Modeling the Dynamics of Human Brain Activity with Recurrent Neural Networks

@article{Gl2017ModelingTD,
  title={Modeling the Dynamics of Human Brain Activity with Recurrent Neural Networks},
  author={Umut G{\"u}çl{\"u} and M. V. Gerven},
  journal={Frontiers in Computational Neuroscience},
  year={2017},
  volume={11}
}
Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of stimuli to features (feature model) and a linear convolution of features to responses (response model). While there has been extensive work on developing better feature models, the work on developing better response models has been rather limited. Here, we… Expand
68 Citations
Recognizing Brain States Using Deep Sparse Recurrent Neural Network
  • 17
Identifying Brain Networks at Multiple Time Scales via Deep Recurrent Neural Network
  • Y. Cui, Shijie Zhao, +6 authors T. Liu
  • Computer Science, Medicine
  • IEEE Journal of Biomedical and Health Informatics
  • 2019
  • 2
  • Highly Influenced
Modeling Brain Diverse and Complex Hemodynamic Response Patterns via Deep Recurrent Autoencoder
  • 3
  • Highly Influenced
Supervised Brain Network Learning Based on Deep Recurrent Neural Networks
  • 1
  • PDF
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 71 REFERENCES
Unsupervised Feature Learning Improves Prediction of Human Brain Activity in Response to Natural Images
  • 49
  • PDF
Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.
  • N. Kriegeskorte
  • Computer Science, Medicine
  • Annual review of vision science
  • 2015
  • 489
  • PDF
Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies
  • 670
  • Highly Influential
  • PDF
ENCODING AND DECODING V1 FMRI RESPONSES TO NATURAL IMAGES WITH SPARSE NONPARAMETRIC MODELS.
  • 35
  • PDF
Performance-optimized hierarchical models predict neural responses in higher visual cortex
  • 1,055
  • PDF
Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics
  • 999
  • PDF
Nonlinear event‐related responses in fMRI
  • 626
  • Highly Influential
  • PDF
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition
  • 63
  • PDF
Seeing it all: Convolutional network layers map the function of the human visual system
  • 162
  • PDF
...
1
2
3
4
5
...