DOCSLIB.ORG

Altersabhängigkeit Der Impliziten, Sequentiellen Lern- Und Gedächtnisleistung Bei Gesunden Probanden

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Altersabhängigkeit Der Impliziten, Sequentiellen Lern- Und Gedächtnisleistung Bei Gesunden Probanden Aus der Klinik für Neurologie Direktor: Professor Dr. med. L. Timmermann Fachbereich Medizin der Philipps-Universität Marburg in Zusammenarbeit mit dem Universitätsklinikum Gießen und Marburg GmbH Standort Marburg Altersabhängigkeit der impliziten, sequentiellen Lern- und Gedächtnisleistung bei gesunden Probanden Implementierung eines standardisierten Normkollektivs für den seriellen Reaktionszeittest Inaugural-Dissertation Zur Erlangung des Doktorgrades der gesamten Humanmedizin dem Fachbereich Medizin der Philipps-Universität Marburg vorgelegt von Moritz Philipp Böhringer aus Saarbrücken Marburg, 2020 Angenommen vom Fachbereich Medizin der Philipps-Universität Marburg am 27.11.2020 Gedruckt mit Genehmigung des Fachbereichs. Dekan: i.V. der Prodekan Prof. Dr. R. Müller Referent: Prof. Dr. F. Rosenow Korreferent: PD Dr. D. Leube Altersabhängigkeit der impliziten, sequentiellen Lern- und Gedächtnisleistung bei gesunden Probanden Abkürzungsverzeichnis ................................................................................................. 6 1. Einleitung .................................................................................................................. 8 1.1. Lernen und Gedächtnis ...................................................................................... 8 1.2. Einteilung des Gedächtnisses ............................................................................ 8 1.2.1. Explizites und implizites Gedächtnis .............................................................. 11 1.2.2. Erfassen des impliziten Gedächtnisses ......................................................... 13 1.2.3. Neuroanatomische Zuordnung des sequentiellen Lernens ............................ 15 1.2.4 Rolle des Striatums ........................................................................................ 17 1.2.5. Rolle des Hippocampus ................................................................................. 18 1.2.5.1. Dissoziation ................................................................................................ 19 1.2.5.2. Interaktion................................................................................................... 19 1.2.5.3. Konkurrenz ................................................................................................. 20 1.2.5.4. Hippokampektomie ..................................................................................... 20 1.2.5. Aktuelle Studienlage ...................................................................................... 21 1.3. Stichproben und Normkollektiv ......................................................................... 22 1.3.1. Problematik geeigneter Vergleichsgruppen ................................................... 22 1.3.2. Parallelisierte Stichproben ............................................................................. 22 1.3.3. Unabhängige Gruppe .................................................................................... 23 1.3.4. Normstichproben ........................................................................................... 24 1.4. Fragestellung und Hypothesen ......................................................................... 24 2. Methoden ................................................................................................................ 25 2.1. Probanden ........................................................................................................ 26 2.2. Ausschlusskriterien .......................................................................................... 27 2.3. Aufklärung und Anonymisierung ....................................................................... 28 2.4. Ablauf der Studie .............................................................................................. 29 2.5. Standardisierte SRTT-Version dieser Studie .................................................... 29 2.5.1. Technische Details und Durchführung des SRTT .......................................... 30 2.5.1.2. Auswertung des SRTT................................................................................ 32 2.5.1.3. Bestimmung der impliziten Lernleistung ..................................................... 32 2.5.2. Generation Task (GT) .................................................................................... 34 2.6 Verbaler Lern und Merkfähigkeitstest (VLMT) ................................................... 34 2.7 Edinburgh Handedness Inventory (EHI) ............................................................ 35 2.8 Strukturiertes Interview ...................................................................................... 36 2.9 Archivierung ...................................................................................................... 37 3. Statistik ................................................................................................................... 37 4. Ergebnis ................................................................................................................. 39 3 Altersabhängigkeit der impliziten, sequentiellen Lern- und Gedächtnisleistung bei gesunden Probanden 4.1 Probandencharakteristik .................................................................................... 39 4.1.1 Altersverteilung ............................................................................................... 39 4.1.2. Geschlechterverteilung .................................................................................. 39 4.1.3. Bildungsniveau .............................................................................................. 39 4.1.4. Händigkeit ..................................................................................................... 40 4.1.5. Neuropsychiatrische Familienanamnese ....................................................... 40 4.2. Messung des expliziten verbalen Lernens ........................................................ 41 4.3.1. Implizites Lernen beim SRTT ........................................................................ 44 4.3.1.1. Reaktionszeit der Gesamtgruppe ............................................................... 44 4.3.1.1. Fehlerrate der Gesamtgruppe..................................................................... 46 4.3.1.2. Verlauf der Reaktionszeit pro Altersgruppe................................................. 46 4.3.1.2.1. Erste Altersgruppe (18-30 Jahre) ............................................................. 46 4.3.1.2.2. Zweite Altersgruppe (31-40 Jahre)........................................................... 47 4.3.1.2.3. Dritte Altersgruppe (41-50 Jahre) ............................................................ 49 4.3.1.2.4. Vierte Altersgruppe (51-60 Jahre) ............................................................ 49 4.3.1.2.5. Fünfte Altersgruppe (61-75 Jahre) ........................................................... 51 4.3.2.1. Vergleich der RZ pro Block und Altersgruppe ............................................. 51 4.3.2.2. Altersabhängigkeit ...................................................................................... 52 4.3.2.3. Post-hoc-Analyse in Bezug auf den Faktor Altersgruppe ............................ 53 4.3.3. Analyse der Fehlerraten ................................................................................ 54 4.3.3.1. Verlauf der Fehlerrate pro Altersgruppe ...................................................... 54 4.3.3.1.1. Erste Altersgruppe (18-30 Jahre) ............................................................. 54 4.3.3.1.2. Zweite Altersgruppe (31-40 Jahre)........................................................... 55 4.3.1.2.3. Dritte Altersgruppe (41-50 Jahre) ............................................................ 55 4.3.1.2.4. Vierte Altersgruppe 51-60 Jahre) ............................................................. 56 4.3.1.2.5. Fünfte Altersgruppe (61-75 Jahre) ........................................................... 56 4.3.1.3. Vergleich anhand der Fehlerrate ................................................................ 57 4.4 Bestimmung des impliziten Lernens .................................................................. 58 4.4.1. Reaktionszeitanalyse relevanter Blöcke 5,6,7 ................................................ 58 4.4.2.1 Implizites Lernen anhand der Reaktionszeit ................................................ 60 4.4.2.2 Implizites Lernen anhand der Fehlerrate ..................................................... 61 4.5. Einflussfaktoren auf das implizite Lernen .......................................................... 63 4.5.1 Händigkeit ...................................................................................................... 63 4.5.2 Computeraktivität ........................................................................................... 63 4.5.3. Instrumentale Fähigkeit ................................................................................. 63 4.5.4. Medikamenteneinnahme ............................................................................... 63 4 Altersabhängigkeit der impliziten, sequentiellen Lern- und Gedächtnisleistung bei gesunden Probanden 4.6. Korrelation explizites Lernen (VLMT) und implizites Lernen (SRTT) ................. 64 4.7. Generation task (GT) ........................................................................................ 66 4.8. Subjektive Einschätzung der Lernleistung ........................................................ 67 4.9 Verwendung des Normkollektivs
Load more

Recommended publications
  • The Cognitive Neuroscience of Music
    THE COGNITIVE NEUROSCIENCE OF MUSIC Isabelle Peretz Robert J. Zatorre Editors OXFORD UNIVERSITY PRESS Zat-fm.qxd 6/5/03 11:16 PM Page i THE COGNITIVE NEUROSCIENCE OF MUSIC This page intentionally left blank THE COGNITIVE NEUROSCIENCE OF MUSIC Edited by ISABELLE PERETZ Départment de Psychologie, Université de Montréal, C.P. 6128, Succ. Centre-Ville, Montréal, Québec, H3C 3J7, Canada and ROBERT J. ZATORRE Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada 1 Zat-fm.qxd 6/5/03 11:16 PM Page iv 1 Great Clarendon Street, Oxford Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide in Oxford New York Auckland Bangkok Buenos Aires Cape Town Chennai Dar es Salaam Delhi Hong Kong Istanbul Karachi Kolkata Kuala Lumpur Madrid Melbourne Mexico City Mumbai Nairobi São Paulo Shanghai Taipei Tokyo Toronto Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries Published in the United States by Oxford University Press Inc., New York © The New York Academy of Sciences, Chapters 1–7, 9–20, and 22–8, and Oxford University Press, Chapters 8 and 21. Most of the materials in this book originally appeared in The Biological Foundations of Music, published as Volume 930 of the Annals of the New York Academy of Sciences, June 2001 (ISBN 1-57331-306-8). This book is an expanded version of the original Annals volume. The moral rights of the author have been asserted Database right Oxford University Press (maker) First published 2003 All rights reserved.
    [Show full text]
  • Why Digit Span Measures Long-Term Associative Learning
    Cognition 144 (2015) 1–13 Contents lists available at ScienceDirect Cognition journal homepage: www.elsevier.com/locate/COGNIT Questioning short-term memory and its measurement: Why digit span measures long-term associative learning ⇑ Gary Jones a, , Bill Macken b a Nottingham Trent University, UK b Cardiff University, UK article info abstract Article history: Traditional accounts of verbal short-term memory explain differences in performance for different types Received 23 December 2014 of verbal material by reference to inherent characteristics of the verbal items making up memory Revised 13 July 2015 sequences. The role of previous experience with sequences of different types is ostensibly controlled Accepted 15 July 2015 for either by deliberate exclusion or by presenting multiple trials constructed from different random per- mutations. We cast doubt on this general approach in a detailed analysis of the basis for the robust find- ing that short-term memory for digit sequences is superior to that for other sequences of verbal material. Keywords: Specifically, we show across four experiments that this advantage is not due to inherent characteristics of Digit span digits as verbal items, nor are individual digits within sequences better remembered than other types of Associative learning Short-term memory individual verbal items. Rather, the advantage for digit sequences stems from the increased frequency, Long-term memory compared to other verbal material, with which digits appear in random sequences in natural language, Sequence learning and furthermore, relatively frequent digit sequences support better short-term serial recall than less fre- Computational modelling quent ones. We also provide corpus-based computational support for the argument that performance in a short-term memory setting is a function of basic associative learning processes operating on the linguis- tic experience of the rememberer.
    [Show full text]
  • The Relationship Between Mood and Implicit Learning
    UNLV Theses, Dissertations, Professional Papers, and Capstones May 2017 The Relationship Between Mood and Implicit Learning Kathleen Larson University of Nevada, Las Vegas Follow this and additional works at: https://digitalscholarship.unlv.edu/thesesdissertations Part of the Cognitive Psychology Commons, and the Experimental Analysis of Behavior Commons Repository Citation Larson, Kathleen, "The Relationship Between Mood and Implicit Learning" (2017). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3003. http://dx.doi.org/10.34917/10985984 This Dissertation is protected by copyright and/or related rights. It has been brought to you by Digital Scholarship@UNLV with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/or on the work itself. This Dissertation has been accepted for inclusion in UNLV Theses, Dissertations, Professional Papers, and Capstones by an authorized administrator of Digital Scholarship@UNLV. For more information, please contact [email protected]. THE RELATIONSHIP BETWEEN MOOD AND IMPLICIT LEARNING By Kathleen G. Larson Bachelor of Arts – Psychology Indiana University of Pennsylvania 2011 Master of Arts – Psychology University of Nevada, Las Vegas 2014 A dissertation submitted in partial fulfillment of
    [Show full text]
  • New Learning of Music After Bilateral Medial Temporal Lobe Damage: Evidence from an Amnesic Patient
    ORIGINAL RESEARCH ARTICLE published: 03 September 2014 HUMAN NEUROSCIENCE doi: 10.3389/fnhum.2014.00694 New learning of music after bilateral medial temporal lobe damage: evidence from an amnesic patient Jussi Valtonen1*, Emma Gregory 2, Barbara Landau 2 and Michael McCloskey 2 1 Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland 2 Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, USA Edited by: Damage to the hippocampus impairs the ability to acquire new declarative memories, but Isabelle Peretz, Université de not the ability to learn simple motor tasks. An unresolved question is whether hippocampal Montréal, Canada damage affects learning for music performance, which requires motor processes, but in a Reviewed by: cognitively complex context. We studied learning of novel musical pieces by sight-reading Séverine Samson, Université de Lille, France in a newly identified amnesic, LSJ, who was a skilled amateur violist prior to contract- Aline Moussard, Rotman Research ing herpes simplex encephalitis. LSJ has suffered virtually complete destruction of the Institute, Canada hippocampus bilaterally, as well as extensive damage to other medial temporal lobe struc- *Correspondence: tures and the left anterior temporal lobe. Because of LSJ’s rare combination of musical Jussi Valtonen, Institute of Behavioural Sciences, University of training and near-complete hippocampal destruction, her case provides a unique oppor- Helsinki, P.O. Box 9, Helsinki tunity to investigate the role of the hippocampus for complex motor learning processes FI-00014, Finland specifically related to music performance. Three novel pieces of viola music were com- e-mail: jussi.valtonen@helsinki.fi posed and closely matched for factors contributing to a piece’s musical complexity.
    [Show full text]
  • Differentiating Visual from Response Sequencing During Long-Term Skill Learning
    Differentiating Visual from Response Sequencing during Long-term Skill Learning Brighid Lynch1, Patrick Beukema2, and Timothy Verstynen1 Abstract ■ The dual-system model of sequence learning posits that dur- order of key presses across training days), Combined (same ing early learning there is an advantage for encoding sequences serial order of cues and responses on all training days), and a in sensory frames; however, it remains unclear whether this ad- Control group (a novel sequence each training day). Across 5 days vantage extends to long-term consolidation. Using the serial RT of training, sequence-specific measures of response speed and task, we set out to distinguish the dynamics of learning sequen- accuracy improved faster in the Visual group than any of the tial orders of visual cues from learning sequential responses. On other three groups, despite no group differences in explicit each day, most participants learned a new mapping between awareness of the sequence. The two groups that were exposed a set of symbolic cues and responses made with one of four to the same visual sequence across days showed a marginal im- fingers, after which they were exposed to trial blocks of either provement in response binding that was not found in the other randomly ordered cues or deterministic ordered cues (12-item groups. These results indicate that there is an advantage, in sequence). Participants were randomly assigned to one of four terms of rate of consolidation across multiple days of training, groups (n = 15 per group): Visual sequences (same sequence for learning sequences of actions in a sensory representational of visual cues across training days), Response sequences (same space, rather than as motoric representations.
    [Show full text]
  • Attention and Structure in Sequence Learning
    Journal of Experimental Psychology: Copyright 1990 by the American Psychological Association, Inc. Learning, Memory, and Cognition 0278-7393/90/$00.75 1990, Vol. 16, No. 1, 17-30 Attention and Structure in Sequence Learning Asher Cohen, Richard I. Ivry, and Steven W. Keele University of Oregon In this study we investigated the role of attention, sequence structure, and effector specificity in learning a structured sequence of actions. Experiment 1 demonstrated that simple structured sequences can be learned in the presence of attentional distraction. The learning is unaffected by variation in distractor task difficulty, and subjects appear unaware of the structure. The structured sequence knowledge transfers from finger production to arm production {Experiment 2), sug- gesting that sequence specification resides in an effector-independent system. Experiments 3 and 4 demonstrated that only structures with at least some unique associations (e.g., any association in Structure 15243... or 4 to 3 in Structure 143132...) can be learned under attentional distraction. Structures with all items repeated in different orders in different parts of the structure (e.g., Sequence 132312...) require attention for learning. Such structures may require hierarchic representation, the construction of which takes attention. One of the remarkable capabilities of humans is their ability four keys in response to an asterisk at one of four spatial to learn a variety of novel tasks involving complex motor positions. In one condition, the signals came on in a particular sequences. They learn to play the violin, knit, serve tennis sequence of 10 events, with the same order repeating cyclically balls, and perform a variety of language tasks such as speaking, (hereafter, structured sequence).
    [Show full text]
  • Facial Feedback in Implicit Sequence Learning
    International Journal of Psychology & Psychological Therapy, 2013, 13, 2, 145-162 Printed in Spain. All rights reserved. Copyright © 2013 AAC Facial Feedback in Implicit Sequence Learning Christina Bermeitinger, Anna-Maria Machmer, Julia Schramm, Dennis Mertens D. Luisa Wilborn, Larissa Bonin, Heidi Femppel, Friederike Koch University of Hildesheim, Germany ABSTRACT There is continuous debate how closely or loosely emotion is linked to behavior and especially to facial expressions. In strong versions of the so-called facial feedback hypothesis, it is assumed that facial activity can intensify, modulate and initiate emotions. The hypothesis has been largely investigated with various emotions, however, surprise was tested only in a few studies. Additionally, it has been discussed frequently how obtrusively manipulations of facial feedback as well as the dependent measures are. Thus, in the present experiment we analyzed whether unobtrusive facial feedback of surprise versus no-surprise can modulate reactions following deviations in an implicit sequence learning task. Participants had to quickly and accurately press keys which corresponded to one of four letters appearing at the screen. After several blocks in which a standard sequence (consisting of a predefined order of 12 letters) was repeated, standard sequences and deviation sequences (i.e. one element differed from the standard sequence) were intermixed. The results confirmed our hypothesis: Participants of the surprise face condition showed longer reaction times to deviation sequences than to standard sequences. In contrast, participants of the no-surprise face condition did not show this difference in reaction times. Results were discussed with respect to implicit learning as well as to theories on emotion and facial feedback taking the special status of surprise into account.
    [Show full text]
  • Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives
    Human Movement Science 23 (2004) 699–746 www.elsevier.com/locate/humov Learning and production of movement sequences: Behavioral, neurophysiological, and modeling perspectives Bradley J. Rhodes a, Daniel Bullock a,*, Willem B. Verwey b, Bruno B. Averbeck c, Michael P.A. Page d a Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA 02215, USA b Department of Psychonomics and Human Performance, University of Twente, 7500 AE Enschede, The Netherlands c Center for Visual Science, Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627-0270, USA d Psychology Department, University of Hertfordshire, Hatfield AL10 9AB, UK Abstract A wave of recent behavioral studies has generated a new wealth of parametric observations about serial order behavior. What was a trickle of neurophysiological studies has grown to a steady stream of probes of neural sites and mechanisms underlying sequential behavior. More- over, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we review major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2 · N, discrete sequence production, and serial reaction time. These tasks populate a contin- uum from higher to lower degrees of internal control of sequential organization and probe important contemporary issues such as the nature of working-memory representations for sequential behavior, and the development and role of chunks in hierarchical control. The main movement classes reviewed are speech and keypressing, both involving small amplitude move- ments amenable to parametric study. A synopsis of serial order models, vis-a`-vis major * Corresponding author.
    [Show full text]
  • Sequence Learning in Pianists and Nonpianists: an Fmri Study of Motor Expertise
    JournalCognitive, Affective, & Behavioral Neuroscience 2006, ??6 (3), (?), 246-259 ???-??? Sequence learning in pianists and nonpianists: An fMRI study of motor expertise SUSAN M. LANDAU and MARK D’ESPOSITO University of California, Berkeley, California Previous studies of motor learning have proposed a distinction between fast and slow learning, but these mechanisms have rarely been examined simultaneously. We examined the influence of long- term motor expertise (slow learning) while pianists and nonpianists performed alternating epochs of sequenced and random keypresses in response to visual cues (fast learning) during functional neuro- imaging. All of the participants demonstrated learning of the sequence as demonstrated by decreasing reaction times (RTs) on sequence trials relative to random trials throughout the session. Pianists also demonstrated faster RTs and superior sequence acquisition in comparison with nonpianists. Within- session decreases in bilateral sensorimotor and parietal activation were observed for both groups. Additionally, there was more extensive activation throughout the session for pianists in comparison with nonpianists across a network of primarily right-lateralized prefrontal, sensorimotor, and parietal regions. These findings provide evidence that different neural systems subserve slow and fast phases of learning. The brain has a remarkable ability to adapt flexibly to improved neural efficiency. Previous neuroimaging stud- new demands. Functional plasticity in sensory and motor ies tracing the time course of practice-related changes regions occurs in response to short-term training, on the across a number of different types of tasks (Karni et al., order of minutes or hours, or in response to long-term 1998; Kelly & Garavan, 2005) suggest that fast learning, training, over the course of weeks or years (Karni et al., linked to repetitive task performance, is associated with 1995; Merzenich et al., 1983; Sanes & Donoghue, 2000).
    [Show full text]
  • Sequence Learning
    Sequence learning In cognitive psychology, sequence learning is inher- long-term future.[3] ent to human ability because it is an integrated part of conscious and nonconscious learning as well as activi- Lashley argued that sequence learning, or behavioral se- ties. Sequences of information or sequences of actions quencing or serial order in behavior, is not attributable are used in various everyday tasks: “from sequencing to sensory feedback. Rather, he proposed that there are sounds in speech, to sequencing movements in typing or plans for behavior since the nervous system prepares for playing instruments, to sequencing actions in driving an some behaviors but not others. He said that there was a [1] automobile.” Sequence learning can be used to study hierarchical organization of plans. He came up with sev- skill acquisition and in studies of various groups rang- eral lines of evidence. The first of these is that the context [1] ing from neuropsychological patients to infants. Ac- changes functional interpretations of the same behaviors, cording to Ritter and Nerb, “The order in which material such as the way “wright, right, right, rite, and write” are is presented can strongly influence what is learned, how interpreted based on the context of the sentence. “Right” fast performance increases, and sometimes even whether can be interpreted as a direction or as something good [2] the material is learned at all.” Sequence learning, more depending on the context. A second line of evidence known and understood as a form of explicit learning, is says that errors are involved in human behavior as hier- now also being studied as a form of implicit learning as archical organization.
    [Show full text]
  • Learning the Structure of Event Sequences Axel Cleeremans and James L
    Journal of Experimental Psychology: General Copyright 1991 by the American Psychological Association, Inc. 1991, Vol. 120, No. 3, 235-253 0096-3445/91/$3.00 Learning the Structure of Event Sequences Axel Cleeremans and James L. McClelland Carnegie Mellon University How is complex sequential material acquired, processed, and represented when there is no intention to learn? Two experiments exploring a choice reaction time task are reported. Unknown to Ss, successive stimuli followed a sequence derived from a "noisy" finite-state grammar. After considerable practice (60,000 exposures) with Experiment 1, Ss acquired a complex body of procedural knowledge about the sequential structure of the material. Experiment 2 was an attempt to identify limits on Ss ability to encode the temporal context by using more distant contingencies that spanned irrelevant material. Taken together, the results indicate that Ss become increasingly sensitive to the temporal context set by previous elements of the sequence, up to 3 elements. Responses are also affected by priming effects from recent trials. A connectionist model that incorporates sensitivity to the sequential structure and to priming effects is shown to capture key aspects of both acquisition and processing and to account for the interaction between attention and sequence structure reported by Cohen, Ivry, and Keele (1990). In many situations, learning does not proceed in the explicit explicit memory (conscious recollection)and implicit memory and goal-directed way characteristic of traditional models of (a facilitation of performance without conscious recollection). cognition (Newell & Simon, 1972). Rather, it appears that a Despite this wealth of evidence documenting implicit learn- good deal of our knowledge and skills are acquired in an ing, few models of the mechanisms involved have been pro- incidental and unintentional manner.
    [Show full text]
  • Implicit Sequence Learning in Recurrent Neural Networks
    INSTITUT FUR¨ INFORMATIONS- UND KOMMUNIKATIONSTECHNIK (IIKT) Implicit Sequence Learning in Recurrent Neural Networks DISSERTATION zur Erlangung des akademischen Grades Doktoringenieur (Dr.-Ing.) von Dipl.-Ing. Stefan Gluge¨ geb. am 16.07.1982 in Magdeburg, Deutschland genehmigt durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik der Otto-von-Guericke-Universit¨at Magdeburg Gutachter: Prof. Dr. rer. nat. Andreas Wendemuth Prof. Dr. G¨unther Palm Jun.-Prof. PD. Dr.-Ing. habil. Ayoub Al-Hamadi Promotionskolloquium am 11.10.2013 ii Ehrenerkl¨arung Ich versichere hiermit, dass ich die vorliegende Arbeit ohne unzul¨assige Hilfe Dritter und ohne Benutzung anderer als der angegebenen Hilfsmittel angefertigt habe. Die Hilfe eines kommerziellen Promotionsberaters habe ich nicht in Anspruch genommen. Dritte haben von mir weder unmittelbar noch mittelbar geldwerte Leistungen fr Arbeiten erhalten, die im Zusammenhang mit dem Inhalt der vorgelegten Dissertation stehen. Verwendete fremde und eigene Quellen sind als solche kenntlich gemacht. Ich habe insbesondere nicht wissentlich: Ergebnisse erfunden oder widerspr¨uchliche Ergebnisse verschwiegen, • statistische Verfahren absichtlich missbraucht, um Daten in ungerechtfertigter Weise • zu interpretieren, fremde Ergebnisse oder Ver¨offentlichungen plagiiert, • fremde Forschungsergebnisse verzerrt wiedergegeben. • Mir ist bekannt, dass Verst¨oße gegen das Urheberrecht Unterlassungs- und Schadenser- satzanspr¨uche des Urhebers sowie eine strafrechtliche Ahndung durch die Strafverfol- gungsbeh¨orden begr¨unden kann. Ich erkl¨are mich damit einverstanden, dass die Dissertation ggf. mit Mitteln der elek- tronischen Datenverarbeitung auf Plagiate ¨uberpr¨uft werden kann. Die Arbeit wurde bisher weder im Inland noch im Ausland in gleicher oder ¨ahnlicher Form als Dissertation eingereicht und ist als Ganzes auch noch nicht ver¨offentlicht. Magdeburg, den 26.06.2013 Dipl.-Ing.
    [Show full text]