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

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

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

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

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

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

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

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

Editorial: Home Cage-Based Phenotyping in Rodents: Innovation, Standardization, Reproducibility and Translational Improvement

Peer Reviewe

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

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

Synapse Plasticity in Motor, Sensory, and Limbo-Prefrontal Cortex Areas as Measured by Degrading Axon Terminals in an Environment Model of Gerbils (Meriones unguiculatus)

Still little is known about naturally occurring synaptogenesis in the adult neocortex and related impacts of epigenetic influences. We therefore investigated (pre)synaptic plasticity in various cortices of adult rodents, visualized by secondary lysosome accumulations (LA) in remodeling axon terminals. Twenty-two male gerbils from either enriched (ER) or impoverished rearing (IR) were used for quantification of silver-stained LA. ER-animals showed rather low LA densities in most primary fields, whereas barrel and secondary/associative cortices exhibited higher densities and layer-specific differences. In IR-animals, these differences were evened out or even inverted. Basic plastic capacities might be linked with remodeling of local intrinsic circuits in the context of cortical map adaptation in both IR- and ER-animals. Frequently described disturbances due to IR in multiple corticocortical and extracortical afferent systems, including the mesocortical dopamine projection, might have led to maladaptations in the plastic capacities of prefronto-limbic areas, as indicated by different LA densities in IR- compared with ER-animals