Cover Image

fMRI predictors based on language models of increasing complexity recover brain left lateralization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bonnasse-Gahot, Laurent, Pallier, Christophe
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Neurons and Cognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Left-right asymmetry in predicting brain activity from LLMs' representations emerges with their formal linguistic competence
by: Bonnasse-Gahot, Laurent, et al.
Published: (2026)

Optimizing fMRI Data Acquisition for Decoding Natural Speech with Limited Participants
by: Jalouzot, Louis, et al.
Published: (2025)

BrainCodec: Neural fMRI codec for the decoding of cognitive brain states
by: Nishimura, Yuto, et al.
Published: (2024)

EmoMind: Decoding Affective Captions from Human Brain fMRI
by: Mohammed, Bilal A., et al.
Published: (2026)

Category learning in deep neural networks: Information content and geometry of internal representations
by: Bonnasse-Gahot, Laurent, et al.
Published: (2025)

Uncovering cognitive taskonomy through transfer learning in masked autoencoder-based fMRI reconstruction
by: Qu, Youzhi, et al.
Published: (2024)

Emergence of psychopathological computations in large language models
by: Lee, Soo Yong, et al.
Published: (2025)

Linguistic properties and model scale in brain encoding: from small to compressed language models
by: Oota, Subba Reddy, et al.
Published: (2026)

Intra-neuronal attention within language models Relationships between activation and semantics
by: Pichat, Michael, et al.
Published: (2025)

Hebbian learning the local structure of language
by: Eugenio, P. Myles
Published: (2025)

Resting state fMRI-based brain information flow mapping
by: Wang, Ze
Published: (2024)

Fusion Learning from Dynamic Functional Connectivity: Combining the Amplitude and Phase of fMRI Signals to Identify Brain Disorders
by: Hu, Jinlong, et al.
Published: (2026)

Spatiotemporal Learning of Brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention for Cognitive and Psychiatric Applications
by: Bae, Sangyoon, et al.
Published: (2025)

Do self-supervised speech and language models extract similar representations as human brain?
by: Chen, Peili, et al.
Published: (2023)

Talking to the brain: Using Large Language Models as Proxies to Model Brain Semantic Representation
by: Liu, Xin, et al.
Published: (2025)

Brain-IT: Image Reconstruction from fMRI via Brain-Interaction Transformer
by: Beliy, Roman, et al.
Published: (2025)

Do Large Language Models Think Like the Brain? Sentence-Level Evidences from Layer-Wise Embeddings and fMRI
by: Lei, Yu, et al.
Published: (2025)

The neural correlates of logical-mathematical symbol systems processing resemble that of spatial cognition more than natural language processing
by: Li, Yuannan, et al.
Published: (2024)

Scaling up ridge regression for brain encoding in a massive individual fMRI dataset
by: Ahmadi, Sana, et al.
Published: (2024)

MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data
by: Scotti, Paul S., et al.
Published: (2024)

A neural network for modeling human concept formation, understanding and communication
by: Guo, Liangxuan, et al.
Published: (2026)

The brain-AI convergence: Predictive and generative world models for general-purpose computation
by: Ohmae, Shogo, et al.
Published: (2025)

Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data
by: Thapaliya, Bishal, et al.
Published: (2023)

Brain-OF: An Omnifunctional Foundation Model for fMRI, EEG and MEG
by: Guo, Hanning, et al.
Published: (2026)

Distinct social-linguistic processing between humans and large audio-language models: Evidence from model-brain alignment
by: Wu, Hanlin, et al.
Published: (2025)

The Dynamics of Triple Interactions in Resting fMRI: Insights into Psychotic Disorders
by: Li, Qiang, et al.
Published: (2024)

Neural network-based encoding in free-viewing fMRI with gaze-aware models
by: Gozukara, Dora, et al.
Published: (2026)

Large language models are not about natural language
by: Bolhuis, Johan J., et al.
Published: (2025)

Seeing the imagined: a latent functional alignment in visual imagery decoding from fMRI data
by: Spera, Fabrizio, et al.
Published: (2026)

Ensemble-based graph representation of fMRI data for cognitive brain state classification
by: Vlasenko, Daniil, et al.
Published: (2025)

The age of spiritual machines: Language quietus induces synthetic altered states of consciousness in artificial intelligence
by: Skipper, Jeremy I, et al.
Published: (2024)

Computational Thought Experiments for a More Rigorous Philosophy and Science of the Mind
by: Oved, Iris, et al.
Published: (2024)

Neural Erosion: Emulating Controlled Neurodegeneration and Aging in AI Systems
by: Alexos, Antonios, et al.
Published: (2024)

Self-Attention Limits Working Memory Capacity of Transformer-Based Models
by: Gong, Dongyu, et al.
Published: (2024)

Matching domain experts by training from scratch on domain knowledge
by: Luo, Xiaoliang, et al.
Published: (2024)

Memory, Consciousness and Large Language Model
by: Li, Jitang, et al.
Published: (2024)

Contextual Feature Extraction Hierarchies Converge in Large Language Models and the Brain
by: Mischler, Gavin, et al.
Published: (2024)

Comparing Abstraction in Humans and Large Language Models Using Multimodal Serial Reproduction
by: Kumar, Sreejan, et al.
Published: (2024)

Lost in Translation: The Algorithmic Gap Between LMs and the Brain
by: Tosato, Tommaso, et al.
Published: (2024)

A Comparison of Large Language Model and Human Performance on Random Number Generation Tasks
by: Harrison, Rachel M.
Published: (2024)