Functional connectivity among spikes in low dimensional space during working memory task in rat

The dynamic properties of a brain network during working memory based on the algorithm of cross-frequency coupling

Working memory (WM) refers to a memory system with limited energy for short-term maintenance and plays an important role in cognitive functions. At present, research regarding WM mostly focuses on the coordination between neural signals in the signal microelectrode channel. However, how neural signals coordinate the coding of WM at the network level is rarely studied. Cross-frequency coupling (CFC) reflects the coordinated effect between different frequency components (e.g., theta and gamma) of local field potentials (LFPs) during WM. In this study, we try to map the changes that occur in the brain networks during WM at the level of CFC between theta-gamma of LFPs. First, a 16-channel brain network by using the CFC between theta-gamma of LFPs during WM was constructed. Then, the dynamic properties of the brain network during WM were analyzed based on graph theory. Experimental results show that the LFPs power increased at the WM state than at resting stat, but decreased across learning; the CFC between theta-gamma increased with learning days and phase-amplitude coupling (PAC) in the WM state was higher than that in free choice state and rest state; the changes of average degree, average shortest path length and global efficiency had significant difference on learning days. We can indicate that the CFC between theta-gamma in the network plays an important role in the WM formation. Furthermore, correct storage of WM information will not change local information transmission and the small-world attribute, while, it can increase the network connection and efficiency of information transmission.

Information transmission in HPC-PFC network for spatial working memory in rat

Spatial working memory is a short-term system for the temporary holding and manipulation of spatial information. Evidence shows that the hippocampus (HPC) and prefrontal cortex (PFC) play important roles in spatial working memory. Though the communication between HPC and PFC is recognized as essential for successful execution of spatial working memory tasks, the directional information transmission in the HPC-PFC network is largely unclear. Therefore, in the present study, neuronal activity was recorded from rat ventral hippocampus (vHPC) and medial prefrontal cortex (mPFC) while the rats performed a spatial working memory task in Y-maze. Then the causality connectivity among the spikes from recorded neurons was estimated using the maximum likelihood estimation and the information flow in the vHPC-mPFC network was calculated to investigate the functional dynamics of the vHPC-mPFC information transmission. Our results showed the increased bidirectional information flow in the vHPC-mPFC network during the spatial working memory task. Both directions of information flow were observed only on trials in which the animal subsequently made the correct response, indicating that the increase in information flow predicted memory accuracy. Furthermore, the information flow from vHPC to mPFC was remarkably higher and preceded that from mPFC to vHPC. These findings suggest that the direct vHPC-mPFC information transmission may be predominant for spatial working memory in rat.