REVEALS: An Open Source Multi Camera GUI For Rodent Behavior Acquisition.

Understanding the rich behavioral data generated by mice is essential for deciphering the function of the healthy and diseased brain. However, the current landscape lacks effective, affordable, and accessible methods for acquiring such data, especially when employing multiple cameras simultaneously. We have developed REVEALS (Rodent BEhaVior Multi-camErA Laboratory AcquiSition), a graphical user interface (GUI) written in python for acquiring rodent behavioral data via commonly used USB3 cameras. REVEALS allows for user-friendly control of recording from one or multiple cameras simultaneously while streamlining the data acquisition process, enabling researchers to collect and analyze large datasets efficiently. We release this software package as a stand-alone, open-source framework for researchers to use and modify according to their needs. We describe the details of the GUI implementation, including the camera control software and the video recording functionality. We validate results demonstrating the GUI's stability, reliability, and accuracy for capturing and analyzing rodent behavior using DeepLabCut pose estimation in both an object and social interaction assay. REVEALS can also be incorporated into other custom pipelines to analyze complex behavior, such as MoSeq. In summary, REVEALS provides an interface for collecting behavioral data from one or multiple perspectives that, combined with deep learning algorithms, will allow the scientific community to discover and characterize complex behavioral phenotypes to understand brain function better.

A transcriptional constraint mechanism limits the homeostatic response to activity deprivation in mammalian neocortex.

Healthy neuronal networks rely on homeostatic plasticity to maintain stable firing rates despite changing synaptic drive. These mechanisms, however, can themselves be destabilizing if activated inappropriately or excessively. For example, prolonged activity deprivation can lead to rebound hyperactivity and seizures. While many forms of homeostasis have been described, whether and how the magnitude of homeostatic plasticity is constrained remains unknown. Here, we uncover negative regulation of cortical network homeostasis by the PARbZIP family of transcription factors. In cortical slice cultures made from knockout mice lacking all three of these factors, the network response to prolonged activity withdrawal measured with calcium imaging is much stronger, while baseline activity is unchanged. Whole-cell recordings reveal an exaggerated increase in the frequency of miniature excitatory synaptic currents reflecting enhanced upregulation of recurrent excitatory synaptic transmission. Genetic analyses reveal that two of the factors, Hlf and Tef, are critical for constraining plasticity and for preventing life-threatening seizures. These data indicate that transcriptional activation is not only required for many forms of homeostatic plasticity but is also involved in restraint of the response to activity deprivation.

The human brain is made up of billions of nerve cells called neurons which receive and send signals to one another. To avoid being over- or under-stimulated, neurons can adjust the strength of the inputs they receive by altering how connected they are to other nerve cells. This process, known as homeostatic plasticity, is thought to be necessary for normal brain activity as it helps keep the outgoing signals of neurons relatively constant. However, homeostatic plasticity can lead to seizures if it becomes too strong and overcompensates for weak input signals. Regulating this process is therefore central to brain health, but scientists do not understand if or how it is controlled. To address this, Valakh et al. analyzed the genes activated in neurons lacking incoming signals to find proteins that regulate homeostatic plasticity. This revealed a class of molecules called transcription factors (which switch genes on or off) that constrain the process. In brain samples from mice without these regulatory proteins, neurons received twice as much input, leading to an increase in brain activity resembling that observed during seizures. Valakh et al. confirmed this finding using live mice, which developed seizures in the absence of these transcription factors. These findings suggest that this type of regulation to keep homeostatic plasticity from becoming too strong may be important. This could be especially vital as the brain develops, when the strength of connections between neurons changes rapidly. The discovery of the transcription factors involved provides a potential target for activating or restraining homeostatic plasticity. This control could help researchers better understand how the process stabilizes brain signaling.

C4 induces pathological synaptic loss by impairing AMPAR trafficking.

During development, activation of the complement pathway, an extracellular proteolytic cascade, results in microglia-dependent synaptic elimination via complement receptor 3 (CR3). Here, we report that decreased connectivity caused by overexpression of C4 (C4-OE), a schizophrenia-associated gene, is CR3 independent. Instead, C4-OE triggers GluR1 degradation through an intracellular mechanism involving endosomal trafficking protein SNX27, resulting in pathological synaptic loss. Moreover, the connectivity deficits associated with C4-OE were rescued by increasing levels of SNX27, linking excessive complement activity to an intracellular endolysosomal recycling pathway affecting synapses.