third talk, Eddie Chang will examine how intracranial recordings and emerging neuroprosthetic technologies reveal the population-level neural codes that underlie speech perception and production, and how these insights are transforming efforts to restore communication. Finally, Jean-Remi King will show how modern deep learning models provide a powerful computational framework for explaining brain responses to natural speech across development, offering an operational bridge between neural data and the algorithms that support language processing. Together, these talks illustrate a unique cross-scale synthesis—from genes to pathways, neural dynamics, and computational architectures—advancing a mechanistic understanding of how the brain produces and comprehends language.

Presentations

Genetic Foundations of Human Language

Reyna Gordon¹; ¹Vanderbilt University Medical Center, USA

This talk will provide a state-of-the-art overview on how genetic variation shapes the development and functioning of neural systems supporting human speech and language. I will introduce the concept of Genome-Wide-Association Studies (GWAS) and explain how recent large-scale GWAS of language and reading traits have provided new perspectives on the biological foundations of typical and atypical human communicative abilities, in part through the integration of neurogenomic data. The talk will also cover the principles of measuring language skills for GWAS, and will expose unique opportunities afforded by genomic approaches to language such as measuring genetic overlap with other behavioral, cognitive, neural, and health traits at scale.

The Neuroanatomy of Language Pathways

Stephanie Forkel^1,2; ¹Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands, ²Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands

Classical models have long ascribed language to specialized cortical “modules” such as Broca’s and Wernicke’s areas. Yet accumulating evidence reveals a far more distributed and variable architecture. This talk combines advanced diffusion tractography, functional MRI, and post-mortem anatomy to chart the structural and functional networks that underpin language across individuals. By integrating tract-based dissections with embedding analyses, we capture the latent geometry of the language connectome — revealing that language organization is neither fully modular nor random, but structurally distributed. This framework of neurovariability and precision connectomics shows how individual brains instantiate shared linguistic functions through distinct anatomical routes. Moving beyond fixed parcellations, I argue that language emerges from the interplay of distributed circuits whose configuration reflects both biological constraints and experiential history.

Neural Codes for Speech

Edward Chang¹; ¹University of California, San Francisco, USA

This talk will present recent advances in understanding the fine-grained neural mechanisms underlying human speech production and perception. Using high-density intracranial recordings, the research tracks how cortical circuits encode phonetic, articulatory, and prosodic features of speech. The presentation will also highlight progress toward neuroprosthetic systems designed to restore communication in individuals who have lost the ability to speak, illustrating how knowledge of the brain’s dynamic speech code is driving transformative clinical innovation.

Modeling the Emergence and Processing of Language in the Human Brain

Jean-Remi King¹; ¹CNRS, École Normale Supérieure, France

Deep learning has driven major advances in natural language processing. In addition to their technical performance, these algorithms offer new methods to understand and model how language is processed in the human brain. Using both encoding (representations -> brain) and decoding (brain -> representations), we show that the comparison between modern speech and language models effectively accounts for brain responses to natural speech as recorded with EEG, MEG, iEEG and fMRI, including in children between 2 and 12 years old. This systematic comparison provides an operational foundation to model language in the adult and developing brain, thus offering a new path to understand the neural and computational bases of this human-specific ability.