228 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Massachusetts Institute of TechnologyUS9 papers
- McGovern Institute for Brain ResearchUS7 papers
- Center for Art StudiesKR5 papers
- Harvard UniversityUS3 papers
- University of California, BerkeleyUS3 papers
- Artificial Intelligence in Medicine (Canada)CA2 papers
- Cognitive Research (United States)US2 papers
- Intelligent Machines (Sweden)SE2 papers
- Johns Hopkins UniversityUS2 papers
- Mitsubishi Electric (United States)US2 papers
- Moscow Institute of Thermal TechnologyRU2 papers
- New York UniversityUS2 papers
24 papers
Fine-Grained Prediction of Reading Comprehension from Eye Movements
Omer Shubi, Yoav Meiri, Cfir Avraham Hadar +1
Can human reading comprehension be assessed from eye movements in reading? In this work, we address this longstanding question using large-scale eyetracking data over textual mater…
How does the primate brain combine generative and discriminative computations in vision?
Benjamin Peters, James J. DiCarlo, Todd Gureckis +10
Vision is widely understood as an inference problem. However, two contrasting conceptions of the inference process have each been influential in research on biological vision as we…
Disentangling Fact from Grid Cell Fiction in Trained Deep Path Integrators
Rylan Schaeffer, Mikail Khona, Sanmi Koyejo +1
Work on deep learning-based models of grid cells suggests that grid cells generically and robustly arise from optimizing networks to path integrate, i.e., track one's spatial posit…
Can Language Models Be Tricked by Language Illusions? Easier with Syntax, Harder with Semantics
Yuhan Zhang, Edward Gibson, Forrest Davis
Language models (LMs) have been argued to overlap substantially with human beings in grammaticality judgment tasks. But when humans systematically make errors in language processin…
Joint cortical registration of geometry and function using semi-supervised learning
Jian Li, Greta Tuckute, Evelina Fedorenko +3
Brain surface-based image registration, an important component of brain image analysis, establishes spatial correspondence between cortical surfaces. Existing iterative and learnin…
Beyond linear regression: mapping models in cognitive neuroscience should align with research goals
Anna A. Ivanova, Martin Schrimpf, Stefano Anzellotti +3
Many cognitive neuroscience studies use large feature sets to predict and interpret brain activity patterns. Feature sets take many forms, from human stimulus annotations to repres…
Decoding Event-related Potential from Ear-EEG Signals based on Ensemble Convolutional Neural Networks in Ambulatory Environment
Young-Eun Lee, Seong-Whan Lee
Recently, practical brain-computer interface is actively carried out, especially, in an ambulatory environment. However, the electroencephalography (EEG) signals are distorted by m…
Vector-based Pedestrian Navigation in Cities
Christian Bongiorno, Yulun Zhou, Marta Kryven +5
How do pedestrians choose their paths within city street networks? Researchers have tried to shed light on this matter through strictly controlled experiments, but an ultimate answ…
Evaluating Models of Robust Word Recognition with Serial Reproduction
Stephan C. Meylan, Sathvik Nair, Thomas L. Griffiths
Spoken communication occurs in a "noisy channel" characterized by high levels of environmental noise, variability within and between speakers, and lexical and syntactic ambiguity.…
Design of an EEG-based Drone Swarm Control System using Endogenous BCI Paradigms
Dae-Hyeok Lee, Hyung-Ju Ahn, Ji-Hoon Jeong +1
Non-invasive brain-computer interface (BCI) has been developed for understanding users' intentions by using electroencephalogram (EEG) signals. With the recent development of artif…
Functional Connectivity of Imagined Speech and Visual Imagery based on Spectral Dynamics
Seo-Hyun Lee, Minji Lee, Seong-Whan Lee
Recent advances in brain-computer interface technology have shown the potential of imagined speech and visual imagery as a robust paradigm for intuitive brain-computer interface co…
Automatic Micro-sleep Detection under Car-driving Simulation Environment using Night-sleep EEG
Young-Seok Kweon, Gi-Hwan Shin, Heon-Gyu Kwak +1
A micro-sleep is a short sleep that lasts from 1 to 30 secs. Its detection during driving is crucial to prevent accidents that could claim a lot of people's lives. Electroencephalo…
Data-Efficient Learning for Complex and Real-Time Physical Problem Solving using Augmented Simulation
Kei Ota, Devesh K. Jha, Diego Romeres +7
Humans quickly solve tasks in novel systems with complex dynamics, without requiring much interaction. While deep reinforcement learning algorithms have achieved tremendous success…
Decoding Visual Recognition of Objects from EEG Signals based on Attention-Driven Convolutional Neural Network
Jenifer Kalafatovich, Minji Lee, Seong-Whan Lee
The ability to perceive and recognize objects is fundamental for the interaction with the external environment. Studies that investigate them and their relationship with brain acti…
Decoding of Intuitive Visual Motion Imagery Using Convolutional Neural Network under 3D-BCI Training Environment
Byoung-Hee Kwon, Ji-Hoon Jeong, Jeong-Hyun Cho +1
In this study, we adopted visual motion imagery, which is a more intuitive brain-computer interface (BCI) paradigm, for decoding the intuitive user intention. We developed a 3-dime…
Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits
Lili Su, Chia-Jung Chang, Nancy Lynch
Winner-Take-All (WTA) refers to the neural operation that selects a (typically small) group of neurons from a large neuron pool. It is conjectured to underlie many of the brain's f…
Deep Learning Based Phase Reconstruction for Speaker Separation: A Trigonometric Perspective
Zhong-Qiu Wang, Ke Tan, DeLiang Wang
This study investigates phase reconstruction for deep learning based monaural talker-independent speaker separation in the short-time Fourier transform (STFT) domain. The key obser…
Does the brain represent words? An evaluation of brain decoding studies of language understanding
Jon Gauthier, Anna Ivanova
Language decoding studies have identified word representations which can be used to predict brain activity in response to novel words and sentences (Anderson et al., 2016; Pereira…
End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction
Zhong-Qiu Wang, Jonathan Le Roux, DeLiang Wang +1
This paper proposes an end-to-end approach for single-channel speaker-independent multi-speaker speech separation, where time-frequency (T-F) masking, the short-time Fourier transf…
Slip Detection with Combined Tactile and Visual Information
Jianhua Li, Siyuan Dong, Edward Adelson
Slip detection plays a vital role in robotic manipulation and it has long been a challenging problem in the robotic community. In this paper, we propose a new method based on deep…
BIRNet: Brain Image Registration Using Dual-Supervised Fully Convolutional Networks
Jingfan Fan, Xiaohuan Cao, Pew-Thian Yap +1
In this paper, we propose a deep learning approach for image registration by predicting deformation from image appearance. Since obtaining ground-truth deformation fields for train…
Modeling Human Understanding of Complex Intentional Action with a Bayesian Nonparametric Subgoal Model
Ryo Nakahashi, Chris L. Baker, Joshua B. Tenenbaum
Most human behaviors consist of multiple parts, steps, or subtasks. These structures guide our action planning and execution, but when we observe others, the latent structure of th…
Emergence of bimodality in controlling complex networks
Tao Jia, Yang-Yu Liu, Endre Csóka +3
Our ability to control complex systems is a fundamental challenge of contemporary science. Recently introduced tools to identify the driver nodes, nodes through which we can achiev…
Almost Optimal Intervention Sets for Causal Discovery
Frederick Eberhardt
We conjecture that the worst case number of experiments necessary and sufficient to discover a causal graph uniquely given its observational Markov equivalence class can be specifi…