You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review 
Chapter Title:  Introduction 
1. Abstract of Cited Paper (BIB001):  In Alzheimer disease (AD), which is the most common cause of dementia, the underlying disease pathology most probably precedes the onset of cognitive symptoms by many years. Thus, efforts are underway to find early diagnostic markers as well as disease-modifying treatments for this disorder. PET enables various brain systems to be monitored in living individuals. In patients with AD, PET can be used to investigate changes in cerebral glucose metabolism, various neurotransmitter systems, neuroinflammation, and the protein aggregates that are characteristic of the disease, notably the amyloid deposits. These investigations are helping to further our understanding of the complex pathophysiological mechanisms that underlie AD, as well as aiding the early and differential diagnosis of the disease in the clinic. In the future, PET studies will also be useful for identifying new therapeutic targets and monitoring treatment outcomes. Amyloid imaging could be useful as early diagnostic marker of AD and for selecting patients for anti-amyloid-beta therapy, while cerebral glucose metabolism could be a suitable PET marker for monitoring disease progression. For the near future, multitracer PET studies are unlikely to be used routinely in the clinic for AD, being both burdensome and expensive; however, such studies are very informative in a research context. 
2. Abstract of Cited Paper (BIB002):  Functional imaging may be useful for both the early diagnosis as well as preclinical detection of neurodegenerative disease. Additionally, while structural imaging has traditionally been regarded as a tool to exclude alternate diagnoses, recent advances in magnetic resonance show promise for greater diagnostic specificity. The role of MR and radionuclide imaging in early diagnosis and preclinical detection of dementia and parkinsonism are reviewed here. 
3. Abstract of Cited Paper (BIB003):  We investigated rapid object categorization and, more specifically, the ability to detect a target object within a natural scene in people with mild Alzheimer's disease (AD) using a saccadic choice task. It has been suggested that the anatomical pathway likely used to initiate rapid oculomotor responses in the saccadic choice task could involve the Frontal Eye Field, a structure that is part of the dorsal attentional network, in which connectivity is disrupted in AD. Seventeen patients with mild AD and 23 healthy age-matched controls took part in the study. A group of 24 young healthy observers was included as it has been reported that normal aging affects eye movements. Participants were presented with pairs of colored photographs of natural scenes, one containing an animal (the target) and one containing various objects (distracter), displayed for 1 s left and right of fixation. They were asked to saccade to the scene containing an animal. Neither pathology nor age affected temporal (saccade latencies and durations) and spatial (saccade amplitude) parameters of eye movements. Patients with AD were significantly less accurate than age-matched controls, and older participants were less accurate than young observers. The results are interpreted in terms of noisier sensory information and increased uncertainty in relation to deficits in the magnocellular pathway. The results suggest that, even at a mild stage of the pathology, people exhibit difficulties in selecting relevant objects. 
4. Abstract of Cited Paper (BIB004):  Abstract Clinical and population research on dementia and related neurologic conditions, including Alzheimer's disease, faces several unique methodological challenges. Progress to identify preventive and therapeutic strategies rests on valid and rigorous analytic approaches, but the research literature reflects little consensus on "best practices." We present findings from a large scientific working group on research methods for clinical and population studies of dementia, which identified five categories of methodological challenges as follows: (1) attrition/sample selection, including selective survival; (2) measurement, including uncertainty in diagnostic criteria, measurement error in neuropsychological assessments, and practice or retest effects; (3) specification of longitudinal models when participants are followed for months, years, or even decades; (4) time-varying measurements; and (5) high-dimensional data. We explain why each challenge is important in dementia research and how it could compromise the translation of research findings into effective prevention or care strategies. We advance a checklist of potential sources of bias that should be routinely addressed when reporting dementia research. 
5. Abstract of Cited Paper (BIB005):  Different neurodegenerative diseases can cause memory disorders and other cognitive impairments. The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge. This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia. Such a bilateral comparison does not resemble clinical practice, where a clinician is faced with a number of different possible types of dementia. Here we studied which features in structural magnetic resonance imaging (MRI) scans could best distinguish four types of dementia, Alzheimer's disease, frontotemporal dementia, vascular dementia, and dementia with Lewy bodies, and control subjects. We extracted an extensive set of features quantifying volumetric and morphometric characteristics from T1 images, and vascular characteristics from FLAIR images. Classification was performed using a multi-class classifier based on Disease State Index methodology. The classifier provided continuous probability indices for each disease to support clinical decision making. A dataset of 504 individuals was used for evaluation. The cross-validated classification accuracy was 70.6% and balanced accuracy was 69.1% for the five disease groups using only automatically determined MRI features. Vascular dementia patients could be detected with high sensitivity (96%) using features from FLAIR images. Controls (sensitivity 82%) and Alzheimer's disease patients (sensitivity 74%) could be accurately classified using T1-based features, whereas the most difficult group was the dementia with Lewy bodies (sensitivity 32%). These results were notable better than the classification accuracies obtained with visual MRI ratings (accuracy 44.6%, balanced accuracy 51.6%). Different quantification methods provided complementary information, and consequently, the best results were obtained by utilizing several quantification methods. The results prove that automatic quantification methods and computerized decision support methods are feasible for clinical practice and provide comprehensive information that may help clinicians in the diagnosis making. 
6. Abstract of Cited Paper (BIB006):  Patients with Alzheimer's disease (AD) develop progressive language, visuoperceptual, attentional, and oculomotor changes that can have an impact on their reading comprehension. However, few studies have examined reading behavior in AD, and none have examined the contribution of predictive cueing in reading performance. For this purpose we analyzed the eye movement behavior of 35 healthy readers (Controls) and 35 patients with probable AD during reading of regular and high- predictable sentences. The cloze predictability of words N - 1, and N + 1 exerted an influence on the reader's gaze duration. The predictabilities of preceding words in high-predictable sentences served as task-appropriate cues that were used by Control readers. In contrast, these effects were not present in AD patients. In Controls, changes in predictability significantly affected fixation duration along the sentence; noteworthy, these changes did not affect fixation durations in AD patients. Hence, only in healthy readers did predictability of upcoming words influence fixation durations via memory retrieval. Our results suggest that Controls used stored information of familiar texts for enhancing their reading performance and imply that contextual-word predictability, whose processing is proposed to require memory retrieval, only affected reading behavior in healthy subjects. In AD patients, this loss reveals impairments in brain areas such as those corresponding to working memory and memory retrieval. These findings might be relevant for expanding the options for the early detection and monitoring in the early stages of AD. Furthermore, evaluation of eye movements during reading could provide a new tool for measuring drug impact on patients' behavior. 
7. Abstract of Cited Paper (BIB007):  Recently, saliency detection has been becoming a popular topic in computer vision. In this paper we propose an object-level saliency detection algorithm which explicitly explores bottom-up visual attention and objectness cues. Firstly, some category-independent object candidates are segmented from the image by the quantized color attributes. Then two metrics, global cues and candidate objectness, are developed to estimate the saliency in the whole image and the object candidates respectively. We use global cues to describe the focusness and spatial distribution of color attributes in the entire image. As supplementary, candidate objectness can reveal the objectness of the object candidates. Finally, we integrate the two saliency cues to derive a saliency map of the image. By explicitly fusing candidate objectness and global cues, our proposed method is more suitable for processing images with complex background. Experimental results on three large benchmark databases demonstrate that the proposed method achieves more favorable performance than 15 recent state-of-the-art methods in terms of three evaluation criterions. We propose an object-level salient detection algorithm which explicitly explores bottom-up visual attention and objectness cues.Some category-independent object candidates are firstly segmented from the image by the quantized color attributes of images.Global cues and candidate objectness are developed, to evaluate bottom-up visual attention of the whole image and the objectness of the object candidates respectively.By explicitly combining local objectness cue with global low-level saliency cues with candidates location and color attributes, our proposed method is more suitable for processing images with complex background. 
8. Abstract of Cited Paper (BIB008):  Alzheimer's disease (AD) is the primary cause of age-related dementia. Effective strategies to prevent and treat AD remain elusive despite major efforts to understand its basic biology and clinical pathophysiology. Significant investments in therapeutic drug discovery programs over the past two decades have yielded some important insights but no blockbuster drugs to alter the course of disease. Because significant memory loss and cognitive decline are associated with neuron death and loss of gray matter, especially in the frontal cortex and hippocampus, some focus in drug development has shifted to early prevention of cellular pathology. Although clinical trial design is challenging, due in part to a lack of robust biomarkers with predictive value, some optimism has come from the identification and study of inherited forms of early-onset AD and genetic risk factors that provide insights about molecular pathophysiology and potential drug targets. In addition, better understanding of the Aβ amyloid pathway and the tau pathway-leading to amyloid plaques and neurofibrillary tangles, respectively, which are histopathological hallmarks of AD-continues to drive significant drug research and development programs. The main focus of this review is to summarize the most recent basic biology, biochemistry, and pharmacology that serve as a foundation for more than 50 active advanced-phase clinical trials for AD prevention and therapy. 
9. Abstract of Cited Paper (BIB009):  As lifespan tendency is increasing, age-related diseases are becoming a burden to the society and health care system. Mostly incurable, constitute a subject of researchers' work. In this review, the insight into the problem of Alzheimer Disease (AD) diagnostics will be given. The unquestionable diagnosis is possible only during a post-mortem examination. AD is known as one of the forms of dementia and its differentiation from mild cognitive impairments has to be improved. Despite a great diagnostic progress during last decades, medicine still needs more accurate tools for an early detection of this incurable disease. It is hoped that this strategy will enable an administration of more aggressive therapy preventing AD development. Nowadays, pharmacotherapy is based mainly on symptomatic treatment which is not able to reverse pathological changes caused by the disease. Hence, more accurate identifying testing and monitoring methods are crucial to reveal new therapeutic targets. The most popular techniques present for detecting local brain functional changes use nuclear medicine imaging devices: Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT). Constant process of improving is not possible without new radiotracers. Magnetic Resonance Imaging (MRI) is a tool for an assessment of structural changes in brain tissue. However, providing satisfying results, these methods are not completely specific and accurate. As very promising hallmarks of AD enhancing high accuracy of testing, biomarkers - tau tangles and β-amyloid plaques have been found. At the present time they are being used only as an additional examination, one day they may become a gold standard of AD diagnostics.

Literature Review:
Neurodegenerative diseases are a group of disorders characterized by the progressive degeneration of the neurons of the central or peripheral nervous systems. The degeneration affects neuron synapsis or produces neuron death BIB001 . The most frequent neurodegenerative diseases are Alzheimer's disease (AD) and Parkinson disease (PD) BIB006 BIB003 . According to the Alzheimer's Association (https://www.alz.org/), currently there are 5.7 million people living with AD only in the US and it is expected that this number would increase to 13.8 million by 2050  . Although there is no cure for AD  , several treatments have been tested BIB002 , for example, currently approved drugs such as donepezil, galantamine, and rivastigmine BIB009 and nonpharmacologic therapies  . Alzheimer' disease is frequently diagnosed at late stages when symptoms have become evident, which occurs after a process of months or years of neuron degeneration BIB002 . However, when diagnosed at early stages, treatment helps to overcome the symptoms and improves the quality of life BIB006 BIB002 and offers to caregivers the opportunity to adapt and prepare the characteristics changes of dementia  . Also, the early diagnosis would allow testing the administration of more aggressive therapy to prevent AD development BIB010 . Despite many efforts, the noninvasive diagnosis of AD at early stages remains unsolved  BIB005 . Recent literature reviews have outlined robust findings demonstrating that eye movements abnormalities are sign of cognitive decline BIB007 BIB004 and can eventually be used to assess AD disease progression. Furthermore, current technology provides noninvasive equipment and methods to assess visual deficits ubiquitously and objectively in naturalistic scenarios  . An example is the use of eye trackers, which are devices that measure gaze fixation and saccadic motions of eyes. Eye trackers have been used in experiments of oculomotor performance related to AD diagnosis  . However, currently To analyze eye movements in naturalistic scenarios, such as in activities of daily living (ADL), besides the gaze fixation points, understanding the scene is required. The understanding of the scene can be achieved through analysis of recorded video with computer vision techniques. The computational analysis of the video, supported by the areas of psychology and neurology, allows distinguishing the items from the scenes that grab the attention of the viewer  BIB008 . This information can be used to compare the areas of interest from people with AD (PwAD) and control groups (people without AD) when observing natural scenes with a potential use in early detection. In this paper, we firstly describe technological tools and methods that have been used to gather eye movements data. Then, we review existing research that has encountered relation between eye movements and AD. This section also describes a evolution of research on eye movements and AD since earliest research towards naturalistic scenarios more suitable for early detection. Section 4 describes computational techniques that are useful for complementing the analysis of eye movements and AD in naturalistic scenarios. Finally, Section 5 includes the conclusion and future directions.