Electrophysiological Correlates of Multiple Object Processing

Total Page:16

File Type:pdf, Size:1020Kb

Electrophysiological Correlates of Multiple Object Processing ELECTROPHYSIOLOGICAL CORRELATES OF MULTIPLE OBJECT PROCESSING PhD student: Silvia Pagano Advisor: Veronica Mazza Doctoral School in Cognitive and Brain Sciences XXV Cycle Center for Mind/Brain Sciences (CIMeC), University of Trento 1 2 Table of contents Abstract ............................................................................................................................ 7 Chapter 1 ......................................................................................................................... 9 1.1 Experimental paradigms for the study of multiple object processing .............. 11 1.1.1 Reviewing paradigm ....................................................................................... 11 1.1.2 Multiple object tracking ................................................................................. 14 1.1.3 Enumeration tasks ......................................................................................... 16 1.2 Theories of multiple object processing ................................................................. 20 1.2.1 The FINSTs theory ......................................................................................... 21 1.2.2 The object-file theory ..................................................................................... 25 1.2.3 The neural object-file theory .......................................................................... 27 1.3 Electrophysiological correlates of multiple object processing ........................... 29 1.3.1 N2pc ............................................................................................................... 29 1.3.2 CDA ................................................................................................................ 32 1.4 Rationale of the present thesis .............................................................................. 34 Chapter 2 ....................................................................................................................... 37 2.1 Experiment 1........................................................................................................... 37 2.1.1 Methods .......................................................................................................... 43 2.1.1.1 Participants ................................................................................................. 43 2.1.1.2 Stimuli and procedure ................................................................................. 43 2.1.1.3 EEG recording and data analysis ............................................................... 44 2.1.2 Results ............................................................................................................ 47 2.1.2.1 Behavioral results ....................................................................................... 47 2.1.2.1.1 RTs ........................................................................................................... 47 2.1.2.1.2 Accuracy ............................................................................................... 48 2.1.2.2 ERP results ................................................................................................. 49 2.1.2.2.1 N1 ......................................................................................................... 49 2.1.2.2.2 P2p ....................................................................................................... 50 2.1.2.2.3 N2pc ..................................................................................................... 51 2.1.2.2.4 CDA ...................................................................................................... 51 2.1.2.3 Group analysis ............................................................................................ 51 2.1.2.4 Correlational analyses ................................................................................ 54 2.1.3 Discussion ....................................................................................................... 56 2.2 Experiment 2........................................................................................................... 58 2.2.1 Participants ..................................................................................................... 59 2.2.2 Stimuli and procedure ..................................................................................... 59 3 2.2.3 EEG recordings and analysis .......................................................................... 60 2.2.4 Results ............................................................................................................ 61 2.2.5 Discussion ....................................................................................................... 63 2.3 General Discussion ................................................................................................. 64 Chapter 3 ....................................................................................................................... 71 3.1 Experiment 3........................................................................................................... 71 3.2 General Methods ............................................................................................... 77 3.2.1 Participants .................................................................................................... 77 3.2.2 Stimuli and procedure .................................................................................... 77 3.2.3 EEG recording and data analysis .................................................................. 78 3.3 Results ............................................................................................................... 80 3.3.1 Behavioral results .......................................................................................... 80 3.3.2 ERP results .................................................................................................... 81 3.3.2.1 N1 ............................................................................................................ 81 3.3.2.2 N2pc ........................................................................................................ 83 3.2.2.3 Control analysis ...................................................................................... 85 3.3 Discussion .......................................................................................................... 85 Chapter 4 ....................................................................................................................... 91 4.1 Experiment 4........................................................................................................... 91 4.2 Methods ............................................................................................................. 94 4.2.1 Participants .................................................................................................... 94 4.2.2 Stimuli and procedure .................................................................................... 94 4.2.3 EEG recordings and data analysis ................................................................ 96 4.3 Results ............................................................................................................... 97 4.4 Discussion .......................................................................................................... 99 Chapter 5 ..................................................................................................................... 101 5.1 Experiment 5a: Masking shapes ......................................................................... 106 5.1.2 Participants ................................................................................................... 107 5.1.3 Stimuli and Procedure .................................................................................. 107 5.1.4 Results and discussion .................................................................................. 108 5.2 Experiment 5b: Masking colors .......................................................................... 109 5.2.1 Participants ................................................................................................... 109 5.2.2 Stimuli and Procedure .................................................................................. 110 5.2.3 Results and discussion .................................................................................. 110 5.3 Experiment 5c: The final paradigm ................................................................... 111 5.3.1 Participants ................................................................................................... 112 5.3.2 Stimuli and Procedure .................................................................................. 112 5.3.3 Results and discussion .................................................................................. 113 4 5.4 Experiment 6: Electrophysiological correlates of multiple object processing in the absence of awareness ....................................................................................... 114 5.4.1 Participants ................................................................................................... 114 5.4.2 Stimuli and procedure ................................................................................... 114 5.4.4 EEG recordings and analysis ........................................................................ 115 5.4.5 Results .........................................................................................................
Recommended publications
  • The Deficit of Multimodal Perception of Congruent and Non-Congruent Fearful Expressions in Patients with Schizophrenia: the ERP Study
    brain sciences Article The Deficit of Multimodal Perception of Congruent and Non-Congruent Fearful Expressions in Patients with Schizophrenia: The ERP Study Galina V. Portnova 1,2,*, Aleksandra V. Maslennikova 1,3, Natalya V. Zakharova 3 and Olga V. Martynova 1,4 1 Institute of Higher Nervous Activity and Neurophysiology of RAS, 117485 Moscow, Russia; [email protected] (A.V.M.); [email protected] (O.V.M.) 2 The Pushkin State Russian Language Institute, 117485 Moscow, Russia 3 Psychiatric Clinical Hospital No. 1 Named after ON. Alekseeva of the Moscow City Health Department, 117152 Moscow, Russia; [email protected] 4 Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, 109548 Moscow, Russia * Correspondence: [email protected] Abstract: Emotional dysfunction, including flat affect and emotional perception deficits, is a specific symptom of schizophrenia disorder. We used a modified multimodal odd-ball paradigm with fearful facial expressions accompanied by congruent and non-congruent emotional vocalizations (sounds of women screaming and laughing) to investigate the impairment of emotional perception and reactions to other people’s emotions in schizophrenia. We compared subjective ratings of emotional state and event-related potentials (EPPs) in response to congruent and non-congruent stimuli in patients with schizophrenia and healthy controls. The results showed the altered multimodal perception of fearful stimuli in patients with schizophrenia. The amplitude of N50 was significantly higher for non-congruent stimuli than congruent ones in the control group and did not differ in patients. The Citation: Portnova, G.V.; P100 and N200 amplitudes were higher in response to non-congruent stimuli in patients than in Maslennikova, A.V.; Zakharova, N.V.; controls, implying impaired sensory gating in schizophrenia.
    [Show full text]
  • Traffic Sign Recognition Evaluation for Senior Adults Using EEG Signals
    sensors Article Traffic Sign Recognition Evaluation for Senior Adults Using EEG Signals Dong-Woo Koh 1, Jin-Kook Kwon 2 and Sang-Goog Lee 1,* 1 Department of Media Engineering, Catholic University of Korea, 43 Jibong-ro, Bucheon-si 14662, Korea; [email protected] 2 CookingMind Cop. 23 Seocho-daero 74-gil, Seocho-gu, Seoul 06621, Korea; [email protected] * Correspondence: [email protected]; Tel.: +82-2-2164-4909 Abstract: Elderly people are not likely to recognize road signs due to low cognitive ability and presbyopia. In our study, three shapes of traffic symbols (circles, squares, and triangles) which are most commonly used in road driving were used to evaluate the elderly drivers’ recognition. When traffic signs are randomly shown in HUD (head-up display), subjects compare them with the symbol displayed outside of the vehicle. In this test, we conducted a Go/Nogo test and determined the differences in ERP (event-related potential) data between correct and incorrect answers of EEG signals. As a result, the wrong answer rate for the elderly was 1.5 times higher than for the youths. All generation groups had a delay of 20–30 ms of P300 with incorrect answers. In order to achieve clearer differentiation, ERP data were modeled with unsupervised machine learning and supervised deep learning. The young group’s correct/incorrect data were classified well using unsupervised machine learning with no pre-processing, but the elderly group’s data were not. On the other hand, the elderly group’s data were classified with a high accuracy of 75% using supervised deep learning with simple signal processing.
    [Show full text]
  • Modality-Specific and Modality-General Encoding of Auditory and Visual Rhythms
    UNLV Theses, Dissertations, Professional Papers, and Capstones 5-1-2012 Modality-Specific and Modality-General Encoding of Auditory and Visual Rhythms Amanda Pasinski University of Nevada, Las Vegas Follow this and additional works at: https://digitalscholarship.unlv.edu/thesesdissertations Part of the Cognition and Perception Commons Repository Citation Pasinski, Amanda, "Modality-Specific and Modality-General Encoding of Auditory and Visual Rhythms" (2012). UNLV Theses, Dissertations, Professional Papers, and Capstones. 1608. http://dx.doi.org/10.34917/4332589 This Thesis 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 Thesis 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 Thesis 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]. MODALITY-SPECIFIC AND MODALITY-GENERAL ENCODING OF AUDITORY AND VISUAL RHYTHMS by Amanda Claire Pasinski Bachelor of Arts University of Nevada, Las Vegas 2007 A thesis document submitted in partial fulfillment of the requirements for the Master of Arts in Psychology Department
    [Show full text]
  • Long-Latency Somatosensory Evoked Potentials of the Subthalamic Nucleus in Patients with Parkinson’S Disease
    RESEARCH ARTICLE Long-Latency Somatosensory Evoked Potentials of the Subthalamic Nucleus in Patients with Parkinson's Disease Carlos Trenado1,2, Saskia Elben1,2, Lena Friggemann1, Sonja Gruhn1, Stefan Jun Groiss1,2, Jan Vesper3, Alfons Schnitzler1,2, Lars Wojtecki1,2* 1 Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany, 2 Department of Neurology, University Clinic, Heinrich Heine University, Duesseldorf, a1111111111 Germany, 3 Department of Functional and Stereotactic Neurosurgery, University Clinic, Heinrich Heine a1111111111 University, Duesseldorf, Germany a1111111111 a1111111111 * [email protected] a1111111111 Abstract Somatosensory evoked potentials (SSEPs) are a viable way to measure processing of OPEN ACCESS somatosensory information. SSEPs have been described at the scalp and the cortical level Citation: Trenado C, Elben S, Friggemann L, Gruhn by electroencephalographic, magnetoencephalographic and intracranial cortical recordings S, Groiss SJ, Vesper J, et al. (2017) Long-Latency focusing on short-latency (SL; latency<40 ms) and long-latency (LL; latency>40 ms) SSEPs Somatosensory Evoked Potentials of the as well as by deep brain stimulation (DBS) electrode studies targeting SL-SSEPs. Unfortu- Subthalamic Nucleus in Patients with Parkinson's Disease. PLoS ONE 12(1): e0168151. doi:10.1371/ nately, LL-SSEPs have not been addressed at the subcortical level aside from the fact that journal.pone.0168151 studies targeting the characteristics and generators of SSEPs have been neglected for the Editor: Robert Chen, University of Toronto, last ten years. To cope with these issues, we investigated LL-SSEPs of the subthalamic CANADA nucleus (STN) in twelve patients with Parkinson's disease (PD) that underwent deep brain Received: June 5, 2016 stimulation (DBS) treatment.
    [Show full text]
  • The Learning-Oddball Paradigm: Data of 24 Separate Individuals Illustrate Its Potential Usefulness As a New Clinical Tool ⇑ Marijtje L.A
    Clinical Neurophysiology 124 (2013) 514–521 Contents lists available at SciVerse ScienceDirect Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph The learning-oddball paradigm: Data of 24 separate individuals illustrate its potential usefulness as a new clinical tool ⇑ Marijtje L.A. Jongsma a,c, , Clementina M. van Rijn a, Niels J.H.M. Gerrits a, Tom Eichele b, Bert Steenbergen c, Joseph H.R. Maes a, Rodrigo Quian Quiroga d,e a Donders Institute for Brain, Cognition, and Behavior, DCC, Radboud University Nijmegen, Montessorilaan 3, 6525 HR Nijmegen, The Netherlands b Department of Biological and Medical Psychology, Division of Cognitive Neuroscience, University of Bergen, Building for Basic Biological Research, Jonas Lies vei 91, N-5009 Bergen, Norway c Behavioural Science Institute, Radboud University Nijmegen, Montessorilaan 3, 6525 HR Nijmegen, The Netherlands d Department of Engineering, University of Leicester, LE1 7RH Leicester, United Kingdom e Leibniz Institute for Neurobiology, University of Magdeburg, Germany article info highlights Article history: An ERP study using a learning-oddball paradigm was employed to assess pattern detection in individual Accepted 4 September 2012 participants. Available online 10 October 2012 ERP changes across learning trials corresponded to sigmoid curves that could be established in each individual participant. Keywords: The ERP/learning-oddball paradigm implicates a potential tool for assessing pattern detection capacities ERP in individuals. Single-trial Pattern detection N2 abstract P3 Individuality Objective: In a previous article reporting group data, we presented event-related potentials (ERPs), which were evoked by randomly presented target stimuli in a ‘learning-oddball’ task. These ERPs contained a large N2-P3 complex that decreased and a Contingent Negative Variation (CNV) that increased when the targets were presented in a regular fashion.
    [Show full text]
  • Education Level Is Associated with Specific N200 and P300 Profiles Reflecting Higher Cognitive Functioning
    Journal of Advances in Medical and Pharmaceutical Sciences 10(4): XX-XX, 2016; Article no.JAMPS.29783 ISSN: 2394-1111 SCIENCEDOMAIN international www.sciencedomain.org Education Level is Associated with Specific N200 and P300 Profiles Reflecting Higher Cognitive Functioning Rumaisa Abu Hasan 1, Faruque Reza 1 and Tahamina Begum 2* 1Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia. 2Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia. Authors’ contributions This work was carried out in collaboration among all authors. Authors FR and TB designed the study, wrote the protocol, guided the data collection and performed the statistical analysis. Authors RAH and TB performed the data acquisition and literature review. Author RAH wrote the first draft of the manuscript. Authors TB and FR reviewed the final manuscript. All authors read and approved the final manuscript. Article Information DOI: 10.9734/JAMPS/2016/29783 Editor(s): (1) (2) Reviewers: (1) (2) (3) Complete Peer review History: Received 29 th September 2016 Accepted 7th November 2016 Original Research Article th Published 19 November 2016 ABSTRACT Background: While different colors are commonly used during neuropsychological assessments, there is a general lack of information about the influence of education on color processing, which could affect the results of neuropsychological testing. Higher education is directly related to higher cognitive functions. Therefore, we investigated educational influences on color processing in different tasks using reaction times (RTs) in an event-related potential (ERP) study. Methods: A 128-sensor net was used for the ERP study with participants from low (G1), medium (G2) and high (G3) educational groups (n=17 per group).
    [Show full text]
  • Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface
    Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface Young-Eun Lee Minji Lee Seong-Whan Lee Dept. Brain and Cognitive Engineering Dept. Brain and Cognitive Engineering Dept. Artificial Intelligence Korea University Korea University Korea University Seoul, Republic of Korea Seoul, Republic of Korea Seoul, Republic of Korea ye [email protected] [email protected] [email protected] Abstract—Practical brain-machine interfaces have been widely or robots by decoding human intention from brain signals [1]– studied to accurately detect human intentions using brain signals [4]. There are many state-of-the-art BMI systems to increase in the real world. However, the electroencephalography (EEG) the performance of identifying user intention in a laboratory signals are distorted owing to the artifacts such as walking and head movement, so brain signals may be large in amplitude condition [5], [6]. In particular, BMIs under an ambulatory rather than desired EEG signals. Due to these artifacts, de- condition are important issues for practical BMIs to recognize tecting accurately human intention in the mobile environment human intention in the real world [7]–[9]. However, the is challenging. In this paper, we proposed the reconstruction movement artifacts can have difficulty detecting user intention framework based on generative adversarial networks using the because they affect electroencephalography (EEG) signals event-related potentials (ERP) during walking. We used a pre- trained convolutional encoder to represent latent variables and with large magnitudes. These artifacts could arise from head reconstructed ERP through the generative model which shape movement, electromyography, muscle activity, skin, and cable similar to the opposite of encoder.
    [Show full text]
  • A Clinical Trial to Validate Event-Related Potential Markers of Alzheimer's Disease in Outpatient Settings
    Alzheimer’s& Dementia: Diagnosis, Assessment & Disease Monitoring 1 (2015) 387-394 Electrophysiological Biomarkers A clinical trial to validate event-related potential markers of Alzheimer’s disease in outpatient settings Marco Cecchia,*, Dennis K. Moorea, Carl H. Sadowskyb, Paul R. Solomonc, P. Murali Doraiswamyd, Charles D. Smithe, Gregory A. Jichae, Andrew E. Budsonf, Steven E. Arnoldg, Kalford C. Fadema aNeuronetrix, Louisville, KY, USA bDepartment of Neurology, Nova Southeastern University, Fort Lauderdale, FL, USA cDepartment of Psychology, Williams College, Williamstown, MA, USA dDepartments of Psychiatry and Medicine, Duke Medicine and Duke Institute for Brain Sciences, Durham, NC, USA eDepartment of Neurology, University of Kentucky, Lexington, KY, USA fDepartment of Cognitive & Behavioral Neurology, VA Boston Healthcare System, Boston, MA, USA gDepartments of Psychiatry and Neurology, University of Pennsylvania, Philadelphia, PA, USA Abstract Introduction: We investigated whether event-related potentials (ERP) collected in outpatient set- tings and analyzed with standardized methods can provide a sensitive and reliable measure of the cognitive deficits associated with early Alzheimer’s disease (AD). Methods: A total of 103 subjects with probable mild AD and 101 healthy controls were recruited at seven clinical study sites. Subjects were tested using an auditory oddball ERP paradigm. Results: Subjects with mild AD showed lower amplitude and increased latency for ERP features associated with attention, working memory, and executive function. These subjects also had decreased accuracy and longer reaction time in the target detection task associated with the ERP test. Discussion: Analysis of ERP data showed significant changes in subjects with mild AD that are consistent with the cognitive deficits found in this population.
    [Show full text]
  • The Mismatch Negativity (MMN) – a Unique Window to Disturbed Central Auditory Processing in Ageing and Different Clinical Conditions ⇑ R
    Clinical Neurophysiology 123 (2012) 424–458 Contents lists available at SciVerse ScienceDirect Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph Invited Review The mismatch negativity (MMN) – A unique window to disturbed central auditory processing in ageing and different clinical conditions ⇑ R. Näätänen a,b,c, , T. Kujala c,d, C. Escera e,f, T. Baldeweg g,h, K. Kreegipuu a, S. Carlson i,j,k, C. Ponton l a Institute of Psychology, University of Tartu, Tartu, Estonia b Center of Integrative Neuroscience (CFIN), University of Aarhus, Aarhus, Denmark c Cognitive Brain Research Unit, Cognitive Science, Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland d Cicero Learning, University of Helsinki, Helsinki, Finland e Institute for Brain, Cognition and Behavior (IR3C), University of Barcelona, Barcelona, Catalonia, Spain f Cognitive Neuroscience Research Group, Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Barcelona, Catalonia, Spain g Institute of Child Health, University College London, London, UK h Great Ormond Street Hospital for Sick Children NHS Trust, London, UK i Neuroscience Unit, Institute of Biomedicine/Physiology, University of Helsinki, Helsinki, Finland j Brain Research Unit, Low Temperature Laboratory, Aalto University School of Science and Technology, Espoo, Finland k Medical School, University of Tampere, Tampere, Finland l Compumedics NeuroScan, Santa Fe, NM, USA article info highlights Article history: The mismatch negativity (MMN) indexes different types of central auditory abnormalities in different Accepted 20 September 2011 neuropsychiatric, neurological, and neurodevelopmental disorders. Available online 13 December 2011 The diminished amplitude/prolonged peak latency observed in patients usually indexes decreased audi- tory discrimination. Keywords: An MMN deficit may also index cognitive and functional decline shared by different disorders irrespec- The mismatch negativity (MMN) tive of their specific aetiology and symptomatology.
    [Show full text]
  • ERP TUTORIAL 1 a Brief Introduction to the Use of Event-Related Potentials
    ERP TUTORIAL 1 A Brief Introduction to the Use of Event-Related Potentials (ERPs) in Studies of Perception and Attention Geoffrey F. Woodman Vanderbilt University Vanderbilt Vision Research Center Center for Integrative and Cognitive Neuroscience Abstract Due to the precise temporal resolution of electrophysiological recordings, the event-related potential (ERP) technique has proven particularly valuable for testing theories of perception and attention. Here, I provide a brief tutorial of the ERP technique for consumers of such research and those considering the use of human electrophysiology in their own work. My discussion begins with the basics regarding what brain activity ERPs measure and why they are well suited to reveal critical aspects of perceptual processing, attentional selection, and cognition that are unobservable with behavioral methods alone. I then review a number of important methodological issues and often forgotten facts that should be considered when evaluating or planning ERP experiments. Electroencephalogram (EEG) technique continue to make it one of the most recordings were the first method developed for widely used methods to study the architecture direct and noninvasive measurements brain of cognitive processing. activity from human subjects (Adrian & The primary goal of this tutorial is to Yamagiwa, 1935; Berger, 1929; Jasper, 1937, introduce researchers who are unfamiliar with 1948). By noting when stimuli were presented ERPs to their use, interpretation, and and tasks were performed, early studies dissemination in studies of sensation, examining the raw EEG sought to characterize perception, attention, and cognition. I hope the changes in the state of electrical activity that the uninitiated readers will become better during sensory processing and the consumers of ERP research.
    [Show full text]
  • Pe Novelty P3 N200, P3a, P3b, SW
    1964 1975 1980 1990 2000 time O-wave SPN CNV, PINV MPN Grey Walter E-wave Loveless & Sanford Damen & Brunia LRP (CMA) Coles & Gratton; DeJong BSP, RP ERN (Ne), Pe CRN Kornhuber & Deecke Falkenstein; Gehring Vaughan et al. Novelty P3 N400 P600 /SPS P300 Kutas & Hillyard CPS Chapman & Bragdon Courchesne et al. LAN Steinhauer et al. Sutton et al. Osterhout N200, P3a, P3b, N2a, N2b Dm Kluender SW complex N2a=MMN Paller et al. Neville Squires et al. Naatanen Other components: Nd, PN, N2pc, nogoN200, ADAN, LDAN, CDA, etc. The first psychological ERP effects…1964 CNV – contingent negative variation, Grey Walter et al. BSP, RP – readiness potential, Kornhuber & Deecke, Vaughan et al. P300 – Sutton et al. SLOW (MOSTLY NEGATIVE) POTENTIALS e.g., BSP/RP, CNV, SPN/MPN Slowly rising negativities - prior to voluntary movement (RP – readiness potential) - prior to imperative stimulus or between warning and imperative, i.e., foreperiod (CNV – contingent negative variation) - prior to intake of information (SPN – stimulus preceding negativity) Bereitschaftspotential (BSP): aka Readiness Potential (RP) L. motor How might we test the R. premotor hypothesis that RP related to voluntary movement? Mid-parietal Bipolar L vs R Kornhuber & Deecke, 1964 MOVEMENT-RELATED POTENTIALS Movement onset Motor Potential - MP Premotion Positivity - PMP Reafference Potential Pre-movement-related potentials • RPsym - Readiness Potential symmetric • RPlat - Readiness Potential lateralized • PMP - Premotion Positivity • MP - Motor Potential RP - Readiness Potential symmetric
    [Show full text]
  • The N170 As a Marker of Reading Proficiency
    The N170 as a marker of Reading Proficiency Inaugural-Dissertation in der Fakultät Humanwissenschaft der Otto-Friedrich-Universität Bamberg Vorgelegt von Ulrike Kagel aus Parchim Bamberg, den 20.11.2019 Tag der mündlichen Prüfung: 25.04.2020 Dekan: Universitätsprofessor Dr. Jörg Wolstein. Erstgutachter: Universitätsprofessor Dr. Jascha Rüsseler Zweitgutachter: Universitätsprofessor Dr. Claus-Christian Carbon URN: urn:nbn:de:bvb:473-irb-488426 DOI: https://doi.org/10.20378/irb-48842 Dieses Werk ist als freie Onlineversion über das Forschungsinformationssystem (FIS; https://fis.uni-bamberg.de) der Universität Bamberg erreichbar. Das Werk steht unter der CC-Lizenz CC-BY. Dedication I thank My family, who supported me all my life, Dr. Klaus Kagel, who inspired me, and Dr. C. Hoffmann, I also thank Prof. Dr. Jascha Rüsseler for his support. i Contents Dedication .............................................................................................................................. i 1 Introduction ........................................................................................................... 5 1.1 Overview of language-related event-related potentials (ERPs) .............................. 5 The N170 – A Marker for Reading Proficiency? ............................................... 8 2.1 Definition ................................................................................................................ 8 2.2 Sources of the N170 Signal ...................................................................................
    [Show full text]