Mechanical problem solving in mice

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июль 30, 2024

Abstract Recent advances in automated tracking tools have sparked a growing interest studying naturalistic behavior. Yet, traditional decision-making tasks remain the norm for assessing learning behavior neuroscience. We introduce an alternative sequential task mouse It consists of open-source, 3D-printed “lockbox”, mechanical riddle that requires four different mechanisms to be solved sequence obtain reward. During task, mice move around freely, allowing expression complex behavioral patterns. observed willingly engage and learn solve it only few trials. To analyze how we recorded their multi-camera setup developed custom data analysis pipeline automatically detect interactions with lockbox large corpus video footage ( > 300h, 12 mice). The allows us further delineate why performance increases over Our analyses suggest this is not due increased interaction time or acquisition smart solution strategy, but primarily habituation lockbox. Lockboxes may hence promising approach study both abstract decision making low-level motor single can rapidly learned by mice.

Язык: Английский

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The Neurobiology of Parenting and Infant-Evoked Aggression

Physiological Reviews, Год журнала: 2024, Номер 105(1), С. 315 - 381

Опубликована: Авг. 15, 2024

Parenting behavior comprises a variety of adult-infant and adult-adult interactions across multiple timescales. The state transition from nonparent to parent requires an extensive reorganization individual priorities physiology is facilitated by combinatorial hormone action on specific cell types that are integrated throughout interconnected brainwide neuronal circuits. In this review, we take comprehensive approach integrate historical current literature each these topics species, with focus rodents. New emerging molecular, circuit-based, computational technologies have recently been used address outstanding gaps in our framework knowledge infant-directed behavior. This work raising fundamental questions about the interplay between instinctive learned components parenting mutual regulation affiliative versus agonistic behaviors health disease. Whenever possible, point how helped gain novel insights opened new avenues research into neurobiology parenting. We hope review will serve as introduction for those field, resource already studying parenting, guidepost designing future studies.

Язык: Английский

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Unsupervised decomposition of natural monkey behavior into a sequence of motion motifs

Communications Biology, Год журнала: 2024, Номер 7(1)

Опубликована: Сен. 3, 2024

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

Язык: Английский

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Beyond the lab: feasibility of cognitive neuroscience data collection during a speleological expedition

Journal of Environmental Psychology, Год журнала: 2024, Номер unknown, С. 102443 - 102443

Опубликована: Окт. 1, 2024

Язык: Английский

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Linking Brain and Behavior States in Zebrafish Larvae Locomotion using Hidden Markov Models

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 22, 2024

Understanding how collective neuronal activity in the brain orchestrates behavior is a central question integrative neuroscience. Addressing this requires models that can offer unified interpretation of multimodal data. In study, we jointly examine video-recordings zebrafish larvae freely exploring their environment and calcium imaging Anterior Rhombencephalic Turning Region (ARTR) circuit, which known to control swimming orientation, recorded vivo under tethered conditions. We show both behavioral neural data be accurately modeled using Hidden Markov Model (HMM) with three hidden states. context behavior, states correspond leftward, rightward, forward swimming. The HMM robustly captures key statistical features motion, including bout-type persistence its dependence on bath temperature, while also revealing inter-individual phenotypic variability. For data, left- right-lateral activation ARTR govern selection left vs. right reorientation, balanced state, likely corresponds state. To further unify two analysis, exploit generative nature HMM, sequences generate synthetic trajectories whose properties are similar Overall, work demonstrates state-space used link providing insights into mechanisms self-generated action.

Язык: Английский

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