Working memory plays an important role in human cognition. This study investigated how working memory was encoded by the power of multichannel local field potentials （LFPs） based on sparse non negative matrix factorization （SNMF）. SNMF was used to extract features from LFPs recorded from the prefrontal cortex of four SpragueDawley rats during a memory task in a Y maze, with 10 trials for each rat. Then the powerincreased LFP components were selected as working memoryrelated features and the other components were removed. After that, the inverse operation of SNMF was used to study the encoding of working memory in the time frequency domain. We demonstrated that theta and gamma power increased significantly during the working memory task. The results suggested that postsynaptic activity was simulated well by the sparse activity model. The theta and gamma bands were meaningful for encoding working memory.
Objective Working memory is a key cognitive function in which the prefrontal cortex plays a crucial role. This study aimed to show the firing patterns of a neuronal population in the prefrontal cortex of the rat in a working memory task and to explore how a neuronal ensemble encodes a working memory event. Methods Sprague-Dawley rats were trained in a Y-maze until they reached an 80% correct rate in a working memory task. Then a 16-channel microelectrode array was implanted in the prefrontal cortex. After recovery, neuronal population activity was recorded during the task, using the Cerebus data-acquisition system. Spatio-temporal trains of action potentials were obtained from the original neuronal population signals. Results During the Y-maze working memory task, some neurons showed significantly in- creased firing rates and evident neuronal ensemble activity. Moreover, the anticipatory activity was associated with the delayed alternate choice of the upcoming movement. In correct trials, the averaged pre-event firing rate （10.86 ± 1.82 spikes/ bin） was higher than the post-event rate （8.17 ± 1.15 spikes/bin） （P 〈0.05）. However, in incorrect trials, the rates did not differ. Conclusion The results indicate that the anticipatory activity of a neuronal ensemble in the prefrontal cortex may play a role in encoding working memory events.
Neuronal ensemble activity codes working memory.In this work,we developed a neuronal ensemble sparse coding method,which can effectively reduce the dimension of the neuronal activity and express neural coding.Multichannel spike trains were recorded in rat prefrontal cortex during a work memory task in Y-maze.As discretesignals,spikes were transferred into cont inuous signals by estinating entropy.Then the normalized continuous signals were decomposed via non-negative sparse met hod.The non-negative components were extracted to reconstruct a low-dimensional ensemble,while none of the feature components were missed.The results showed that,for well-trained rats,neuronal ensemble activities in the prefrontal cortex changed dynamically during the.working memory task.And the neuronal ensemble is more explicit via using non-negative sparse coding.Our results indicate that the neuronal ensemblesparse coding method can effectively reduce the dimnension of neuronal activity and it is a useful tool to express neural coding.
