Masashi Kondo

In the diagnosis of lung cancer, imaging findings of lung nodules are essential for benign and malignant classifications. Although numerous studies have investigated the classification of lung nodules, no method has been proposed for obtaining detailed imaging findings. This study aimed to develop a novel method for generating image findings and classifying benign and malignant nodules in chest computed tomography (CT) images using vision–language models. In this study, we collected chest CT images of 77 patients diagnosed with either benign or malignant tumors at Fujita Health University Hospital. For these images, we cropped the regions of interest around the nodules, and a pulmonologist provided the corresponding image findings. We used vision–language models for image captioning to generate image findings. The findings generated by these two models were grammatically correct, with no deviations in notation, as expected from the image findings. Moreover, the descriptions of benign and malignant characteristics were accurately obtained. The bootstrapping language–image pretraining (BLIP) base model achieved an accuracy of 79.2% in classifying nodules, and the bilingual evaluation understudy-4 score for agreement with physician findings was 0.561. These results suggest that the proposed method may be effective for classifying and generating lung nodule findings.

Models of cognition often treat fast electrical dynamics as separate from slower associative plasticity. We asked whether rapid synaptic structural plasticity is required for coordinated cortical processing during wakefulness. We developed SynC, a chemogenetic perturbation that, upon A/C administration, reversibly blocks associative dendritic spine enlargement and impairs motor learning without detectably altering baseline synaptic/neuronal physiology. SynC activation in frontoparietal cortex reduced laser-dot chasing and delayed feeding initiation, and reduced wake-state stability. Population recordings revealed a locomotor-active but impaired regime with preserved mean activity and γ power but reduced pairwise correlations during quiet, immobile epochs, with increased network dimensionality (Interm-C), intermittently interrupted by an arrest state (State-C) with suppressed γ power. Thus, intact Rac1-dependent spine-enlargement mechanisms are acutely required to maintain the functional coupling necessary for coordinated cortical processing during wakefulness. One sentence summary: Acute, reversible in vivo blockade of associative spine enlargement shows that rapid structural plasticity is required to sustain cortical processing in EEG/EMG-defined waking.

The link between comprehensive behavioral measurements during a behavioral task and brain-wide neuronal activity is an essential strategy to better understand the brain dynamics underlying the emergence of behavior changes. To tackle this, we provide an extensive, multimodal dataset that includes 15 sessions spanning 2 weeks of motor skill learning, in which 25 mice were trained to pull a lever to obtain water rewards. Simultaneous high-speed videography captured body, facial, and eye movements, and environmental parameters were 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 (Findable, Accessible, Interoperable, Reusable). 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.

“To act or not to act” is a fundamental decision made in daily life. However, it is unknown how the relevant signals are transmitted to the secondary motor cortex (M2), which is the cortical origin of motor initiation. Here, we found that in a decision-making task in male mice, inputs from the thalamus to M2 positively regulated the action while inputs from the lateral part of the orbitofrontal cortex (LO) negatively regulated it. The motor thalamus that received the basal ganglia outputs transmitted action value-related signals to M2 regardless of whether the animal acted or not. By contrast, a large subpopulation of LO inputs showed decreased activity before and during the action, regardless of the action value. These results suggest that M2 integrates the positive signal of the action value from the motor thalamus with the negative action-biased signal from the LO to finally determine whether to act or not.

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 an operant conditioning task. This dataset 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.

Neural activity across the dorsal neocortex of rodents is dominated by orofacial and limb movements, irrespective of whether the movements are task-relevant or task-irrelevant. To examine the extent to which movements and a primitive cognitive signal, i.e., reward expectancy, modulate the activity of multiple cortical areas in primates, we conducted unprecedented wide-field one-photon calcium imaging of frontoparietal and auditory cortices in common marmosets while they performed a classical conditioning task with two auditory cues associated with different reward probabilities. Licking, eye movement, and hand movement strongly modulated the neuronal activity after cue presentation in the motor and somatosensory cortices in accordance with the somatotopy. By contrast, the posterior parietal cortex and primary auditory cortex did not show much influence from licking. Licking increased the activity in the caudal part of the dorsal premotor cortex, but decreased the activity in the central and lateral parts of the rostral part of the dorsal premotor cortex (PMdr). Reward expectancy that was separable from both spontaneous and goal-directed movements was mainly represented in the medial part of PMdr. Our results suggest that the influence of movement on primate cortical activity varies across areas and movement types, and that the premotor cortex processes motor and cognitive information in different ways within further subdivided areas.

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). To reveal PM- and M1-specific reorganization in a primate, we conducted calcium imaging in common marmosets while they learned a two-target reaching (pull/push) task after mastering a one-target reaching (pull) task. Throughout learning of the two-target reaching task, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. During learning, the reaction time in pull trials increased and correlated strongly with the peak timing of PMdr activity. PMdr showed decreasing representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation of pull and push movements. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction depending on their performance in push trials in the early learning stage, whereas M1 neurons stably retained their preferred direction and high similarity of preferred direction between neighbors. These results suggest that in primate sensorimotor learning, dynamic directional motor tuning in PMdc converts the sensorimotor association formed in PMdr to the stable and specific motor representation of M1.

Reward-seeking behavior is frequently associated with risk of punishment. There are two types of punishment: positive, resulting in an unpleasant outcome, and negative, resulting in omission of a reinforcing outcome. Although the medial prefrontal cortex (mPFC) is important in avoiding punishment, whether it is important for avoiding both positive and negative punishment and how it contributes to such avoidance are not clear. In this study, we trained male mice to perform decision-making tasks under the risks of positive (air-puff stimulus) and negative (reward omission) punishment. We found that pharmacological inactivation of mPFC enhanced the reward-seeking choice under the risk of positive, but not negative, punishment. In reinforcement learning models, this behavioral change was well-explained by hypersensitivity to the reward, rather than a decrease in the strength of aversion to punishment. Our results suggest that mPFC suppresses reward-seeking behavior by reducing sensitivity to reward under the risk of positive punishment.