Multiple types of navigational information is diffusely and independently encoded in the population activities of the dentate gyrus neurons

The dentate gyrus (DG) plays critical roles in cognitive functions such as learning, memory, and spatial coding, and its dysfunction is implicated in various neuropsychiatric disorders. However, it remains largely unknown how information is represented in this region. Here, we recorded neuronal activity in the DG using Ca imaging in freely moving mice and analysed this activity using machine learning. Although each individual neuron was weakly and diversely tuned to multiple information types, the activity patterns of populations of DG neurons enabled us to successfully decode position, speed, and motion direction in an open field as well as current and future location in a T-maze. In αCaMKII heterozygous knockout mice, which have deficits in spatial learning and working memory, the decoding accuracy of position in the open field and future location in the T-maze were selectively reduced. These results suggest that multiple types of information are diffusely and independently distributed in DG neurons.