A 3D particle tracking tool for next generation neuroscience microscopy

DESCRIPTION provided by applicant Time lapse D imaging of functional neural networks composed of many neurons connected through a complex web of synapses is a promising approach for gaining in depth understanding of how the central nervous system CNS works Using high speed confocal and fluorescence microscopy D sequences are routinely acquired to elucidate the development of functional circuits as well as the molecular kinetics and interactions that drive CNS development or pathological degeneration It is now possible to image more complex and intact neural circuits in the CNS in situ with high lateral and axial resolution Imaging of these new model systems could unleash a new generation of scientific inquiries that would lead to new discoveries and therapies However D neuronal sequences have a lower signal to noise ratio SNR while the complexity of particle motion is exacerbated by the more physiological environment Therefore quantification of particle dynamics and molecular interactions in these complex models is difficult due to the limitations of the current D image analysis tools In particular current particle tracking tools struggle to address these twin challenges This constitutes a critical bottleneck and rate limiting step for quantitative analysis of the biological mechanisms that underlie neural development and disease We have developed a high performance and configurable tracking tool well suited for a broad range of D particle tracking applications which is now being commercialized by Nikon Corp In a benchmark study covering broad particle tracking applications this tracking tool achieved significantly better performance than several commercial and academic tools Table I Our collaborators at the Harvard Medical School are leaders in the field of neural development and synaptic morphogenesis They routinely acquire high resolution D confocal in vitro imaging data showing microtubule dynamics and neuronal process morphometry using both vertebrate and invertebrate cells This provide an excellent test platform for the next generation D tracking tool The objective of this Phase I proposal is to develop and validate an informatics tool optimized for D subcellular tracking applications The general purpose tool would address the challenge of detecting and tracking moving particles with heterogeneous motion in functional neural networks These types of complex experimental preparations are increasingly being adopted and are drawing attention to the limitations of the current generation of tracking tools The key innovations of the proposed tool include a Dynamic model and adaptive control that represents dynamic object states and transitions and executes state dependent particle detection and tracking methods Self regulation of valid state transitions and track matching using motion energy an independent check on the matching outcomes Weandapos ll prove the feasibility in Phase I using intact preparations from Drosophila and Xenopus as well as simulated data In Phase II we will tackle a broader set of D particle tracking applications and also broadly address the market requirement for D kinetic microscopy informatics including D kinetic event characterization and screening The specific aims are Aim Create and validate the D heterogeneous tracking tool using simulated D images Aim Validate the tool in broad fluorescence D kinetic microscopy applications Aim Execute a proof of principle experiment in TIP tracking for functional neural networksPUBLIC HEALTH RELEVANCE The automated and adaptive D particle tracking tool would enable analysis of subcellular dynamics in next generation quantitative neuroimaging to study neural network function and diseases