- Computational Neurogenetic Modeling: Integration of Spiking Neural Networks, Gene Networks,
- Network: Comput. Neural Syst. 9 (1998) 513530. Printed in the UK PII: S0954-898X(98)89953-3 Hypothetical neural mechanism that may play a role in
- Processing Symbolic Sequences by Recurrent Neural Networks Trained by Kalman
- The intra-spine electric force can drive vesicles for fusion: a theoretical model for long-term potentiation
- Building predictive models on complex symbolic sequences via a firstorder recurrent
- PIRIFORM CORTEX MODEL OF EEG HAS RANDOM UNDERLYING DYNAMICS
- Principles of the Design of DNeuronal Networks I. Net Representation for Computer Simulation of a Melody
- Antidepressants and Synaptic Plasticity: A Hypothesis Lubica Benuskova
- Finite-State Reber Automaton and the Recurrent Neural Networks Trained
- Neurocomputing 70 (2007) 20352040 Modeling L-LTP based on changes in concentration of pCREB
- S. Kollias et al. (Eds.): ICANN 2006, Part I, LNCS 4131, pp. 61 70, 2006. Springer-Verlag Berlin Heidelberg 2006
- Computing and Informatics, Vol. 28, 2009, 695710 INTERACTIVE VISUALISATION OF OLIGOMER
- J. Marques de S et al. (Eds.): ICANN, Part II, LNCS 4669, pp. 758767, 2007. Springer-Verlag Berlin Heidelberg 2007
- J.C. Rajapakse, L. Wong, and R. Acharya (Eds): PRIB 2006, LNBI 4146, pp. 163-173, Springer, Berlin/Heidelberg Image and fractal information processing for large-scale
- An Electrophoretic Coupling Mechanism between E ciency Modi cation of Spine Synapses and Their Stimulation
- Building predictive models on complex symbolic sequences with a secondorder recurrent BCM network with lateral inhibition \Lambda
- Markovian Architectural Bias of Recurrent Neural Networks
- Principles of the Design of DNeuronal Networks II. Composing Simple Melodies \Lambda
- 98:1048-1051, 2007. First published May 30, 2007; doi:10.1152/jn.00250.2007J Neurophysiol Wickliffe C. Abraham, Barbara Logan, Amy Wolff and Lubica Benuskova
- J Comput Neurosci (2007) 22:129133 DOI 10.1007/s10827-006-0002-x
- Theory for normal and impaired experience-dependent plasticity in neocortex of
- Network: Comput. Neural Syst. 10 (1999) 303323. Printed in the UK PII: S0954-898X(99)08260-3 Computational study of experience-dependent plasticity in
- M. Ishikawa et al. (Eds.): ICONIP 2007, Part II, pp. 406415, 2008. Springer-Verlag Berlin Heidelberg 2008
- J. Blanc-Talon et al. (Eds.): ACIVS 2006, LNCS 4179, pp. 1133 1142, 2006. Springer-Verlag Berlin Heidelberg 2006
- Network Computation in Neural Systems 6 (1995) 313-331. Printed in the UK Modellingtranspositionalinvariancy of melody recognition
- ARTICLE IN PRESS Neural Networks ( )
- Approaches Based on Markovian Architectural Bias in Recurrent Neural Networks
- Neural Comput & Applic (2002)11:7179 Ownership and Copyright
- Neural Networks 21 (2008) 266275 www.elsevier.com/locate/neunet
- June 27, 2006 18:26 00062 International Journal of Neural Systems, Vol. 16, No. 3 (2006) 112
- Abstract--We present new results from Computational Neurogenetic Modeling to aid discoveries of complex gene
- A Computational Neurogenetic Model of a Spiking Neuron
- In: Proc. IEEE Intl. Joint Conference on Neural Networks, vol. 2. pp. 1203-1208, 2004. Computational Neurogenetic Modelling
- Quark, 6(9): 21-23, 2000. Modely neurnovch siet pomhaj objas ova podstatu udskho vnmania
- In: Spasmus, vol. 9, No. 2, 2001, pp. 6-8. Neurovedn okno do vedomia1
- RESEARCHARTICLE 1. INTRODUCTION
- Artificial Neural Networks ICANN'97, Lecture Notes in Computer Science, vol. 1327, W. Gerstner, A. Germond, M. Hasler and J.D. Nicaud (Eds.),
- Network Camputationin Neural System 5 (1994) 33S349.Printed in the UK Modellingthe effectof themissingfundamentalwith an
- On the role of inhibition in cortical plasticity: a computational study \Lambda Lubica Benuskov'a
- 6 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 15, NO. 1, JANUARY 2004 Markovian Architectural Bias of Recurrent
- Fast and adaptive network of spiking neurons for multi-view visual pattern recognition
- 3URFHVVLQJ 6\PEROLF 6HTXHQFHV E\ WKH %&0 1HXURQ 3DYHO 3HWURYL1
- How certain characteristics of cortical frequency representation may in uence our perception of sounds
- Pattern Classification with the BCM Neural Network Stanislav Poljovka and
- Neural Networks-Based Parametric Testing of Analog IC V. Stopjakov 1)
