Automatic and Controlled Processes in Semantic Priming: an Attractor Neural Network Model with Latching Dynamics
نویسندگان
چکیده
Semantic priming involves a combination of automatic processes like spreading activation (SA) and controlled processes like expectancy and semantic matching. An alternative account for automatic priming has been suggested using attractor neural networks. Such networks offer a more biologically plausible model of real neuronal dynamics but fall short in explaining several important effects such as mediated and asymmetrical priming, as well as controlled effects. We describe a new attractor network which incorporates synaptic adaptation mechanisms and performs latching dynamics. We show that this model can implement spreading activation in a statistical manner and therefore exhibit all priming effects previously attributed to automatic priming. In addition, we show how controlled processes are implemented in the same network, explaining many other semantic priming results.
منابع مشابه
Integrating the Automatic and the Controlled: Strategies in Semantic Priming in an Attractor Network With Latching Dynamics
Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic prim...
متن کاملSpreading Activation in an Attractor Network With Latching Dynamics: Automatic Semantic Priming Revisited
Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified framework for the two approaches. Our models assum...
متن کاملSemantic Priming in Typical and Schizophrenic Individuals: An Attractor Network Model with Latching Dynamics
متن کامل
بهبود بازشناسی مقاوم الگو در شبکه های عصبی بازگشتی جاذب از طریق به کارگیری دینامیک های آشوب گونه
In this paper, two kinds of chaotic neural networks are proposed to evaluate the efficiency of chaotic dynamics in robust pattern recognition. The First model is designed based on natural selection theory. In this model, attractor recurrent neural network, intelligently, guides the evaluation of chaotic nodes in order to obtain the best solution. In the second model, a different structure of ch...
متن کاملInternally- and externally-driven network transitions as a basis for automatic and strategic processes in semantic priming: theory and experimental validation
For the last four decades, semantic priming-the facilitation in recognition of a target word when it follows the presentation of a semantically related prime word-has been a central topic in research of human cognitive processing. Studies have drawn a complex picture of findings which demonstrated the sensitivity of this priming effect to a unique combination of variables, including, but not li...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010