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Biology subjects

Asai, H.

Publications and source records attributed to Asai, H..

5 recordsLinked to original sources

Sleep neural code perpetuates the evolving negativity bias under stress

Negativity bias is the distorted cognitive processing of how self-experiences are negatively perceived through rumination and overgeneralization. Despite proposed theories of higher-order emotional representation and the involvement of default mode networks, the biological mechanisms underlying how negative emotional bias is persistently generated remain unknown. Here, we show that under negative emotional state, sleep orchestrates neural dynamics to shape persistent negativity bias. A negative emotional state, induced by repeated social defeat stress (SoD), generates negativity bias in both memory-recall and novel experiences such as fear conditioning. Longitudinal Ca2+ imaging of the hippocampus across days revealed that in emotional states, negative schema-like representations that encode the semantic aspect of negativity across experiences are generated. These negative schema-like representations are continuously processed along with dynamic co-reactivations of distinct emotional experiences during sleep. Closed-loop optogenetic silencing of stress experience-tagged cellular ensembles during sleep, but not during awake, prevents negativity bias in future memory-recall and novel experiences. Finally, sleep-active, but not sleep-nonactive, SoD cells predict and decode emotional behaviours during learned and novel situations. Together, these results reveal the biological emergence of semantic-like representations of emotional experiences and sleep causally coordinate neuronal dynamics to persistently shape negativity in future conscious states. These findings offer a new perspective on how higher-order emotional processing during sleep may determine our emotional interpretation of past and future experiences.

neuroscience↗

Dual roles of idling moments in past and future memories

Every day, we experience new daily episodes and store new memories. Although memories are stored in corresponding engram cells, how different sets of engram cells are selected for current and next episodes, and how they create their memories, remains unclear. We report that in mice, hippocampal CA1 neurons show an organized synchronous activity in prelearning home cage sleep that correlates with the learning ensembles only in engram cells, termed preconfigured ensembles. Moreover, after learning, a subset of nonengram cells develops population activity, which is constructed during postlearning offline periods through synaptic depression and scaling, and then emerges to represent engram cells for new learning. Together, our findings indicate that during offline periods there are two parallel processes occurring: conserving of past memories through reactivation, and preparation for upcoming ones through offline synaptic plasticity mechanisms.

neuroscience↗

Dentate neurogenesis mediates cognitive flexibility via modulation of the hippocampal longitudinal-axis network

Adult neurogenesis endows the hippocampus with unparalleled neural plasticity, essential for intricate cognitive functions. However, the manner in which sparse newborn neurons (NBNs) modulate neural activities and subsequently shape behavior remains enigmatic. Utilizing a newly engineered NBN-Tetanus Toxin mouse model, we non-invasively silenced NBNs and confirmed their crucial role in cognitive flexibility, as demonstrated through reversal learning in the Morris water maze and the Go/Nogo task in operant learning. Pairing task-based functional MRI (tb-fMRI) with operant learning revealed a dorsal hippocampal hyperactivation during Nogo task, implying that hippocampal hyperexcitability might underlie the observed behavioral deficits. Notably, resting-state fMRI (rs-fMRI) revealed enhanced functional connectivity between the dorsal and ventral dentate gyrus following NBN silencing. Further exploration of PV+ interneurons and mossy cells activities highlighted NBNs integral part in preserving the excitation/inhibition balance within the hippocampus. Our findings emphasize how the neural plasticity driven by NBNs extensively modulates the hippocampus, sculpting cognitive flexibility.

neuroscience↗

HOTARU: Automatic sorting system for large scale calcium imaging data

Currently, calcium imaging allows long-term recording of large-scale neuronal activity in diverse states. However, it remains difficult to extract neuronal dynamics from recorded imaging data. In this study, we propose an improved constrained nonnegative matrix factorization (CNMF)-based algorithm and an effective method to extract cell shapes with fewer false positives and false negatives through image processing. We also show that the evaluation metrics obtained during image and signal processing can be combined and used for false-positive cell determination. For the CNMF algorithm, we combined cell-by-cell regularization and baseline shrinkage estimation, which greatly improved its stability and robustness. We applied these methods to real data and confirmed their effectiveness. Our method is simpler and faster, detects more cells with lower firing rates and signal-to-noise ratios, and enhances the quality of the extracted cell signals. These advances can improve the standard of downstream analysis and contribute to progress in neuroscience.

neuroscience↗

Automatic sorting system for large calcium imaging data

It has become possible to observe neural activity in freely moving animals via calcium imaging using a microscope, which could not be observed previously. However, it remains difficult to extract the dynamics of nerve cells from the recorded imaging data. In this study, we greatly improved the stability, and robustness of the cell activity estimation method via non-negative matrix decomposition with shrinkage estimation of the baseline. In addition, by improving the initial state of the iterative algorithm using a newly proposed method to extract the shape of the cell via image processing, a solution could be obtained with a small number of iterations. These methods were applied to artificial and real data, and their effectiveness was confirmed.

neuroscience↗