Optogenetics and deep brain stimulation neurotechnologies

Brain neural network is composed of densely packed, intricately wired neurons whose activity patterns ultimately give rise to every behavior, thought, or emotion that we experience. Over the past decade, a novel neurotechnique, optogenetics that combines light and genetic methods to control or monitor neural activity patterns, has proven to be revolutionary in understanding the functional role of specific neural circuits. We here briefly describe recent advance in optogenetics and compare optogenetics with deep brain stimulation technology that holds the promise for treating many neurological and psychiatric disorders

Focusing and imaging with increased numerical apertures through multimode fibers with micro-fabricated optics

The use of individual multimode optical fibers in endoscopy applications has the potential to provide highly miniaturized and noninvasive probes for microscopy and optical micromanipulation. A few different strategies have been proposed recently, but they all suffer from intrinsically low resolution related to the low numerical aperture of multimode fibers. Here, we show that two-photon polymerization allows for direct fabrication of micro-optics components on the fiber end, resulting in an increase of the numerical aperture to a value that is close to 1. Coupling light into the fiber through a spatial light modulator, we were able to optically scan a submicrometer spot (300 nm FWHM) over an extended region, facing the opposite fiber end. Fluorescence imaging with improved resolution is also demonstrated.Comment: 5 pages, 3 figure

Odors: from chemical structures to gaseous plumes

We are immersed within an odorous sea of chemical currents that we parse into individual odors with complex structures. Odors have been posited as determined by the structural relation between the molecules that compose the chemical compounds and their interactions with the receptor site. But, naturally occurring smells are parsed from gaseous odor plumes. To give a comprehensive account of the nature of odors the chemosciences must account for these large distributed entities as well. We offer a focused review of what is known about the perception of odor plumes for olfactory navigation and tracking, which we then connect to what is known about the role odorants play as properties of the plume in determining odor identity with respect to odor quality. We end by motivating our central claim that more research needs to be conducted on the role that odorants play within the odor plume in determining odor identity

Design and fabrication of a precision alignment system and package for a two-photon fluorescence imaging device

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (leaf 24).A compact, lightweight precision alignment system and package for an endomicroscope was designed and fabricated. The endomicroscope will consist of a millimeter-scale fiber resonator and a two-axis silicon optical bench. The alignment system provided five degrees of freedom and was designed to align the fiber resonator with the microchip with a resolution of one micron. The alignment system consisted of a system of ultra-fine screws and two compliant mechanisms to deamplify the motion of the screw. Finite element analysis was performed to optimize the compliant mechanisms for the desired transmission ratio of 20:1. The alignment system was fabricated and testing showed that the transmission ratios were lower than expected (18.6 for one compliant mechanism and 2.68 for the other). Testing also showed that the alignment system met the functional requirements for the ranges of motion.by Jean H. Chang.S.B

A forward-backward splitting algorithm for the minimization of non-smooth convex functionals in Banach space

We consider the task of computing an approximate minimizer of the sum of a smooth and non-smooth convex functional, respectively, in Banach space. Motivated by the classical forward-backward splitting method for the subgradients in Hilbert space, we propose a generalization which involves the iterative solution of simpler subproblems. Descent and convergence properties of this new algorithm are studied. Furthermore, the results are applied to the minimization of Tikhonov-functionals associated with linear inverse problems and semi-norm penalization in Banach spaces. With the help of Bregman-Taylor-distance estimates, rates of convergence for the forward-backward splitting procedure are obtained. Examples which demonstrate the applicability are given, in particular, a generalization of the iterative soft-thresholding method by Daubechies, Defrise and De Mol to Banach spaces as well as total-variation based image restoration in higher dimensions are presented

Test-retest reliability of structural brain networks from diffusion MRI

Structural brain networks constructed from diffusion MRI (dMRI) and tractography have been demonstrated in healthy volunteers and more recently in various disorders affecting brain connectivity. However, few studies have addressed the reproducibility of the resulting networks. We measured the test–retest properties of such networks by varying several factors affecting network construction using ten healthy volunteers who underwent a dMRI protocol at 1.5 T on two separate occasions. Each T1-weighted brain was parcellated into 84 regions-of-interest and network connections were identified using dMRI and two alternative tractography algorithms, two alternative seeding strategies, a white matter waypoint constraint and three alternative network weightings. In each case, four common graph-theoretic measures were obtained. Network properties were assessed both node-wise and per network in terms of the intraclass correlation coefficient (ICC) and by comparing within- and between-subject differences. Our findings suggest that test–retest performance was improved when: 1) seeding from white matter, rather than grey; and 2) using probabilistic tractography with a two-fibre model and sufficient streamlines, rather than deterministic tensor tractography. In terms of network weighting, a measure of streamline density produced better test–retest performance than tract-averaged diffusion anisotropy, although it remains unclear which is a more accurate representation of the underlying connectivity. For the best performing configuration, the global within-subject differences were between 3.2% and 11.9% with ICCs between 0.62 and 0.76. The mean nodal within-subject differences were between 5.2% and 24.2% with mean ICCs between 0.46 and 0.62. For 83.3% (70/84) of nodes, the within-subject differences were smaller than between-subject differences. Overall, these findings suggest that whilst current techniques produce networks capable of characterising the genuine between-subject differences in connectivity, future work must be undertaken to improve network reliability

Time-Frequency Mixed-Norm Estimates: Sparse M/EEG imaging with non-stationary source activations

International audienceMagnetoencephalography (MEG) and electroencephalography (EEG) allow functional brain imaging with high temporal resolution. While solving the inverse problem independently at every time point can give an image of the active brain at every millisecond, such a procedure does not capitalize on the temporal dynamics of the signal. Linear inverse methods (Minimum-norm, dSPM, sLORETA, beamformers) typically assume that the signal is stationary: regularization parameter and data covariance are independent of time and the time varying signal-to-noise ratio (SNR). Other recently proposed non-linear inverse solvers promoting focal activations estimate the sources in both space and time while also assuming stationary sources during a time interval. However such an hypothesis only holds for short time intervals. To overcome this limitation, we propose time-frequency mixed-norm estimates (TF-MxNE), which use time-frequency analysis to regularize the ill-posed inverse problem. This method makes use of structured sparse priors defined in the time-frequency domain, offering more accurate estimates by capturing the non-stationary and transient nature of brain signals. State-of-the-art convex optimization procedures based on proximal operators are employed, allowing the derivation of a fast estimation algorithm. The accuracy of the TF-MxNE is compared to recently proposed inverse solvers with help of simulations and by analyzing publicly available MEG datasets

Novel Methodology for Creating Macaque Retinas with Sortable Photoreceptors and Ganglion Cells

Purpose: The ability to generate macaque retinas with sortable cell populations would be of great benefit to both basic and translational studies of the primate retina. The purpose of our study was therefore to develop methods to achieve this goal by selectively labeling, in life, photoreceptors (PRs) and retinal ganglion cells (RGCs) with separate fluorescent markers. Methods: Labeling of macaque (Macaca fascicularis) PRs and RGCs was accomplished by subretinal delivery of AAV5-hGRK1-GFP, and retrograde transport of micro-ruby™ from the lateral geniculate nucleus, respectively. Retinas were anatomically separated into different regions. Dissociation conditions were optimized, and cells from each region underwent fluorescent activated cell sorting (FACS). Expression of retinal cell type- specific genes was assessed by quantitative real-time PCR to characterize isolated cell populations. Results: We show that macaque PRs and RGCs can be simultaneously labeled in-life and enriched populations isolated by FACS. Recovery from different retinal regions indicated efficient isolation/enrichment for PRs and RGCs, with the macula being particularly amendable to this technique. Conclusions: The methods and materials presented here allow for the identification of novel reagents designed to target retinal ganglion cells and/or photoreceptors in a species that is phylogenetically and anatomically similar to human. These techniques will enable screening of intravitreally- delivered AAV capsid libraries for variants with increased tropism for PRs and/or RGCs and the evaluation of vector tropism and/or cellular promoter activity of gene therapy vectors in a clinically relevant species