Neurocomputational models of language processing

JT Hale, L Campanelli, J Li, S Bhattasali… - Annual Review of …, 2022 - annualreviews.org
Efforts to understand the brain bases of language face the Map** Problem: At what level
do linguistic computations and representations connect to human neurobiology? We review …

Computational language modeling and the promise of in silico experimentation

S Jain, VA Vo, L Wehbe, AG Huth - Neurobiology of Language, 2024 - direct.mit.edu
Abstract Language neuroscience currently relies on two major experimental paradigms:
controlled experiments using carefully hand-designed stimuli, and natural stimulus …

Naturalistic stimuli: A paradigm for multiscale functional characterization of the human brain

Y Zhang, JH Kim, D Brang, Z Liu - Current opinion in biomedical …, 2021 - Elsevier
Movies, audio stories, and virtual reality are increasingly used as stimuli for functional brain
imaging. Such naturalistic paradigms are in sharp contrast to the tradition of experimental …

Le Petit Prince multilingual naturalistic fMRI corpus

J Li, S Bhattasali, S Zhang, B Franzluebbers, WM Luh… - Scientific data, 2022 - nature.com
Neuroimaging using more ecologically valid stimuli such as audiobooks has advanced our
understanding of natural language comprehension in the brain. However, prior naturalistic …

Eelbrain, a Python toolkit for time-continuous analysis with temporal response functions

C Brodbeck, P Das, M Gillis, JP Kulasingham… - Elife, 2023 - elifesciences.org
Even though human experience unfolds continuously in time, it is not strictly linear; instead,
it entails cascading processes building hierarchical cognitive structures. For instance, during …

A synchronized multimodal neuroimaging dataset for studying brain language processing

S Wang, X Zhang, J Zhang, C Zong - Scientific Data, 2022 - nature.com
We present a synchronized multimodal neuroimaging dataset for studying brain language
processing (SMN4Lang) that contains functional magnetic resonance imaging (fMRI) and …

From form (s) to meaning: Probing the semantic depths of language models using multisense consistency

X Ohmer, E Bruni, D Hupke - Computational Linguistics, 2024 - direct.mit.edu
The staggering pace with which the capabilities of large language models (LLMs) are
increasing, as measured by a range of commonly used natural language understanding …

Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability

E Roger, LR De Almeida, H Loevenbruck… - NeuroImage, 2022 - Elsevier
Abstract Language processing is a highly integrative function, intertwining linguistic
operations (processing the language code intentionally used for communication) and extra …

Decoding part-of-speech from human EEG signals

A Murphy, B Bohnet, R McDonald… - Proceedings of the 60th …, 2022 - aclanthology.org
This work explores techniques to predict Part-of-Speech (PoS) tags from neural signals
measured at millisecond resolution with electroencephalography (EEG) during text reading …

Exploring temporal sensitivity in the brain using multi-timescale language models: An EEG decoding study

S Ling, A Murphy, A Fyshe - Computational Linguistics, 2024 - direct.mit.edu
The brain's ability to perform complex computations at varying timescales is crucial, ranging
from understanding single words to gras** the overarching narrative of a story. Recently …