村野 友幸

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 Ca2+ imaging in freely moving mice and analyzed this activity using machine learning. 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, and each individual neuron was diversely and independently tuned to these multiple information types. Our data also showed that each type of information is unevenly distributed in groups of DG neurons, and different types of information are independently encoded in overlapping, but different, populations of neurons. In alpha-calcium/calmodulin-dependent kinase II (αCaMKII) heterozygous knockout mice, which present deficits in spatial remote 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 independently distributed in DG neurons.

Abstract 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 Ca²⁺imaging in freely moving mice and analysed this activity using machine learning. 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, and each individual neuron was diversely and independently tuned to these multiple information types. In αCaMKII heterozygous knockout mice, which present deficits in spatial remote 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 independently distributed in DG neurons.

Abstract Biomarkers are needed to improve the diagnosis of neuropsychiatric disorders, which are often associated to excitatory/inhibitory imbalances in neural transmission and abnormal maturation. Here, we characterized different disease conditions by mapping changes in the expression patterns of maturation-related genes whose expression was altered by experimental neural hyperexcitation in published studies. This analysis revealed two gene expression patterns: decreases in maturity markers and increases in immaturity markers. These two groups of genes were characterized by the over-representation of genes related to synaptic function and chromosomal modification, respectively. Using these two groups in a transdiagnostic analysis of 87 disease datasets for eight neuropsychiatric disorders and 12 datasets from corresponding animal models, we found that transcriptomic pseudoimmaturity inducible by neural hyperexcitation is shared by multiple neuropsychiatric disorders, such as schizophrenia, Alzheimer disorders, and amyotrophic lateral sclerosis. Our results indicate that this endophenotype serves as a basis for the transdiagnostic characterization of these disorders.