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Laparoscopic Endoscopic Surgical Science Neural Networks in the Brain: A Review of the Connectionist Approach to Language Acquisition [ALRJournal]
ALRJournal. Ahead of Print: ALRJ-87587 | DOI: 10.14744/alrj.2019.87587

Neural Networks in the Brain: A Review of the Connectionist Approach to Language Acquisition

Maliheh Khodabakhshi
Department of Applied Linguistics, Payame Noor University, Tehran, Iran

Connectionism is an approach to the study of human cognition which tries to explain how the human brain works using mathematical models, known as connectionist networks or artificial neural networks. The present paper aimed at reviewing the basic assumptions of connectionism and providing a general introduction to some of the terms and concepts used in connectionist modeling. Initially, the paper offered a brief history of connectionism, followed by different definitions of the term. Next, the basic assumptions of the model were delineated, moving to components of a connection namely, neuron and synapse. Furthermore, the differences between “brain” and “network” were discussed. The paper, then, introduced and explained Parallel Distributed Processing (PDP) models. Afterwards, the traditional symbolic models were compared with the connectionist models. The basic features of connectionist models were subsequently mentioned. Following that, two types of connectionist models were explained: the localist model and the distributed model. Then, how connectionism can be applied in language acquisition was discussed. As concluding remarks, the main points of connectionism were summed up along with some problems and limitations of connectionist models which should be regarded in future studies.

Keywords: Connectionism, neural networks, PDP, language acquisition

Corresponding Author: Maliheh Khodabakhshi, Iran
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