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Contemporary pose estimation methods enable precise measurements of behavior via supervised deep learning with hand-labeled video frames. Although effective in many cases, the supervised approach requires extensive labeling and often produces outputs that are unreliable for downstream analyses. Here, we introduce 'Lightning Pose', an efficient pose estimation package with three algorithmic contributions. First, in addition to training on a few labeled video frames, we use many unlabeled videos and penalize the network whenever its predictions violate motion continuity, multiple-view geometry and posture plausibility (semi-supervised learning). Second, we introduce a network architecture that resolves occlusions by predicting pose on any given frame using surrounding unlabeled frames. Third, we refine the pose predictions post hoc by combining ensembling and Kalman smoothing. Together, these components render pose trajectories more accurate and scientifically usable. We released a cloud application that allows users to label data, train networks and process new videos directly from the browser.
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Algoritmos , Teorema de Bayes , Grabación en Video , Animales , Grabación en Video/métodos , Aprendizaje Automático Supervisado , Nube Computacional , Programas Informáticos , Postura/fisiología , Aprendizaje Profundo , Procesamiento de Imagen Asistido por Computador/métodos , Conducta AnimalRESUMEN
Animals learn the value of foods based on their postingestive effects and thereby develop aversions to foods that are toxic1-6 and preferences to those that are nutritious7-14. However, it remains unclear how the brain is able to assign credit to flavors experienced during a meal with postingestive feedback signals that can arise after a substantial delay. Here, we reveal an unexpected role for postingestive reactivation of neural flavor representations in this temporal credit assignment process. To begin, we leverage the fact that mice learn to associate novel15-18, but not familiar, flavors with delayed gastric malaise signals to investigate how the brain represents flavors that support aversive postingestive learning. Surveying cellular resolution brainwide activation patterns reveals that a network of amygdala regions is unique in being preferentially activated by novel flavors across every stage of the learning process: the initial meal, delayed malaise, and memory retrieval. By combining high-density recordings in the amygdala with optogenetic stimulation of genetically defined hindbrain malaise cells, we find that postingestive malaise signals potently and specifically reactivate amygdalar novel flavor representations from a recent meal. The degree of malaise-driven reactivation of individual neurons predicts strengthening of flavor responses upon memory retrieval, leading to stabilization of the population-level representation of the recently consumed flavor. In contrast, meals without postingestive consequences degrade neural flavor representations as flavors become familiar and safe. Thus, our findings demonstrate that interoceptive reactivation of amygdalar flavor representations provides a neural mechanism to resolve the temporal credit assignment problem inherent to postingestive learning.
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Contemporary pose estimation methods enable precise measurements of behavior via supervised deep learning with hand-labeled video frames. Although effective in many cases, the supervised approach requires extensive labeling and often produces outputs that are unreliable for downstream analyses. Here, we introduce "Lightning Pose," an efficient pose estimation package with three algorithmic contributions. First, in addition to training on a few labeled video frames, we use many unlabeled videos and penalize the network whenever its predictions violate motion continuity, multiple-view geometry, and posture plausibility (semi-supervised learning). Second, we introduce a network architecture that resolves occlusions by predicting pose on any given frame using surrounding unlabeled frames. Third, we refine the pose predictions post-hoc by combining ensembling and Kalman smoothing. Together, these components render pose trajectories more accurate and scientifically usable. We release a cloud application that allows users to label data, train networks, and predict new videos directly from the browser.
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Some individuals are susceptible to the experience of chronic stress and others are more resilient. While many brain regions implicated in learning are dysregulated after stress, little is known about whether and how neural teaching signals during stress differ between susceptible and resilient individuals. Here, we seek to determine if activity in the lateral habenula (LHb), which encodes a negative teaching signal, differs between susceptible and resilient mice during stress to produce different outcomes. After, but not before, chronic social defeat stress (CSDS), the LHb is active when susceptible mice are in the proximity of the aggressor strain. During stress itself, LHb activity is higher in susceptible mice during aggressor proximity, and activation of the LHb during stress biases mice towards susceptibility. This manipulation generates a persistent and widespread increase in the balance of subcortical versus cortical activity in susceptible mice. Taken together, our results indicate that heightened activity in the LHb during stress produces lasting brainwide and behavioral substrates of susceptibility.
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Methodological advances in neuroscience have enabled the collection of massive datasets which demand innovative approaches for scientific communication. Existing platforms for data storage lack intuitive tools for data exploration, limiting our ability to interact effectively with these brain-wide datasets. We introduce two public websites: (Data and Atlas) developed for the International Brain Laboratory which provide access to millions of behavioral trials and hundreds of thousands of individual neurons. These interfaces allow users to discover both the raw and processed brain-wide data released by the IBL at the scale of the whole brain, individual sessions, trials, and neurons. By hosting these data interfaces as websites they are available cross-platform with no installation. By releasing each site's code as a modular open-source framework, other researchers can easily develop their own web interfaces and explore their own data. As neuroscience datasets continue to expand, customizable web interfaces offer a glimpse into a future of streamlined data exploration and act as blueprints for future tools.
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Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches.
In science, it is of vital importance that multiple studies corroborate the same result. Researchers therefore need to know all the details of previous experiments in order to implement the procedures as exactly as possible. However, this is becoming a major problem in neuroscience, as animal studies of behavior have proven to be hard to reproduce, and most experiments are never replicated by other laboratories. Mice are increasingly being used to study the neural mechanisms of decision making, taking advantage of the genetic, imaging and physiological tools that are available for mouse brains. Yet, the lack of standardized behavioral assays is leading to inconsistent results between laboratories. This makes it challenging to carry out large-scale collaborations which have led to massive breakthroughs in other fields such as physics and genetics. To help make these studies more reproducible, the International Brain Laboratory (a collaborative research group) et al. developed a standardized approach for investigating decision making in mice that incorporates every step of the process; from the training protocol to the software used to analyze the data. In the experiment, mice were shown images with different contrast and had to indicate, using a steering wheel, whether it appeared on their right or left. The mice then received a drop of sugar water for every correction decision. When the image contrast was high, mice could rely on their vision. However, when the image contrast was very low or zero, they needed to consider the information of previous trials and choose the side that had recently appeared more frequently. This method was used to train 140 mice in seven laboratories from three different countries. The results showed that learning speed was different across mice and laboratories, but once training was complete the mice behaved consistently, relying on visual stimuli or experiences to guide their choices in a similar way. These results show that complex behaviors in mice can be reproduced across multiple laboratories, providing an unprecedented dataset and open-access tools for studying decision making. This work could serve as a foundation for other groups, paving the way to a more collaborative approach in the field of neuroscience that could help to tackle complex research challenges.
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Conducta Animal , Investigación Biomédica/normas , Toma de Decisiones , Neurociencias/normas , Animales , Señales (Psicología) , Femenino , Aprendizaje , Masculino , Ratones Endogámicos C57BL , Modelos Animales , Variaciones Dependientes del Observador , Estimulación Luminosa , Reproducibilidad de los Resultados , Factores de Tiempo , Percepción VisualRESUMEN
The activity-dependent rules that govern the wiring of GABAergic interneurons are not well understood. Chandelier cells (ChCs) are a type of GABAergic interneuron that control pyramidal cell output through axo-axonic synapses that target the axon initial segment. In vivo imaging of ChCs during development uncovered a narrow window (P12-P18) over which axons arborized and formed connections. We found that increases in the activity of either pyramidal cells or individual ChCs during this temporal window result in a reversible decrease in axo-axonic connections. Voltage imaging of GABAergic transmission at the axon initial segment (AIS) showed that axo-axonic synapses were depolarizing during this period. Identical manipulations of network activity in older mice (P40-P46), when ChC synapses are inhibitory, resulted instead in an increase in axo-axonic synapses. We propose that the direction of ChC synaptic plasticity follows homeostatic rules that depend on the polarity of axo-axonic synapses.
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Segmento Inicial del Axón/fisiología , Axones/fisiología , Plasticidad Neuronal/fisiología , Sinapsis/fisiología , Envejecimiento/fisiología , Animales , Interneuronas/fisiología , Ratones , Ratones Transgénicos , Terminales Presinápticos/fisiología , Células Piramidales/fisiología , Corteza Somatosensorial/citología , Corteza Somatosensorial/crecimiento & desarrollo , Corteza Somatosensorial/fisiología , Factor Nuclear Tiroideo 1/genética , Ácido gamma-Aminobutírico/fisiologíaRESUMEN
Recent progress revealed the complexity of RNA processing and its association to human disorders. Here, we unveil a new facet of this complexity. Complete loss of function of the ubiquitous splicing factor SFPQ affects zebrafish motoneuron differentiation cell autonomously. In addition to its nuclear localization, the protein unexpectedly localizes to motor axons. The cytosolic version of SFPQ abolishes motor axonal defects, rescuing key transcripts, and restores motility in the paralyzed sfpq null mutants, indicating a non-nuclear processing role in motor axons. Novel variants affecting the conserved coiled-coil domain, so far exclusively found in fALS exomes, specifically affect the ability of SFPQ to localize in axons. They broadly rescue morphology and motility in the zebrafish mutant, but alter motor axon morphology, demonstrating functional requirement for axonal SFPQ. Altogether, we uncover the axonal function of the splicing factor SFPQ in motor development and highlight the importance of the coiled-coil domain in this process. VIDEO ABSTRACT.
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Axones/metabolismo , Neuronas Motoras/metabolismo , Factor de Empalme Asociado a PTB/metabolismo , Empalme del ARN/genética , Esclerosis Amiotrófica Lateral/metabolismo , Animales , Proteínas de Unión al ADN/metabolismo , Humanos , Ratones , Corteza Motora/crecimiento & desarrollo , Factor de Empalme Asociado a PTB/genética , ARN Mensajero/metabolismo , Proteínas de Unión al ARN/metabolismo , Pez CebraRESUMEN
BACKGROUND: Lack of physical activity and increased levels of stress contribute to the development of multiple physical and mental disorders. An increasing number of studies relate voluntary exercise with greater resilience to psychological stress, a process that is highly regulated by the hypothalamic-pituitary-adrenal (HPA) axis. However, the molecular mechanisms underlying the beneficial effects of exercise on stress resilience are still poorly understood. Here we have studied the impact of long term exercise and housing conditions on: a) hippocampal expression of glucocorticoid receptor (Nr3c1), b) epigenetic regulation of Nr3c1 (DNA methylation at the Nr3c1-1F promoter and miR-124 expression), c) anxiety (elevated plus maze, EPM), and d) adrenal gland weight and adrenocorticotropic hormone receptor (Mc2r) expression. RESULTS: Exercise increased Nr3c1 and Nr3c1-1F expression and decreased miR-124 levels in the hippocampus in single-housed mice, suggesting enhanced resilience to stress. The opposite was found for pair-housed animals. Bisulfite sequencing showed virtually no DNA methylation in the Nr3c1-1F promoter region. Single-housing increased the time spent on stretch attend postures. Exercise decreased the time spent at the open arms of the EPM, however, the mobility of the exercise groups was significantly lower. Exercise had opposite effects on the adrenal gland weight of single and pair-housed mice, while it had no effect on adrenal Mc2r expression. CONCLUSIONS: These results suggest that exercise exerts a positive impact on stress resilience in single-housed mice that could be mediated by decreasing miR-124 and increasing Nr3c1 expression in the hippocampus. However, pair-housing reverses these effects possibly due to stress from dominance disputes between pairs.