Perspectives in Affective Disorders: Clocks and Sleep
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Association of Locomotor Activity During Sleep Deprivation Treatment with Response
ORIGINAL RESEARCH published: 21 July 2020 doi: 10.3389/fpsyt.2020.00688 Association of Locomotor Activity During Sleep Deprivation Treatment With Response Jerome Clifford Foo 1*, Lea Sirignano 1, Nina Trautmann 1,2,3, Jinhyuk Kim 4, Stephanie H. Witt 1, Fabian Streit 1, Josef Frank 1, Lea Zillich 1, Andreas Meyer-Lindenberg 2, Ulrich Ebner-Priemer 5, Claudia Schilling 2, Michael Schredl 2, Yoshiharu Yamamoto 6, Maria Gilles 2, Michael Deuschle 2 and Marcella Rietschel 1 1 Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany, 2 Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany, 3 Department of Child and Adolescent Psychiatry Edited by: and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Andrea De Bartolomeis, Germany, 4 Department of Informatics, Graduate School of Integrated Science and Technology, Shizuoka University, University of Naples Federico II, Italy Shizuoka, Japan, 5 Department of Sport and Sport Science, Karlsruhe Institute of Technology, Karlsruhe, Germany, 6 Reviewed by: Department of Physical and Health Education, Graduate School of Education, The University of Tokyo, Tokyo, Japan Vincenzo Natale, University of Bologna, Italy Disrupted circadian rhythms and sleep patterns are frequently observed features of Mirko Manchia, University of Cagliari, Italy psychiatric disorders, and especially mood disorders. Sleep deprivation treatment (SD) *Correspondence: exerts rapid but transient antidepressant effects in depressed patients and has gained Jerome Clifford Foo recognition as a model to study quick-acting antidepressant effects. It is of interest how [email protected] locomotor activity patterns during SD might be associated with and potentially predict Specialty section: treatment response. -
New Trends in Connectomics
FOCUS FEATURE: New Trends in Connectomics Editorial: New Trends in Connectomics 1 2,3,4,5 Olaf Sporns and Danielle S. Bassett 1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA 2Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA 3Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA 4Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA 5Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA ABSTRACT Connectomics is an integral part of network neuroscience. The field has undergone rapid Downloaded from http://direct.mit.edu/netn/article-pdf/02/02/125/1092204/netn_e_00052.pdf by guest on 28 September 2021 expansion over recent years and increasingly involves a blend of experimental and computational approaches to brain connectivity. This Focus Feature on “New Trends in an open access journal Connectomics” aims to track the progress of the field and its many applications across different neurobiological systems and species. The idea that connections among neural elements are crucial for brain function has been central to modern neuroscience almost since its inception. Building on this idea, the emerg- ing field of connectomics adds several new and important components. First, connectomics provides comprehensive maps of neural connections, with the ultimate goal of achieving com- plete coverage of any given nervous system. Second, connectomics delivers insights into the principles that underlie network architecture and uncovers how these principles support net- work function. These dual aims can be accomplished through the confluence of new experi- mental techniques for mapping connections and new network science methods for modeling and analyzing the resulting large connectivity datasets. -
Connectomics of Morphogenetically Engineered Neurons As a Predictor of Functional Integration in the Ischemic Brain
http://www.diva-portal.org This is the published version of a paper published in Frontiers in Neurology. Citation for the original published paper (version of record): Sandvig, A., Sandvig, I. (2019) Connectomics of Morphogenetically Engineered Neurons as a Predictor of Functional Integration in the Ischemic Brain Frontiers in Neurology, 10: 630 https://doi.org/10.3389/fneur.2019.00630 Access to the published version may require subscription. N.B. When citing this work, cite the original published paper. Permanent link to this version: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-161446 REVIEW published: 12 June 2019 doi: 10.3389/fneur.2019.00630 Connectomics of Morphogenetically Engineered Neurons as a Predictor of Functional Integration in the Ischemic Brain Axel Sandvig 1,2,3 and Ioanna Sandvig 1* 1 Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway, 2 Department of Neurology, St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway, 3 Department of Pharmacology and Clinical Neurosciences, Division of Neuro, Head, and Neck, Umeå University Hospital, Umeå, Sweden Recent advances in cell reprogramming technologies enable the in vitro generation of theoretically unlimited numbers of cells, including cells of neural lineage and specific neuronal subtypes from human, including patient-specific, somatic cells. Similarly, as demonstrated in recent animal studies, by applying morphogenetic neuroengineering principles in situ, it is possible to reprogram resident brain cells to the desired phenotype. These developments open new exciting possibilities for cell replacement therapy in Edited by: stroke, albeit not without caveats. -
Patient-Tailored Connectomics Visualization for the Assessment of White Matter Atrophy in Traumatic Brain Injury
Patient-Tailored Connectomics Visualization for the Assessment of White Matter Atrophy in Traumatic Brain Injury The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Irimia, Andrei, Micah C. Chambers, Carinna M. Torgerson, Maria Filippou, David A. Hovda, Jeffry R. Alger, Guido Gerig, et al. 2012. Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury. Frontiers in Neurology 3:10. Published Version doi://10.3389/fneur.2012.00010 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:8462352 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA METHODS ARTICLE published: 06 February 2012 doi: 10.3389/fneur.2012.00010 Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury Andrei Irimia1, Micah C. Chambers 1, Carinna M.Torgerson1, Maria Filippou 2, David A. Hovda2, Jeffry R. Alger 3, Guido Gerig 4, Arthur W.Toga1, Paul M. Vespa2, Ron Kikinis 5 and John D. Van Horn1* 1 Laboratory of Neuro Imaging, Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA 2 Brain Injury Research Center, Departments of Neurology and Neurosurgery, University of California Los Angeles, Los Angeles, CA, USA 3 Department of Radiology, David -
Coupling Sleep-Wake and Circadian Neurobiology to the Antidepressant Effects of Ketamine
Pharmacology & Therapeutics 221 (2021) 107741 Contents lists available at ScienceDirect Pharmacology & Therapeutics journal homepage: www.elsevier.com/locate/pharmthera Time is of the essence: Coupling sleep-wake and circadian neurobiology to the antidepressant effects of ketamine S. Kohtala a,b,1, O. Alitalo a,b,1,M.Rosenholma,b, S. Rozov a,b,T.Rantamäkia,b,⁎ a Laboratory of Neurotherapeutics, Drug Research Program, Division of Pharmacology and Pharmacotherapy, Faculty of Pharmacy, University of Helsinki, Finland b SleepWell Research Program, Faculty of Medicine, University of Helsinki, Finland article info abstract Available online 12 November 2020 Several studies have demonstrated the effectiveness of ketamine in rapidly alleviating depression and suicidal ideation. Intense research efforts have been undertaken to expose the precise mechanism underlying the antide- Keywords: pressant action of ketamine; however, the translation of findings into new clinical treatments has been slow. This Sleep translational gap is partially explained by a lack of understanding of the function of time and circadian timing in Circadian the complex neurobiology around ketamine. Indeed, the acute pharmacological effects of a single ketamine treat- Plasticity ment last for only a few hours, whereas the antidepressant effects peak at around 24 hours and are sustained for Depression the following few days. Numerous studies have investigated the acute and long-lasting neurobiological changes Rapid-acting antidepressant Slow-wave sleep induced by ketamine; however, the most dramatic and fundamental change that the brain undergoes each day is rarely taken into consideration. Here, we explore the link between sleep and circadian regulation and rapid-act- ing antidepressant effects and summarize how diverse phenomena associated with ketamine’s antidepressant actions – such as cortical excitation, synaptogenesis, and involved molecular determinants – are intimately con- nected with the neurobiology of wake, sleep, and circadian rhythms. -
Brain Connectivity Meets Reservoir Computing
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.22.427750; this version posted January 23, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Brain Connectivity meets Reservoir Computing Fabrizio Damicelli1, Claus C. Hilgetag1, 2, Alexandros Goulas1 1 Institute of Computational Neuroscience, University Medical Center Hamburg Eppendorf, Hamburg University, Hamburg, Germany 2 Department of Health Sciences, Boston University, Boston, MA, USA * [email protected] Abstract The connectivity of Artificial Neural Networks (ANNs) is different from the one observed in Biological Neural Networks (BNNs). Can the wiring of actual brains help improve ANNs architectures? Can we learn from ANNs about what network features support computation in the brain when solving a task? ANNs’ architectures are carefully engineered and have crucial importance in many recent perfor- mance improvements. On the other hand, BNNs’ exhibit complex emergent connectivity patterns. At the individual level, BNNs connectivity results from brain development and plasticity processes, while at the species level, adaptive reconfigurations during evolution also play a major role shaping connectivity. Ubiquitous features of brain connectivity have been identified in recent years, but their role in the brain’s ability to perform concrete computations remains poorly understood. Computational neuroscience studies reveal the influence of specific brain connectivity features only on abstract dynamical properties, although the implications of real brain networks topologies on machine learning or cognitive tasks have been barely explored. Here we present a cross-species study with a hybrid approach integrating real brain connectomes and Bio-Echo State Networks, which we use to solve concrete memory tasks, allowing us to probe the potential computational implications of real brain connectivity patterns on task solving. -
A Multi-Pass Approach to Large-Scale Connectomics
A Multi-Pass Approach to Large-Scale Connectomics Yaron Meirovitch1;∗;z Alexander Matveev1;∗ Hayk Saribekyan1 David Budden1 David Rolnick1 Gergely Odor1 Seymour Knowles-Barley2 Thouis Raymond Jones2 Hanspeter Pfister2 Jeff William Lichtman3 Nir Shavit1 1Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology 2School of Engineering and Applied Sciences, 3Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University ∗These authors equally contributed to this work zTo whom correspondence should be addressed: [email protected] Abstract The field of connectomics faces unprecedented “big data” challenges. To recon- struct neuronal connectivity, automated pixel-level segmentation is required for petabytes of streaming electron microscopy data. Existing algorithms provide relatively good accuracy but are unacceptably slow, and would require years to extract connectivity graphs from even a single cubic millimeter of neural tissue. Here we present a viable real-time solution, a multi-pass pipeline optimized for shared-memory multicore systems, capable of processing data at near the terabyte- per-hour pace of multi-beam electron microscopes. The pipeline makes an initial fast-pass over the data, and then makes a second slow-pass to iteratively correct errors in the output of the fast-pass. We demonstrate the accuracy of a sparse slow-pass reconstruction algorithm and suggest new methods for detecting mor- phological errors. Our fast-pass approach provided many algorithmic challenges, including the design and implementation of novel shallow convolutional neural nets and the parallelization of watershed and object-merging techniques. We use it to reconstruct, from image stack to skeletons, the full dataset of Kasthuri et al. -
A Critical Look at Connectomics
EDITORIAL A critical look at connectomics There is a public perception that connectomics will translate directly into insights for disease. It is essential that scientists and funding institutions avoid misrepresentation and accurately communicate the scope of their work. onnectomes are generating interest and excitement, both among nervous system, dubbed the classic connectome because it is currently neuroscientists and the public. This September, the first grants the only wiring diagram for an animal’s entire nervous system at the level Cunder the Human Connectome Project, totaling $40 million of the synapse. Although major neurobiological insights have been made over 5 years, were awarded by the US National Institutes of Health using C. elegans and its known connectivity and genome, there are still (NIH). In the public arena, striking, colorful pictures of human brains many questions remaining that can only be answered by hypothesis-driven have accompanied claims that imply that understanding the complete experiments. For example, we still don’t completely understand the process connectivity of the human brain’s billions of neurons by a trillion synapses of axon regeneration, relevant to spinal cord injury in humans, in this is not only possible, but that this will also directly translate into insights comparatively simple system. Thus, a connectome, at any resolution, is for neurological and psychiatric disorders. Even a press release from only one of several complementary tools necessary to understand nervous the NIH touted that the Human Connectome Project would map the system disease and injury. wiring diagram of the entire living human brain and would link these There are substantial efforts aimed at generating connectomes for circuits to the full spectrum of brain function in health and disease. -
Connectomics and Molecular Imaging in Neurodegeneration
European Journal of Nuclear Medicine and Molecular Imaging (2019) 46:2819–2830 https://doi.org/10.1007/s00259-019-04394-5 REVIEW ARTICLE Connectomics and molecular imaging in neurodegeneration Gérard N. Bischof1,2 & Michael Ewers3 & Nicolai Franzmeier3 & Michel J. Grothe4 & Merle Hoenig1,5 & Ece Kocagoncu 6 & Julia Neitzel3 & James B Rowe6,7 & Antonio Strafella8,9,10,11,12 & Alexander Drzezga1,5,13 & Thilo van Eimeren1,13,14 & on behalf of the MINC faculty Received: 29 May 2019 /Accepted: 4 June 2019 / Published online: 11 July 2019 # Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Our understanding on human neurodegenerative disease was previously limited to clinical data and inferences about the underlying pathology based on histopathological examination. Animal models and in vitro experiments have provided evidence for a cell-autonomous and a non-cell-autonomous mechanism for the accumulation of neuropathology. Combining modern neuroimaging tools to identify distinct neural networks (connectomics) with target-specific positron emission tomography (PET) tracers is an emerging and vibrant field of research with the potential to examine the contributions of cell-autonomous and non-cell-autonomous mechanisms to the spread of pathology. The evidence pro- vided here suggests that both cell-autonomous and non-cell-autonomous processes relate to the observed in vivo char- acteristics of protein pathology and neurodegeneration across the disease spectrum. We propose a synergistic model of cell-autonomous and non-cell-autonomous accounts that integrates the most critical factors (i.e., protein strain, suscep- tible cell feature and connectome) contributing to the development of neuronal dysfunction and in turn produces the observed clinical phenotypes. -
Effects of Light Therapy on Mood and Insulin Sensitivity in Patients With
Diabetes Care Volume 42, April 2019 529 Annelies Brouwer,1 Daniel H. van Raalte,2 Effects of Light Therapy on Mood Hoang-Ton Nguyen,3 Femke Rutters,4 CLIN CARE/EDUCATION/NUTRITION/PSYCHOSOCIAL Peter M. van de Ven,4 Petra J.M. Elders,5 and Insulin Sensitivity in Patients Annette C. Moll,3 Eus J.W. Van Someren,1,6,7 Frank J. Snoek,8 With Type 2 Diabetes and Aartjan T.F. Beekman,1 and Depression: Results From a Marijke A. Bremmer1 Randomized Placebo-Controlled Trial Diabetes Care 2019;42:529–538 | https://doi.org/10.2337/dc18-1732 1Amsterdam UMC, Vrije Universiteit, and GGZ inGeest, Department of Psychiatry, Amsterdam Public Health research institute, Amsterdam, the OBJECTIVE Netherlands 2Amsterdam UMC, Vrije Universiteit, Depart- Depression is common in patients with type 2 diabetes and adversely affects ment of Internal Medicine, Diabetes Center, quality of life and diabetes outcomes. We assessed whether light therapy, an Amsterdam, the Netherlands 3 antidepressant, improves mood and insulin sensitivity in patients with depression and Amsterdam UMC, Vrije Universiteit, Depart- ment of Ophthalmology, Amsterdam, the Nether- type 2 diabetes. lands 4Amsterdam UMC, Vrije Universiteit, Depart- RESEARCH DESIGN AND METHODS ment of Epidemiology and Biostatistics, Am- This randomized, double-blind, placebo-controlled trial included 83 patients with sterdam Public Health research institute, depression and type 2 diabetes. The intervention comprised 4 weeks of light Amsterdam, the Netherlands 5Amsterdam UMC, Vrije Universiteit, Depart- therapy (10,000 lux) or placebo light therapy daily at home. Primary outcomes ment of General Practice and Elderly Care included depressive symptoms (Inventory of Depressive Symptomatology [IDS]) Medicine, Amsterdam Public Health research and insulin sensitivity (M-value derived from the results of a hyperinsulinemic- institute, Amsterdam, the Netherlands 6 euglycemic clamp). -
Adam H. Marblestone Adam.H.Marblestone [At] Gmail [Dot] Com
Adam H. Marblestone www.adammarblestone.org Adam.H.Marblestone [at] gmail [dot] com Experience Google DeepMind Research Scientist, Oct 2018- Neuroscience-inspired artificial intelligence. Kernel Chief Strategy Officer, Jan 2017-August 2018 Technologies for interfacing with the human brain. [$53M from leading VCs, 2020] MIT Media Lab Research Scientist and “Director of Scientific Architecting”, Synthetic Neurobiology Group, 2014-2017. Research affiliate, 2017-2020 Advisor: Ed Boyden Inventing methods for scalable and comprehensive brain circuit analysis, in-situ RNA sequencing, protein sequencing, 3D nanofabrication, and neural recording. BioBright LLC Co-founder, 2012-2020 [Acquired by Dotmatics, 2020] “Smart Lab” startup funded by investments, DARPA, and industry contracts. Dana Farber Cancer Institute Intern, 2007 Advisors: William Shih, Shawn Douglas Research on DNA nanotechnology. [Co-authored leading design software for the field, cited over 700 times in the scientific literature.] Education Harvard University Ph.D., Biophysics, 2014 Thesis: Designing scalable biological interfaces Advisor: George Church Research on bio-nanotechnology, synthetic biology and molecular tickertapes. Technology roadmaps for scalable neural recording and connectomics. Yale University B.S., Physics, 2009 Advisor: Michel Devoret Research on quantum information theory and superconducting quantum circuits. Key Publications (* indicates equal contribution) [H-Index: 15, Citations: >2500] Physical principles for scalable neural recording Adam H. Marblestone*, Brad Zamft*, Yael Maguire, Mikhail Shapiro, Josh Glaser, Ted Cybulski, Dario Amodei, P. Benjamin Stranges, Reza Kalhor, David Dalrymple, Dongjin Seo, Elad Alon, Michel M. Maharbiz, Jose M. Carmena, Jan M. Rabaey, Ed Boyden**, George Church**, Konrad Kording** Frontiers in Computational Neuroscience (2013). Featured in Nature Physics. Towards an integration of deep learning and neuroscience Adam H. -
Promisomics and the Short-Circuiting of Mind
Commentary | Cognition and Behavior Promisomics and the Short-Circuiting of Mind https://doi.org/10.1523/ENEURO.0521-20.2021 Cite as: eNeuro 2021; 10.1523/ENEURO.0521-20.2021 Received: 2 December 2020 Revised: 3 January 2021 Accepted: 11 January 2021 This Early Release article has been peer-reviewed and accepted, but has not been through the composition and copyediting processes. The final version may differ slightly in style or formatting and will contain links to any extended data. Alerts: Sign up at www.eneuro.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Copyright © 2021 Gomez-Marin This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. 1 Promisomics and the short-circuiting of mind 2 Alex Gomez-Marin 3 Instituto de Neurociencias de Alicante, SPAIN 4 [email protected] 5 6 (January 6th, 2021) 7 8 9 Significance Statement: Grand neuroscience projects, such as connectomics, have a recurrent 10 tendency to overpromise and underdeliver. Here I critically assess what is done in contrast with 11 what is claimed about such endeavors, especially when the results are "horizontal" and the 12 conclusions "vertical", namely, when maps of one level (synaptic connections) are conflated with 13 mappings between levels (neural function, animal behavior, cognitive processes). I argue that to 14 suggest that connectomics will give us the mind of a mouse, a human or even a fly is 15 theoretically flawed at many levels.