A Spiking Neural Model of the n-Back Task
نویسندگان
چکیده
We present a computational model performing the n-back task. This task requires a number of cognitive processes including rapid binding, updating, and retrieval of items in working memory. The model is implemented in spiking leakyintegrate-and-fire neurons with physiologically constrained parameters, and anatomically constrained organization. The methods of the Semantic Pointer Architecture (SPA) are used to construct the model. Accuracies and reaction times produced by the model are shown to match human data. Namely, characteristic decline in accuracy and response speed with increase of n is reproduced. Furthermore, the model provides evidence, contrary to some past proposals, that an active removal process of items in working memory is not necessary for an accurate performance on the n-back task.
منابع مشابه
Improving the Izhikevich Model Based on Rat Basolateral Amygdala and Hippocampus Neurons, and Recognizing Their Possible Firing Patterns
Introduction: Identifying the potential firing patterns following different brain regions under normal and abnormal conditions increases our understanding of events at the level of neural interactions in the brain. Furthermore, it is important to be capable of modeling the potential neural activities to build precise artificial neural networks. The Izhikevich model is one of the simplest biolog...
متن کاملThe Effect of Working Memory Training on Vocabulary Recall and Retention of Iranian EFL Learners: The Case of Dual N-Back Task
This study examined the effect of working memory training on vocabulary recall and retention ofIranian EFL learners using dual N-back task technique. To this end, 50 EFL learners at IslamicAzad University of Shoushtar were randomly assigned to the experimental (n = 25) and control (n= 25) groups. Before the treatment, a vocabulary test was administered to the participants to assessthe participa...
متن کاملArtificial Neural Network Involved in the Action of Optimum Mixed Refrigerant (Domestic Refrigerator) (TECHNICAL NOTE)
This analysis principally focuses on the implementation of Radial basis function (RBF) and back propagation (BPA) algorithms for training artificial neural network (ANN) to get the optimum mixture of Hydro fluorocarbon (HFC) and organic compound (Hydrocarbons) for obtaining higher coefficient of Performances (COPs). The thermodynamical properties of mixed refrigerants are observed using REFPROP...
متن کاملDynamic neural networks, comparing spiking circuits and LSTM
We have investigated two specific network types in the class of dynamic neural networks: LSTM and spiking neural networks. Dynamic neural networks in general are computationally powerful and very promising for tasks in which temporal information has to be processed. We’d like to remark that this is the case for virtually any task or application interacting with the real world. We have tested th...
متن کاملExploring Temporal Memory of LSTM and Spiking Circuits
We have investigated two specific network types in the class of dynamic neural networks: LSTM and spiking neural networks. Dynamic neural networks in general are computationally powerful and very promising for tasks in which temporal information has to be processed. We’d like to remark that this is the case for virtually any task or application interacting with the real world. We have tested th...
متن کامل