Dissociating language and thought in large language models

K Mahowald, AA Ivanova, IA Blank, N Kanwisher… - Trends in Cognitive …, 2024 - cell.com
Large language models (LLMs) have come closest among all models to date to mastering
human language, yet opinions about their linguistic and cognitive capabilities remain split …

The language network as a natural kind within the broader landscape of the human brain

E Fedorenko, AA Ivanova, TI Regev - Nature Reviews Neuroscience, 2024 - nature.com
Abstract Language behaviour is complex, but neuroscientific evidence disentangles it into
distinct components supported by dedicated brain areas or networks. In this Review, we …

Evidence of a predictive coding hierarchy in the human brain listening to speech

C Caucheteux, A Gramfort, JR King - Nature human behaviour, 2023 - nature.com
Considerable progress has recently been made in natural language processing: deep
learning algorithms are increasingly able to generate, summarize, translate and classify …

Driving and suppressing the human language network using large language models

G Tuckute, A Sathe, S Srikant, M Taliaferro… - Nature Human …, 2024 - nature.com
Transformer models such as GPT generate human-like language and are predictive of
human brain responses to language. Here, using functional-MRI-measured brain responses …

Robust effects of working memory demand during naturalistic language comprehension in language-selective cortex

C Shain, IA Blank, E Fedorenko, E Gibson… - Journal of …, 2022 - Soc Neuroscience
To understand language, we must infer structured meanings from real-time auditory or visual
signals. Researchers have long focused on word-by-word structure building in working …

Artificial neural network language models align neurally and behaviorally with humans even after a developmentally realistic amount of training

EA Hosseini, M Schrimpf, Y Zhang, S Bowman… - BioRxiv, 2022 - biorxiv.org
Artificial neural networks have emerged as computationally plausible models of human
language processing. A major criticism of these models is that the amount of training data …

The human language system, including its inferior frontal component in “Broca's area,” does not support music perception

X Chen, J Affourtit, R Ryskin, TI Regev… - Cerebral …, 2023 - academic.oup.com
Abstract Language and music are two human-unique capacities whose relationship remains
debated. Some have argued for overlap in processing mechanisms, especially for structure …

Precision fMRI reveals that the language-selective network supports both phrase-structure building and lexical access during language production

J Hu, H Small, H Kean, A Takahashi… - Cerebral …, 2023 - academic.oup.com
A fronto-temporal brain network has long been implicated in language comprehension.
However, this network's role in language production remains debated. In particular, it …

Artificial neural network language models predict human brain responses to language even after a developmentally realistic amount of training

EA Hosseini, M Schrimpf, Y Zhang… - Neurobiology of …, 2024 - direct.mit.edu
Artificial neural networks have emerged as computationally plausible models of human
language processing. A major criticism of these models is that the amount of training data …

Long-range and hierarchical language predictions in brains and algorithms

C Caucheteux, A Gramfort, JR King - arxiv preprint arxiv:2111.14232, 2021 - arxiv.org
Deep learning has recently made remarkable progress in natural language processing. Yet,
the resulting algorithms remain far from competing with the language abilities of the human …