Coupling of in vitro Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks - Chang, ChihHsiang; Furukawa, Takuma; Asahina, Takahiro; Shimba, Kenta; Kotani, Kiyoshi; Jimbo, Yasuhiko (Frontiers in Neuroscience, 2022)
Different brain states are important for long-term memory formation. Each brain state can be referred to as a specific process in memory formation, i.e., encoding during wakefulness or consolidation during sleeping. The hippocampal-neocortical dialogue was proposed as a hypothetical framework for systems consolidation, with variant cross-frequency coupling between the hippocampus and distributed neocortical regions under different brain states. Despite evidence supporting the above hypothesis, little has been reported about how information was processed as it shifts between brain states. To address this, we developed an in vitro neocortical-hippocampal coculture model to study how activity coupling can affect connections between coupled networks. Neocortical and hippocampal neurons were cultured in two different cell chamber compartments and connected by a micro-tunnel structure. The network activity of the coculture model was recorded by underlaid micro-electrode arrays. Two types of burst activity coupling patterns, a slow burst coupling (neocortex: 0.1~0.5 Hz, hippocampus: 1 Hz) and a fast burst coupling (neocortex: 20~40 Hz, hippocampus: 4~10 Hz), were observed between heterogeneous networks in spontaneous activity and electrical stimulation evoked response. In slow burst coupling, network activity showed higher synchronicity as analyzed by the burstiness index. Network synchronicity analysis implicates different information processing states under different burst activity coupling patterns. Our results suggest the possibility of the hippocampal-neocortical coculture model possessing multi-states of burst activity coupling between heterogeneous networks. Through the application of external stimulation, the developed neocortical-hippocampal network can provide insights to elucidate the influence of state shifting on information processing.