The problem of serial order: a neural network model of sequence learning and recall
Current research in natural language generation
Neuromodulation of decision and response selection
Neural Networks - Computational models of neuromodulation
Hold your horses: a dynamic computational role for the subthalamic nucleus in decision making
Neural Networks - 2006 Special issue: Neurobiology of decision making
| Hi-index | 0.00 |
Sequential behavior is observed in various domains of cognitive psychology, including free recall paradigms. In this article, within a neurocomputational framework, resampling (RS) mechanisms are compared with competitive queuing (CQ) mechanisms. While both types of implementations select the most active representation, the subsequent inhibition is at the level of selection for RS models and at the level of (re)activation for CQ models. It is shown that despite the overwhelming success of CQ models in serial recall (with regard to types of sequencing error) RS models outperform CQ models with regard to inter-response times in a free recall task. Additional analyses show that decay of response suppression reduces the difference between the models. The RS model is sensitive to the size of the search set and accounts for memory selection performance in patients with Alzheimer's dementia or Huntington's disease. Finally, a non-mnemonic clustering behavior is observed, which is related to the dynamical process of the selection mechanism.