Strategies for recovering exact structure of neural circuits with broadly targeted fluorescent connectivity probes

We present a framework for reconstructing structure of complete neural circuits
in the brain using collections of independent measurements of connectivity
performed with existing anatomical or functional fluorescent probes, and
designed to provide complementary information about neural circuit’s structure
by targeting slightly different its parts either in deterministic or stochastic
succession. We discuss specific implementation of this procedure using
synaptic fluorescent marker GRASP and Cre/Lox system Brainbow to collect
ensemble of observations of the sets of synapses between stochastically labeled
samples of neurons. By representing such measurements mathematically as
weak constraints on circuit’s connectivity matrix and by solving a constrained
optimization problem, we are able to exactly deduce the wiring diagram in C.
Elegans in an in-silico experiment from only ~10,000 measurements. This
offers possibility for routinely reconstructing complete connectivity in smaller
organisms, such as C. Elegans, using exclusively light microscopy instruments
over the span of single weeks

Strategies for identifying exact structure of neural circuits with broad light microscopy connectivity probes

Dissecting the structure of neural circuits in the brain is one of the central problems of neuroscience. Until present day, the only way to obtain complete and detailed reconstructions of neural circuits was thought to be the serial section Electron Microscopy, which could take decades to complete a small circuit. In this paper, we develop a mathematical framework that allows performing such reconstructions much faster and cheaper with existing light microscopy and genetic tools. In this framework, a collection of genetically targeted light probes of connectivity is prepared from different animals and then used to systematically deduce the circuit's connectivity. Each measurement is represented as mathematical constraint on the circuit architecture. Such constraints are then computationally combined to identify the detailed connectivity matrix for the probed circuit. Connectivity here is understood broadly, such as that between different identifiable neurons or identifiable classes of neurons, etc. This paradigm may be applied with connectivity probes such as ChR2-assisted circuit mapping, GRASP or transsynaptic viruses, and genetic targeting techniques such as Brainbow, MARCM/MADM or UAS/Gal4, in model organisms such as C. Elegans, Drosophila, zerbafish, mouse, etc. In particular, we demonstrate how, by using this paradigm, the wiring diagram between all neurons in C. Elegans may be reconstructed with GRASP and Brainbow and off-the-shelf light microscopy tools in the time span of one week or less. Described approach allows recovering exact connectivity matrix even if neurons may not be targeted individually in ~Np*log(N) time (Np is the number of nonzero entries and N is the size of the connectivity matrix). For comparison, the minimal time that would be necessary to determine connectivity matrix directly by probing connections between individual neurons when one knows a-priory which pairs should be tested, e.g. with whole-cell patches, is ~Np

A novel variational approach for Quantum Field Theory: example of study of the ground state and phase transition in Nonlinear Sigma Model

We discuss a novel form of the variational approach in Quantum Field Theory in which the trial quantum configuration is represented directly in terms of relevant expectation values rather than, e.g., increasingly complicated structure from Fock space. The quantum algebra imposes constraints on such expectation values so that the variational problem is formulated here as an optimization under constraints. As an example of application of such approach we consider the study of ground state and critical properties in a variant of nonlinear sigma model.Comment: talk presented at DPF2004 meeting in Riverside, CA; to appear in a supplement in International Journal of Modern Physics

On Optical Detection of Densely Labeled Synapses in Neuropil and Mapping Connectivity with Combinatorially Multiplexed Fluorescent Synaptic Markers

We propose a new method for mapping neural connectivity optically, by utilizing Cre/Lox system Brainbow to tag synapses of different neurons with random mixtures of different fluorophores, such as GFP, YFP, etc., and then detecting patterns of fluorophores at different synapses using light microscopy (LM). Such patterns will immediately report the pre- and post-synaptic cells at each synaptic connection, without tracing neural projections from individual synapses to corresponding cell bodies. We simulate fluorescence from a population of densely labeled synapses in a block of hippocampal neuropil, completely reconstructed from electron microscopy data, and show that high-end LM is able to detect such patterns with over 95% accuracy. We conclude, therefore, that with the described approach neural connectivity in macroscopically large neural circuits can be mapped with great accuracy, in scalable manner, using fast optical tools, and straightforward image processing. Relying on an electron microscopy dataset, we also derive and explicitly enumerate the conditions that should be met to allow synaptic connectivity studies with high-resolution optical tools

Exploring Properties of Dark and Visible Mass Distribution on Different Scales in the Universe

In this short note we discuss recent observation of linear correlation on log-log scale between distribution of dark and visible mass in gravitationally bound systems. The coefficient of such correlation appears to be essentially the same for various systems of dramatically different scales such as spiral galaxies of different luminosities and galaxy clusters. We briefly touch possible interpretations of this observation and implications for the mass of dark matter particle.Comment: presented at the DPF2004 meeting in Riverside, CA; to be published in a supplement in International Journal of Modern Physics

Higher Fock State Contributions to the Generalized Parton Distribution of Pion

We discuss the higher Fock state (q \bar q g) contributions to the nonzero value of the pion GPD at the crossover point x = zeta between the DGLAP and ERBL regions. Using the phenomenological light-front constituent quark model, we confirm that the higher Fock state contributions indeed give a nonzero value of the GPD at the crossover point. Iterating the light-front quark model wave function of the lowest q \bar q Fock state with the Bethe-Salpeter kernel corresponding to the one-gluon-exchange, we include all possible time-ordered q \bar q g Fock state contributions and obtain the pion GPD satisfying necessary sum rules and continuity conditions.Comment: References adde

Accurate Detection of Wake Word Start and End Using a CNN

Small footprint embedded devices require keyword spotters (KWS) with small model size and detection latency for enabling voice assistants. Such a keyword is often referred to as \textit{wake word} as it is used to wake up voice assistant enabled devices. Together with wake word detection, accurate estimation of wake word endpoints (start and end) is an important task of KWS. In this paper, we propose two new methods for detecting the endpoints of wake words in neural KWS that use single-stage word-level neural networks. Our results show that the new techniques give superior accuracy for detecting wake words' endpoints of up to 50 msec standard error versus human annotations, on par with the conventional Acoustic Model plus HMM forced alignment. To our knowledge, this is the first study of wake word endpoints detection methods for single-stage neural KWS.Comment: Proceedings of INTERSPEEC

Time-to-space conversion in quantum field theory of flavor mixing

We consider the problem of time-to-space conversion in quantum field theory of flavor mixing using a generalization of the wave-packet method in quantum mechanics. We work entirely within the canonical formalism of creation and annihilation operators that allows us, unlike the usual wave-packet formulation, to include the nontrivial effect due to flavor condensation in the vacuum

Rosetta Brains: A Strategy for Molecularly-Annotated Connectomics

We propose a neural connectomics strategy called Fluorescent In-Situ Sequencing of Barcoded Individual Neuronal Connections (FISSEQ-BOINC), leveraging fluorescent in situ nucleic acid sequencing in fixed tissue (FISSEQ). FISSEQ-BOINC exhibits different properties from BOINC, which relies on bulk nucleic acid sequencing. FISSEQ-BOINC could become a scalable approach for mapping whole-mammalian-brain connectomes with rich molecular annotations