ABSTRACT
The common marmoset (Callithrix jacchus) is a small and highly social New World monkey with high reproduction rates, which has been proven to be a compelling non-human primate model for biomedical and neuroscience research. Some females give birth to triplets; however, the parents cannot raise all of them. To save these infants, we have developed a hand-rearing method for raising newborn marmosets. In this protocol, we describe the formula of the food, the time for feeding, the configuration of the temperature and humidity, as well as the adaptation of the hand-reared infants to the colony environment. This hand-rearing method significantly increases the survival rate of marmoset infants (without hand-rearing: 45%; with hand-rearing: 86%) and provides the opportunity to study the development of marmoset infants with similar genetic backgrounds raised in different postnatal environments. As the method is practical and easy to use, we anticipate that it could also be applied to other labs working with common marmosets.
Subject(s)
Callithrix , Food , Animals , FemaleABSTRACT
The cerebellum is involved in encoding balance, posture, speed, and gravity during locomotion. However, most studies are carried out on flat surfaces, and little is known about cerebellar activity during free ambulation on slopes. Here, it has been imaged the neuronal activity of cerebellar molecular interneurons (MLIs) and Purkinje cells (PCs) using a miniaturized microscope while a mouse is walking on a slope. It has been found that the neuronal activity of vermal MLIs specifically enhanced during uphill and downhill locomotion. In addition, a subset of MLIs is activated during entire uphill or downhill positions on the slope and is modulated by the slope inclines. In contrast, PCs showed counter-balanced neuronal activity to MLIs, which reduced activity at the ramp peak. So, PCs may represent the ramp environment at the population level. In addition, chemogenetic inactivation of lobule V of the vermis impaired uphill locomotion. These results revealed a novel micro-circuit in the vermal cerebellum that regulates ambulatory behavior in 3D terrains.
ABSTRACT
Behavioral measurement and evaluation are broadly used to understand brain functions in neuroscience, especially for investigations of movement disorders, social deficits, and mental diseases. Numerous commercial software and open-source programs have been developed for tracking the movement of laboratory animals, allowing animal behavior to be analyzed digitally. In vivo optical imaging and electrophysiological recording in freely behaving animals are now widely used to understand neural functions in circuits. However, it is always a challenge to accurately track the movement of an animal under certain complex conditions due to uneven environment illumination, variations in animal models, and interference from recording devices and experimenters. To overcome these challenges, we have developed a strategy to track the movement of an animal by combining a deep learning technique, the You Only Look Once (YOLO) algorithm, with a background subtraction algorithm, a method we label DeepBhvTracking. In our method, we first train the detector using manually labeled images and a pretrained deep-learning neural network combined with YOLO, then generate bounding boxes of the targets using the trained detector, and finally track the center of the targets by calculating their centroid in the bounding box using background subtraction. Using DeepBhvTracking, the movement of animals can be tracked accurately in complex environments and can be used in different behavior paradigms and for different animal models. Therefore, DeepBhvTracking can be broadly used in studies of neuroscience, medicine, and machine learning algorithms.
ABSTRACT
Spatial updating of self-to-object spatial relations may be performed online or offline. The set size effects in spatial updating are generally considered as a benchmark for indicating which updating strategy is used. Online updating is associated with transient egocentric representations and the presence of set size effects, whereas offline updating is associated with enduring allocentric representations and the absence of set size effects. In the present study, the updating strategy and the available spatial representations in updating were manipulated factorially. In a working memory (WM) paradigm, observers briefly learned a new layout of objects in each trial such that only the transient spatial representation was available during updating, whereas in a reference memory (RM) paradigm, observers learned the same layout of objects across trials such that both transient and enduring representations were available in updating. In both paradigms, observers were instructed to update online or offline. Set size effects showed up only in the WM paradigm but disappeared in the RM paradigm, regardless of the updating strategy. These results suggest that both updating strategies will produce set size effects if they use transient representations alone and that set size effects can be eliminated as long as enduring representations are used. These findings challenge the 2-system theories of spatial updating by showing that although online updating is naturally associated with transient spatial presentations, whereas offline updating is naturally associated with enduring representations, these default associations can be switched under manipulation. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
