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https://github.com/robi56/awesome-cognitive-science-and-deep-learning

A curated list of resources dedicated to bridge between Cognitive Science and Deep Learning
https://github.com/robi56/awesome-cognitive-science-and-deep-learning

List: awesome-cognitive-science-and-deep-learning

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A curated list of resources dedicated to bridge between Cognitive Science and Deep Learning

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# awesome-cognitive-science-and-deep-learning
A curated list of resources dedicated to bridge between coginitive science and deep learning
## Table of Contents
- [Theory](#theory)
- [Papers / Thesis](#papers--thesis)

## Theory
### Papers / Thesis
#### 2017:
1. STDP-Compatible Approximation of Backpropagation in an Energy-Based Model|Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhuai Wu|2017

Source: http://www.mitpressjournals.org/doi/full/10.1162/NECO_a_00934#.WRFhOiakU_s
2. Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights |Arash Samadi, Timothy P. Lillicrap, Douglas B. Tweed|2017

Source: http://sci-hub.cc/10.1162/neco_a_00929
3. Solving Nonlinearly Separable Classifications in a Single-Layer Neural Network|Nolan Conaway, Kenneth J. Kurtz|2017

Source: http://sci-hub.cc/10.1162/neco_a_00931
4. Learning the Structural Vocabulary of a Network|Saket Navlakha|2014

Source: http://www.mitpressjournals.org/doi/pdf/10.1162/NECO_a_00924
5. Multistability of Delayed Recurrent Neural Networks with Mexican Hat Activation Functions|Peng Liu, Zhigang Zeng, Jun Wang|2017

Source: http://sci-hub.cc/10.1162/neco_a_00922
6. Controllability Analysis of the Neural Mass Model with Dynamic Parameters|Xian Liu, Jing Gao, Guan Wang, Zhi-Wang Chen|2017

Source: http://sci-hub.cc/10.1162/neco_a_00925
7. Energy Model of Neuron Activation|Yuriy Romanyshyn, Andriy Smerdov, Svitlana Petrytska|2017
Source: http://sci-hub.cc/10.1162/neco_a_00913
8. Active Inference: A Process Theory|Karl Friston, Thomas FitzGerald, Francesco Rigoli, Philipp Schwartenbeck, Giovanni Pezzulo|2017

Source: http://www.mitpressjournals.org/doi/pdf/10.1162/NECO_a_00912
9. A Combinatorial Model for Dentate Gyrus Sparse Coding |William Severa, Ojas Parekh, Conrad D. James, James B. Aimone|2017

Source: http://sci-hub.cc/10.1162/neco_a_00905
10. A Network Model of the Emotional Brain|Luiz Pessoa|2017

Source: http://sci-hub.cc/10.1016/j.tics.2017.03.002
11. Bayesian Brains without Probabilities|Sanborn et al.|2017

Source: http://sci-hub.cc/10.1016/j.tics.2016.10.003
12. Perceptual Decision-Making: Picking the Low-Hanging Fruit?|Floris P. de Lange, Matthias Fritsche|2017

Source: http://sci-hub.cc/10.1016/j.tics.2017.03.006
13. Exercising Control Over Memory Consolidation|Edwin M. Robertson, Adam Takacs|2017

Source: http://twin.sci-hub.cc/9b3a10641014af416f50d91b0db04091/robertson2017.pdf?download=true
14. Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity|Frank G. Hillary, Jordan H. Grafman|2017

Source: http://sci-hub.cc/10.1016/j.tics.2017.03.003
15. An Update on Memory Reconsolidation Updating|Jonathan L.C. Lee, Karim Nader, Daniela Schiller|2017

16. Linking ADHD to the Neural Circuitry of Attention|Adrienne Mueller, David S. Hong, Steven Shepard, Tirin Moore|2017M

Source: http://sci-hub.cc/10.1016/j.tics.2017.03.009
17. Emotion Perception from Face, Voice, and Touch: Comparisons and Convergence|Annett Schirmer, Ralph Adolphs|2017

Source: http://sci-hub.cc/10.1016/j.tics.2017.01.001
18. The Depressed Brain: An Evolutionary Systems Theory|Paul B. Badcock, Christopher G. Davey, Sarah Whittle, Nicholas B. Allen, Karl J. Friston |2017

Source: http://sci-hub.cc/10.1016/j.tics.2017.01.005
19. Gradients of Connectivity in the Cerebral Cortex|Fenna M. Krienen, Chet C. Sherwood|2016

Source: http://sci-hub.cc/10.1016/j.tics.2016.12.002
20. How Do We Keep Information ‘Online’?|David Soto|2017

21. The Distributed Nature of Working Memory|Thomas B. Christophel, P. Christiaan Klink, Bernhard Spitzer, Pieter R. Roelfsema, John-Dylan Haynes|2017

Source: http://sci-hub.bz/10.1016/j.tics.2016.12.007

22. F2 Heterogeneous layers stabilize propagation of a multiplexed spike signal in a feedforward network|Dongqi Han, Sungho Hong|2017

Source: https://bmcneurosci.biomedcentral.com/articles/10.1186/s12868-017-0370-3