Biology subjects

Tanaka, Y. R.

Publications and source records attributed to Tanaka, Y. R..

3 recordsLinked to original sources

bioRxiv2025

Paw switching with lateralized cholinergic modulation

Motor preferences, such as handedness, reflect fundamental asymmetries in brain function and behavior across vertebrate species, including humans and rodents1. Although individual hand or paw preferences are typically stable, they can be reshaped through experience or training, underscoring the plasticity of lateralized motor circuits2. However, the neural mechanisms that enable this behavioral switching remain unclear. Here we show that experience-driven shifts in paw preference in mice arise from asymmetric cholinergic modulation between the two hemispheres. Using a behavioral paradigm designed to induce paw switching, we found that a subset of animals developed a stable change in preference following training. Selective activation or inhibition of cholinergic neurons on one side of the brain was sufficient to bias this switching behavior. During lateralized movements, an endogenous imbalance in cholinergic activity emerges between the hemispheres, suggesting that interhemispheric cholinergic asymmetry enables motor flexibility. These findings identify a previously unrecognized mechanism by which cholinergic signaling dynamically regulates lateralized motor control, providing insight into how hemispheric imbalances may shape persistent individual motor preferences.

neuroscience↗

bioRxiv2025

A multimodal dataset linking wide-field calcium imaging to behavior changes in mice during an operant lever-pull task

The BraiDyn-BC (Brain Dynamics underlying emergence of Behavioral Change) Database offers an extensive, multimodal dataset that links wide-field calcium imaging of the mouse neocortex to comprehensive behavioral measurements during a behavioral task. As one of the contents in this database, we newly provide a dataset that includes 15 sessions spanning two weeks of motor skill learning, in which 25 mice were trained to pull a lever to obtain water rewards. Simultaneous high-speed videography captures body, facial, and eye movements, and environmental parameters are monitored. The dataset also features resting-state cortical activity and sensory-evoked responses, enhancing its utility for both learning-related and sensory-driven neural dynamics studies. Data are formatted in accordance with the Neurodata Without Borders (NWB) standard, ensuring compatibility with existing analysis tools and adherence to the FAIR principles. This resource enables in-depth investigations into the neural mechanisms underlying behavior and learning. The platform encourages collaborative research, supporting the exploration of rapid within-session learning effects, long-term behavioral adaptations, and neural circuit dynamics.

neuroscience↗

bioRxiv2021

Optical and computational dissection of emergent prefrontal rewiring to encode fear memory

Associative learning is crucial for adapting to environmental changes. The encoding of associative learning involves the dorso-medial prefrontal cortex (dmPFC), and is underpinned by interactions within the resident neuronal population. However, the nature of this population coding is poorly understood. Here we developed a pipeline for computational dissection and longitudinal two-photon imaging of neural population activities in the mouse dmPFC during fear-conditioning procedures, enabling us to detect learning-dependent changes in the dmPFC topology. Through regularized regression methods and graphical modeling, we found fear conditioning organized neuronal ensembles encoding conditioned responses (CR), with enhancing their coactivity, functional connectivity, and association with conditioned stimuli (CS). This suggests that fear conditioning drives dmPFC reorganization to generate novel associative circuits for CS-to-CR transformation. Importantly, neurons strongly responding to unconditioned stimuli (US) during conditioning anterogradely became a hub of the CR ensemble. Altogether, we demonstrate learning-dependent dynamic modulation of population coding structured on an activity-dependent hub-network formation within the dmPFC. TeaserOptical and computational dissection uncovered how prefrontal cortical networks are rewired to encode new associative memory Significance statementAnimals learn to adapt to changing environments. Associative learning is one of the simplest types of learning that has been intensively studied over the past century. Recent development in molecular, genetic, and optogenetic methods has enabled the identification of a neural population encoding the associative memory in the brain. However, it remains unclear how information is stored and processed by the neural population to encode and retrieve the associative memory. To investigate the nature of this population coding, we developed an optical and computational dissection method, demonstrating how associative learning drives reorganization of the neural network in the dorso-medial prefrontal cortex and generates novel circuits for associative memory and signal transformation.

neuroscience↗