303 research outputs found

    Creating Detailed Metadata for an R Shiny Analysis of Rodent Behavior Sequence Data Detected Along One Light-Dark Cycle

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    Automated mouse phenotyping through the high-throughput analysis of home cage behavior has brought hope of a more effective and efficient method for testing rodent models of diseases. Advanced video analysis software is able to derive behavioral sequence data sets from multiple-day recordings. However, no dedicated mechanisms exist for sharing or analyzing these types of data. In this article, we present a free, open-source software actionable through a web browser (an R Shiny application), which performs an analysis of home cage behavioral sequence data, which is designed to spot differences in circadian activity while preventing p-hacking. The software aligns time-series data to the light/dark cycle, and then uses different time windows to produce up to 162 behavior variables per animal. A principal component analysis strategy detected differences between groups. The behavior activity is represented graphically for further explorative analysis. A machine-learning approach was implemented, but it proved ineffective at separating the experimental groups. The software requires spreadsheets that provide information about the experiment (i.e., metadata), thus promoting a data management strategy that leads to FAIR data production. This encourages the publication of some metadata even when the data are kept private. We tested our software by comparing the behavior of female mice in videos recorded twice at 3 and 7 months in a home cage monitoring system. This study demonstrated that combining data management with data analysis leads to a more efficient and effective research process

    The Stop Signal Task for Measuring Behavioral Inhibition in Mice With Increased Sensitivity and High-Throughput Operation

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    Ceasing an ongoing motor response requires action cancelation. This is impaired in many pathologies such as attention deficit disorder and schizophrenia. Action cancelation is measured by the stop signal task that estimates how quickly a motor response can be stopped when it is already being executed. Apart from human studies, the stop signal task has been used to investigate neurobiological mechanisms of action cancelation overwhelmingly in rats and only rarely in mice, despite the need for a genetic model approach. Contributing factors to the limited number of mice studies may be the long and laborious training that is necessary and the requirement for a very loud (100 dB) stop signal. We overcame these limitations by employing a fully automated home-cage-based setup. We connected a home-cage to the operant box via a gating mechanism, that allowed individual ID chipped mice to start sessions voluntarily. Furthermore, we added a negative reinforcement consisting of a mild air puff with escape option to the protocol. This specifically improved baseline inhibition to 94% (from 84% with the conventional approach). To measure baseline inhibition the stop is signaled immediately with trial onset thus measuring action restraint rather than action cancelation ability. A high baseline allowed us to measure action cancelation ability with higher sensitivity. Furthermore, our setup allowed us to reduce the intensity of the acoustic stop signal from 100 to 70 dB. We constructed inhibition curves from stop trials with daily adjusted delays to estimate stop signal reaction times (SSRTs). SSRTs (median 88 ms) were lower than reported previously, which we attribute to the observed high baseline inhibition. Our automated training protocol reduced training time by 17% while also promoting minimal experimenter involvement. This sensitive and labor efficient stop signal task procedure should therefore facilitate the investigation of action cancelation pathologies in genetic mouse models.Peer Reviewe

    The Stop Signal Task for Measuring Behavioral Inhibition in Mice With Increased Sensitivity and High-Throughput Operation

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    Ceasing an ongoing motor response requires action cancelation. This is impaired in many pathologies such as attention deficit disorder and schizophrenia. Action cancelation is measured by the stop signal task that estimates how quickly a motor response can be stopped when it is already being executed. Apart from human studies, the stop signal task has been used to investigate neurobiological mechanisms of action cancelation overwhelmingly in rats and only rarely in mice, despite the need for a genetic model approach. Contributing factors to the limited number of mice studies may be the long and laborious training that is necessary and the requirement for a very loud (100 dB) stop signal. We overcame these limitations by employing a fully automated home-cage-based setup. We connected a home-cage to the operant box via a gating mechanism, that allowed individual ID chipped mice to start sessions voluntarily. Furthermore, we added a negative reinforcement consisting of a mild air puff with escape option to the protocol. This specifically improved baseline inhibition to 94% (from 84% with the conventional approach). To measure baseline inhibition the stop is signaled immediately with trial onset thus measuring action restraint rather than action cancelation ability. A high baseline allowed us to measure action cancelation ability with higher sensitivity. Furthermore, our setup allowed us to reduce the intensity of the acoustic stop signal from 100 to 70 dB. We constructed inhibition curves from stop trials with daily adjusted delays to estimate stop signal reaction times (SSRTs). SSRTs (median 88 ms) were lower than reported previously, which we attribute to the observed high baseline inhibition. Our automated training protocol reduced training time by 17% while also promoting minimal experimenter involvement. This sensitive and labor efficient stop signal task procedure should therefore facilitate the investigation of action cancelation pathologies in genetic mouse models

    Two-dimensional reward evaluation in mice

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    When choosing among multi-attribute options, integrating the full information may be computationally costly and time-consuming. So-called non-compensatory decision rules only rely on partial information, for example when a difference on a single attribute overrides all others. Such rules may be ecologically more advantageous, despite being economically suboptimal. Here, we present a study that investigates to what extent animals rely on integrative rules (using the full information) versus non-compensatory rules when choosing where to forage. Groups of mice were trained to obtain water from dispensers varying along two reward dimensions: volume and probability. The mice’s choices over the course of the experiment suggested an initial reliance on integrative rules, later displaced by a sequential rule, in which volume was evaluated before probability. Our results also demonstrate that while the evaluation of probability differences may depend on the reward volumes, the evaluation of volume differences is seemingly unaffected by the reward probabilities.Humboldt-Universität zu Berlin (1034)Peer Reviewe

    Learning Set Formation and Reversal Learning in Mice During High-Throughput Home-Cage-Based Olfactory Discrimination

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    Rodent behavioral tasks are crucial to understanding the nature and underlying biology of cognition and cognitive deficits observed in psychiatric and neurological pathologies. Olfaction, as the primary sensory modality in rodents, is widely used to investigate cognition in rodents. In recent years, automation of olfactory tasks has made it possible to conduct olfactory experiments in a time- and labor-efficient manner while also minimizing experimenter-induced variability. In this study, we bring automation to the next level in two ways: First, by incorporating a radio frequency identification-based sorter that automatically isolates individuals for the experimental session. Thus, we can not only test animals during defined experimental sessions throughout the day but also prevent cagemate interference during task performance. Second, by implementing software that advances individuals to the next test stage as soon as performance criteria are reached. Thus, we can prevent overtraining, a known confounder especially in cognitive flexibility tasks. With this system in hand, we trained mice on a series of four odor pair discrimination tasks as well as their respective reversals. Due to performance-based advancement, mice normally advanced to the next stage in less than a day. Over the series of subsequent odor pair discriminations, the number of errors to criterion decreased significantly, thus indicating the formation of a learning set. As expected, errors to criterion were higher during reversals. Our results confirm that the system allows investigating higher-order cognitive functions such as learning set formation (which is understudied in mice) and reversal learning (which is a measure of cognitive flexibility and impaired in many clinical populations). Therefore, our system will facilitate investigations into the nature of cognition and cognitive deficits in pathological conditions by providing a high-throughput and labor-efficient experimental approach without the risks of overtraining or cagemate interference

    Cognitive training of mice attenuates age-related decline in associative learning and behavioral flexibility

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    Identifying factors that influence age-related cognitive decline is crucial, given its severe personal and societal impacts. However, studying aging in human or animal models is challenging due to the significant variability in aging processes among individuals. Additionally, longitudinal and cross-sectional studies often produce differing results. In this context, home-cage-based behavioral analysis over lifespans has emerged as a significant method in recent years. This study aimed to explore how prior experience affects cognitive performance in mice of various age groups (4, 12, and 22 months) using a home-cage-based touchscreen test battery. In this automated system, group-housed, ID-chipped mice primarily obtain their food during task performance throughout the day, motivated by their own initiative, without being subjected to food deprivation. Spatial working memory and attention were evaluated using the trial unique non-matching to location (TUNL) and the five-choice serial reaction time task (5-CSRTT), respectively. The same set of mice learned both of these demanding tasks. While signs of cognitive decline were already apparent in middle-aged mice, older mice exhibited poorer performance in both tasks. Mice at both 12 and 22 months displayed an increase in perseverance and a decrease in the percentage of correct responses in the TUNL test compared to the 4-month-old mice. Furthermore, during the 5-CSRTT, they exhibited higher rates of omissions and premature responses compared to their younger counterparts. Additionally, the correct response rate in 22-month-old mice was lower than that of the 4-month-old ones. However, mice that had undergone cognitive training at 4 months maintained high-performance levels when re-tested at 12 months, showing an increase in correct responses during TUNL testing compared to their untrained controls. In the 5-CSRTT, previously trained mice demonstrated higher correct response rates, fewer omissions, and reduced premature responses compared to naive control mice. Notably, even when assessed on a visual discrimination and behavioral flexibility task at 22 months, experienced mice outperformed naive 4-month-old mice. These findings highlight the advantages of early-life cognitive training and suggest that its benefits extend beyond the cognitive domains primarily targeted during early training. The success of this study was significantly aided by the fully automated home-cage-based testing system, which allows for high throughput with minimal human intervention.Peer Reviewe

    Absent or Low Rate of Adult Neurogenesis in the Hippocampus of Bats (Chiroptera)

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    Bats are the only flying mammals and have well developed navigation abilities for 3D-space. Even bats with comparatively small home ranges cover much larger territories than rodents, and long-distance migration by some species is unique among small mammals. Adult proliferation of neurons, i.e., adult neurogenesis, in the dentate gyrus of rodents is thought to play an important role in spatial memory and learning, as indicated by lesion studies and recordings of neurons active during spatial behavior. Assuming a role of adult neurogenesis in hippocampal function, one might expect high levels of adult neurogenesis in bats, particularly among fruit- and nectar-eating bats in need of excellent spatial working memory. The dentate gyrus of 12 tropical bat species was examined immunohistochemically, using multiple antibodies against proteins specific for proliferating cells (Ki-67, MCM2), and migrating and differentiating neurons (Doublecortin, NeuroD). Our data show a complete lack of hippocampal neurogenesis in nine of the species (Glossophaga soricina, Carollia perspicillata, Phyllostomus discolor, Nycteris macrotis, Nycteris thebaica, Hipposideros cyclops, Neoromicia rendalli, Pipistrellus guineensis, and Scotophilus leucogaster), while it was present at low levels in three species (Chaerephon pumila, Mops condylurus and Hipposideros caffer). Although not all antigens were recognized in all species, proliferation activity in the subventricular zone and rostral migratory stream was found in all species, confirming the appropriateness of our methods for detecting neurogenesis. The small variation of adult hippocampal neurogenesis within our sample of bats showed no indication of a correlation with phylogenetic relationship, foraging strategy, type of hunting habitat or diet. Our data indicate that the widely accepted notion of adult neurogenesis supporting spatial abilities needs to be considered carefully. Given their astonishing longevity, certain bat species may be useful subjects to compare adult neurogenesis with other long-living species, such as monkeys and humans, showing low rates of adult hippocampal neurogenesis

    Putting aquifers into atmospheric simulation models: an example from the Mill Creek Watershed, northeastern Kansas

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    Aquifer–atmosphere interactions can be important in regions where the water table is shallow (\u3c2 m). A shallow water table provides moisture for the soil and vegetation and thus acts as a source term for evapotranspiration to the atmosphere. A coupled aquifer–land surface–atmosphere model has been developed to study aquifer–atmosphere interactions in watersheds, on decadal timescales. A single column vertically discretized atmospheric model is linked to a distributed soil-vegetation–aquifer model. This physically based model was able to reproduce monthly and yearly trends in precipitation, stream discharge, and evapotranspiration, for a catchment in northeastern Kansas. However, the calculated soil moisture tended to drop to levels lower than were observed in drier years. The evapotranspiration varies spatially and seasonally and was highest in cells situated in topographic depressions where the water table is in the root zone. Annually, simulation results indicate that from 5–20% of groundwater supported evapotranspiration is drawn from the aquifer. The groundwater supported fraction of evapotranspiration is higher in drier years, when evapotranspiration exceeds precipitation. A long-term (40 year) simulation of extended drought conditions indicated that water table position is a function of groundwater hydrodynamics and cannot be predicted solely on the basis of topography. The response time of the aquifer to drought conditions was on the order of 200 years indicating that feedbacks between these two water reservoirs act on disparate time scales. With recent advances in the computational power of massively parallel supercomputers, it may soon become possible to incorporate physically based representations of aquifer hydrodynamics into general circulation models (GCM) land surface parameterization schemes

    Synaptic Remodeling in the Dentate Gyrus, CA3, CA1, Subiculum, and Entorhinal Cortex of Mice: Effects of Deprived Rearing and Voluntary Running

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    Hippocampal cell proliferation is strongly increased and synaptic turnover decreased after rearing under social and physical deprivation in gerbils (Meriones unguiculatus). We examined if a similar epigenetic effect of rearing environment on adult neuroplastic responses can be found in mice (Mus musculus). We examined synaptic turnover rates in the dentate gyrus, CA3, CA1, subiculum, and entorhinal cortex. No direct effects of deprived rearing on rates of synaptic turnover were found in any of the studied regions. However, adult wheel running had the effect of leveling layer-specific differences in synaptic remodeling in the dentate gyrus, CA3, and CA1, but not in the entorhinal cortex and subiculum of animals of both rearing treatments. Epigenetic effects during juvenile development affected adult neural plasticity in mice, but seemed to be less pronounced than in gerbils
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