These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

202 related articles for article (PubMed ID: 30768590)

  • 1. Efficient neural decoding of self-location with a deep recurrent network.
    Tampuu A; Matiisen T; Ólafsdóttir HF; Barry C; Vicente R
    PLoS Comput Biol; 2019 Feb; 15(2):e1006822. PubMed ID: 30768590
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells.
    Brown EN; Frank LM; Tang D; Quirk MC; Wilson MA
    J Neurosci; 1998 Sep; 18(18):7411-25. PubMed ID: 9736661
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Place cells on a maze encode routes rather than destinations.
    Grieves RM; Wood ER; Dudchenko PA
    Elife; 2016 Jun; 5():. PubMed ID: 27282386
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Place cells recorded in the parasubiculum of freely moving rats.
    Taube JS
    Hippocampus; 1995; 5(6):569-83. PubMed ID: 8646283
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Non-structured spike sequences of hippocampal neuronal ensembles in awake animals.
    Sasaki T
    Neurosci Res; 2019 May; 142():1-6. PubMed ID: 29842894
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Bayesian decoding using unsorted spikes in the rat hippocampus.
    Kloosterman F; Layton SP; Chen Z; Wilson MA
    J Neurophysiol; 2014 Jan; 111(1):217-27. PubMed ID: 24089403
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An uncertainty principle for neural coding: Conjugate representations of position and velocity are mapped onto firing rates and co-firing rates of neural spike trains.
    Grgurich R; Blair HT
    Hippocampus; 2020 Apr; 30(4):396-421. PubMed ID: 32065487
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Interpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cells.
    Zhang K; Ginzburg I; McNaughton BL; Sejnowski TJ
    J Neurophysiol; 1998 Feb; 79(2):1017-44. PubMed ID: 9463459
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Optimizing for generalization in the decoding of internally generated activity in the hippocampus.
    van der Meer MAA; Carey AA; Tanaka Y
    Hippocampus; 2017 May; 27(5):580-595. PubMed ID: 28177571
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Decoding movement trajectories through a T-maze using point process filters applied to place field data from rat hippocampal region CA1.
    Huang Y; Brandon MP; Griffin AL; Hasselmo ME; Eden UT
    Neural Comput; 2009 Dec; 21(12):3305-34. PubMed ID: 19764871
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Recalibration of path integration in hippocampal place cells.
    Jayakumar RP; Madhav MS; Savelli F; Blair HT; Cowan NJ; Knierim JJ
    Nature; 2019 Feb; 566(7745):533-537. PubMed ID: 30742074
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Hippocampal place cells are topographically organized, but physical space has nothing to do with it.
    França TFA; Monserrat JM
    Brain Struct Funct; 2019 Dec; 224(9):3019-3029. PubMed ID: 31654118
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Novel Nonparametric Approach for Neural Encoding and Decoding Models of Multimodal Receptive Fields.
    Agarwal R; Chen Z; Kloosterman F; Wilson MA; Sarma SV
    Neural Comput; 2016 Jul; 28(7):1356-87. PubMed ID: 27172447
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A unified hierarchical oscillatory network model of head direction cells, spatially periodic cells, and place cells.
    Soman K; Muralidharan V; Chakravarthy VS
    Eur J Neurosci; 2018 May; 47(10):1266-1281. PubMed ID: 29575125
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A controlled attractor network model of path integration in the rat.
    Conklin J; Eliasmith C
    J Comput Neurosci; 2005; 18(2):183-203. PubMed ID: 15714269
    [TBL] [Abstract][Full Text] [Related]  

  • 17. An analysis of hippocampal spatio-temporal representations using a Bayesian algorithm for neural spike train decoding.
    Barbieri R; Wilson MA; Frank LM; Brown EN
    IEEE Trans Neural Syst Rehabil Eng; 2005 Jun; 13(2):131-6. PubMed ID: 16003890
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Self-organizing continuous attractor network models of hippocampal spatial view cells.
    Stringer SM; Rolls ET; Trappenberg TP
    Neurobiol Learn Mem; 2005 Jan; 83(1):79-92. PubMed ID: 15607692
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Network dynamics of hippocampal cell-assemblies resemble multiple spatial maps within single tasks.
    Jackson J; Redish AD
    Hippocampus; 2007; 17(12):1209-29. PubMed ID: 17764083
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Bayesian nonparametric approach for uncovering rat hippocampal population codes during spatial navigation.
    Linderman SW; Johnson MJ; Wilson MA; Chen Z
    J Neurosci Methods; 2016 Apr; 263():36-47. PubMed ID: 26854398
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.