bioRxiv Science⌕ Search

Biology subjects

Nishijo, H.

Publications and source records attributed to Nishijo, H..

8 recordsLinked to original sources

A novel critic signal in identified midbrain dopaminergic neurons of mice training inoperant tasks

Classically, midbrain dopaminergic neuron activity is triggered by unexpected rewards, then, upon learning, by reward-predictive conditioned stimuli. When expected rewards are withheld, firing is inhibited. This activity occurs too late to directly affect the neuronal circuitry underlying decision-making, inspiring the development of temporal difference (TD) reinforcement learning models. To test for more timely critical feedback during decision-making and learning, we recorded optogenetically identified dopaminergic, putative GABAergic and other neurons of the ventral tegmental area (VTA) and substantia nigra pars compacta in mice training in visual and olfactory discrimination tasks. The mice often adhered to unrewarded and untrained task strategies (e.g., spatial alternation) rather than making random choices. In order to probe for reward/punishment predictive activity, a delay was imposed between nose-poke choices and signals for reward or punishment. As animals performed below criterion levels, dopaminergic and other neurons firing rates signaled correct versus incorrect choices immediately after choices, but prior to the onset of trial outcome signals. Thus, this activity signaled the rewarded rule even as the mice performed other unrewarded strategies. Putative GABAergic neurons fired during nose-poke choices, potentially reducing network activity prior to reward prediction signals. This reward predictive activity could serve as a critic signal expressed immediately after choices are made, priming the network for canonical DA reward/punishment activity, facilitating network functional modifications. This is consistent with a role for dopamine in arbitration between brain modules to choose among diverse strategies during goal-directed behavior. These findings suggest extensions of theoretical formulations interpreting dopaminergic neuronal activity. Significance statementModels of dopaminergic influence on circuit modifications during learning evoke mechanisms dealing with the delay between neural activity leading up to choices, and when the reinforcing outcome actually occurs. Here, as mice trained in sensory discrimination tasks with a delay between behavioral responses and reinforcement signals, they performed several unrewarded behavioral strategies. Simultaneously, dopaminergic nuclei neurons instead reflected the current task rule, predicting whether the choice was correct or not, providing an immediate "critic" signal prior to canonical trial outcome signals. This provides evidence for brain mechanisms to overcome innate or acquired habits to perform behaviors optimizing positive outcomes.

neuroscience↗

Establishing an AI-based evaluation system that quantifies social/pathophysiological behaviors of common marmosets

Nonhuman primates (NHPs) are indispensable animal models by virtue of the continuity of behavioral repertoires across primates, including humans. However, behavioral assessment at the laboratory level has so far been limited. By applying multiple deep neural networks trained with large-scale datasets, we established an evaluation system that could reconstruct and estimate three-dimensional (3D) poses of common marmosets, a small NHP that is suitable for analyzing complex natural behaviors in laboratory setups. We further developed downstream analytic methodologies to quantify a variety of behavioral parameters beyond simple motion kinematics, such as social interactions and the internal state behind actions, obtained solely from 3D pose data. Moreover, a fully unsupervised approach enabled us to detect progressively-appearing symptomatic behaviors over a year in a Parkinsons disease model. The high-throughput and versatile nature of our analytic pipeline will open a new avenue for neuroscience research dealing with big-data analyses of social/pathophysiological behaviors in NHPs.

neuroscience↗

Three-dimensional markerless motion capture of multiple freely behaving monkeys for automated characterization of social behavior

Given their high sociality and close evolutionary distance to humans, monkeys are an essential animal model for unraveling the biological mechanisms underlying human social behavior and elucidating the pathogenesis of diseases exhibiting abnormal social behavior. However, behavioral analysis of naturally behaving monkeys requires manual counting of various behaviors, which has been a bottleneck due to problems in throughput and objectivity. Here, we developed a three-dimensional markerless motion capture system that utilized multi-view data for robust tracking of individual monkeys and accurate reconstruction of the three-dimensional poses of multiple monkeys living in groups. Validation analysis in two monkey groups revealed that the system enabled the characterization of individual social dispositions and relationships through automated detection of various social events. Analyses of social looking facilitated the investigation of adaptive behaviors in a social group. These results suggest that this motion capture system will significantly enhance our ability to analyze primate social behavior.

animal behavior and cognition↗

Unsupervised decomposition and description of nonhuman primate behavior

Nonhuman primates (NHPs) exhibit complex and diverse behavior that typifies advanced cognitive function and social communication, but quantitative and systematical measure of this natural nonverbal processing has been a technical challenge. Specifically, a method is required to automatically segment time series of behavior into elemental motion motifs, much like finding meaningful words in character strings. Here, we propose a solution called SyntacticMotionParser (SMP), a general-purpose unsupervised behavior parsing algorithm using a non-parametric Bayesian model. Using three-dimensional posture-tracking data from NHPs, SMP automatically outputs an optimized sequence of latent motion motifs classified into the most likely number of states. When applied to behavioral datasets from common marmosets and rhesus monkeys, SMP outperformed conventional posture-clustering models and detected a set of behavioral ethograms from publicly available data. SMP also quantified and visualized the behavioral effects of chemogenetic neural manipulations. SMP thus has the potential to dramatically improve our understanding of natural NHP behavior in a variety of contexts.

neuroscience↗

Rhythmic oscillations in the midbrain dopaminergic nuclei in mice

Dopamine release in the forebrain by midbrain ventral tegmental nucleus (VTA) and substantia nigra pars compacta (SNpc) neurons is implicated in reward processing, goal-directed learning, and decision-making. Rhythmic oscillations of neural excitability underlie coordination of network processing, and have been reported in these dopaminergic nuclei at several frequency bands. This paper provides a comparative characterization of several frequencies of oscillations of local field potential and single unit activity, highlighting some behavioral correlates. We recorded from optogenetically identified dopaminergic sites in mice training in operant olfactory and visual discrimination tasks. Rayleigh and Pairwise Phase Consistency (PPC) analyses revealed some VTA/SNc neurons phase-locked to each frequency range, with fast spiking interneurons (FSIs) prevalent at 1-2.5 Hz (slow) and 4 Hz bands, and dopaminergic neurons predominant in the theta band. More FSIs than dopaminergic neurons were phase-locked in the slow and 4 Hz bands during many task events. The highest incidence of phase-locking in neurons was in the slow and 4 Hz bands, and occurred during the delay between the operant choice and trial outcome (reward or punishment) signals. These data provide a basis for further examination of rhythmic coordination of activity of dopaminergic nuclei with other brain structures, and its impact for adaptive behavior.

neuroscience↗

Acoustic camera system for measuring ultrasound communication in mice

To investigate molecular, genetic, and neural mechanisms underlying social behaviors and their deficits in neuropsychiatric disorders, social communication via ultrasonic vocalizations (USVs) in mice has received considerable attention as a powerful experimental model. The advances in sound localization technology have facilitated the analysis of vocal interactions between multiple mice. However, existing sound localization systems are built around distributed-microphone arrays, which require a special recording arena and long processing time. Here we report a novel acoustic camera system, USVCAM, which enables simpler and faster USV localization and assignment. The system comprises recently developed USV segmentation algorithms with a modification for overlapping vocalizations that results in high accuracy. Using USVCAM, we analyzed USV communications in a conventional home cage, and demonstrated novel vocal interactions in female ICR mice under a resident-intruder paradigm. The extended applicability and usability of USVCAM may facilitate future studies investigating normal and abnormal vocal communication and social behaviors, as well as the underlying physiological mechanisms.

neuroscience↗

Reward-associated configural cues elicit theta oscillations of rat retrosplenial neurons phase-locked to LFP theta cycle

Previous behavioral studies implicated the retrosplenial cortex (RSC) in stimulus-stimulus associations, and also in retrieval of remote associative memory based on EEG theta oscillations. To investigate the neural mechanisms underlying these processes, RSC neurons and local field potentials (LFPs) were simultaneously recorded from well-trained rats performing a cue-reward association task. In the task, simultaneous presentation of two multimodal conditioned stimuli (configural CSs) predicted a reward outcome opposite to that associated with individual presentation of each elemental CS. Here, we show neurophysiological evidence that the RSC is involved in stimulus-stimulus association where configural CSs are discriminated from each elementary CS that is a constituent of the configural CSs, and that memory retrieval of rewarding CSs is associated with theta oscillation of RSC neurons during CS presentation, which is phase-locked to LFP theta cycles.

neuroscience↗

MacaquePose: A novel 'in the wild' macaque monkey pose dataset for markerless motion capture

Video-based markerless motion capture permits quantification of an animals pose and motion, with a high spatiotemporal resolution in a naturalistic context, and is a powerful tool for analyzing the relationship between the animals behaviors and its brain functions. Macaque monkeys are excellent non-human primate models, especially for studying neuroscience. Due to the lack of a dataset allowing training of a deep neural network for the macaques markerless motion capture in the naturalistic context, it has been challenging to apply this technology for macaques-based studies. In this study, we created MacaquePose, a novel open dataset with manually labeled body part positions for macaques in naturalistic scenes, consisting of >13,000 images, refined by researchers. We show that the pose estimation performance of an artificial neural network trained with the dataset is close to that of a human-level. The MacaquePose will provide a platform for innovative behavior analysis for non-human primate.

neuroscience↗