Self organising maps with a point neuron model

Article

Huyck, C. and Mitchell, I. 2013. Self organising maps with a point neuron model. Intl Conf. on Cognitive and Neural Systems.
TypeArticle
TitleSelf organising maps with a point neuron model
AuthorsHuyck, C. and Mitchell, I.
Abstract

This abstract describes simulations using a reasonably biological accurate point neuron model, a fatiguing leaky integrate and fire model. These model neurons use a novel compensatory Hebbian learning rule to categorise data items, a standard machine learning task. The resulting system is a kind of self organising map, which compares favourably with a Kohonen map on one machine learning task.

Research GroupArtificial Intelligence group
JournalIntl Conf. on Cognitive and Neural Systems
Publication dates
Print2013
Publication process dates
Deposited12 May 2015
Output statusPublished
LanguageEnglish
Permalink -

https://repository.mdx.ac.uk/item/854v9

Log in to edit
  • 63
    total views
  • 0
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

Quasi Biologically Plausible Category Learning
Huyck, C. 2024. Quasi Biologically Plausible Category Learning. 44th SGAI International Conference on Artificial Intelligence, AI 2024. Cambridge, UK 17 - 19 Dec 2024 Springer.
Parameter tuning of the Firefly Algorithm by standard Monte Carlo and Quasi-Monte Carlo methods
Joy, G., Huyck, C. and Yang, X. 2024. Parameter tuning of the Firefly Algorithm by standard Monte Carlo and Quasi-Monte Carlo methods. Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V., Dongarra, J. and Sloot, P. (ed.) 24th International Conference on Computational Science. Malaga, Spain 02 - 04 Jul 2024 Cham Springer. pp. 242–253 https://doi.org/10.1007/978-3-031-63775-9_17
A proposal for extending the Common Model of Cognition to emotion
Rosenbloom, P., Laird, J., Lebiere, C., Stocco, A., Granger, R. and Huyck, C. 2024. A proposal for extending the Common Model of Cognition to emotion. 22nd International Conference on Cognitive Modeling. Tilburg University, the Netherlands 19 - 22 Jul 2024
Enhancing individual UAV path planning with Parallel Multi-Swarm Treatment Coronavirus Herd Immunity Optimizer (PMST-CHIO) algorithm
Fouad, A., Abboudi, A., Huyck, C., Gao, X., Bououden, S., Khezami, N. and Shall, H. 2024. Enhancing individual UAV path planning with Parallel Multi-Swarm Treatment Coronavirus Herd Immunity Optimizer (PMST-CHIO) algorithm. IEEE Access. 12, pp. 28395-28416. https://doi.org/10.1109/ACCESS.2024.3367753
Associative memory with biologically-inspired cell assemblies
Ji, Y., Gamez, D. and Huyck, C. 2024. Associative memory with biologically-inspired cell assemblies. Samsonovich, A.V. and Liu, T. (ed.) 2023 Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence, the 14th Annual Meeting of the BICA Society (BICA*AI 2023). Ningbo, China 13 - 15 Oct 2023 Springer. pp. 422-428 https://doi.org/10.1007/978-3-031-50381-8_43
A spiking model of Cell Assemblies: Short term and associative memory
Huyck, C. 2023. A spiking model of Cell Assemblies: Short term and associative memory. Medical Research Archives. 11 (9), pp. 1-20. https://doi.org/10.18103/mra.v11i9.4406
Bridging neuroscience and robotics: spiking neural networks in action
Jones, A., Gandhi, V., Mahiddine, A. and Huyck, C. 2023. Bridging neuroscience and robotics: spiking neural networks in action. Sensors. 23 (21), pp. 1-14. https://doi.org/10.3390/s23218880
Review of parameter tuning methods for nature-inspired algorithms
Joy, G., Huyck, C. and Yang, X. 2023. Review of parameter tuning methods for nature-inspired algorithms. in: Yang, X. (ed.) Benchmarks and Hybrid Algorithms in Optimization and Applications Singapore Springer. pp. 33-47
CAGE: Consensus Algorithm Genetically Enhanced
Mitchell, I. and Maka, K. 2023. CAGE: Consensus Algorithm Genetically Enhanced. 15th International Conference on Global Security, Safety & Sustainability. Virtual Online 11 - 12 Oct 2023 Springer.
Competitive learning with spiking nets and spike timing dependent plasticity
Huyck, C. and Orume, E. 2022. Competitive learning with spiking nets and spike timing dependent plasticity. Bramer, M. and Stahl, F. (ed.) AI-2022: The Forty-second SGAI International Conference. Cambridge, England, UK 13 - 15 Dec 2022 Springer. pp. 153-166 https://doi.org/10.1007/978-3-031-21441-7_11
Cell Assembly-based Task Analysis (CAbTA)
Diaper, D. and Huyck, C. 2021. Cell Assembly-based Task Analysis (CAbTA). Arai, K. (ed.) Computing Conference 2021 (formerly called Science and Information (SAI) Conference). Virtual (from London, UK) 15 - 16 Jul 2021 Springer. https://doi.org/10.1007/978-3-030-80119-9_22
Learning categories with spiking nets and spike timing dependent plasticity
Huyck, C. 2020. Learning categories with spiking nets and spike timing dependent plasticity. Bramer, M. and Ellis, R. (ed.) 40th SGAI 2020. Cambridge, UK 15 - 17 Dec 2020 Springer. pp. 139-144 https://doi.org/10.1007/978-3-030-63799-6_10
IoT and cloud forensic investigation guidelines
Mitchell, I., Hara, S., Ibarra-Jiminez, J., Jahankhani, H. and Montasari, R. 2020. IoT and cloud forensic investigation guidelines. in: Jahankhani, H., Akhgar, B., Cochrane, P. and Dastbaz, M. (ed.) Policing in the Era of AI and Smart Societies Cham, Switzerland Springer. pp. 119-138
dAppER: decentralised application for examination reviews
Mitchell, I., Hara, S. and Sheriff, M. 2019. dAppER: decentralised application for examination reviews. 12th International Conference on Global Security, Safety & Sustainability. Northumbria University London, England 16 - 18 Jan 2019 IEEE. https://doi.org/10.1109/ICGS3.2019.8688143
Blockchain of custody, BoC
Mitchell, I., Hara, S., Jahankhani, H. and Neilson, D. 2020. Blockchain of custody, BoC. in: Jahankhani, H. (ed.) Cyber Security Practitioner's Guide World Scientific. pp. 365-397
BMAR - blockchain for medication administration records
Mitchell, I. and Hara, S. 2019. BMAR - blockchain for medication administration records. in: Jahankhani, H., Kendzierskyj, S., Jamal, A., Epiphaniou, G. and Al-Khateeb, H. (ed.) Blockchain and Clinical Trial: Securing Patient Data Cham, Switzerland Springer.
Hot coffee: associative memory with bump attractor cell assemblies of spiking neurons
Huyck, C. and Vergani, A. 2020. Hot coffee: associative memory with bump attractor cell assemblies of spiking neurons. Journal of Computational Neuroscience. 48 (3), pp. 299-316. https://doi.org/10.1007/s10827-020-00758-1
Quality audits with Blockchain for healthcare in the UK
Mitchell, I. and Hara, S. 2019. Quality audits with Blockchain for healthcare in the UK. George, C., Whitehouse, D. and Duquenoy, P. (ed.) Health IT Workshop 2019. Middlesex University, London 07 - 08 Nov 2019 pp. 42-43
Are quiz-games an effective revision tool in Anatomical Sciences for Higher Education and what do students think of them?
Wilkinson, K., Dafoulas, G., Garelick, H. and Huyck, C. 2020. Are quiz-games an effective revision tool in Anatomical Sciences for Higher Education and what do students think of them? British Journal of Educational Technology. 51 (3), pp. 761-777. https://doi.org/10.1111/bjet.12883
A neural cognitive architecture
Huyck, C. 2020. A neural cognitive architecture. Cognitive Systems Research. 59, pp. 171-178. https://doi.org/10.1016/j.cogsys.2019.09.023
DaP∀ : Deconstruct and Preserve for all: a procedure for the preservation of digital evidence on solid state drives and traditional storage media
Mitchell, I., Ferriera, J., Anandaraja, T. and Hara, S. 2018. DaP∀ : Deconstruct and Preserve for all: a procedure for the preservation of digital evidence on solid state drives and traditional storage media. in: Jahankhani, H. (ed.) Cyber Criminology Cham, Switzerland Springer. pp. 275-281
SMERF: Social Media, Ethics and Risk Framework
Mitchell, I., Cockerton, T., Hara, S. and Evans, C. 2018. SMERF: Social Media, Ethics and Risk Framework. in: Jahankhani, H. (ed.) Cyber Criminology Cham, Switzerland Springer. pp. 203-225
A brain-inspired cognitive system that mimics the dynamics of human thought
Ji, Y., Gamez, D. and Huyck, C. 2018. A brain-inspired cognitive system that mimics the dynamics of human thought. AI-2018 Thirty-eighth SGAI International Conference on Artificial Intelligence. Cambridge, UK 11 - 13 Dec 2018 Springer. pp. 50-62 https://doi.org/10.1007/978-3-030-04191-5_4
Two simple NeuroCognitive associative memory models
Huyck, C. and Ji, Y. 2018. Two simple NeuroCognitive associative memory models. International Conference on Cognitive Modeling 2018. Madison Wisconsin 20 - 24 Jul 2018 pp. 31-36
Implementing Rules with Aritificial Neurons
Huyck, C. and Kreivena, D. 2018. Implementing Rules with Aritificial Neurons. AI-2018 38th SGAI International Conference on Artificial Intelligence. Cambridge 11 - 13 Dec 2018 Springer. pp. 21-33 https://doi.org/10.1007/978-3-030-04191-5_2
A spiking half-cognitive model for classification
Huyck, C. and Kulkarni, R. 2018. A spiking half-cognitive model for classification. Connection Science. 30 (3), pp. 285-305. https://doi.org/10.1080/09540091.2018.1443317
CABots and other neural agents
Huyck, C. and Mitchell, I. 2018. CABots and other neural agents. Frontiers in Neurorobotics. 12, pp. 1-12. https://doi.org/10.3389/fnbot.2018.00079
The neural cognitive architecture
Huyck, C. 2017. The neural cognitive architecture. AAAI 2017 FALL Symposium Series: Symposium on A Standard Models of the Mind. Arlington, Virginia, USA 09 - 11 Nov 2017 Association for the Advancement of Artificial Intelligence (AAAI). pp. 365-370
Neuron-based control mechanisms for a robotic arm and hand
Singh, N., Huyck, C., Gandhi, V. and Jones, A. 2017. Neuron-based control mechanisms for a robotic arm and hand. International Journal of Computer, Electrical, Automation, Control and Information Engineering. 11 (2), pp. 221-229. https://doi.org/10.5281/zenodo.1128871
Programming a cognitive architecture with simulated neurons, Chris Eliasmith. How to Build a Brain: A Neural Architecture for Biological Cognition. Oxford University Press, Oxford (2013). 456 pp., ISBN: 978-0-19-026212-9 [Book review]
Huyck, C. 2017. Programming a cognitive architecture with simulated neurons, Chris Eliasmith. How to Build a Brain: A Neural Architecture for Biological Cognition. Oxford University Press, Oxford (2013). 456 pp., ISBN: 978-0-19-026212-9 [Book review]. Cognitive Systems Research. 41, pp. 36-37. https://doi.org/10.1016/j.cogsys.2016.09.002
Bitcoin forensics: a tutorial
Neilson, D., Hara, S. and Mitchell, I. 2017. Bitcoin forensics: a tutorial. Jahankhani, H., Carlile, A., Emm, D., Hosseinian-Far, A., Brown, G., Sexton, G. and Jamal, A. (ed.) 11th International Conference on Global Security, Safety and Sustainability. London, UK 18 - 20 Jan 2017 Cham Springer. pp. 12-26 https://doi.org/10.1007/978-3-319-51064-4_2
Deconstruct and preserve (DaP): a method for the preservation of digital evidence on solid state drives (SSD)
Mitchell, I., Anandaraja, T., Hara, S., Hadzhinenov, G. and Neilson, D. 2017. Deconstruct and preserve (DaP): a method for the preservation of digital evidence on solid state drives (SSD). Jahankhani, H., Carlile, A., Emm, D., Hosseinian-Far, A., Brown, G., Sexton, G. and Jamal, A. (ed.) 11th International Conference on Global Security, Safety and Sustainability. London, UK 18 - 20 Jan 2017 Cham Springer. https://doi.org/10.1007/978-3-319-51064-4_1
Programming with simulated neurons: a first design pattern
Evans, C., Mitchell, I. and Huyck, C. 2016. Programming with simulated neurons: a first design pattern. PPIG 2016 - 27th Annual Workshop of the Psychology of Programming Interest Group. University of Cambridge, Cambridge, UK 07 - 10 Sep 2016 Psychology of Programming Interest Group. pp. 36-45
PlaNeural: spiking neural networks that plan
Mitchell, I., Huyck, C. and Evans, C. 2016. PlaNeural: spiking neural networks that plan. 7th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2016. New York City, NY, USA 16 Jul 2016 Elsevier. pp. 198-204 https://doi.org/10.1016/j.procs.2016.07.425
Advancing ambient assisted living with caution
Huyck, C., Augusto, J., Gao, X. and Botia, J. 2015. Advancing ambient assisted living with caution. in: Helfert, M., Holzinger, A., Ziefle, M., Fred, A., O'Donoghue, J. and Röcker, C. (ed.) Information and Communication Technologies for Ageing Well and e-Health: First International Conference, ICT4AgeingWell 2015, Lisbon, Portugal, May 20-22, 2015. Revised Selected Papers Springer.
Neural constraints and flexibility in language processing
Huyck, C. 2016. Neural constraints and flexibility in language processing. Behavioral and Brain Sciences: An International Journal of Current Research and Theory with Open Peer Commentary. 39, p. e78. https://doi.org/10.1017/s0140525x15000837
Computer forensics: challenges to evidential integrity
Mitchell, I. and Hara, S. 2014. Computer forensics: challenges to evidential integrity. in: Jennions, I. (ed.) Integrated vehicle health management: implementation and lessons learned Warrendale, PA, USA SAE International.
A comparison of simple agents implemented in simulated neurons
Huyck, C., Evans, C. and Mitchell, I. 2015. A comparison of simple agents implemented in simulated neurons. Biologically Inspired Cognitive Architectures. 12, pp. 9-19. https://doi.org/10.1016/j.bica.2015.03.001
Programming the MIRTO robot with neurons
Huyck, C., Primiero, G. and Raimondi, F. 2014. Programming the MIRTO robot with neurons. Procedia Computer Science. 41, pp. 75-82. https://doi.org/10.1016/j.procs.2014.11.087
A neuro-computational approach to PP attachment ambiguity resolution
Nadh, K. and Huyck, C. 2012. A neuro-computational approach to PP attachment ambiguity resolution. Neural Computation. 24 (7), pp. 1906-1925. https://doi.org/10.1162/NECO_a_00298
A review of cell assemblies
Huyck, C. and Passmore, P. 2013. A review of cell assemblies. Biological Cybernetics. 107 (3), pp. 263-288. https://doi.org/10.1007/s00422-013-0555-5
Compensatory Hebbian learning for categorisation in simulated biological neural nets
Huyck, C. and Mitchell, I. 2013. Compensatory Hebbian learning for categorisation in simulated biological neural nets. Biologically Inspired Cognitive Architectures. 6 (5), pp. 3-7. https://doi.org/10.1016/j.bica.2013.06.003
Post and pre-compensatory Hebbian Learning for categorisation
Huyck, C. and Mitchell, I. 2014. Post and pre-compensatory Hebbian Learning for categorisation. Cognitive Neurodynamics. 8 (4), pp. 299-311. https://doi.org/10.1007/s11571-014-9282-4
True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms
Yang, X., Huyck, C., Karamanoglu, M. and Khan, N. 2013. True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms. International Journal of Bio-Inspired Computation. 5 (6), pp. 329-335. https://doi.org/10.1504/IJBIC.2013.058910
A framework for digital investigations: a case study using BPB modifications
Mitchell, I. 2011. A framework for digital investigations: a case study using BPB modifications. 6th International Annual Workshop on Digital Forensics and Incident Analysis (WDFIA 2011). Kingston University, London Jul 2011
KCMAC-BYY: Kernel CMAC using Bayesian Ying-Yang learning
Tian, K., Guo, B., Liu, G., Mitchell, I., Cheng, D. and Zhao, W. 2013. KCMAC-BYY: Kernel CMAC using Bayesian Ying-Yang learning. Neurocomputing. 101, pp. 24-31. https://doi.org/10.1016/j.neucom.2012.06.028
Genetic sequences: tracing the mutations of a disease.
Mitchell, I., Passmore, P. and Xu, K. 2010. Genetic sequences: tracing the mutations of a disease. IEEE VAST Symposium 2010 Challenge. Salt Lake City, Utah, USA 24 - 29 Oct 2010
Cell assemblies for query expansion in information retrieval
Volpe, I., Moreira, V. and Huyck, C. 2011. Cell assemblies for query expansion in information retrieval. 2011 International Joint Conference on Neural Networks (IJCNN). San Jose, CA, USA 31 Jul - 05 Aug 2011 IEEE. pp. 551-558 https://doi.org/10.1109/IJCNN.2011.6033269
Conflict resolution and learning probability matching in a neural cell-assembly architecture
Belavkin, R. and Huyck, C. 2011. Conflict resolution and learning probability matching in a neural cell-assembly architecture. Cognitive Systems Research. 12 (2), pp. 93-101. https://doi.org/10.1016/j.cogsys.2010.08.003
A Pong playing agent modelled with massively overlapping cell assemblies
Nadh, K. and Huyck, C. 2010. A Pong playing agent modelled with massively overlapping cell assemblies. Neurocomputing. 73 (16-18), pp. 2928-2934. https://doi.org/10.1016/j.neucom.2010.07.013
Multi-associative memory in fLIF cell assemblies.
Huyck, C. and Nadh, K. 2009. Multi-associative memory in fLIF cell assemblies. 9th International Conference on Cognitive Modeling. Manchester 24 - 26 Jul 2009
Processing with cell assemblies
Byrne, E. and Huyck, C. 2010. Processing with cell assemblies. Neurocomputing. 74 (1-3), pp. 76-83. https://doi.org/10.1016/j.neucom.2009.09.024
Using cohesive devices to recognize rhetorical relations in text.
Le, H., Abeysinghe, G. and Huyck, C. 2003. Using cohesive devices to recognize rhetorical relations in text. 4th Computational Linguistics UK Research Colloquium (CLUK-4). Edinburgh University Jan 2003 pp. 123-128
Automated discourse segmentation by syntactic information and cue phrases.
Le, H., Abeysinghe, G. and Huyck, C. 2004. Automated discourse segmentation by syntactic information and cue phrases. IASTED International Conference on Artificial Intelligence and Applications (AIA 2004). Innsbruck, Austria 16 - 18 Feb 2004 pp. 293-298
Generating discourse structures for written texts
Le, H., Abeysinghe, G. and Huyck, C. 2004. Generating discourse structures for written texts. International Conference on Computational Linguistics, (COLING 2004). University of Geneva, Switzerland 23 - 27 Aug 2004 pp. 329-355
A study to improve the efficiency of a discourse parsing system
Le, H., Abeysinghe, G. and Huyck, C. 2003. A study to improve the efficiency of a discourse parsing system. 4th International Conference on Intelligent Text Processing and Computational Linguistics, (CICLing’03). Mexico City 16 - 22 Feb 2003 pp. 101-114
Emergence of rules in cell assemblies of fLIF neurons.
Belavkin, R. and Huyck, C. 2008. Emergence of rules in cell assemblies of fLIF neurons. The 18th European Conference on Artificial Intelligence. University of Patras, Greece 21 - 25 Jul 2008
A model of probability matching in a two-choice task based on stochastic control of learning in neural cell-assemblies.
Belavkin, R. and Huyck, C. 2009. A model of probability matching in a two-choice task based on stochastic control of learning in neural cell-assemblies. 9th International conference on cognitive modelling {ICCM 2009]. University of Manchester 24 - 26 Jul 2009
Models of cell assembly decay
Passmore, P. and Huyck, C. 2008. Models of cell assembly decay. Institute of Electrical and Electronics Engineers. pp. 1-6 https://doi.org/10.1109/UKRICIS.2008.4798946
Dialogue based interfaces for universal access.
Huyck, C. 2010. Dialogue based interfaces for universal access. Universal Access in the Information Society. https://doi.org/10.1007/s10209-010-0209-5
A psycholinguistic model of natural language parsing implemented in simulated neurons
Huyck, C. 2009. A psycholinguistic model of natural language parsing implemented in simulated neurons. Cognitive Neurodynamics. 3 (4), pp. 316-330. https://doi.org/10.1007/s11571-009-9080-6
Variable binding by synaptic strength change
Huyck, C. 2009. Variable binding by synaptic strength change. Connection Science. 21 (4), pp. 327-357. https://doi.org/10.1080/09540090902954188
Prepositional phrase attachment ambiguity resolution using semantic hierarchies
Nadh, K. and Huyck, C. 2009. Prepositional phrase attachment ambiguity resolution using semantic hierarchies. Hamza, M. (ed.) 9th IASTED International Conference on Artificial Intelligence and Applications. Innsbruck, Austria 17 - 18 Feb 2009 Acta Press.
A connectionist inference model for pattern-directed knowledge representation
Mitchell, I. and Bavan, A. 2000. A connectionist inference model for pattern-directed knowledge representation. Expert Systems. 17 (2), pp. 106-113.
Neural cell assemblies for practical applications.
Huyck, C. and Bavan, A. 2002. Neural cell assemblies for practical applications. in: Callaos, N. (ed.) SCI 2002: ISAS: the 6th world multiconference on systemics, cybernetics and informatics: proceedings. Orlando, Florida. International Institute of Informatics and Systemics.. pp. 174-177
Agent design method for enhancing accessibility.
Cook, J., Huyck, C. and Whitney, G. 2004. Agent design method for enhancing accessibility. in: McLoughlin, C. and Cantoni, L. (ed.) ED-MEDIA 2004: world conference on educational multimedia, hypermedia and telecommunications: proceedings of ED-MEDIA 2004. Association for the Advancement of Computing in Education.
Quality assurance of curricula through the use of an integrated framework for programme validation.
Mitchell, I., Sheriff, M. and Georgiadou, E. 2008. Quality assurance of curricula through the use of an integrated framework for programme validation. Tempus JEP-27178-2006, Dissemination Workshop.. Yerevan, Armenia Sep 2008
MESSM: a framework for protein fold recognition using neural networks and support vector machines.
Mitchell, I., Jiang, N. and Wu, W. 2006. MESSM: a framework for protein fold recognition using neural networks and support vector machines. International Journal of Bioinformatics Research and Applications. 2 (4), pp. 381-393. https://doi.org/10.1504/IJBRA.2006.011037
Selection enthusiasm.
Mitchell, I. and Agrawal, A. 2006. Selection enthusiasm. in: 6th International Conference on Simulated Evolutionand Learning, Hefei, China. Proceedings. Heidelberg Springer Verlag.
Dynamics in proportionate selection.
Mitchell, I., Agrawal, A., Litovski, I. and Passmore, P. 2005. Dynamics in proportionate selection. in: International Conference on Adaptive and Natural Computnig Alogorithms, Coimbra, Portugal. Proceedings. Vienna. Springer. pp. 226-229
Counting with neurons: rule application with nets of fatiguing leaking integrate and fire neurons.
Huyck, C. and Belavkin, R. 2006. Counting with neurons: rule application with nets of fatiguing leaking integrate and fire neurons. 7th International Conference on Cognitive Modelling. Trieste, Italy pp. 142-147
Creating hierarchical categories using cell assemblies
Huyck, C. 2007. Creating hierarchical categories using cell assemblies. Connection Science. 19 (1), pp. 1-24. https://doi.org/10.1080/09540090600779713
Threading with environment-specific score by artificial neural networks
Mitchell, I., Jiang, N. and Wu, W. 2006. Threading with environment-specific score by artificial neural networks. Soft Computing. 10 (4), pp. 305-314. https://doi.org/10.1007/s00500-005-0488-6
Relevance feedback and cross-language information retrieval
Orengo, V. and Huyck, C. 2006. Relevance feedback and cross-language information retrieval. Information Processing and Management. 42 (5), pp. 1203-1217. https://doi.org/10.1016/j.ipm.2005.12.003
Information retrieval and categorisation using a cell assembly network
Huyck, C. and Orengo, V. 2005. Information retrieval and categorisation using a cell assembly network. Neural Computing and Applications. 14 (4), pp. 282-289. https://doi.org/10.1007/s00521-004-0464-6
Overlapping cell assemblies from correlators
Huyck, C. 2004. Overlapping cell assemblies from correlators. Neural Computing Letters. 56, pp. 435-439. https://doi.org/10.1016/j.neucom.2003.08.003