Huyck, C.

A neural cognitive architecture

Article

Huyck, C. 2020. A neural cognitive architecture. Cognitive Systems Research. 59, pp. 171-178. https://doi.org/10.1016/j.cogsys.2019.09.023

Publication dates
Type	Article
Title	A neural cognitive architecture
Authors	Huyck, C.
Abstract	It is difficult to study the mind, but cognitive architectures are one tool. As the mind emerges from the behaviour of the brain, neuropsychological methods are another method to study the mind, though a rather indirect method. A cognitive architecture that is implemented in spiking neurons is a method of studying the mind that can use neuropsychological evidence directly. A neural cognitive architecture, based on rule based systems and associative memory, can be readily implemented, and would provide a good bridge between standard cognitive architectures, such as \Soar, and neuropsychology. This architecture could be implemented in spiking neurons, and made available via the Human Brain Project, which provides a good collaborative environment. The architecture could be readily extended to use spiking neurons for subsystems, such as spatial reasoning, and could evolve over time toward a complete architecture. The theory behind this architecture could evolve over time. Simplifying assumptions, made explicit, such as those behind the rule based system, could gradually be replaced by more neuropsychologically accurate behaviour. The overall task of collaborative architecture development would be eased by direct evidence of the actual neural cognitive architectures in human brains. While the initial architecture is biologically inspired, the ultimate goal is a biological cognitive architecture.
Research Group	Artificial Intelligence group
Publisher	Elsevier
Journal	Cognitive Systems Research
ISSN	1389-0417
Online	26 Sep 2019
Print	01 Jan 2020
Publication process dates
Deposited	19 Sep 2019
Accepted	16 Sep 2019
Output status	Published
Accepted author manuscript	neuralCogArch.pdf License CC BY-NC-ND 4.0
Copyright Statement	© 2019. This author's accepted manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Digital Object Identifier (DOI)	https://doi.org/10.1016/j.cogsys.2019.09.023
Language	English

Permalink -

https://repository.mdx.ac.uk/item/8876v

Log in to edit

Download files

Accepted author manuscript

	neuralCogArch.pdf
License: CC BY-NC-ND 4.0

100
total views
23
total downloads
1
views this month
1
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

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

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

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 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

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

Self organising maps with a point neuron model

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

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

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.

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.