Neocortical-Medial Temporal Lobe Interactions during Visuospatial Memory Formation and Implications for Screening of Memory Impairment in Alzheimer's Disease Open Access

Haque, Rafi (Spring 2020)

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Alzheimer’s disease (AD) is a chronic neurodegenerative disorder characterized by pathological changes prior to onset of clinical symptoms. The earliest site of cortical pathology is the medial temporal lobe (MTL), a region critical for the formation of memories. The presence of pathology within the MTL has generated interest in developing memory assessments that involve the MTL and may identify individuals with memory impairment due to AD.  To address this need, we developed a visuospatial memory paradigm that requires participants to retrieve their past memories and recognize differences between these memories and the current experience. We presented this memory paradigm while recording electrophysiological activity in visual association areas and the MTL. Successful recognition of visuospatial memories was associated with increases in 80-120 Hz power within visual association areas and the MTL and also accompanied by 8-12 Hz communication between these regions. We then developed a version of this visuospatial memory paradigm that strictly uses eye movements as an index of retrieval. Visuospatial memory performance based on eye movements was substantially reduced in participants with AD and could differentiate the two populations with high sensitivity and specificity. To improve the scalability of this assessment, we developed an iPad-based version of the memory task that utilizes iTracker, a convolutional neural network (CNN) architecture used to track eye movements on Apple devices. We found that the iPad-based implementation could also differentiate cognitively impaired participants from healthy controls with high sensitivity and specificity. This work advances our understanding of the neocortical-MTL interactions underlying visuospatial memory formation and provides a passive, sensitive, and efficient memory assessment that may be used to identify individuals at risk of future memory impairment.

Table of Contents

Table of Contents

Chapter 1: Introduction                                                                                                                  

1.1 Molecular Pathogenesis and Pathophysiology of Alzheimer’s Disease                             1

1.2 Clinical Assessment of Cognitive Impairment in Alzheimer’s Disease                             4

1.3 The Medial Temporal Lobe and Memory Formation                                                         6

1.4 Neocortical and Medial Temporal Lobe Interactions during Visuospatial Memory Formation      7

1.6 Visuospatial Memory Assessments Screening for Memory Impairment                            9

1.6 Thesis Aims                                                                                                                       10

Chapter 2: Neocortical-Medial Temporal Lobe Interactions during Visuospatial Memory Formation       12

2.1 Introduction                                                                                                                       12

2.2 Materials and Methods                                                                                                      14

2.2.1 Participants                                                                                                               14

2.2.2 Visuospatial Recognition Memory Task                                                                  15

2.2.3 Intracranial EEG (iEEG) Recordings                                                                       16

2.2.5 Spectral Power                                                                                                          20

2.2.6 Spectral Coherence                                                                                                   20

2.2.7 Generation and Characterization of Cross-Correlograms                                        21

2.2.8 Metrics of Reinstatement                                                                                         23

2.2.9 Temporal Dynamics of Spectral Power                                                                   24

2.2.10 Statistical Analyses                                                                                                27

2.3 Results                                                                                                                               29

2.3.1 80-120 Hz power progresses down the visual hierarchy and reflects specific visual experience        33

2.3.2 80-120 Hz power increases within visual association areas and the MTL when present visual experience differs from the remembered experience                                                                                                                          38

2.3.3 Differences in 80-120 Hz power during manipulated images progress down the visual hierarchy     45

2.4. Discussion                                                                                                                        51

Chapter 2: Visuospatial Memory Performance during Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease    62

3.1 Introduction                                                                                                                       63

3.2 Methods                                                                                                                             64

3.2.2 Visuospatial Memory Eye-tracking Test (VisMET)                                                65

3.2.3 Eye movement detection                                                                                          67

3.2.4 Fixation Detection                                                                                                    68

3.2.5 Measurement of Visual Exploration                                                                        68

3.2.6 Measurement of VisMET Performance                                                                   69

3.2.7 Logistic Regression Models                                                                                     70

3.3 Results                                                                                                                               71

3.3.1 Visual Exploration in Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease during Encoding       71

3.3.2 VisMET Performance in Healthy Aging                                                                  74

3.3.3 VisMET Is impaired in Mild Cognitive Impairment and Alzheimer’s Disease      77

3.3.4 VisMET as a screening tool for cognitive impairment and disease status               81

3.4 Discussion                                                                                                                         85

Chapter 4: Deep convolutional neural networks and transfer learning for measuring cognitive impairment using eye-tracking in a distributed tablet-based environment                                                                                       89

4.1 Introduction                                                                                                                       90

4.2 Materials and Methods                                                                                                      91

4.2.1 Participants                                                                                                               91

4.2.2 Mobile Device Data Capture                                                                                    92

4.2.3 Calibration Procedure                                                                                               92

4.2.4 Visuospatial Memory Eye-tracking Task (VisMET)                                               93

4.2.5 Regression Tree Face and Eye Detection                                                                 94

4.2.7 Convolutional Neural Network and Support Vector Regression for Tablet-Based Gaze Estimation 96

4.2.8 Re-Calibration of Gaze Estimations Between Successive Images                           97

4.2.9 EyeTribe-Based Gaze Estimation                                                                            98

4.2.10 Feature Extraction                                                                                                  98

4.2.11 Logistic Regression Models for Detection of Cognitive Impairment                    99

4.3 Results                                                                                                                             100

4.3.1 Performance Evaluation of Tablet-Based Methods for Gaze Estimation              100

4.3.2 Assessment of Visual Exploration on the Tablet and EyeTribe                             100

4.3.3 Assessment of Cognitive Impairment on the Tablet and EyeTribe                       103

4.3.4 Tablet Administration of VisMET as a Screening Tool for Cognitive Impairment 105

4.4 Discussion                                                                                                                       107

Chapter 5: Future Directions and Conclusions                                                                      109

5.1 Summary                                                                                                                         109

5.2 Future Directions                                                                                                             111

5.2.1 Visuospatial Memory Performance in Healthy Participants                                  111

5.2.2 Neurophysiological Mechanisms of Visuospatial Memory Recognition              112

5.3 Conclusions                                                                                                                     113

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