Talk:Dehaene–Changeux model

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WP:MOS

The article should be cleaned to conform to our style guidelines (especially the excessive use of boldface in the sources and references). --Crusio (talk) 09:55, 28 October 2011 (UTC)[reply]

the model is a Multi-Agent System and a Swarm of Integrate and Fire Neurons

references and proofs. Saying the model is a neural network and that as such it can't be a Multi Agent Syetem or a Swarm is like saying it is a parallelogram and thus cannot be a square. The DCM is a neural network which is also a MAS and a Swarm, just like a square is also a rhombus. Here are other references about neural networks that are MAS:
  • Roya Asadi, Norwati Mustapha, Nasir Sulaiman, A Framework For Intelligent Multi Agent System Based Neural Network Classification Model (IJCSIS) International Journal of Computer Science and Information Security, Vol. 5, No. 1, 2009 [1]
  • Ying Xu; Mural, R.J.; Einstein, J.R.; Shah, M.B.; Uberbacher, E.C.; GRAIL: a multi-agent neural network system for gene identification Proceedings of the IEEE Oct 1996 84 Issue:10 1544 - 1552 [2]
  • Yong S. Choi, Suk I. Yoo , Multi-agent learning approach to WWW information retrieval using neural network IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces p23 - 30 [3]
  • Minar, N., R. Burkhart, C. Langton, and M. Askenazi. 1996. The Swarm simulation system: A toolkit for building multi-agent simulations. Working Paper 96-06-042, Santa Fe Institute, Santa Fe.
  • K.G. Jolly K.P. Ravindran, R. Vijayakumar, R. Sreerama Kumar, Intelligent decision making in multi-agent robot soccer system through compounded artificial neural networksRobotics and Autonomous Systems Volume 55, Issue 7, 31 July 2007, Pages 589-596 [4]

Besides, the brain at large is a multi-agent system and a swarm of neurons and glial cells... Cheers :--GrandPhilliesFan (talk) 12:08, 3 November 2011 (UTC)[reply]

It's possible to have a MAS containing one or more agents which are neural networks; but individual neurons are not agents. Nor do individual neurons meet the definition of
Wisconsin card sort model as well as for other work. If those different models are fundamentally the same, the article should justify its title by explaining why. At present the article appears to conflate unrelated ideas, and it could do with attention from an expert. -- 202.124.72.1 (talk) 14:11, 3 November 2011 (UTC)[reply
]
  • Your arguments might be stronger, GrandPhilliesFan, if your method of communicating them were not. Dennis Brown (talk) 17:31, 3 November 2011 (UTC)[reply]
  • I think the onus is on editors adding material to the article to back up claims (without
    WP:SYNTH, i.e. with sources that explicitly support the claim in question). Intelligent agents are my area of expertise, and nobody in the field refers to individual neurons as agents. Nor do the Wikipedia articles on MAS and swarms have individual neurons as examples. -- 202.124.75.29 (talk) 22:42, 3 November 2011 (UTC)[reply
    ]

history section repeats info from the lead

It was used to provide a predictive framework to the study of inattentional blindness and the solving of the Tower of London test.[3] [4] vs It would later be used to predict observable reaction times within the priming paradigm[5] and in inattentional blindness.

I am not sure I understand the topic well enough to do structural edits but that sure looks redundant Elinruby (talk) 06:22, 4 November 2011 (UTC) Category:Mind[reply]

Very technical article

So... somebody had to say it. It needs to address itself to people who do not have a Ph.D in pertinent subjects. I do realize that it's still a very new work in progress though.

Meanwhile, the English is a bit strange so I am trying to address that part of the article's readability issues. Since these really are deep waters I will raise these issues in separate sections in case I'm the one missing something. — Preceding unsigned comment added by Elinruby (talkcontribs) 07:12, 4 November 2011 (UTC)[reply]

clarify tag

"a critical role[clarification needed] played by the interaction between von Economo's areas."

what is that role? — Preceding unsigned comment added by Elinruby (talkcontribs) 07:17, 4 November 2011 (UTC)[reply]

clarify tags in Behavior section

1. Google does not seem to have ever heard of "surcritical" either. Please define.

2a) "The DCM exhibits several... behaviors such as multistability and a Hopf bifurcation between two very different regimes (ok so far) which may represent either sleep or arousal (the two regimes represent this? If so put commas after "regimes" and "arousal")...

2b) "with a various all-or-none behaviors which Dehaene et al. use to determine a testable taxonomy between different states of consciousness." -- cannot tell from sentence structure if the all-or-none behaviors are used to represent sleep vs arousal or some other categories of "different states of consciousness."

2c) Also, how do you test a taxonomy? — Preceding unsigned comment added by Elinruby (talkcontribs) 07:38, 4 November 2011 (UTC)[reply]

clarify tag in lead

swarm behavior of brain? I think you are talking about something like this: http://wiredset.com/2011/01/09/digital-swarm-behavior/

but this is really not something your reader should have to guess about.Elinruby (talk) 07:42, 4 November 2011 (UTC)[reply]

I want to wait until the article is accepted to make such improvements, but thanks for having underlined them--GrandPhilliesFan (talk) 12:04, 4 November 2011 (UTC)[reply]

Synth

I note that the article contains an entire section consisting of

WP:OR arguing for the classification of this model as a MAS/swarm. It would be more to the point to find a source which explicitly classifies this model as a MAS/swarm. -- 202.124.72.112 (talk) 01:14, 6 November 2011 (UTC)[reply
]

The PLOS paper from which the diagram was taken does not claim the model is a MAS or a swarm. -- 202.124.73.2 (talk) 08:20, 6 November 2011 (UTC)[reply]
It also confirms that this model is different from the other models by the same authors ("In previous neuronal modeling studies and computer simulations, we illustrated the possible contribution of spontaneous activity to tasks that involve a random search, such as the learning of a temporal sequence, the search for and selection of the correct rule in the delayed response and Wisconsin card-sorting tests, or the discovery of a multistep solution in the Tower of London test.") This article erroneously conflates this previous work with the model described by the figure. -- 202.124.73.2 (talk) 08:27, 6 November 2011 (UTC)[reply]