Informatics

The increasing availability and ease of use of confocal, two-photon, and light-sheet microscopes coupled with rapid developments in fluorescent protein reporters have made 3D and functional imaging and its analysis a central component of modern Neuroscience research. Yet, the ease of acquiring 3D and functional images is creating progressively larger datasets, prompting the need for high-throughput image analysis algorithms and software that can be both rapid and accurate.

Project Summary/Abstract The effective sharing of data requires the development and broad adoption of standards for the organization of data and metadata. Within the field of neuroimaging, there is an emerging standard for data/metadata organization, the Brain Imaging Data Structure (BIDS), which is currently implemented for MRI and is under development for PET and MEG.

Project Summary The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative promotes the development and application of technologies to describe the temporal and spatial dynamics of cell types and neural circuits in the brain.

PROJECT SUMMARY Advancements in the field of microscopy and imaging have pushed the boundaries of what was once thought possible in many fields of research. New techniques coupled with the application of new technologies allows researchers to probe further and with greater accuracy to answer increasingly complex questions. While these new techniques allow for far greater specificity of observation and increased sensitivity in regard to both resolution and frequency, the amount of data generated is increasing to a point where conventional systems are unable to manage it.

Project Abstract Advances in imaging have had a profound effect on our ability to generate high-resolution measurements of the brain’s structure. One of the major hurdles in processing modern neuroimaging datasets designed to produce large-scale maps of the connections and the organization of the brain lies in the sheer size of these data. For instance, electron microscopic (EM) images of a cubic millimeter of cortex occupies roughly 3 PBon disk, and lower resolution emerging X-ray microtomography (XRM) data can exceed 10 TB for a single mouse brain.

Project Summary (Abstract) The goal of this application is to develop, test, and disseminate multi-context (command line, desktop, server, and web applications) software for robust and reproducible neuroscience image analysis from data across mul- tiple scales (two photon microscopy, mesoscale Ca2+ optical imaging, small animal fMRI, and human fMRI) and species (mice, rats, and humans). In particular, we will provide tools for computation and visualization of con- nectomes (connectivity matrices) for such image data sets that will include both modality specific preprocessing (e.g.

The past decade has seen major advances in the tools available to neuroscientists, making it possible to ask increasingly specific questions regarding which neurons and circuits are correlated with, necessary for, and sufficient for, specific behavioral or computational functions. Advancements in our understanding of neural computation and how it leads to complex behavior critically depend on accurate measurements of coordinated neural activities in behaving animals.

PROJECT SUMMARY/ABSTRACT Fast microscopy techniques, coupled with recent advances in tissue clearing, are now able to efficiently produce cellular-resolution images of intact brain samples. These technologies have generated three- dimensional (3D) images of entire intact brains from model organisms and large sections of human brain samples, enabling mapping of neuronal circuits from synapse to systems levels. Going forward, it will be essential to share data across laboratories to replicate findings, perform cross-study analyses, and develop robust new analysis tools.

PROJECT SUMMARY Technology for recording from the brain is developing at a breakneck pace. But the digital integration of data acquired from different recording technologies is an impediment to the rapid adoption of these technologies across labs, and also makes analysis by interested 3rd parties, such as theorists, difficult. This lack of integration is a major barrier to scientific inquiry, as labs cannot easily analyze each other's data.

Project Summary/Abstract Brain function is produced by the coordinated activity of multiple neuronal types that are widely distributed across many brain regions. Neuronal signals are acquired using extra- and intracellular recordings, and increasingly optical imaging, during sensory, motor, and cognitive tasks. Neurophysiology research generates large, complex, heterogeneous datasets at terabyte scale. The data size and complexity is expected to continue to grow with the increasing sophistication of experimental apparatus.