Effect Of Newborn Granule Cells In Dentate Gyrus On Pattern Separation

Pattern separation related to memory processes has been studied extensively for many years.It has been reported that the dentate gyrus in the hippocampus is considered to be the main brain region for pattern separation.Through pattern separation,similar inputs are represented by highly different,non-overlapping information,thus ensuring that the brain encodes new memories without interference from previously stored memories with similar characteristics.Due to their unique neuronal properties,the newborn granule cells generated by hippocampal neurogenesis are believed to participate effectively in the pattern separation process of dentate gyrus network,but the detailed mechanism remain unknown.Focusing on how newborn granule cells affect the pattern separation of dentate gyrus network,this paper establishes a simplified,biologically related dentate gyrus network computing model including various types of interneurons,and mainly explores the influence of 4-6-week newborn granule cells produced by hippocampal neurogenesis on the pattern separation of dentate gyrus network.The main results of this paper are as follows:We propose a new dentate gyrus neural network model related to adult hippocampal neurogenesis.Using this model,we found that 4-6 weeks of newborn granule cells can significantly increase the firing sparsity of mature granule cells and effectively enhance the pattern separation under the medium level of neurogenesis(5%of mature granule cells).The effect of newborn granule cells on pattern separation of dentate gyrus network can be understood from two aspects.On the one hand,newborn granule cells compete with mature granule cells for inputs from the entorhinal cortex and weaken the firing activity of mature granule cells;On the other hand,newborn granule cells effectively enhance the feedback inhibition level of the network by promoting the firing activity of interneurons(mossy cells and basket cells),and then indirectly regulate the firing sparsity of mature granule cells.In order to verify the effectiveness of the pattern separation model,we apply the proposed model to the similar concept separation task and achieves better results than the nonneurogenesis model in this task.In addition,we also investigated the contribution of newborn granule cells to pattern separation under different input stimuli.With the aid of simulation results,it show that newborn granule cells play different roles in the DG network when receiving different intensities of stimulation.Under low intensity stimulus,newborn granule cells can restore the information representation ability of the network and avoid pattern separation failure by taking advantage of their easily activated neuronal properties.Under high intensity stimulus,as a kind of interneurons,newborn granule cells can enhance the feedback inhibition effect of local circuits to improve the sparsity of mature granule cells,and ultimately improve the function of pattern separation.Therefore,this model predicts a critical role of adult hippocampal neurogenesis in pattern separation robustness under more subtle and extensive input.