EVALUATING THE EFFICACY OF NEUROREHABILITATION PROTOCOLS USING BRAIN CONNECTIVITY ANALYSIS (Record no. 10894)

MARC details
000 -LEADER
fixed length control field 08829nam a22002657a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 201210s2024 a|||f bm|| 00| 0 eng d
024 7# - Author Identifier
Standard number or code 0000-0002-6909-7985
Source of number or code ORCID
040 ## - CATALOGING SOURCE
Original cataloging agency EG-CaNU
Transcribing agency EG-CaNU
041 0# - Language Code
Language code of text eng
Language code of abstract eng
-- ara
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 610
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Heba Ali Abdelbary Ali
245 1# - TITLE STATEMENT
Title EVALUATING THE EFFICACY OF NEUROREHABILITATION PROTOCOLS USING BRAIN CONNECTIVITY ANALYSIS
Statement of responsibility, etc. /Heba Ali Abdelbary Ali
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2024
300 ## - PHYSICAL DESCRIPTION
Extent 81p.
Other physical details ill.
Dimensions 21 cm.
500 ## - GENERAL NOTE
Materials specified Supervisor: Prof. Walid Al-atabany
502 ## - Dissertation Note
Dissertation type Thesis (M.A.)—Nile University, Egypt, 2024.
504 ## - Bibliography
Bibliography "Includes bibliographical references"
505 0# - Contents
Formatted contents note Contents:<br/>CERTIFICATION OF APPROVAL i<br/>CERTIFICATE OF ORIGINALITY ii<br/>ACKNOWLEDGEMENTS iii<br/>LIST OF FIGURES ix<br/>LIST OF TABLES xi<br/>ACRONYMS xiii<br/>ABSTRACT xiv<br/>1 INTRODUCTION 1<br/>1.1 Motivation.................................................................................................................. 1<br/>1.1.1 The importance of brain networks in humans ................................................. 1<br/>1.1.2 The Significance of Brain Connectivity in Stroke Patient Recovery .............. 2<br/>1.2 Problem Statement and Objectives ............................................................................... 5<br/>1.2.1 Problem Definition......................................................................................... 5<br/>1.2.2 Objectives and Contribution........................................................................... 5<br/>1.3 Thesis Structure ......................................................................................................... 6<br/>2 BACKGROUND AND LITERATURE REVIEW 8<br/>v<br/>2.1 Electroencephalography (EEG)................................................................................... 9<br/>2.2 Connectivity of Brain Regions ..................................................................................10<br/>2.2.1 Types of Brain Connectivity .........................................................................11<br/>2.2.2 Difference between Intra and Inter-Brain Connectivity..................................12<br/>2.2.3 Brain Connectivity Identification Techniques................................................14<br/>2.3 Human Connectome Project (HCP)............................................................................17<br/>2.4 Connectivity and Brain Diseases...............................................................................20<br/>2.5 Neural OscillationNetwork......................................................................................21<br/>2.6 Plasticity and Brain Repair........................................................................................22<br/>2.7 Static and Dynamic Functional Connectivity ............................................................24<br/>3 METHODOLOGY 26<br/>3.1 Approach Overview..................................................................................................26<br/>3.2 Datasets....................................................................................................................26<br/>3.2.1 Phase 1 datasets:..........................................................................................28<br/>3.2.2 Phase 2 Dataset: g.tec dataset......................................................................30<br/>3.2.3 Phase 3 Dataset: Aphasia dataset.................................................................33<br/>3.3 Data-Preprocessing ...................................................................................................33<br/>3.3.1 Independent Component Analysis (ICA)........................................................34<br/>3.3.2 Preprocessing of NMT Dataset....................................................................35<br/>3.3.3 Preprocessing of TUH Dataset.....................................................................37<br/>3.3.4 Preprocessing of g.tec Dataset......................................................................37<br/>3.3.5 Preprocessing of Aphasia Dataset................................................................39<br/>3.4 Functional connectivity measurement .......................................................................41<br/>3.4.1 Pearson Correlation.....................................................................................41<br/>3.4.2 Mutual Information .....................................................................................42<br/>3.5 Similarity Measurement of Functional Connectivity Matrix .....................................42<br/>3.6 Graph Representation..............................................................................................43<br/>vi<br/>4 RESULTS 45<br/>4.1 Phase 1: Differentiation between healthy and pathological Functional Brain<br/>Connectivity ............................................................................................................. 45<br/>4.2 Phase-2: Functional Brain Connectivity for Assessing Post-Stroke Rehabilitation Recovery............................................................................................................. 47<br/>4.2.1 Inter and Intra Functional Connectivity.......................................................... 49<br/>4.2.2 Linear and Nonlinear Techniques for Functional Connectivity ...................... 51<br/>4.2.3 Neural Oscillation Analysis .......................................................................... 53<br/>4.2.4 Graph Representation for Functional Connectivity ........................................ 56<br/>4.3 Phase 3: Post-Stroke Aphasia.................................................................................... 57<br/>5 DISCUSSION 68<br/>5.1 Phase 1: Differentiation between Normal and Abnormal Functional Connectivity Patterns ............................................................................................................... 68<br/>5.2 Phase 2: Functional Brain Connectivity for Assessing Post-Stroke Rehabilitation 69<br/>5.2.1 I: Inter and Intra- Functional Connectivity matrices..................................... 70<br/>5.2.2 II: Frequency Bands and Inter-neuron Networks ........................................... 72<br/>5.2.3 Graph Representation for Brain Functional Connectivity .............................. 74<br/>5.3 Phase 3: Post-Stroke Aphasia Analysis ..................................................................... 77<br/>5.4 Strengths and Limitations........................................................................................... 78<br/>6 CONCLUSION AND FUTURE WORK 79<br/>6.1 Conclusion................................................................................................................ 79<br/>6.2 Future Work.............................................................................................................. 80<br/>A ACHIEVEMENTS 97<br/>A.1 Publications.............................................................................................................. 97<br/>A.2 Awards...................................................................................................................... 97<br/>
520 3# - Abstract
Abstract Abstract:<br/>Stroke is the primary factor behind enduring disabilities, leading to motor and cognitive impairment. Despite receiving standard stroke therapy, most patients remain disabled when<br/>entering the chronic phase. Researchers are exploring alternative approaches to enhance brain <br/>plasticity and connectivity, utilizing effective biomarkers to improve recovery chances.<br/>Enhanced neu- ral activity has been identified as a sign of improved functional recovery.<br/>This work utilizes the functional brain connectivity network to assess the rehabilitation <br/>protocols for post-stroke recovery in two case studies: patients with aphasia and those<br/>with motor deficits. The study demonstrates the success of the primary objective through <br/>three comprehensive research phases that utilized linear and nonlinear techniques for <br/>measuring static and dynamic functional con- nectivity. Our study reveals a consistent <br/>brain connectivity pattern observed in healthy cases, with a prevalence rate of 96% among <br/>all participants. Meanwhile, pathological cases exhibit distinct patterns depending on the<br/>type of abnormality. Furthermore, our results confirm the effectiveness of the rehabilitation <br/>strategies utilized with these patients using functional connec- tivity as a biomarker for <br/>recovery. Additionally, employing functional connectivity can lead to the identification of <br/>hemisphere dominance which helps the neurologist to customize the treatment.<br/>Keywords<br/>Neurorehabilitation, Brain Computer Interface, Functional Brain Connectivity, <br/>Neuroplasticity, Brain Network
546 ## - Language Note
Language Note Text in English, abstracts in English and Arabic
650 #4 - Subject
Subject informatics
655 #7 - Index Term-Genre/Form
Source of term NULIB
focus term Dissertation, Academic
690 ## - Subject
School informatics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
655 #7 - Index Term-Genre/Form
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    Dewey Decimal Classification     Main library Main library 08/27/2024   610/H.A.E /2024 08/27/2024 08/27/2024 Thesis