Biology subjects

Yuriy Mishchenko

Publications and source records attributed to Yuriy Mishchenko.

4 recordsLinked to original sources

bioRxiv2015

Consistent estimation of complete neuronal connectivity in large neuronal populations using sparse "shotgun" neuronal activity sampling

We investigate the properties of the recently proposed \"shotgun\" sampling approach for the common inputs problem in the functional estimation of neuronal connectivity. We study the asymptotic correctness, the speed of convergence, and the data size requirements of such an approach. We find that the shotgun approach can be expected to allow the inference of the complete connectivity matrix in large neuronal populations under some rather general conditions. However, we find that the posterior error of the shotgun connectivity estimator may grow quickly with the size of the unobserved neuronal populations, the connectivity strength, and the square of the observations sparseness. This implies that the shotgun connectivity estimation will require significant amounts of neuronal activity data whenever the number of neurons in the observed populations is small. We present a numerical approach for solving the shotgun estimation problem in general settings and use it to demonstrate the shotgun connectivity inference in simulated synfire and weakly coupled cortical neuronal networks.

Neuroscience↗

bioRxiv2015

Variability in cellular gene expression profiles and homeostatic regulation

One of surprising recent discoveries in biology is that the gene and protein expression profiles in cells with identical genetic and environmental makeup can exhibit large variability. The nature and the significance of this variability had been posed as one of the current fundamental questions of biology. In this letter, we argue that the observed variability in cellular gene and protein expression can be understood as an outcome of homeostatic regulation mechanisms controlling the gene and protein expression profiles.

Cell Biology↗

bioRxiv2014

Application of the radial distribution function for quantitative analysis of neuropil microstructure in stratum radiatum of CA1 region in hippocampus.

Various structures in the brain contain many important clues to the brain?s development and function. Among these, the microscopic organization of neural tissue is of particular interest since such organization has direct potential to affect the formation of local synaptic connectivity between axons and dendrites, serving as an important factor affecting the brain?s development. While the organization of the brain at large and intermediate scales had been well studied, the organization of neural tissue at micrometer scales remains largely unknown. In particular, at present it is not known what specific structures exist in neuropil at micrometer scales, what effect such structures have on formation of synaptic connectivity, and what processes shape the micrometer-scale organization of neuropil. In this work, we present an analysis of recent electron microscopy reconstructions of blocks of neuropil tissue from rat s. radiatum of hippocampal CA1 to provide insights into these questions. We propose a new statistical method for systematically analyzing the small-scale organization of neuropil based on an adaptation of the approach of radial distribution functions from statistical physics. Our results show that the micrometer-scale organization of hippocampal CA1 neuropil can be viewed as a disordered arrangement of axonal and dendritic processes without significant small-scale positional coordinations. We observe several deviations from this picture in the distributions of glia and dendritic spines. Finally, we study the relationship between local synaptic connectivity and the small-scale organization of neuropil.

Neuroscience↗

bioRxiv2013

Conneconomics: The Economics of Dense, Large-Scale, High-Resolution Neural Connectomics

We analyze the scaling and cost-performance characteristics of current and projected connectomics approaches, with reference to the potential implications of recent advances in diverse contributing fields. Three generalized strategies for dense connectivity mapping at the scale of whole mammalian brains are considered: electron microscopic axon tracing, optical imaging of combinatorial molecular markers at synapses, and bulk DNA sequencing of trans-synaptically exchanged nucleic acid barcode pairs. Due to advances in parallel-beam instrumentation, whole mouse brain electron microscopic image acquisition could cost less than $100 million, with total costs presently limited by image analysis to trace axons through large image stacks. Optical microscopy at 50-100 nm isotropic resolution could potentially read combinatorially multiplexed molecular information from individual synapses, which could indicate the identifies of the pre-synaptic and post-synaptic cells without relying on axon tracing. An optical approach to whole mouse brain connectomics may be achievable for less than $10 million and could be enabled by emerging technologies to sequence nucleic acids in-situ in fixed tissue via fluorescent microscopy. Novel strategies relying on bulk DNA sequencing, which would extract the connectome without direct imaging of the tissue, could produce a whole mouse brain connectome for $100k-$1 million or a mouse cortical connectome for $10k-$100k. Anticipated further reductions in the cost of DNA sequencing could lead to a $1000 mouse cortical connectome.

Neuroscience↗