Lubica Benuskova - Publications
Publications of Luba Benuskova
Computational Neuroscience
Benuskova L (2010) Computational modelling of homo- and heterosynaptic
LTD: insights from STDP, metaplasticity and spontaneous activity.
Technical report OUCS-2010-01, University of Otago.
link
Benuskova L (2009) STDP rule with metaplasticity accounts for homo- and
heterosynaptic plasticity in dentate gyrus. Frontiers in Systems Neuroscience.
Conference Abstract: 12th Meeting of the Hungarian Neuroscience Society.
doi: 10.3389/conf.neuro.01.2009.04.189
abstract
Abraham WC, Logan B, Wolff A, Benuskova L (2007)
"Heterosynaptic" LTD in the dentate gyrus of anesthetized rat requires
homosynaptic activity. Journal of Neurophysiology 98: 1048-1051.
ISSN 0022-3077. Published
online 30 May 2007.
(pdf)
Benuskova L and Kasabov N (2007) Modeling L-LTP based on changes in
concentration of pCREB transcription factor. Neurocomputing
70(10-12) 2035-2040. ISSN 0925-2312. Published
online
15 Nov 2006.
(pdf)
Benuskova L and
Abraham WC (2007) STDP rule endowed with the BCM sliding
threshold accounts for hippocampal heterosynaptic plasticity.
Journal of Comp. Neurosci. 22(2): 129-133. ISSN 0929-5313. Published
online 12 Oct 2006.
(pdf)
Benuskova L, Rema V, Armstrong-James M and
Ebner FF
(2001) Theory for normal and impaired experience-dependent plasticity in neocortex of adult rats.
Proc. Natl. Acad. Sci. USA 98(5): 2797-2802. ISSN 0027-8424
(pdf)
Benuskova L, Kanich M,
Krakovska A (2001)
Piriform cortex model of EEG has random underlying dynamics.
In: Proc. World Congress on Neuroinformatics.
F. Rattay (Ed), ARGESIM/ASIM-Verlag, Vienna, pp. 287-292.
ISBN 3-901608-20-6 (pdf)
Benuskova L (2001) How some characteristics
of cortical frequency representation may influence our perception of sounds.
In: Proc. Intl. Conf. Art. Neural Net. and Genet. Alg. -
ICANNGA'2001. V. Kurkova, N.C. Steele, R. Neruda
and M. Karny (Eds), Springer-Verlag, Wien, New York, pp. 130-133.
ISBN 3-211-83651-9 (ps)
Benuskova L (2000)
The intra-spine electric force can drive vesicles for fusion:
a theoretical model for long-term potentiation
Neuroscience Letters 280(1): 17-20. ISSN 0304-3904
(pdf)
Benuskova L, Ebner FF,
Diamond ME and Armstrong-James M (1999)
Computational study of experience-dependent plasticity in adult rat cortical
barrel-column. Network: Computation in Neural Systems 10(4):
303-323. (pdf)
Benuskova L (1997) Modelling plasticity
in rat barrel cortex induced by one spared whisker. In: Artificial
Neural Networks - ICANN'97, Lecture Notes in Computer Science 1327.
W.Gerstner, W.Germond, M.Hasler, J.-D.Nicaud (Eds), Springer-Verlag, Berlin,
pp. 127-132. (ps)
Benuskova L (1995) On the role of inhibition
in cortical plasticity: a computational study. In: Proc. ICANN'95,
vol.2 , pp. 521-526. (ps)
Benuskova L,
Diamond ME and Ebner FF (1994) Dynamic synaptic
modification threshold: Computational model of experience-dependent
plasticity in adult rat barrel cortex. Proc. Natl. Acad. Sci.
USA 91: 4791-4795.
(pdf)
Benuskova L (1991) Antidepressants and synaptic
plasticity: a hypothesis. Medical Hypotheses 35: 17-22.
(ps)
Fedor P, Benuskova L, Jakes H and Majernik V (1982)
An electrophoretic coupling mechanism between
the efficiency modification of spine synapses and their stimulation.
Studia Biophysica 92: 141-146.
(ps)
Spiking and Hopfield neural networks
Wysoski SG, Benuskova L and Kasabov N (2008)
Fast and adaptive network of spiking neurons for multi-view visual pattern
recognition. Neurocomputing 71(13-15): 2563-2575.
(pdf)
Wysoski SG, Benuskova L and Kasabov N (2008) Adaptive spiking neural networks
for audiovisual pattern recognition. In: M. Ishikawa et al
(Eds) ICONIP'2007, Part II, Lecture Notes in Computer Science, vol.
4985-0406, Springer-Verlag, Berlin/Heidelberg, pp. 406-415.
(pdf)
Wysoski SG, Benuskova L and Kasabov N (2007) Text-independent speaker
authentication with spiking neural networks. In: J. Marques de Sa et al
(Eds) ICANN'2007, Part II, Lecture Notes in Computer Science, vol.
4669, Springer-Verlag, Berlin/Heidelberg, pp. 758-767.
(pdf)
Wysoski SG and Benuskova L (2006) Biologically Realistic Neural Networks
and Adaptive Visual Information Processing. Bulletin of Applied
Computing and Information Technology 4(2): A3. ISSN 1176-4120.
(html)
Wysoski SG, Benuskova L and Kasabov N (2006) On-line learning with
structural adaptation in a network of spiking neurons for visual pattern
recognition. In: S. Kollias et al (Eds) Intl. Conf. Art. Neural Net.
- ICANN 2006. Lecture Notes in Computer Science, vol. 4131,
Springer-Verlag, Berlin/Heidelberg, pp. 61-70. ISBN 978-3-540-38625-4.
(pdf)
Wysoski SG, Benuskova L, Kasabov N (2006) Adaptive learning procedure for a
network of spiking neurons and visual pattern recognition. In:
Advanced Concepts for Intelligent Vision Systems (ACIVS), Lecture Notes
in Computer Science, vol. 4179, pp. 1133-1142, Springer,
Berlin/Heidelberg. ISBN 978-3-540-44630-9.
(pdf)
Benuskova L and Estok S (1998) A hypothetical
neural mechanism that may play a role in mental rotation: an attractor neural
network model. Network: Computation in Neural Systems 9(4):
513-530. (pdf)
Benuskova L (1995) Modelling transpositional
invariancy of melody recognition with an attractor neural network.
Network: Computation in Neural Systems 6: 313-331.
(pdf)
Benuskova L (1994) Modelling of the effect of
the missing fundamental with an attractor neural network. Network:
Computation in Neural Systems 5: 333-349.
(pdf)
Artificial neural networks
Cernansky M, Benuskova L (2009) Training recurrent connectionist models
on symbolic time series In: M. Koeppen, N. Kasabov, G. Coghill (Eds)
Advances in Neuro-Information Processing, ICONIP'2008,
Lecture Notes in Computer Science, vol. 5506,
Springer-Verlag, Berlin/Heidelberg, pp. 285-292. ISBN 978-3-642-02489-4.
link
Cernansky M, Makula M and Benuskova L (2009) Improving the state space
organization of untrained recurrent neural networks. In: M. Koeppen,
N. Kasabov, G. Coghill (Eds) Advances in Neuro-Information Processing,
ICONIP'2008, Lecture Notes in Computer Science, vol. 5506,
Springer-Verlag, Berlin/Heidelberg, pp. 671-678. ISBN 978-3-642-02489-4.
link
Makula M and Benuskova L (2008) Analysis and visualization of the
dynamics of recurrent neural networks for symbolic sequences processing.
Artificial Neural Networks - ICANN'08, Lecture Notes in Computer Science,
vol. 5164, pp. 577-586, Springer Berlin / Heidelberg. ISBN
978-3-540-87558-1.
link
Cernansky M,
Makula M,
and Benuskova L (2007) Organization of the
state space of a simple recurrent neural network before and after
training on recursive linguistic structures. Neural Networks
20(2):236-244. ISSN 0893-6080. Available
online 9 May 2006.
(pdf)
Tino P ,
Cernansky M and Benuskova L (2004)
Markovian architectural bias of recurrent neural networks.
IEEE Transactions on Neural Networks 15(1): 6-15.
ISSN 1045-9227.
(pdf)
Makula M, Cernansky M and Benuskova L (2004)
Approaches based on Markovian architectural bias in recurrent
neural networks. In: SOFSEM'2004 - Theory and Practise of Computer
Science. Lecture Notes in Computer Science, vol. 2932,
P. Van Emde Boas, J. Pokorny, M. Bielikova, J. Stuller (eds),
Springer-Verlag, Berlin Heidelberg, pp. 257-264. ISBN: 3-540-20779-1.
(pdf)
Cernansky M, Makula M and Benuskova L (2004)
Processing symbolic sequences by recurrent neural networks trained by
Kalman filter based algorithms. In: SOFSEM 2004: Theory and Practice
of Computer Science. Vol. II. , P. Van Emde Boas, J. Pokorny,
M. Bielikova, J. Stuller (eds),
Matfyzpress. Praha, 2004, pp. 58 - 65. ISBN: 80-86732-19-3
(ps)
Cernansky M and Benuskova L (2003)
Simple recurrent network trained by RTRL and extended Kalman
filter algorithms. Neural Network World 13(3): 223-234.
ISSN: 1210-0552. (ps)
Makula M and Benuskova L (2003)
Analysis of state space of RNNs trained on a chaotic symbolic
sequence. Neural Network World 13(3): 267-276.
ISSN: 1210-0552.
(ps)
Benuskova L, Lacko D. (2003)
Word segmentation: RNNs outperform humans. Proc.
Cognition, Artificial Life and Computational Intelligence ,
P. Sincak, V. Kvasnicka, J. Pospichal et al (Eds), May 15-17,
Tatry, Slovakia, pp. 109-114.
(pdf)
Tino P, Cernansky M and Benuskova L (2002)
Markovian architectural bias of recurrent neural networks.
In: Intelligent Technologies - Theory and Applications.
Frontiers in AI and Applications, vol. 76. P. Sincak, J. Vascak,
V. Kvasnicka and J. Pospichal (Eds), IOS Press, Amsterdam, pp. 17-23.
ISBN: 1-58603-256-9
(ps)
Micusik D, Stopjakova V, Benuskova L (2002) Application of
feed-forward artificial neural networks to the identification of defective
analog integrated circuits. Neural Computing and Applications
11(1): 71-79. ISSN: 0941-0643.
(pdf)
Stopjakova V, Micusik D, Benuskova L, Margala M (2002) Neural
Networks-Based Parametric Testing of Analog IC. In: Proc. 17th IEEE Intl.
Symposium on Defect and Fault-Tolerance in VLSI Systems, DFT 2002, (pp.
408-418) Vancouver, BC, Canada: IEEE Press. ISSN: 1063-6722.
(pdf)
Cernansky M and Benuskova L (2001)
Finite-state Reber automaton and the recurrent neural networks trained
in supervised and unsupervised manner. In: Artificial Neural Networks
- ICANN'2001, Lecture Notes in Computer Science 2130. G. Dorffner,
H. Bischof and K. Hornik (Eds), Springer-Verlag,
Berlin, Heidelberg, pp. 737-742. ISBN: 3-540-42486-5
(ps)
Tino P, Stancik M and Benuskova L (2000) Building predictive models
on complex symbolic sequences with a second-order recurrent BCM network with
lateral inhibition. In: Proc. IEEE-INNS-ENNS Intl. Joint Conference
on Neural Networks, vol. 2, pp. 265-270. ISBN: 0-7695-0619-4
(ps)
Tino P, Stancik M and Benuskova L (2000) Building predictive
models on complex symbolic sequences via a first-order recurrent BCM network
with lateral inhibition. In: Quo Vadis Computational Intelligence?
New Trends and Approaches in Computational Intelligence. P. Sincak
and J. Vascak (Eds), Physica-Verlag, Heidelberg, pp. 42-50.
ISBN 37-9081-324-9 (ps)
Poljovka S, Benuskova L (1999) Pattern
classification with the BCM neural network. In: Proc. 2nd Electronic
Circuits and Systems Conference - ECS'99 , V. Stopjakova (Ed),
Bratislava, pp. 207-210.
(ps)
Petrovic P, Tino P, Benuskova L (1998)
Processing symbolic sequences by the BCM
neuron. Neural Network World 8(5): 491-500.
(pdf)
Bioinformatics and Neuroinformatics
Markosova M, Franz L and Benuskova (2009) Topology of brain functional networks:
towards the role of genes. In: M. Koeppen, N. Kasabov, G. Coghill (Eds),
Advances in Neuro-Information Processing, ICONIP 2008, LNCS 5506,
Springer, Berlin/Heidelberg, pp. 111-118. ISBN 978-3-642-02489-4.
link
Makula M and Benuskova L (2008) Interactive visualisation of oligomer
frequency in DNA. Computing and Informatics, vol. 28, pp. 695-710.
(pdf)
Havukkala I, Benuskova L, Pang S, Jain V, Kroon R, Kasabov N (2006)
Image and fractal information processing for large-scale chemoinformatics,
genomics analyses and pattern discovery. In: J.C. Rajapakse, L.
Wong, R. Acharya (Eds), Proc. Pattern Recognition in Bioinformatics,
PRIB 2006. Lecture Notes in Bioinformatics, vol. 4146, pp. 163-173,
Springer, Berlin/Heidelberg. ISBN 3-540-37446-9.
link
(pdf)
Computational Neurogenetics
Benuskova L, Kasabov N (2008) Modeling brain dynamics using computational
neurogenetic approach. Cognitive Neurodynamics, accepted.
link
Kasabov N, Jain V, Benuskova L (2008) Integrating evolving brain-gene
ontology and connectionist-based system for modeling and knowledge
discovery. Neural Networks, 21(2-3): 266-275. ISSN 0893-6080.
(pdf)
Kasabov N, Jain V, Gottgtroy PCM, Benuskova L, Joseph F (2007)
Brain gene ontology and simulation system (BGOS) for a better understanding
of the brain. Cybernetics and Systems , 38(5-6): 495-508. ISSN 0196-9722.
(pdf)
Kasabov N, Jain V, Gottgtroy PCM, Benuskova L, Wysoski SG, Joseph F (2007)
Evolving Brain-Gene Ontology System (EBGOS): Towards Integrating
Bioinformatics and Neuroinformatics Data to Facilitate Discoveries.
Proc. IJCNN'2007, pp. 1054-1058. ISBN 1-4244-1380-X.
Kasabov N, Jain V, Gottgtroy PCM, Benuskova L, Joseph F (2006)
Brain gene ontology: integrating bioinformatics and neuroinformatics data,
information and knowledge to enable discoveries. In: Proc. 6th Intl. Conf.
Hybrid Intelligent Systems and 4th Conf. Neuro-Computing and Evolving
Intelligence, A. Abraham, N. Kasabov, M. Koeppen, A. Koenig, Q. Song
(eds), IEEE, Auckland, New Zealand. ISBN 0-7695-2662-4.
Benuskova L, Jain V, Wysoski SG and Kasabov N (2006) Computational neurogenetic
modeling: a pathway to new discoveries in genetic neuroscience.
Intl. Journal of Neural Systems, 16(3): 215-227. ISSN 0129-0657.
(pdf)
Benuskova L, Wysoski SG and Kasabov N (2006) Computational neurogenetic
modeling: a methodology to study gene interactions underlying neural
oscillations. Intl. Joint Conf. Neural Net., IJCNN 2006 ,
pp. 9388-9394. ISBN 0-7803-9490-9.
(pdf)
Kasabov N, Benuskova L and Wysoski SG (2005) Biologically plausible
computational neurogenetic models: modelling interaction between genes,
neurons and neural networks. Journal of Computational and Theoretical
Nanoscience , 2(4): 569-573. ISSN: 1546-198X.
(pdf)
Kasabov N, Benuskova L and Wysoski SG (2005) Computational neurogenetic
modeling: integration of spiking neural networks, gene networks, and
signal processing techniques. In: Artificial Neural Networks: Formal
Models and Their Applications - ICANN 2005, LNCS 3697,
W. Duch, J. Kacprzyk, E. Oja, S. Zadrozny (eds), Springer-Verlag,
Berlin Heidelberg, pp. 509-514. ISBN: 3-540-28755-8.
(pdf)
Kasabov N, Benuskova L and Wysoski SG (2005)
A computational neurogenetic
model of a spiking neuron. Proc. IEEE Intl. Joint Conference
on Neural Networks (IJCNN 2005) , pp. 446-451. ISBN: 0-7803-9049-0.
(pdf)
Benuskova L, Kasabov N and Wysoski SG (2005)
Computational neurogenetic modelling: methodology and preliminary results.
In: Proc.
23rd Australasian Winter Conference on Brain Research, AWCBR'05,
p. 44. ISSN: 1176-3183.
(abstract)
Kasabov N and Benuskova L (2004) Computational
neurogenetics. Journal of Computational and Theoretical
Nanoscience , 1(1): 47-61. ISSN: 1546-198X.
(pdf)
Kasabov N, Benuskova L and Wysoski SG (2004)
Computational neurogenetic modelling: gene networks within neural networks
In: Proc. IEEE Intl. Joint Conference on Neural Networks, vol. 2.
pp. 1203-1208. ISBN: 0-7803-8359-1.
(pdf)
Kasabov N, Benuskova L and Wysoski SG (2004) Computational neurogenetic
modeling: integration of spiking neural networks, gene networks, and
signal processing techniques. Proc. 2004 IEEE Intl. Workshop on
Biomedical Circuits & Systems, BioCAS'04 , pp. S2.7.INV-12-15.
ISBN: 0-7803-8665-5.
Wysoski SG, Benuskova L, Kasabov N (2004) Simulation of
neurogenetic models, In: Proc. Neuro-Computing and Evolving Intelligence
(NCEI 2004) , Kasabov N, Chen ZSH (eds), Auckland, New Zealand, pp 30-31.
ISBN 0-476-01282-1.
Books
Benuskova L and Kasabov N (2007)
Computational Neurogenetic Modeling. Springer, New York. ISBN 978-0-387-48353-5.
(Review in BioEssays)
Navrat P, Bielikova M, Benuskova L, Kapustik I, Unger M (2006)
Umela inteligencia, 2. vydanie Vydavatelstvo STU, Bratislava.
ISBN 80-227-2354-1 (1. vydanie, 2002, ISBN 80-227-1645-6).
( 6. kapitola pdf )
Kvasnicka V,
Benuskova L,
Pospichal J,
Farkas I,
Tino P,
Kral A
(1997) Uvod do teorie neuronovych sieti. Iris, Bratislava.
(cela kniha,
pdf.zip )
Book Chapters
Wysoski SG, Benuskova L and Kasabov N (2010) Brain-like evolving spiking
neural networks for multimodal information processing. In: A. Hanazawa
et al. (eds) Brain-Inspired Information Technology, Studies in
Computational Intelligence, vol. 266, Springer-Verlag, Berlin / Heidelberg,
pp. 15-27. ISBN 978-3-642-04024-5.
link
Kasabov N, Song Q, Jain V, Benuskova L, Gottgtroy P, Jain V, Verma A,
Havukkala I, Rush E, Pears R, Tjahjana A, Hu Y, MacDonel S (2008)
Integrating local and personalised modelling with global ontology knowledge
bases for biomedical and bioinformatics decision support. In:
Comp. Intel. in Biomed. & Bioinform., SCI 151,
T.G. Smolinski et al. (eds), Springer-Verlag, Berlin Heidelberg, pp. 93-116.
Kasabov N, Jain V, Benuskova L, Gottgtroy PCM, Joseph F (2008)
Integration of Brain-Gene Ontology and Simulation Systems for Learning,
Modelling and Discovery. In: Computational Intelligence in Medical
Informatics, chapter 11, A. Kelemen, A. Abraham, Y. Liang
(eds), Series: Studies in Computational Intelligence, vol. 85,
Springer, pp 221-234. ISBN 978-3-540-75766-5.
(about this book)
Benuskova L (2007)
Neurovedne okno do vedomia. In: Mysel, inteligencia
a zivot, V. Kvasnicka, P. Trebaticky, J. Pospichal, J. Kelemen (eds),
Vydavatelstvo STU, Bratislava, pp. 145-156. ISBN 978-80-227-2643-6.
Kasabov N and Benuskova L (2006) Theoretical and Computational Models for
Neuro, Genetic, and Neuro-Genetic Information Processing. In: Handbook
of Computational and Theoretical Nanotechnology , M. Rieth and
W. Schommers (eds), vol 6, chap 17, pp. 779-816, American Scientific
Publishers, Los Angeles. ISBN: 1-58883-048-9.
Benuskova L (2005)
Kde sa jazyk stretava s vedomim. In: Rybar J,
Kvasnicka V, Farkas I (eds) Jazyk a kognicia.
Kalligram, Bratislava, pp. 235-261. ISBN 80-7149-716-9.
Benuskova L (2002)
Kognitivna neuroveda. In: Rybar J, Benuskova L,
Kvasnicka V (eds) Kognitivne vedy. Kalligram, Bratislava,
pp. 47-104. ISBN 80-7149-515-8.
Jedlicka P, Benuskova L, Macakova J, Ostatnikova D (2002)
Molekulove mechanizmy ucenia a pamati.
In: Hulin I (ed) Patofyziologia, 6. vydanie.
Slovak Academic Press (SAP), s.r.o, Bratislava, pp. 1183-1199.
ISBN 80-8910-405-3.
Benuskova L (2000)
Vidiet znamena vediet: pamat neuronovych sieti.
In: Hladanie spolocneho jazyka v kognitivnych vedach.
Benuskova L, Kvasnicka V, Pospichal J (eds), Iris,
Bratislava, pp. 11-26. ISBN 80-88778-13-1.
Other
Benuskova L (2000)
Neurobiology keeps inspiring new neural network models.
ERCIM News No. 43 - Oct 2000, pp. 39-40.
Benuskova L (1988) Mechanizmy synaptickej plasticity.
Ceskoslovenska fysiologie
37(5): 387-400.
(ps)
Benuskova L (2000) Neuronove siete a vnimanie. Quark
6(9): 21-23. (pdf)
Benuskova L (2001) Neurovedne okno do vedomia. Spasmus
9(2): 6-8. (pdf)
Benuskova L (2002) Mapy nasich skusenosti (co tvaruje nas mozog).
Quark 8(2): 21-23.
(pdf)