Integrating Hebbian and Homeostatic Plasticity: the Current State of the Field and Future Research Directions
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Rab3a As a Modulator of Homeostatic Synaptic Plasticity
Wright State University CORE Scholar Browse all Theses and Dissertations Theses and Dissertations 2014 Rab3A as a Modulator of Homeostatic Synaptic Plasticity Andrew G. Koesters Wright State University Follow this and additional works at: https://corescholar.libraries.wright.edu/etd_all Part of the Biomedical Engineering and Bioengineering Commons Repository Citation Koesters, Andrew G., "Rab3A as a Modulator of Homeostatic Synaptic Plasticity" (2014). Browse all Theses and Dissertations. 1246. https://corescholar.libraries.wright.edu/etd_all/1246 This Dissertation is brought to you for free and open access by the Theses and Dissertations at CORE Scholar. It has been accepted for inclusion in Browse all Theses and Dissertations by an authorized administrator of CORE Scholar. For more information, please contact [email protected]. RAB3A AS A MODULATOR OF HOMEOSTATIC SYNAPTIC PLASTICITY A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy By ANDREW G. KOESTERS B.A., Miami University, 2004 2014 Wright State University WRIGHT STATE UNIVERSITY GRADUATE SCHOOL August 22, 2014 I HEREBY RECOMMEND THAT THE DISSERTATION PREPARED UNDER MY SUPERVISION BY Andrew G. Koesters ENTITLED Rab3A as a Modulator of Homeostatic Synaptic Plasticity BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Doctor of Philosophy. Kathrin Engisch, Ph.D. Dissertation Director Mill W. Miller, Ph.D. Director, Biomedical Sciences Ph.D. Program Committee on Final Examination Robert E. W. Fyffe, Ph.D. Vice President for Research Dean of the Graduate School Mark Rich, M.D./Ph.D. David Ladle, Ph.D. F. Javier Alvarez-Leefmans, M.D./Ph.D. Lynn Hartzler, Ph.D. -
Are Systems Neuroscience Explanations Mechanistic?
Are Systems Neuroscience Explanations Mechanistic? Carlos Zednik [email protected] Institute of Cognitive Science, University of Osnabrück 49069 Osnabrück, Germany Paper to be presented at: Philosophy of Science Association 24th Biennial Meeting (Chicago, IL), November 2014 Abstract Whereas most branches of neuroscience are thought to provide mechanistic explanations, systems neuroscience is not. Two reasons are traditionally cited in support of this conclusion. First, systems neuroscientists rarely, if ever, rely on the dual strategies of decomposition and localization. Second, they typically emphasize organizational properties over the properties of individual components. In this paper, I argue that neither reason is conclusive: researchers might rely on alternative strategies for mechanism discovery, and focusing on organization is often appropriate and consistent with the norms of mechanistic explanation. Thus, many explanations in systems neuroscience can also be viewed as mechanistic explanations. 1 1. Introduction There is a widespread consensus in philosophy of science that neuroscientists provide mechanistic explanations. That is, they seek the discovery and description of the mechanisms responsible for the behavioral and neurological phenomena being explained. This consensus is supported by a growing philosophical literature on past and present examples from various branches of neuroscience, including molecular (Craver 2007; Machamer, Darden, and Craver 2000), cognitive (Bechtel 2008; Kaplan and Craver 2011), and computational -
Systems Neuroscience of Mathematical Cognition and Learning
CHAPTER 15 Systems Neuroscience of Mathematical Cognition and Learning: Basic Organization and Neural Sources of Heterogeneity in Typical and Atypical Development Teresa Iuculano, Aarthi Padmanabhan, Vinod Menon Stanford University, Stanford, CA, United States OUTLINE Introduction 288 Ventral and Dorsal Visual Streams: Neural Building Blocks of Mathematical Cognition 292 Basic Organization 292 Heterogeneity in Typical and Atypical Development 295 Parietal-Frontal Systems: Short-Term and Working Memory 296 Basic Organization 296 Heterogeneity in Typical and Atypical Development 299 Lateral Frontotemporal Cortices: Language-Mediated Systems 302 Basic Organization 302 Heterogeneity in Typical and Atypical Development 302 Heterogeneity of Function in Numerical Cognition 287 https://doi.org/10.1016/B978-0-12-811529-9.00015-7 © 2018 Elsevier Inc. All rights reserved. 288 15. SYSTEMS NEUROSCIENCE OF MATHEMATICAL COGNITION AND LEARNING The Medial Temporal Lobe: Declarative Memory 306 Basic Organization 306 Heterogeneity in Typical and Atypical Development 306 The Circuit View: Attention and Control Processes and Dynamic Circuits Orchestrating Mathematical Learning 310 Basic Organization 310 Heterogeneity in Typical and Atypical Development 312 Plasticity in Multiple Brain Systems: Relation to Learning 314 Basic Organization 314 Heterogeneity in Typical and Atypical Development 315 Conclusions and Future Directions 320 References 324 INTRODUCTION Mathematical skill acquisition is hierarchical in nature, and each iteration of increased proficiency builds on knowledge of a lower-level primitive. For example, learning to solve arithmetical operations such as “3 + 4” requires first an understanding of what numbers mean and rep- resent (e.g., the symbol “3” refers to the quantity of three items, which derives from the ability to attend to discrete items in the environment). -
A Meta-Analysis of Functional MRI Results
RESEARCH Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results 1 1 1 2 Katherine L. Bottenhorn , Jessica S. Flannery , Emily R. Boeving , Michael C. Riedel , 3,4 1 2 Simon B. Eickhoff , Matthew T. Sutherland , and Angela R. Laird 1Department of Psychology, Florida International University, Miami, FL, USA 2Department of Physics, Florida International University, Miami, FL, USA 3Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Downloaded from http://direct.mit.edu/netn/article-pdf/3/1/27/1092290/netn_a_00050.pdf by guest on 01 October 2021 4Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany an open access journal Keywords: Neuroimaging meta-analysis, Naturalistic paradigms, Clustering analysis, Neuro- informatics ABSTRACT Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use Citation: Bottenhorn, K. L., Flannery, highly controlled tasks to isolate mental processes of interest. However, a growing literature J. S., Boeving, E. R., Riedel, M. C., Eickhoff, S. B., Sutherland, M. T., & shows how dynamic, interactive tasks have allowed researchers to study cognition as it more Laird, A. R. (2019). Cooperating yet naturally occurs. Collective analysis across such neuroimaging experiments may answer distinct brain networks engaged during naturalistic paradigms: broader questions regarding how naturalistic cognition is biologically distributed throughout A meta-analysis of functional MRI k results. Network Neuroscience, the brain. We applied an unbiased, data-driven, meta-analytic approach that uses -means 3(1), 27–48. -
Systems Processes and Pathologies: Creating an Integrated Framework for Systems Science
IS13-SysProc&Path-Troncale.docx Page 1 of 24 Systems Processes and Pathologies: Creating An Integrated Framework for Systems Science Dr. Len Troncale Professor Emeritus and Past Chair, Biological Sciences Director, Institute for Advanced Systems Science California State Polytechnic University, Pomona, California, 91711 [email protected] Copyright © 2013 by Len Troncale. Published and used by INCOSE with permission Abstract. Among the several official projects of the INCOSE Systems Science Working Group, one focuses on integrating the plethora of systems theories, sources, approaches, and tools developed over the past half-century with the purpose of enabling a new and unified “science” of systems as a fundamental basis for SE. Another seeks to develop a much more SE-usable Systems Pathology also grounded in a “science” of systems. This paper introduces the wider SE community to the current status of this unique knowledge base produced over the past three years by an INCOSE-ISSS alliance summarizing the current output of 7 Workshops, 12 Papers, >24 Presentations or Webinars, and 5 Reports. It describes the need for integration of systems knowledge by demonstrating the extensive fragmentation of numerous contributing fields. It presents the current 12-step “protocol” used by the current group to guide its efforts at synthesis across systems domains, disciplines, tools, and scales asking for feedback to improve the approach. It introduces 15 Working Assumptions or Hypotheses that form the foundation for this attempt at unification citing why these could be used as working principles but why it may be undesirable to call them “principles” as others often do. The paper presents working frameworks for integration and criteria used to judge whether results are a “science” of systems or not with reminders that these early guidelines are being subjected to constant testing and revision. -
Disruption of NMDA Receptor Function Prevents Normal Experience
Research Articles: Development/Plasticity/Repair Disruption of NMDA receptor function prevents normal experience-dependent homeostatic synaptic plasticity in mouse primary visual cortex https://doi.org/10.1523/JNEUROSCI.2117-18.2019 Cite as: J. Neurosci 2019; 10.1523/JNEUROSCI.2117-18.2019 Received: 16 August 2018 Revised: 7 August 2019 Accepted: 8 August 2019 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.jneurosci.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Copyright © 2019 the authors Rodriguez et al. 1 Disruption of NMDA receptor function prevents normal experience-dependent homeostatic 2 synaptic plasticity in mouse primary visual cortex 3 4 Gabriela Rodriguez1,4, Lukas Mesik2,3, Ming Gao2,5, Samuel Parkins1, Rinki Saha2,6, 5 and Hey-Kyoung Lee1,2,3 6 7 8 1. Cell Molecular Developmental Biology and Biophysics (CMDB) Graduate Program, 9 Johns Hopkins University, Baltimore, MD 21218 10 2. Department of Neuroscience, Mind/Brain Institute, Johns Hopkins University, Baltimore, 11 MD 21218 12 3. Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 13 21218 14 4. Current address: Max Planck Florida Institute for Neuroscience, Jupiter, FL 33458 15 5. Current address: Division of Neurology, Barrow Neurological Institute, Pheonix, AZ 16 85013 17 6. Current address: Department of Psychiatry, Columbia University, New York, NY10032 18 19 Abbreviated title: NMDARs in homeostatic synaptic plasticity of V1 20 21 Corresponding Author: Hey-Kyoung Lee, Ph.D. -
SYSTEMS NEUROSCIENCE (FALL 2018) [Neurobio 208 and Anat 210]
SYSTEMS NEUROSCIENCE (FALL 2018) [Neurobio 208 and Anat 210] Neurbio 208 is required for 1st year graduate students in Neurobiology and Behavior and serves as “S” area core courses for the INP. Anat 210 is open to all graduate students in Anatomy and Neurobiology. Graduate students from other departments may enroll in either Neurbio 208 or Anat 210 with permission from the course director, Dr. Ron Frostig. Time/place: 9:00-10:20AM, MWF in MH 2246 Text: Neuroscience, 6th Edition, Purves, D. et al. (Eds.) Sinauer, 2017. The instructors will distribute other readings. Exams and grading: The final grade will be based on performance on the midterm exams. The instructor for that section will announce the format of each exam. Exams will be predominately essay. There will be no cumulative final exam, and grades will be normalized to the number of lectures leading to the midterm. Final grade will be based on averaging of all midterms. Participating Faculty: Neurobiology & Behavior Anatomy & Neurobiology Ron Frostig, director Steve Cramer Steve Mahler Fall 2018 Date Topic Instructor Readings (in text unless noted) Fri Principles of Mahler https://my.rocketmix.com/enrollcourse.aspx?courseid=3087 9/28 Brain --Please enroll in this and look at it BEFORE CLASS Organization Other helpful resources: http://zoomablebrain.bio.uci.edu/ http://www.exploratorium.edu/memory/braindissection/ Mon Neuroanatomy- Mahler William James, 1890, chapter 2 (http://psychclassics.yorku.ca/ 10/1 Dissection James/Principles/prin2.htm) Wed Introduction to Frostig 10/3 sensory systems Fri The eye: Frostig Ch.11 10/5 structure and function Mon The eye: Frostig Ch.11 10/8 structure and function Wed Central visual Frostig Ch.12 10/10 pathways I Fri Central visual Frostig Ch. -
Systems Neuroscience of Natural Behaviors in Rodents
The Journal of Neuroscience, February 3, 2021 • 41(5):911–919 • 911 Symposium/Mini-Symposium Systems Neuroscience of Natural Behaviors in Rodents Emily Jane Dennis,1 Ahmed El Hady,1 Angie Michaiel,2 Ann Clemens,3 Dougal R. Gowan Tervo,4 Jakob Voigts,5 and Sandeep Robert Datta6 1Princeton University and Howard Hughes Medical Institute, Princeton, New Jersey, 08540, 2University of Oregon, Eugene, Oregon, 97403-1254, 3University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, 4Janelia Research Campus, Ashburn, Virginia, 20147, 5Massachusetts Institute of Technology, Cambridge, Massachusets, 02139, and 6Harvard University, Cambridge, Massachusets, 02115 Animals evolved in complex environments, producing a wide range of behaviors, including navigation, foraging, prey capture, and conspecific interactions, which vary over timescales ranging from milliseconds to days. Historically, these behaviors have been the focus of study for ecology and ethology, while systems neuroscience has largely focused on short timescale behaviors that can be repeated thousands of times and occur in highly artificial environments. Thanks to recent advances in machine learning, miniaturization, and computation, it is newly possible to study freely moving animals in more natural conditions while applying systems techniques: performing temporally specific perturbations, modeling behavioral strategies, and record- ing from large numbers of neurons while animals are freely moving. The authors of this review are a group of scientists with deep appreciation for the common aims of systems neuroscience, ecology, and ethology. We believe it is an extremely exciting time to be a neuroscientist, as we have an opportunity to grow as a field, to embrace interdisciplinary, open, collaborative research to provide new insights and allow researchers to link knowledge across disciplines, species, and scales. -
Systems Neuroscience of Natural Behaviors in Rodents
Systems Neuroscience of Natural Behaviors in Rodents 1,2 1,2 3 4 Emily Jane Dennis* , Ahmed El Hady , Angie Michaiel , Ann Clemens , Dougal R. Gowan 5 6 3 Tervo , Jakob Voigts , and Sandeep Robert Datta Abstract Animals evolved in complex environments, producing a wide range of behaviors, including navigation, foraging, prey capture, and conspecific interactions, which vary over timescales ranging from milliseconds to days. Historically, these behaviors have been the focus of study for ecology and ethology, while systems neuroscience has largely focused on short timescale behaviors that can be repeated thousands of times and occur in highly artificial environments.Thanks to recent advances in machine learning, miniaturization, and computation, it is newly possible to study freely-moving animals in more natural conditions while applying systems techniques: performing temporally-specific perturbations, modeling behavioral strategies, and recording from large numbers of neurons while animals are freely moving. The authors of this review are a group of scientists with deep appreciation for the common aims of systems neuroscience, ecology, and ethology. We believe it is an extremely exciting time to be a neuroscientist, as we have an opportunity to grow as a field, to embrace interdisciplinary, open, collaborative research to provide new insights and allow researchers to link knowledge across disciplines, species, and scales. Here we discuss the origins of ethology, ecology, and systems neuroscience in the context of our own work and highlight how combining approaches across these fields has provided fresh insights into our research. We hope this review facilitates some of these interactions and alliances and helps us all do even better science, together. -
Conceptual Nervous System”: Can Computational Cognitive Neuroscience Transform Learning Theory?
Beyond the “Conceptual Nervous System”: Can Computational Cognitive Neuroscience Transform Learning Theory? Fabian A. Sotoa,∗ aDepartment of Psychology, Florida International University, 11200 SW 8th St, AHC4 460, Miami, FL 33199 Abstract In the last century, learning theory has been dominated by an approach assuming that associations between hypothetical representational nodes can support the acquisition of knowledge about the environment. The similarities between this approach and connectionism did not go unnoticed to learning theorists, with many of them explicitly adopting a neural network approach in the modeling of learning phenomena. Skinner famously criticized such use of hypothetical neural structures for the explanation of behavior (the “Conceptual Nervous System”), and one aspect of his criticism has proven to be correct: theory underdetermination is a pervasive problem in cognitive modeling in general, and in associationist and connectionist models in particular. That is, models implementing two very different cognitive processes often make the exact same behavioral predictions, meaning that important theoretical questions posed by contrasting the two models remain unanswered. We show through several examples that theory underdetermination is common in the learning theory literature, affecting the solvability of some of the most important theoretical problems that have been posed in the last decades. Computational cognitive neuroscience (CCN) offers a solution to this problem, by including neurobiological constraints in computational models of behavior and cognition. Rather than simply being inspired by neural computation, CCN models are built to reflect as much as possible about the actual neural structures thought to underlie a particular behavior. They go beyond the “Conceptual Nervous System” and offer a true integration of behavioral and neural levels of analysis. -
Open Science Offer New Hope for Meaningful Scientific Engagement on an International Scale
Welcome Messages On behalf of our entire Steering Committee, it is a pleasure to welcome you to the second meeting of the Global Brain Consortium (GBC). As we pointed out in our previous encounter, numerous workshops in recent years that tackle some of biggest questions in neuroscience. Recent advances in information technology to mediate data-sharing, dedicated support from funders, and a burgeoning culture of Open Science offer new hope for meaningful scientific engagement on an international scale. However, bringing scientists across the globe together to work collectively has been difficult - for a variety of technical, logistical, ethical and sociopolitical reasons. We must work together – scientists, technology developers and Alan Evans, Co - Chair Pedro Valdes-Sosa, Co- Chair funders - to shape strategies that bridge operational gaps and expand access Global Brain Consortium Global Brain Consortium to health resources. This is why we have come together in Varadero, Cuba today Finding a place to begin that provides an opportunity for us to have a scientific focus, tackle major technological challenges and enhance global impact is a delicate balancing act. Modern neuroscience has a considerable arsenal of theoretical, modelling and neuroimaging technologies, but many of these devices are not readily available in Lower- and Middle-Income Countries (LMIC). Fortunately, access to an array of digital and neuro-technologies, enhanced in recent years thanks to the investment of the Big Brain initiatives, may allow us to cross this critical divide. This in turn will open collaborative opportunities for neuroscientists and clinicians in LMIC who have been somewhat marginalized from previous efforts in global collaboration. -
Decoupling of Brain Function from Structure Reveals Regional
Decoupling of brain function from structure reveals re- gional behavioral specialization in humans 1,2 1,2 Maria Giulia Preti∗ & Dimitri Van De Ville 1Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fed´ erale´ de Lausanne (EPFL), Lausanne, Switzerland 2Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland *corresponding author. e-mail address: maria.preti@epfl.ch Full Postal Adresses: Maria Giulia Preti: EPFL STI IBI-STI MIPLAB H4 3 228.084 (Campus Biotech bati- ment H4), Ch. des Mines 9, CH-1202 Geneva, Switzerland Dimitri Van De Ville: Campus Biotech, Chemin des Mines 9, Case postale 60, CH-1211 Geneva 20, Switzerland arXiv:1905.07813v2 [q-bio.NC] 10 Sep 2019 1 Abstract The brain is an assembly of neuronal populations interconnected by structural pathways. Brain activity is expressed on and constrained by this substrate. Therefore, statistical de- pendencies between functional signals in directly connected areas can be expected higher. However, the degree to which brain function is bound by the underlying wiring diagram remains a complex question that has been only partially answered. Here, we introduce the structural-decoupling index to quantify the coupling strength between structure and func- tion, and we reveal a macroscale gradient from brain regions more strongly coupled, to regions more strongly decoupled, than expected by realistic surrogate data. This gradient spans behavioral domains from lower-level sensory function to high-level cognitive ones and shows for the first time that the strength of structure-function coupling is spatially varying in line with evidence derived from other modalities, such as functional connectiv- ity, gene expression, microstructural properties and temporal hierarchy.