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Table of Contents Tuesday, May 25, 2021 ............................................................................................................................................................... 5 T1. Astrocyte-Specific Expression of the Extracellular Matrix Gene HtrA1 Regulates Susceptibility to Stress in a Sex- Specific Manner ....................................................................................................................................................................... 5 T2. Plexin-B2 Regulates Migratory Plasticity of Glioblastoma Cells in a 3D-Printed Micropattern Device ............................. 5 T3. Pathoanatomical Mapping of Differential MAPT Expression and Splicing in Progressive Supranuclear Palsy ............... 5 T4. Behavioral Variability in Response to Chronic Stress and Morphine in BXD and Parental Mouse Lines......................... 6 T5. Thyroid-Stimulating Hormone Receptor Regulates Anxiety .............................................................................................. 6 T6. Drugs That Inhibit Microglial Inflammation Also Ameliorate Aβ1-42 Induced Toxicity in C. Elegans ............................... 7 T7. Phosphodiesterase 1b is an Upstream Regulator of a Key Gene Network in the Nucleus Accumbens Driving Addiction- Like Behaviors ......................................................................................................................................................................... 7 T8. Reduced Gap Effect in Children With FOXP1 Syndrome and Autism Spectrum -
Paper, Involving Edges Between All Nodes, and Consider Dynamics Along We Will Use These Connectomes Scaled Such That C = Kλmaxk = 1, the Simplified Network (Fig
ARTICLES PUBLISHED ONLINE: 25 SEPTEMBER 2017 | DOI: 10.1038/NPHYS4268 Role of graph architecture in controlling dynamical networks with applications to neural systems Jason Z. Kim1, Jonathan M. Soer1, Ari E. Kahn2,3, Jean M. Vettel1,4,5, Fabio Pasqualetti6 and Danielle S. Bassett1,7* Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviours such as synchronization. Although descriptions of these behaviours are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behaviour. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain’s control performance by removing single edges in the network. Generally, our results ground the expectation of a control system’s behaviour in its network architecture, and directly inspire new directions in network analysis and design via distributed control. etwork systems are composed of interconnected units that driver nodes21,22 capable of influencing the system along diverse interact with each other on diverse temporal and spatial trajectories, and optimal inputs that move the system from one state Nscales1. -
Boston University Photonics Center Annual Report 2018
Boston University Photonics Center Annual Report 2018 Letter from the Director THIS ANNUAL REPORT summarizes activities of the Boston University Photonics Center for the 2017-2018 academic year. In it, you will find quantitative and descriptive information regarding our photonics programs in education, interdisciplinary research, business innovation, and technology development. Located at the heart of Boston University’s urban campus, the Photonics Center is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light. Our nine-story building houses world-class research facilities and shared laboratories dedicated to photonics research, and sustains the work of 58 faculty members, 12 staff members, and more than 100 graduate students and postdoctoral fellows. Over the past year, the Center achieved the three main goals of the strategic plan that our community committed itself to nearly six years ago. Our first strategic goal was to strengthen the Center’s research foundation, which we quantified succinctly as sustained grant income of $20M per year by Photonics Center researchers. At the time of our strategic plan, our annual grant income was about half that, and Center operations were substantially leveraged by a single DoD Technology Over the past Translation Contract that ended in 2011. In the years since, we have focused year, the Center our efforts on supporting and catalyzing new research grants by our faculty, and achieved the three the effort has paid off. Our average grant support over the past four years has main goals of the exceeded our target, and this year our grant income was about $21M. -
Tuesday, May 21, 2019
CME-accredited ICMIC Seminar Series 2003 – 2018 Jerry Glickson, PhD NMR Studies of Lonidamine: Stoll 11/14/18 Professor of Radiology Mechanism of Action and Effects Conference University of Pennsylvania on Melanoma and other Cancers Room David Bonekamp, PhD Professor Radiomics and Deep Learning in Stoll Deutsches 11/7/18 Oncology: Examples in Prostate, Conference Krebsforschungszentrum Brain and Breast Cancer Room German Cancer Research Center Mass Spectrometric Imaging and Zoltan Takats, PhD Stoll In-vivo Mass Spectrometry - A 10/24/18 Professor of Analytical Chemistry Conference New Era in Understanding Tissue Imperial College of London Room Biology Elizabeth Hillman, PhD Capturing Dynamic Brain and Stoll Professor of Biomedical Tissue Function with High-speed, 10/17/18 Conference Engineering Multi-scale Optical Imaging and Room Columbia University Microscopy Norma Kanarek, PhD, MPH Stoll Big Picture Cancer Prevention 9/26/18 Associate Professor Conference and Control JHU JHBSPH & SKCCC Room Sridhar Nimmagadda, PhD A non-invasive Tool to Quantify Stoll 08/29/18 Associate Professor the Activity of PD-L1 Therapeutics Conference JHU Dept. of Radiology at the Tumor Room Sanjay Jain, M.D. Stoll Professor Imaging of Infections: Bench to 07/25/18 Conference JHU Dept. of Pediatric Infectious Bedside Room Disease Nimmi Ramanujam, PhD Robert Carr Jr. Professor of Innovations to Accelerate Stoll Biomedical Engineering 5/9/18 Improved Access across the Conference Professor of Pharmacology & Cancer Care Continuum Room Cancer Biology Duke University -
Optimized Connectome Architecture for Sensory-Motor Integration
RESEARCH Optimized connectome architecture for sensory-motor integration Jacob C. Worrell1, Jeffrey Rumschlag2, Richard F. Betzel3, Olaf Sporns1, and Bratislav Mišic´4 1Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA 2Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, CA, USA 3Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA 4Montréal Neurological Institute, McGill University, Montréal, Canada Keywords: Connectome, Brain, Spreading, Drosophila Downloaded from http://direct.mit.edu/netn/article-pdf/1/4/415/1091865/netn_a_00022.pdf by guest on 25 September 2021 an open access journal ABSTRACT The intricate connectivity patterns of neural circuits support a wide repertoire of communication processes and functional interactions. Here we systematically investigate how neural signaling is constrained by anatomical connectivity in the mesoscale Drosophila (fruit fly) brain network. We use a spreading model that describes how local perturbations, such as external stimuli, trigger global signaling cascades that spread through the network. Through a series of simple biological scenarios we demonstrate that anatomical embedding potentiates sensory-motor integration. We find that signal spreading is faster from nodes associated with sensory transduction (sensors) to nodes associated with motor output (effectors). Signal propagation was accelerated if sensor nodes were activated simultaneously, suggesting a topologically mediated synergy among sensors. In addition, the organization of the network increases the likelihood of convergence of multiple cascades towards effector nodes, thereby facilitating integration prior to motor output. Moreover, effector nodes tend to coactivate more frequently than other pairs of nodes, suggesting an anatomically enhanced Citation: Worrell, J. C., Rumschlag, J., coordination of motor output. Altogether, our results show that the organization of the Betzel, R. -
Programme Booklet Elwell Web
THEO MURPHY INTERNATIONAL SCIENTIFIC MEETING ON Making light work: illuminating the future of biomedical optics Monday 8 November – Wednesday 10 November 2010 The Kavli Royal Society International Centre, Chicheley Hall, Buckinghamshire Organised by Professor Clare Elwell, Professor Jeremy Hebden, Professor Paul Beard, Professor Elizabeth Hillman and Professor Chris Cooper - Programme and abstracts - Speaker biographies - Notes - Participant list - Publication order form The abstracts that follow are provided by the presenters and the Royal Society takes no responsibility for their content. 2 Making light work: illuminating the future of biomedical optics Monday 8 – Wednesday 10 November 2010 Organised by Professor Clare Elwell, Professor Jeremy Hebden, Professor Paul Beard, Professor Elizabeth Hillman and Professor Chris Cooper Day 1 – Monday 8 November 2010 12.00 Registration and lunch* 13.00 Welcome by Professor Clare Elwell , Organiser Welcome by Professor Sir Peter Knight FRS , Principal, The Kavli Royal Society International Centre SESSION 1 – CURRENT STATUS AND INNOVATIONS IN OPTICAL TECHNOLOGIES Chairs – Professor Joseph Culver, Washington University in St Louis, USA Professor Matthias Kohl-Bareis, University of Applied Sciences Koblenz, Germany 13.15 ‘Near-infrared spectroscopy and imaging of living systems’: from 1996 to 2010 and beyond Professor Clare Elwell, University College London, UK 13.40 Discussion 14.00 Blood flow monitors & other recent developments in diffuse optics Professor Arjun Yodh, University of Pennsylvania, -
A Picosecond Optoelectronic Cross Correlator Using a Gain Modulated Avalanche Photodiode for Measuring the Impulse Response of Tissue
A Picosecond Optoelectronic Cross Correlator using a Gain Modulated Avalanche Photodiode for Measuring the Impulse Response of Tissue. David R. Kirkby B.Sc. M.Sc. Department of Medical Physics and Bioengineering, University College London. Thesis submitted for the degree of Doctor of Philosophy (Ph.D.) at the University of London. Supervisor: Professor David T. Delpy, FRS. Second supervisor: Dr. Mark Cope. April 1999. 2 Abstract Human tissue is relatively transparent to light between 700 and 1000 nm in the near infra- red (NIR). NIR spectroscopy is a technique that can measure non-invasively and safely, the optical properties of tissue. Several different types of spectroscopic instrumentation have currently been developed, ranging from simple continuous intensity systems, through to complex time and frequency resolved techniques. This thesis describes the development of a near infra-red time-resolved system, using an inexpensive avalanche photodiode (APD) detector and a microwave step recovery diode (SRD) in a novel way to implement a totally electronic cross- correlator, with no moving parts. The aim of the work was to develop a simple instrument to monitor scattering changes in tissue during laser induced thermal therapy. The APD was gain-modulated by rapidly varying the bias voltage using electrical pulses generated by the SRD (120 ps full width half maximum (FWHM) and8Vinamplitude). The resulting cross-correlator had a temporal resolution of 275 ps FWHM - significantly faster than the 750 ps FWHM of the APD when operating with a conventional fixed bias voltage. Spurious responses caused by the SRD were observed, which were removed by the addition of Schottky diodes on the SRD’s output, although this slightly degraded the system temporal resolution from 275 to 380 ps FWHM. -
Comparisons Between the ON- and OFF- Edge Motion Pathways in the Drosophila Brain
RESEARCH ARTICLE Comparisons between the ON- and OFF- edge motion pathways in the Drosophila brain Kazunori Shinomiya1*, Gary Huang1, Zhiyuan Lu1,2, Toufiq Parag1,3, C Shan Xu1, Roxanne Aniceto1, Namra Ansari1, Natasha Cheatham1, Shirley Lauchie1, Erika Neace1, Omotara Ogundeyi1, Christopher Ordish1, David Peel1, Aya Shinomiya1, Claire Smith1, Satoko Takemura1, Iris Talebi1, Patricia K Rivlin1, Aljoscha Nern1, Louis K Scheffer1, Stephen M Plaza1, Ian A Meinertzhagen2* 1Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States; 2Department of Psychology and Neuroscience, Dalhousie University, Halifax, Canada; 3School of Engineering and Applied Sciences, Harvard University, Cambridge, United States Abstract Understanding the circuit mechanisms behind motion detection is a long-standing question in visual neuroscience. In Drosophila melanogaster, recently discovered synapse-level connectomes in the optic lobe, particularly in ON-pathway (T4) receptive-field circuits, in concert with physiological studies, suggest a motion model that is increasingly intricate when compared with the ubiquitous Hassenstein-Reichardt model. By contrast, our knowledge of OFF-pathway (T5) has been incomplete. Here, we present a conclusive and comprehensive connectome that, for the first time, integrates detailed connectivity information for inputs to both the T4 and T5 pathways in a single EM dataset covering the entire optic lobe. With novel reconstruction methods using automated synapse prediction suited to such a large connectome, we successfully corroborate previous findings in the T4 pathway and comprehensively identify inputs and receptive fields for T5. *For correspondence: Although the two pathways are probably evolutionarily linked and exhibit many similarities, we [email protected] (KS); uncover interesting differences and interactions that may underlie their distinct functional [email protected] (IAM) properties. -
The Drosophila Larval Locomotor Circuit Provides a Model to Understand Neural Circuit Development and Function
The Drosophila Larval Locomotor Circuit Provides a Model to Understand Neural Circuit Development and Function Item Type article Authors Hunter, Iain; email: [email protected]; Coulson, Bramwell; Zarin, Aref Arzan; Baines, Richard A. Citation Frontiers in Neural Circuits, volume 15, page 684969 Publisher Frontiers Media S.A. Rights Licence for this article: http://creativecommons.org/licenses/ by/4.0/ Download date 05/10/2021 14:16:43 Link to Item http://hdl.handle.net/10034/625270 fncir-15-684969 June 26, 2021 Time: 14:16 # 1 REVIEW published: 01 July 2021 doi: 10.3389/fncir.2021.684969 The Drosophila Larval Locomotor Circuit Provides a Model to Understand Neural Circuit Development and Function Iain Hunter1*, Bramwell Coulson1, Aref Arzan Zarin2 and Richard A. Baines1 1 Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, School of Biological Sciences, University of Manchester, Manchester, United Kingdom, 2 Department of Biology, The Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, United States It is difficult to answer important questions in neuroscience, such as: “how do neural circuits generate behaviour?,” because research is limited by the complexity and inaccessibility of the mammalian nervous system. Invertebrate model organisms offer simpler networks that are easier to manipulate. As a result, much of what we know about the development of neural circuits is derived from work in crustaceans, nematode worms and arguably most of all, the fruit fly, Drosophila melanogaster. This review aims to demonstrate the utility of the Drosophila larval locomotor network as a model circuit, to those who do not usually use the fly in their work. -
Manuscript Details
Manuscript Details Manuscript number COIS_2017_98_R1 Title Learning from connectomics on the fly Short title Learning from connectomics on the fly Article type Review article Abstract Parallels between invertebrates and vertebrates in nervous system development, organisation and circuits are powerful reasons to use insects to study the mechanistic basis of behaviour. The last few years have seen the generation in Drosophila melanogaster of very large light microscopy data sets, genetic driver lines and tools to report or manipulate neural activity. These resources in conjunction with computational tools are enabling large scale characterisation of neuronal types and their functional properties. These are complemented by 3D electron microscopy, providing synaptic resolution data. A whole brain connectome of the fly larva is approaching completion based on manual reconstruction of EM data. An adult whole brain dataset is already publicly available and focussed reconstruction is under way, but its 40x greater volume would require ~ 500-5000 person-years of manual labour. Nevertheless rapid technical improvements in imaging and especially automated segmentation will likely deliver a complete adult connectome in the next 5 years. To enhance our understanding of the circuit basis of behaviour, light and electron microscopy outputs must be integrated with functional and physiological information into comprehensive databases. We review presently available data, tools and opportunities in Drosophila. We then consider the limits and potential of -
Core Faculty
CORE FACULTY Elham Azizi Elham Azizi utilizes an interdisciplinary approach combining cutting-edge single-cell Assistant Professor, Biomedical Engineering; Herbert genomic technologies with statistical machine learning techniques, to characterize & Florence Irving Assistant Professor of Cancer complex populations of interacting cells in the tumor microenvironment as well as Data Research (in the Herbert and Florence Irving their dysregulated circuitry. Elham was a postdoctoral fellow at the Memorial Sloan Institute for Cancer Dynamics and in the Herbert Irving Kettering Cancer Center and Columbia University (2014-2019). She received a PhD in Comprehensive Cancer Center) Bioinformatics from Boston University (2014), an MS degree in Electrical Engineering also from Boston University (2010) and a BS in Electrical Engineering from Sharif Machine learning in single cell analysis and cancer. University of Technology (2008). She is a recipient of the NIH NCI Pathway to Independence Award, the Tri-Institutional Breakout Prize for Junior Investigators, and an American Cancer Society Postdoctoral Fellowship. She joined the faculty of Columbia Biomedical Engineering and the Herbert and Florence Irving Institute for Cancer Dynamics in January 2020. Tal Danino Tal Danino’s research explores the emerging field of synthetic biology, focusing on Associate Professor, Biomedical Engineering; engineering bacteria gene circuits to create novel behaviors that have biomedical Director, Synthetic Biological Systems Laboratory applications. The interaction of microbes and tumors is a major target of his work, where DNA sequences and synthetic biology approaches are used to program Synthetic biology. Engineering gene circuits in microbes. bacteria as diagnostics and therapeutics in cancer. Danino also brings this science outside the laboratory as a TED Fellow and through science-art projects. -
A Connectome of the Adult Drosophila Central Brain
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.21.911859; this version posted January 21, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. A Connectome of the Adult Drosophila Central Brain C. Shan Xu1, Michal Januszewski2, Zhiyuan Lu1,3, Shin-ya Takemura1, Kenneth J. Hayworth1, Gary Huang1, Kazunori Shinomiya1, Jeremy Maitin-Shepard2, David Ackerman1, Stuart Berg1, Tim Blakely2, John Bogovic1, Jody Clements1, Tom Dolafi1, Philip Hubbard1, Dagmar Kainmueller1,4, William Katz1, Takashi Kawase1, Khaled A. Khairy1,5, Laramie Leavitt2, Peter H. Li2, Larry Lindsey2, Nicole Neubarth6, Donald J. Olbris1, Hideo Otsuna1, Eric T. Troutman1, Lowell Umayam1, Ting Zhao1, Masayoshi Ito1,7, Jens Goldammer1,8, Tanya Wolff1, Robert Svirskas1, Philipp Schlegel9, Erika R. Neace1, Christopher J. Knecht, Jr.1, Chelsea X. Alvarado1, Dennis A. Bailey1, Samantha Ballinger1, Jolanta A Borycz3, Brandon S. Canino1, Natasha Cheatham1, Michael Cook1, Marisa Dreher1, Octave Duclos1, Bryon Eubanks1, Kelli Fairbanks1, Samantha Finley1, Nora Forknall1, Audrey Francis1, Gary Patrick Hopkins1, Emily M. Joyce1, SungJin Kim1, Nicole A. Kirk1, Julie Kovalyak1, Shirley A. Lauchie1, Alanna Lohff1, Charli Maldonado1, Emily A. Manley1, Sari McLin3, Caroline Mooney1, Miatta Ndama1, Omotara Ogundeyi1, Nneoma Okeoma1, Christopher Ordish1, Nicholas Padilla1, Christopher Patrick1, Tyler Paterson1, Elliott E. Phillips1, Emily M. Phillips1, Neha Rampally1, Caitlin Ribeiro1, Madelaine K Robertson3, Jon Thomson Rymer1, Sean M. Ryan1, Megan Sammons1, Anne K. Scott1, Ashley L. Scott1, Aya Shinomiya1, Claire Smith1, Kelsey Smith1, Natalie L.