Dissemination

This study proposes to refine, integrate and disseminate the NeuroImaging Brain Chart (NIBCh) software toolbox and machine learning (ML) model library, an ecosystem of software components enabling constructive integration, statistical harmonization, and ML-centric data analyses across studies. NIBCh enables large-scale analyses of multi-modal brain MRI data by mapping such data into a compact coordinate system of informative neuroimaging signatures implemented by our library of ML models.

Project Abstract Current common methods for measuring somatosensory function in preclinical rodent models generally rely on withdrawal responses to uncomfortable or painful stimuli. These tests can be stressful to the animal, while also yielding a high variability in measured responses, and repetitive testing in longitudinal models may even result in chronic pain states. To better understand the connection between physiology and perception of touch and proprioception, researchers need a modern, off-the-shelf assessment system to administer and quantify trained, volitional behaviors.

Over the past 15 years, new microscope technologies and methods for high throughput imaging have revolutionized structural biology by extending the resolution and scale of datasets in 3 dimensions. The resulting image volumes are more typically hundreds of GB to even tens of TB and for large volume electron microscope images of brain, can approach PB sizes. These file sizes pose challenges for image analysis, and communication of a representative set of raw data and quantification.

Non-invasive brain stimulation (NIBS) has attracted considerable interest in the cognitive neuroscience community, providing an important basic research tool to study brain function, with emerging clinical applications to enhance function in individuals with neurological disorders. Despite this potential, an emerging literature has highlighted concerns regarding the reliability and robustness of transcranial electric stimulation (tES), the primary NIBS method used to induce changes in brain plasticity through the application of subthreshold stimulation.

Cardiac arrest in infants is a medical emergency requiring rapid resuscitation to restore circulation. However, resuscitation often results in significant brain injury, caused by ischemia/reperfusion injury. Only 36% of infants (<1yr old) treated for out-of-hospital cardiac arrest and 69% of infants that suffer in-hospital cardiac arrest are successfully resuscitated. These infants currently have no therapeutic options to limit brain injury. The current standard treatment for post-cardiac arrest brain injury is therapeutic hypothermia.

Histone modifications carry rich information of cellular memory and gene regulatory mechanisms. Single cell analysis of histone modification in conjunction with transcriptome could recover this critical layer of cell identity and help to dissect the cellular and molecular composition of complex tissues such as the brain. We recently developed an ultra-high throughput single cell multi-omics assay, Paired-Tag, that can jointly map transcriptome and histone modifications from up to a million single cells in parallel.

Brain function is regulated by molecular signaling and metabolism, however, our ability to track neurometabolic transformations deep in the brain is very underdeveloped compared to the central role of neurometabolism in neurodegenerative disease or brain function in general.

The goal of this proposal is to combine the power of the NEURON mathematical modeling software with the Cybercyte “plug and play” dynamic clamp system. Our product will enable all neuronal electrophysiologists to be able to perform sophisticated NEURON model based dynamic clamp experiments, without any requirement for programming, engineering, or mathematical modeling skills.

This project aims to develop the 2P-ActivityScope™, a revolutionary new microscope based on a technological breakthrough called second-generation Scanned Line Angular Projection (SLAP2) two photon laser scanning microscopy that was recently developed by Dr. Kaspar Podgorski (Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA).

Understanding the brain is a profound and fascinating challenge, captivating the scientific community and the public alike. The lack of effective treatment for most brain disorders makes training the next generation of neuroscientists, engineers and physicians a key concern. However, much neuroscience is perceived to be too difficult to be taught in school. To make neuroscience accessible and engaging to students and teachers, Backyard Brains is developing SpikerBots: fun and affordable robots that look like brains and are controlled by computer simulations of biological brains.