Hippocampal neuronal activity is aligned with action plans.

Neurons in the hippocampus are correlated with different variables, including space, time, sensory cues, rewards and actions, in which the extent of tuning depends on ongoing task demands. However, it remains uncertain whether such diverse tuning corresponds to distinct functions within the hippocampal network or whether a more generic computation can account for these observations. Here, to disentangle the contribution of externally driven cues versus internal computation, we developed a task in mice in which space, auditory tones, rewards and context were juxtaposed with changing relevance.

Hippocampal neuronal activity is aligned with action plans.

Neurons in the hippocampus are correlated with different variables, including space, time, sensory cues, rewards, and actions, where the extent of tuning depends on ongoing task demands. However, it remains uncertain whether such diverse tuning corresponds to distinct functions within the hippocampal network or if a more generic computation can account for these observations. To disentangle the contribution of externally driven cues versus internal computation, we developed a task in mice where space, auditory tones, rewards, and context were juxtaposed with changing relevance.

Perpetual step-like restructuring of hippocampal circuit dynamics.

Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single-cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we find that CA1 population vectors decorrelate gradually within a session.

Perpetual step-like restructuring of hippocampal circuit dynamics.

Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we found that CA1 population vectors decorrelated gradually within a session.

Formation and Applications in Electronic Devices of Lattice-Aligned Gallium Oxynitride Nanolayer on Gallium Nitride.

Gallium nitride (GaN), a promising alternative semiconductor to Si, is widely used in photoelectronic and electronic technologies. However, the vulnerability of the GaN surface is a critical restriction that hinders the development of GaN-based devices, especially in terms of device stability and reliability. In this study, this challenge is overcome by converting the GaN surface into a gallium oxynitride (GaON) epitaxial nanolayer through an in situ two-step "oxidation-reconfiguration" process.

Strain Release in GaN Epitaxy on 4° Off-Axis 4H-SiC.

A hybrid field-effect transistor (HyFET), superior for power electronic applications, can be created by harnessing the merits of two representative wide-bandgap semiconductors, gallium nitride (GaN) and silicon carbide (SiC). Yet, the incompactness in the epitaxy techniques hinders the development of the HyFET-GaN is usually grown on on-axis foreign substrates including SiC, whereas SiC homoepitaxy prefers off-axis substrates. This work presents a GaN-based heterostructure epitaxially grown on a conventional 4° off-axis 4H-SiC substrate, which manifests its high quality and suitability for constructing GaN-based high-electron-mobility transistors, thereby suggesting a practical approach to realizing HyFETs.