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Items: 1 to 20 of 27


Working Memory Requires a Combination of Transient and Attractor-Dominated Dynamics to Process Unreliably Timed Inputs.

Nachstedt T, Tetzlaff C.

Sci Rep. 2017 May 30;7(1):2473. doi: 10.1038/s41598-017-02471-z.


Biological modelling of a computational spiking neural network with neuronal avalanches.

Li X, Chen Q, Xue F.

Philos Trans A Math Phys Eng Sci. 2017 Jun 28;375(2096). pii: 20160286. doi: 10.1098/rsta.2016.0286.


Multiplex visibility graphs to investigate recurrent neural network dynamics.

Bianchi FM, Livi L, Alippi C, Jenssen R.

Sci Rep. 2017 Mar 10;7:44037. doi: 10.1038/srep44037.


Persistent Memory in Single Node Delay-Coupled Reservoir Computing.

Kovac AD, Koall M, Pipa G, Toutounji H.

PLoS One. 2016 Oct 26;11(10):e0165170. doi: 10.1371/journal.pone.0165170. eCollection 2016.


Toward an Integration of Deep Learning and Neuroscience.

Marblestone AH, Wayne G, Kording KP.

Front Comput Neurosci. 2016 Sep 14;10:94. doi: 10.3389/fncom.2016.00094. eCollection 2016.


Bursting dynamics remarkably improve the performance of neural networks on liquid computing.

Li X, Chen Q, Xue F.

Cogn Neurodyn. 2016 Oct;10(5):415-21. doi: 10.1007/s11571-016-9387-z. Epub 2016 Apr 28.


Learning Universal Computations with Spikes.

Thalmeier D, Uhlmann M, Kappen HJ, Memmesheimer RM.

PLoS Comput Biol. 2016 Jun 16;12(6):e1004895. doi: 10.1371/journal.pcbi.1004895. eCollection 2016 Jun.


Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex.

Enel P, Procyk E, Quilodran R, Dominey PF.

PLoS Comput Biol. 2016 Jun 10;12(6):e1004967. doi: 10.1371/journal.pcbi.1004967. eCollection 2016 Jun.


Recurrent Network Models of Sequence Generation and Memory.

Rajan K, Harvey CD, Tank DW.

Neuron. 2016 Apr 6;90(1):128-42. doi: 10.1016/j.neuron.2016.02.009. Epub 2016 Mar 10.


Building functional networks of spiking model neurons.

Abbott LF, DePasquale B, Memmesheimer RM.

Nat Neurosci. 2016 Mar;19(3):350-5. doi: 10.1038/nn.4241. Review.


Pattern activation/recognition theory of mind.

du Castel B.

Front Comput Neurosci. 2015 Jul 15;9:90. doi: 10.3389/fncom.2015.00090. eCollection 2015.


Minimal approach to neuro-inspired information processing.

Soriano MC, Brunner D, Escalona-MorĂ¡n M, Mirasso CR, Fischer I.

Front Comput Neurosci. 2015 Jun 2;9:68. doi: 10.3389/fncom.2015.00068. eCollection 2015. Review.


A neural network that finds a naturalistic solution for the production of muscle activity.

Sussillo D, Churchland MM, Kaufman MT, Shenoy KV.

Nat Neurosci. 2015 Jul;18(7):1025-33. doi: 10.1038/nn.4042. Epub 2015 Jun 15.


Modeling reconsolidation in kernel associative memory.

Nowicki D, Verga P, Siegelmann H.

PLoS One. 2013 Aug 2;8(8):e68189. doi: 10.1371/journal.pone.0068189. Print 2013.


Slow cortical dynamics and the accumulation of information over long timescales.

Honey CJ, Thesen T, Donner TH, Silbert LJ, Carlson CE, Devinsky O, Doyle WK, Rubin N, Heeger DJ, Hasson U.

Neuron. 2012 Oct 18;76(2):423-34. doi: 10.1016/j.neuron.2012.08.011. Epub 2012 Oct 17. Erratum in: Neuron. 2012 Nov 8;76(3):668.


The chronotron: a neuron that learns to fire temporally precise spike patterns.

Florian RV.

PLoS One. 2012;7(8):e40233. doi: 10.1371/journal.pone.0040233. Epub 2012 Aug 6.


The neurobiology of syntax: beyond string sets.

Petersson KM, Hagoort P.

Philos Trans R Soc Lond B Biol Sci. 2012 Jul 19;367(1598):1971-83. doi: 10.1098/rstb.2012.0101. Review.


Transferring learning from external to internal weights in echo-state networks with sparse connectivity.

Sussillo D, Abbott LF.

PLoS One. 2012;7(5):e37372. doi: 10.1371/journal.pone.0037372. Epub 2012 May 24.


Choice-specific sequences in parietal cortex during a virtual-navigation decision task.

Harvey CD, Coen P, Tank DW.

Nature. 2012 Mar 14;484(7392):62-8. doi: 10.1038/nature10918.


Information processing using a single dynamical node as complex system.

Appeltant L, Soriano MC, Van der Sande G, Danckaert J, Massar S, Dambre J, Schrauwen B, Mirasso CR, Fischer I.

Nat Commun. 2011 Sep 13;2:468. doi: 10.1038/ncomms1476.

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