336 related articles for article (PubMed ID: 37794121)
1. Reconstructing computational system dynamics from neural data with recurrent neural networks.
Durstewitz D; Koppe G; Thurm MI
Nat Rev Neurosci; 2023 Nov; 24(11):693-710. PubMed ID: 37794121
[TBL] [Abstract][Full Text] [Related]
2. Considerations in using recurrent neural networks to probe neural dynamics.
Kao JC
J Neurophysiol; 2019 Dec; 122(6):2504-2521. PubMed ID: 31619125
[TBL] [Abstract][Full Text] [Related]
3. Recurrent neural networks as versatile tools of neuroscience research.
Barak O
Curr Opin Neurobiol; 2017 Oct; 46():1-6. PubMed ID: 28668365
[TBL] [Abstract][Full Text] [Related]
4. Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks.
Bitzer S; Kiebel SJ
Biol Cybern; 2012 Jul; 106(4-5):201-17. PubMed ID: 22581026
[TBL] [Abstract][Full Text] [Related]
5. PsychRNN: An Accessible and Flexible Python Package for Training Recurrent Neural Network Models on Cognitive Tasks.
Ehrlich DB; Stone JT; Brandfonbrener D; Atanasov A; Murray JD
eNeuro; 2021; 8(1):. PubMed ID: 33328247
[TBL] [Abstract][Full Text] [Related]
6. Exploring weight initialization, diversity of solutions, and degradation in recurrent neural networks trained for temporal and decision-making tasks.
Jarne C; Laje R
J Comput Neurosci; 2023 Nov; 51(4):407-431. PubMed ID: 37561278
[TBL] [Abstract][Full Text] [Related]
7. The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.
Oladyshkin S; Praditia T; Kroeker I; Mohammadi F; Nowak W; Otte S
Neural Netw; 2023 Sep; 166():85-104. PubMed ID: 37480771
[TBL] [Abstract][Full Text] [Related]
8. A Review of Recurrent Neural Network-Based Methods in Computational Physiology.
Mao S; Sejdic E
IEEE Trans Neural Netw Learn Syst; 2023 Oct; 34(10):6983-7003. PubMed ID: 35130174
[TBL] [Abstract][Full Text] [Related]
9. Training deep neural density estimators to identify mechanistic models of neural dynamics.
Gonçalves PJ; Lueckmann JM; Deistler M; Nonnenmacher M; Öcal K; Bassetto G; Chintaluri C; Podlaski WF; Haddad SA; Vogels TP; Greenberg DS; Macke JH
Elife; 2020 Sep; 9():. PubMed ID: 32940606
[TBL] [Abstract][Full Text] [Related]
10. Recurrent neural networks for dynamical systems: Applications to ordinary differential equations, collective motion, and hydrological modeling.
Gajamannage K; Jayathilake DI; Park Y; Bollt EM
Chaos; 2023 Jan; 33(1):013109. PubMed ID: 36725658
[TBL] [Abstract][Full Text] [Related]
11. Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research.
Macpherson T; Churchland A; Sejnowski T; DiCarlo J; Kamitani Y; Takahashi H; Hikida T
Neural Netw; 2021 Dec; 144():603-613. PubMed ID: 34649035
[TBL] [Abstract][Full Text] [Related]
12. Recent Advances at the Interface of Neuroscience and Artificial Neural Networks.
Cohen Y; Engel TA; Langdon C; Lindsay GW; Ott T; Peters MAK; Shine JM; Breton-Provencher V; Ramaswamy S
J Neurosci; 2022 Nov; 42(45):8514-8523. PubMed ID: 36351830
[TBL] [Abstract][Full Text] [Related]
13. Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI.
Koppe G; Toutounji H; Kirsch P; Lis S; Durstewitz D
PLoS Comput Biol; 2019 Aug; 15(8):e1007263. PubMed ID: 31433810
[TBL] [Abstract][Full Text] [Related]
14. Neural circuits as computational dynamical systems.
Sussillo D
Curr Opin Neurobiol; 2014 Apr; 25():156-63. PubMed ID: 24509098
[TBL] [Abstract][Full Text] [Related]
15. Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework.
Song HF; Yang GR; Wang XJ
PLoS Comput Biol; 2016 Feb; 12(2):e1004792. PubMed ID: 26928718
[TBL] [Abstract][Full Text] [Related]
16. A deep learning framework for neuroscience.
Richards BA; Lillicrap TP; Beaudoin P; Bengio Y; Bogacz R; Christensen A; Clopath C; Costa RP; de Berker A; Ganguli S; Gillon CJ; Hafner D; Kepecs A; Kriegeskorte N; Latham P; Lindsay GW; Miller KD; Naud R; Pack CC; Poirazi P; Roelfsema P; Sacramento J; Saxe A; Scellier B; Schapiro AC; Senn W; Wayne G; Yamins D; Zenke F; Zylberberg J; Therien D; Kording KP
Nat Neurosci; 2019 Nov; 22(11):1761-1770. PubMed ID: 31659335
[TBL] [Abstract][Full Text] [Related]
17. [Dynamic paradigm in psychopathology: "chaos theory", from physics to psychiatry].
Pezard L; Nandrino JL
Encephale; 2001; 27(3):260-8. PubMed ID: 11488256
[TBL] [Abstract][Full Text] [Related]
18. Towards the next generation of recurrent network models for cognitive neuroscience.
Yang GR; Molano-Mazón M
Curr Opin Neurobiol; 2021 Oct; 70():182-192. PubMed ID: 34844122
[TBL] [Abstract][Full Text] [Related]
19. Neural population dynamics of computing with synaptic modulations.
Aitken K; Mihalas S
Elife; 2023 Feb; 12():. PubMed ID: 36820526
[TBL] [Abstract][Full Text] [Related]
20. If deep learning is the answer, what is the question?
Saxe A; Nelli S; Summerfield C
Nat Rev Neurosci; 2021 Jan; 22(1):55-67. PubMed ID: 33199854
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]