Peer reviewed publications

To view a quick guide to recent publications, click here.

"Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset"
A. Wang, K. Kay, T. Naselaris, M. Tarr, L. Wehbe.
Nature Machine Intelligence, 2023.
journal view bioRxiv

"Brain diffusion for visual exploration: Cortical discovery using large scale generative models"
A. Luo, M. Henderson, L. Wehbe*, Michael J Tarr*.
Neural Information Processing Systems (NeurIPS), 2023. Chosen for oral presentation.

"Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity"
J. Ye, J. Collinger, L. Wehbe, R. Gaunt.
Neural Information Processing Systems (NeurIPS), 2023.
bioRxiv code

"Brain dissection: fMRI-trained networks reveal spatial selectivity in the processing of natural images"
G. Sarch, M. Tarr, K. Fragkiadaki*, L. Wehbe*.
Neural Information Processing Systems (NeurIPS), 2023.

"A texture statistics encoding model reveals hierarchical feature selectivity across human visual cortex"
M. Henderson, M. Tarr, L. Wehbe.
Journal of Neuroscience, 2023.

"Stacked regressions and structured variance partitioning for interpretable brain maps"
R. Lin, T. Naselaris, K. Kay, L. Wehbe.
in review.
bioRxiv github

"Low-level tuning biases in higher visual cortex reflect the semantic informativeness of visual features"
M. Henderson, M. Tarr, L. Wehbe.
Journal of Vision, 2023.
journal bioRxiv

"Semantic representations during language comprehension are affected by context"
F. Deniz*, C. Tseng*, L. Wehbe, T. Dupre la Tour, J. Gallant.
Journal of Neuroscience, 2023.
journal bioRxiv

"Selectivity for food in human ventral visual cortex"
N. Jain, A. Wang, M. Henderson, R. Lin, J. Prince, M. Tarr, L. Wehbe.
Communications Biology, 2023.
journal github data bioRxiv

"Computational language modeling and the promise of in silico experimentation"
S. Jain, V. Vo, L. Wehbe, A. Huth.
Neurobiology of Language, 2023.

"A roadmap to reverse engineering real-world generalization by combining naturalistic paradigms, deep sampling, and predictive computational models"
P. Herholz, E. Fortier, M. Toneva, N. Farrugia, L. Wehbe, V. Borghesani.
Neurons, Behavior, Data analysis, and Theory, 2023.

"Combining computational controls with natural text reveals aspects of meaning composition"
M. Toneva, T. Mitchell, L. Wehbe
Nature Computational Science, 2022.
journal bioRxiv view

"Brainprint: identifying individuals from Magnetoencephalography"
S. Wu, A. Ramdas and L. Wehbe.
Communications Biology, 2022.
journal bioRxiv

"High-level visual areas act like domain-general filters with strong selectivity and functional specialization"
M. Khosla, L. Wehbe.
in review.

"Same Cause; Different Effects in the Brain "
M. Toneva, J. Williams, A. Bollu, C. Dann, L. Wehbe.
Proceedings of the Conference on Causal Learning and Reasoning (CLeaR) 2022.
conference arXiv

"Behavior measures are predicted by how information is encoded in an individual's brain"
J. Williams, L. Wehbe.
in review.

"Can fMRI reveal the representation of syntactic structure in the brain?"
A. Reddy, L. Wehbe.
Neural Information Processing Systems (NeurIPS) 2021.
NeurIPS bioRxiv

"Single-trial MEG data can be denoised through cross-subject predictive modeling"
S. Ravishankar, M. Toneva, L. Wehbe.
Frontiers In Computational Neuroscience , 2021.

"Incremental language comprehension difficulty predicts activity in the language network but not the multiple demand network"
L. Wehbe , I. Blank, C. Shain, R. Futrell, R. Levy, T. von der Malsburg, N. Smith, E. Gibson, E. Fedorenko.
Cerebral Cortex, 2021.
journal pdf bibtex

"A deep learning model for automated classification of intraoperative continuous EMG"
X. Zha, L. Wehbe, R. Sclabassi, Z. Mace, Y. Liang, A. Yu, J. Leonardo, B. Cheng, T. Hillman, D. Chen, C. Riviere
IEEE Transactions on Medical Robotics and Bionics, 2020.
journal website bibtex

"Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction"
M. Toneva, O. Stretcu, B. Poczos, L. Wehbe, T. Mitchell
Neural Information Processing Systems (NeurIPS) 2020.
neurips arXiv

"Inducing brain-relevant bias in natural language processing models"
D. Schwartz, M. Toneva and L. Wehbe.
Neural Information Processing Systems (NeurIPS) 2019.
NeurIPS arXiv bibtex

"Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity"
A. Wang, M. Tarr and L. Wehbe.
Neural Information Processing Systems (NeurIPS) 2019.
NeurIPS bioRxiv bibtex

"Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)"
M. Toneva and L. Wehbe .
Neural Information Processing Systems (NeurIPS) 2019.
NeurIPS arXiv bibtex

"Self-Discriminative Learning for Unsupervised Document Embedding"
H. Chen, C. Hu, L. Wehbe and S. Lin.
Proceedings of the 2019 Conference of the North American Chapter of the ACL (NAACL), oral presentation.
pdf bibtex

"The lexical semantics of adjective–noun phrases in the human brain"
A. Fyshe, G. Sudre, L. Wehbe, N. Rafidi, T. M. Mitchell
Human Brain Mapping, 2019.
Journal bioRXiv bibtex

"Mapping neural activity to language meaning"
L. Wehbe, A. Fyshe, T. Mitchell
Human Language: from Genes and Brains to Behavior, MIT Press, 2019.

"Decoding Language from the Brain"
B. Murphy, L. Wehbe, A. Fyshe
Language, Cognition, and Computational Models, Cambridge University Press, 2018.

"Regularized Brain Reading with Shrinkage and Smoothing"
L. Wehbe, A. Ramdas, R. C. Steorts, C. R. Shalizi
Annals of Applied Statistics, 2015.
pdf journal website arXiv bibtex

"Nonparametric Independence Testing for Small Sample Sizes"
L. Wehbe*, A. Ramdas* (equal contribution)
Proceedings of the 2015 International Joint Conference on Artificial Intelligence (IJCAI, oral presentation).
pdf arXiv bibtex

"A Compositional and Interpretable Semantic Space"
A. Fyshe, L. Wehbe, P. Talukdar, B. Murphy and T. Mitchell
Proceedings of the 2015 Conference of the North American Chapter of the ACL, chosen for oral presentation (NAACL 2015).
pdf bibtex

"Aligning context-based statistical models of language with
brain activity during reading"

L. Wehbe, A. Vaswani, K. Knight, T. Mitchell
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP, long paper).
supporting website pdf conference talk video bibtex

"Simultaneously uncovering the patterns of brain regions involved in
different story reading subprocesses"

L. Wehbe, B. Murphy, P. Talukdar, A. Fyshe, A. Ramdas, T. Mitchell
PLOS ONE, 2014.
supporting website (data) journal website pdf supplementary material bibtex

"Tracking neural coding of perceptual and semantic features of concrete nouns"
G. Sudre, D. Pomerleau, M. Palatucci, L. Wehbe, A. Fyshe, R. Salmelin and T. Mitchell
NeuroImage, 2012.
journal website pdf bibtex

posters, workshop papers and demos

"Deep multi-view representation learning of brain responses to natural stimuli"
L. Wehbe*, A. Nunez-Elizalde*, A. Huth, F. Deniz, N. Bilenko, J. Gallant.
Cognitive Computational Neuroscience, CCN 2017 poster.

"BOLD predictions: automated simulation of fMRI experiments"
L. Wehbe, A. Huth, F. Deniz, M. Kieseler, J. Gallant.
Organization for Human Brain Mapping, OHBM 2017 poster and talk..
NIPS 2016 demonstration track.
online engine

"Neural activity in the fronto-temporal language system predicts online language comprehension difficulty"
L. Wehbe, I. Blank, K. Mahowald, R. Furell, S. Piantadosi, H. Tily, J. Gallee, A. Vishnevetsky, E. Gibson, N. Kanwisher, E. Fedorenko
Society for the Neurobiology of Language, SNL 2015 poster.

"The dynamics of information integration in the brain during story reading"
L. Wehbe, A. Vaswani, K. Knight, T. Mitchell
Society for the Neurobiology of Language, SNL 2014 poster.

"Tracking story reading in the brain"
L. Wehbe, P. Talukdar, B. Murphy, A. Fyshe, G. Sudre, T. Mitchell
NIPS 2012 Workshop in Machine Learning and Interpretation in NeuroImaging, paper, chosen for oral presentation.

"Decoding Word Semantics from Magnetoencephalography Time Series Transformations"
A. Fyshe L. Wehbe, B. Murphy, T. Mitchell
NIPS 2012 Workshop in Machine Learning and Interpretation in NeuroImaging, paper.