Biology subjects

Okubo-Suzuki, R.

Publications and source records attributed to Okubo-Suzuki, R..

6 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2022

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↗

bioRxiv2022

The hippocampus as a sorter and reverberatory integrator of sensory inputs

In entorhinal-hippocampal networks, the trisynaptic pathway, including the CA3 recurrent circuit, processes episodes of context and space1-3. Recurrent connectivity can generate reverberatory activity4-6, an intrinsic activity pattern of neurons that occurs after sensory inputs have ceased. However, the role of reverberatory activity in memory encoding remains incompletely understood. Here we demonstrate that in mice, synchrony between conditioned stimulus (CS) and unconditioned stimulus (US)-responsible cells occurs during the reverberatory phase, lasting for approximately 15 s, but not during CS and US inputs, in the CA1 and the reverberation is crucial for the linking of CS and US in the encoding of delay-type cued-fear memory. Retrieval-responsive cells developed primarily during the reverberatory phase. Mutant mice lacking N-methyl-D-aspartate receptors (NRs) in CA3 showed a cued-fear memory impairment and a decrease in synchronized reverberatory activities between CS- and US-responsive CA1 cells. Optogenetic CA3 silencing at the reverberatory phase during learning impaired cued-fear memory. Our findings suggest that reverberation recruits future retrieval-responsive cells via synchrony between CS- and US-responsive cells. The hippocampus uses reverberatory activity to link CS and US inputs, and avoid crosstalk during sensory inputs.

neuroscience↗

bioRxiv2021

Inspiring cognitive inference in a cortical network during REM sleep

Idling brain activity has been proposed to facilitate inference, insight, and innovative problem-solving1-4. However, it remains unclear how and when the subconscious brain can create novel ideas. Here, we show coordinated roles of non-rapid eye movement (NREM) and rapid-eye movement (REM) sleep in weaving inferential information from learned information. In a transitive inference paradigm, mice gained the inference one day, but not shortly, after complete training. Inhibiting the neuronal computations in the anterior cingulate cortex (ACC) during post-learning either NREM or REM sleep, but not wakefulness, disrupted the inference without affecting the learned knowledge. In vivo Ca2+ imaging showed gradual development of inference-related representation, peaking at post-training REM sleep. Neurons representing learned information co-reactivated significantly during post-training NREM sleep, while their co-reactivation with neurons representing inferential information was significantly higher during REM sleep. Furthermore, after insufficient learning, artificial activation of medial entorhinal cortex-ACC dialogue during only REM sleep created inferential knowledge. These findings suggest that NREM sleep organizes the scattered learned knowledge in a complete hierarchy, while REM sleep computes the inferential information from the organized hierarchy. Collectively, our study provides a mechanistic insight on NREM and REM coordination in weaving inferential knowledge, thus highlighting the power of idling brain in cognitive flexibility.

neuroscience↗

bioRxiv2021

Offline knowledge assimilations ensue online obscurity to inspire implicit learning

Passive priming of prior knowledge to assimilate ongoing experiences underlies advanced cognitive processing. However, the necessary neural dynamics of memory assimilation remains elusive. Uninstructed brain could also show boosted creativity, particularly after idling states, yet it remains unclear whether the idling brain can spontaneously spark relevant knowledge assimilations. We established a paradigm that links/separates context-dependent memories according to geometrical similarities. Mice exploring one of four contexts one day before undergoing contextual fear conditioning in a square context showed a gradual fear transfer to pre-exposed geometrically relevant contexts next day, but not after 15 min. Anterior cingulate cortex neurons representing relevant, rather than distinct, memories were significantly co-reactivated during post-conditioning sleep only, before their selective integration next day during testing. Disrupting sleep co-reactivations prevented assimilation while preserving recent memory consolidation. Thus, assimilating pertinent memories during sleep through co-reactivation of their respective engrams represents the neural underpinnings of sleep-triggered implicit cortical learning.

neuroscience↗

bioRxiv2017

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↗