Abstract/Compact Notation: You can now build relational networks using the bidirectional nodes and links of the Abstract (formerly “Compact”) notation.
Subnetworks: There is a new item type that allows you to create sub-networks and link in and out of them.
Variable Link Lengths: You can now change the length of links (i.e. the number of time steps it takes for activation to spread through the link).
Neurocognitive Linguistics is an approach to linguistics developed by Sydney Lamb which uses relational networks to model what the brain actually does when it handles language. You can read more about it at the LangBrain site and Glottopedia.
Neurocognitive Linguistics Lab (“NeuroLab” for short) is a program that allows you to experiment with relational networks using a convenient GUI, and record the results of your experiments in tabular form.
The Neurocognitive Linguistics Lab (“NeuroLab” for short) is a program that allows you to experiment with the relational networks of Sydney Lamb’s neurocognitive linguistics model using a convenient GUI, and record the results of your experiments in tabular form.
Memori vortojn kaj gramatikajn leĝojn estas la plej malgranda parto da lingva lernado.
Estas ĉiam multaj manieroj esprimi tiun, kiun oni volas diri. Sed kutime estas plej populara vojo paroli, kies uzo distingas inter flua kaj malflua uzantaj.
Do kial neniam ajn rekomendiĝis la Fundamenta Krestomatio al mi? Estas granda ekzemplaro de stilo kaj kutimoj de Esperanta uzado.
Ĝies stilo estas kompreneble klasika, sed ĝi estas solida bazo sur kio kreskigi onies esperantan sperton.
In the copious free time I’ve had since my daughter was born a year ago (hi Emily!), I have been reading Sydney Lamb‘s work on what he calls Neurocognitive Linguistics. He started out in the 60′s with a relational network model of language that was quite different from the highly symbolic models others were using. Mostly ignored since then, the model turns out to reflect to a surprisingly high degree what the brain actually does when it processes language. It is starting to see a resurgence, particularly in the field of computational linguistics.
I have written the beginnings of a program to experiment with the model. The Neurocognitive Linguistics Lab allows you to graphically create relational networks and then simulate them in time to see how the neural activation and inhibition travels through the network. It has a handy data collection feature that allows you to save the data from your simulations in CSV format for further analysis.
The program is written in C++ using the cross-platform Qt framework. It has a convenient plugin system for implementing new kinds of network entities. It simulates the neural net by means of an asynchronous automata network, which uses Qt’s parallel processing facilities to automatically make use of multiple cores.
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