Biology subjects

Nakai, J.

Publications and source records attributed to Nakai, J..

10 recordsLinked to original sources

bioRxiv2022

VR-based real-time imaging reveals abnormal cortical dynamics during behavioral transitions in a mouse model of autism

Functional connectivity (FC) can provide insight into cortical circuit dysfunction in neuropsychiatric disorders. However, dynamic changes in FC related to locomotion with sensory feedback remain unexplored. To investigate FC dynamics in locomoting mice, we developed mesoscopic Ca2+ imaging with a virtual reality (VR) environment. We find rapid reorganization of cortical FC in response to changing behavioral states. Using machine learning classification, behavioral states are accurately decoded. We then use our VR-based imaging system to study cortical FC in a mouse model of autism and find that locomotion states are associated with altered FC dynamics. Furthermore, we identify FC patterns involving the motor area as the most distinguishing features of the autism mice from wild-type mice during behavioral transitions, which might correlate with motor clumsiness in patients with autism. Our VR-based real-time imaging system provides invaluable information to understand FC dynamics linked to a behavioral abnormality of neuropsychiatric disorders.

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↗

bioRxiv2021

Shared and unique properties of place cells in anterior cingulate cortex and hippocampus

Hippocampal sharp-wave ripples (SWRs) and the associated replay of neuronal sequences are well-established as the primary physiological substrates for memory consolidation. While the local transformations they induce within the hippocampus are well-characterized, their impact on the downstream cortical representations remains unknown. Here, we identify a distinct functional class of neurons in the anterior cingulate cortex "spatial context cells" that emerge through the multi-day integration of discrete hippocampal inputs. Using closed-loop disruption of SWRs and longitudinal calcium imaging, we demonstrate that formation of this global spatial framework depends on SWRs during offline periods. Whereas standard cortical place maps remain intact following SWR disruption, the emergence of spatial context cells is selectively abolished. These cells preferentially express c-Fos, identifying them as constituents of the cortical memory engram, and exhibit broad receptive fields that develop through an experience-dependent process of field convergence. Collectively, these findings establish SWR-mediated replay as a computational bridge transforming high-resolution, fragmented hippocampal spatial codes into generalized, stable cortical schemas. This work reveals a bifurcated consolidation process, identifying SWR-dependent synaptic remodeling as a fundamental mechanism for the ontogeny of remote memory.

neuroscience↗

bioRxiv2020

Fast scanning high optical invariant two-photon microscopy for monitoring a large neural network activity with cellular resolution

Fast and wide imaging with single-cell resolution, high signal-to-noise ratio and no optical aberration has the potential to open up new avenues of investigation in biology. However, this imaging is challenging because of the inevitable tradeoffs among those parameters. Here, we overcome the tradeoffs by combining a resonant scanning system, a large objective with low magnification and high numerical aperture, and highly sensitive large-aperture photodetectors. The result is a practically aberration-free, fast scanning high optical invariant two-photon microscopy (FASHIO-2PM) that enables calcium imaging from a large network composed of [~]16k neurons at 7.5 Hz in a 9 mm2 contiguous image plane including more than 10 sensory-motor and higher-order regions of the cerebral cortex in awake mice. Through a network analysis based on single-cell activities, we discover that the brain exhibits small-world-ness rather than scale-freeness. FASHIO-2PM will enable revealing biological dynamics by simultaneous monitoring of macroscopic activity and its composing elements.

neuroscience↗

bioRxiv2020

Cellular identity and Ca2+ signaling activity of the non-reproductive GnRH system in the Ciona larva

Tunicate larvae have a non-reproductive gonadotropin-releasing hormone (GnRH) system with multiple ligands and receptor heterodimerization enabling complex regulation. In the Ciona larva, one of the gnrh genes, gnrh2, is conspicuously expressed in the motor ganglion and nerve cord, which are homologous structures to the hindbrain and spinal cord, respectively, of vertebrates. The gnrh2 gene is also expressed in the proto-placodal sensory neurons, which are the proposed homologue of vertebrate olfactory neurons. The tunicate larvae occupy a non-reproductive dispersal stage, yet the role of their GnRH system remains elusive. In this study, we investigated neuronal types of gnrh2-expressing cells in Ciona larvae and visualized the activity of these cells by fluorescence imaging using a calcium sensor protein. Some cholinergic neurons and dopaminergic cells express gnrh2, suggesting that GnRH plays a role in controlling swimming behavior. However, none of the gnrh2-expressing cells overlap with glycinergic or GABAergic neurons. A role in motor control is also suggested by the correlation between the activity of some gnrh2-expressing cells and tail movements. Interestingly, gnrh2-positive ependymal cells in the nerve cord, known as a kind of glia cells, actively produced Ca2+ transients, suggesting that neuroendocrine signaling occurs in the glia cells of the nerve cord.

neuroscience↗

bioRxiv2019

Encoding of social exploration by neural ensembles in the insular cortex

The insular cortex participates in diverse complex brain functions including sociality, yet little is known about their cellular bases. Using microendoscopic calcium imaging of the agranular insular cortex (AI) in mice interacting with freely-moving and restrained social targets, we identified two subsets of AI neurons -a larger fraction of Social-ON cells and a smaller fraction of Social-OFF cells- that change their activity in opposite directions during social exploration. Social-ON cells included those that represented social investigation independent of location and consisted of multiple subsets, each of which were preferentially active during exploration under particular behavioral state or with a particular target of physical contact. These results uncover a previously unknown function of AI neurons in encoding conjunctive information on social behavior and suggest that AI may act to monitor the ongoing status of social exploration while an animal interacts with unfamiliar conspecifics.

neuroscience↗

bioRxiv2019

AI on animals: AI-assisted animal-borne logger never misses the moments that biologists want

Animal-borne data loggers, i.e., biologgers, allow researchers to record a variety of sensor data from animals in their natural environments (Hussey et al. 2015; Kays et al. 2015). This data allows biologists to observe many aspects of the animals lives, including their behavior, physiology, social interactions, and external environment. However, the need to limit the size of these devices to a small fraction of the animals size imposes strict limits on the devices hardware and battery capacities (Kays et al. 2015). Here we show how AI can be leveraged on board these devices to intelligently control their activation of costly sensors, e.g., video cameras, allowing them to make the most of their limited resources during long deployment periods. Our method goes beyond previous works that have proposed controlling such costly sensors using simple threshold-based triggers, e.g., depth-based (Watanuki et al. 2007; Volpov et al. 2015) and acceleration-based (Nishiumi et al. 2018; Brown et al. 2012) triggers. Using AI-assisted biologgers, biologists can focus their data collection on specific complex target behaviors such as foraging activities, allowing them to automatically record video that captures only the moments they want to see. By doing so, the biologger can reserve its battery power for recording only those target activities. We anticipate our work will provide motivation for more widespread adoption of AI techniques on biologgers, both for intelligent sensor control and intelligent onboard data processing. Such techniques can not only be used to control what is collected by such devices, but also what is transmitted off the devices, such as is done by satellite relay tags (Cox et al. 2018).

ecology↗

bioRxiv2018

Wide and Deep Imaging of Neuronal Activities by a Wearable NeuroImager Reveals Premotor Activity in the Whole Motor Cortex

Wearable technologies for functional whole brain imaging in freely moving animals would advance our understanding of cognitive processing and adaptive behavior. Fluorescence imaging can visualize the activity of individual neurons in real time, but conventional microscopes have limited sample coverage in both the width and depth of view. Here we developed a novel head-mounted laser camera (HLC) with macro and deep-focus lenses that enable fluorescence imaging at cellular resolution for comprehensive imaging in mice expressing a layer- and cell type-specific calcium probe. We visualized orientation selectivity in individual excitatory neurons across the whole visual cortex of one hemisphere, and cell assembly expressing the premotor activity that precedes voluntary movement across the motor cortex of both hemispheres. Including options for multiplex and wireless interfaces, our wearable, wide- and deep-imaging HLC technology could enable simple and economical mapping of neuronal populations underlying cognition and behavior.

neuroscience↗

bioRxiv2018

Dynamic embedding of salience coding in hippocampal spatial maps

Hippocampal CA1 neurons participate in dynamic ensemble codes for space and memory. Prominent features of the environment are represented by an increased density of place cells, but cellular principles governing the formation and plasticity of such disproportionate maps are unknown. We thus imaged experience-dependent long-term changes in spatial representations at the cellular level in the CA1 deep sublayer in mice learning to navigate in a virtual-reality environment. The maps were highly dynamic but gradually stabilized as over-representations for motivational (reward) and environmental (landmark) salience emerged in different time courses by selective consolidation of relevant spatial representations. Relocation of the reward extensively reorganized pre-formed maps by a mechanism involving rapid recruitment of cells from the previous location followed by their re-stabilization, indicating that a subset of neurons encode reward-related information. The distinct properties of these CA1 cells may provide a substrate by which salient experience forms lasting and adaptable memory traces.

neuroscience↗

bioRxiv2017

Two-photon calcium imaging of medial prefrontal cortex and hippocampus without cortical invasion

In vivo two-photon calcium imaging currently allows us to observe the activity of multiple neurons up to [~]900 m below the cortical surface without cortical invasion. However, many other important brain areas are located deeper than this. Here, we used a 1100 nm laser, which underfilled the back aperture of the objective, and red genetically encoded calcium indicators to establish two-photon calcium imaging of the intact mouse brain and detect neural activity up to 1200 m from the cortical surface. This imaging was obtained from the medial prefrontal cortex (the prelimbic area) and the hippocampal CA1 region. We found that the neural activity related to reward prediction is higher in the prelimbic area than in layer 2/3 of the secondary motor area, while it is negligible in the hippocampal CA1 region. Reducing the invasiveness of imaging is an important strategy to reveal the brain processes active in cognition and memory.

neuroscience↗