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We create a reusable Transformer, BrainBERT, for intracranial recordings bringing modern representation learning approaches to neuroscience.
Fractal dimension of electroencephalographic time series and underlying brain processes
Werner Lutzenberger, Hubert Preissl, and Friedemann Pulvermüller · 1995
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The amygdala and emotion
Michela Gallagher and Andrea A Chiba · 1996
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Automatically Parcellating the Human Cerebral Cortex
Bruce Fischl, André van der Kouwe, Christophe Destrieux, Eric Halgren, Florent Ségonne, David H. Salat, Evelina Busa, Larry J. Seidman, Jill Goldstein, David Kennedy, Verne Caviness, Nikos Makris, Bruce Rosen, and Anders M. Dale · 2004
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Convergence of sensory systems in the orbitofrontal cortex in primates and brain design for emotion
Edmund T Rolls · 2004
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A field-theoretic approach to understanding scale-free neocortical dynamics
Walter J Freeman · 2005
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An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest
Rahul S. Desikan, Florent Ségonne, Bruce Fischl, Brian T. Quinn, Bradford C. Dickerson, Deborah Blacker, Randy L. Buckner, Anders M. Dale, R. Paul Maguire, Bradley T. Hyman, Marilyn S. Albert, and Ronald J. Killiany · 2006
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Timing, timing, timing: fast decoding of object information from intracranial field potentials in human visual cortex
Hesheng Liu, Yigal Agam, Joseph R Madsen, and Gabriel Kreiman · 2009
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Intrinsic dimension estimation of data by principal component analysis
Mingyu Fan, Nannan Gu, Hong Qiao, and Bo Zhang · 2010
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Unified framework for development, deployment and robust testing of neuroimaging algorithms
A. Joshi, D. Scheinost, H. Okuda, D. Belhachemi, I. Murphy, L. H. Staib, and X. Papademetris · 2011
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Localization of dense intracranial electrode arrays using magnetic resonance imaging
A. I. Yang, X. Wang, W. K. Doyle, E. Halgren, C. Carlson, T. L. Belcher, S. S. Cash, O. Devinsky, and T. Thesen · 2012
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Gamma and the coordination of spiking activity in early visual cortex
Xiaoxuan Jia, Seiji Tanabe, and Adam Kohn · 2013
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On the role of the supramarginal gyrus in phonological processing and verbal working memory: evidence from rTMS studies
Isabelle Deschamps, Shari R Baum, and Vincent L Gracco · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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librosa: Audio and music signal analysis in Python
Brian McFee, Colin Raffel, Dawen Liang, Daniel PW Ellis, Matt McVicar, Eric Battenberg, and Oriol Nieto · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Language mapping using high gamma electrocorticography, fMRI, and TMS versus electrocortical stimulation
Abbas Babajani-Feremi, Shalini Narayana, Roozbeh Rezaie, Asim F Choudhri, Stephen P Fulton, Frederick A Boop, James W Wheless, and Andrew C Papanicolaou · 2016
Cited alongside, same era.
Gaussian error linear units (GELUs)
Dan Hendrycks and Kevin Gimpel · 2016
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Decoding local field potentials for neural interfaces
Andrew Jackson and Thomas M Hall · 2016
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The potential of stereotactic-eeg for brain-computer interfaces: current progress and future directions
Christian Herff, Dean J Krusienski, and Pieter Kubben · 2020
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Decoar 2.0: Deep contextualized acoustic representations with vector quantization
Shaoshi Ling and Yuzong Liu · 2020
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Mockingjay: Unsupervised speech representation learning with deep bidirectional transformer encoders
Andy T Liu, Shu-wen Yang, Po-Han Chi, Po-chun Hsu, and Hung-yi Lee · 2020
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Uncovering the structure of clinical EEG signals with self-supervised learning
Hubert Banville, Omar Chehab, Aapo Hyvärinen, Denis Alexander Engemann, and Alexandre Gramfort · 2021
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Cognitive and emotional mapping with SEEG
Daniel L Drane, Nigel P Pedersen, David S Sabsevitz, Cady Block, Adam S Dickey, Abdulrahman Alwaki, and Ammar Kheder · 2021
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iELVis: An open source matlab toolbox for localizing and visualizing human intracranial electrode data
David M. Groppe, Stephan Bickel, Andrew R. Dykstra, Xiuyuan Wang, Pierre Mégevand, Manuel R. Mercier, Fred A. Lado, Ashesh D. Mehta, and Christopher J. Honey · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Optimal referencing for stereo-electroencephalographic (SEEG) recordings
Guangye Li, Shize Jiang, Sivylla E Paraskevopoulou, Meng Wang, Yang Xu, Zehan Wu, Liang Chen, Dingguo Zhang, and Gerwin Schalk · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Cited alongside, same era.
Intrinsic dimension of data representations in deep neural networks
Alessio Ansuini, Alessandro Laio, Jakob H Macke, and Davide Zoccolan · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
BERT rediscovers the classical NLP pipeline
Ian Tenney, Dipanjan Das, and Ellie Pavlick · 2019
Cited alongside, same era.
The low-dimensional linear geometry of contextualized word representations
Evan Hernandez and Jacob Andreas · 2021
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HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed · 2021
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BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data
Demetres Kostas, Stephane Aroca-Ouellette, and Frank Rudzicz · 2021
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TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
Andy T. Liu, Shang Wen Li, and Hung Yi Lee · 2021
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Pre-training and fine-tuning transformers for fMRI prediction tasks
Itzik Malkiel, Gony Rosenman, Lior Wolf, and Talma Hendler · 2021
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Time-frequency super-resolution with superlets
Vasile V Moca, Harald Bârzan, Adriana Nagy-Dăbâcan, and Raul C Mureșan · 2021
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Large batch optimization for deep learning: Training BERT in 76 minutes
Yang You, Jing Li, Sashank Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, and Cho-Jui Hsieh · 2021
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Missing links: The functional unification of language and memory (LuM)
Elise Roger, Sonja Banjac, Michel Thiebaut de Schotten, and Monica Baciu · 2022
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