Alzheimer’s disease (AD) is a chronic and progressive, irreversible syndrome that deteriorates the cognitive functions. Official death certificates of 2013 reported 84,767 deaths from Alzheimer’s disease, making it the 6th leading cause of death in the United States. The rate of AD is estimated to double by 2050. The neurodegeneration of AD occurs decades before symptoms of dementia are evident. Therefore, having an efficient methodology for the early and proper diagnosis can lead to more effective treatments. Neuroimaging techniques such as magnetic resonance imaging (MRI) can detect changes in the brain of living subjects. Moreover, medical imaging techniques are the best diagnostic tools to determine brain atrophies; however, a significant limitation is the level of training, methodology, and experience of the diagnostician. Thus, Computer aided diagnosis (CAD) systems are part of a promising tool to help improve the diagnostic outcomes. No publications addressing the use of Feedforward Artificial Neural Networks (ANN), and MRI image attributes for the classification of AD were found. Consequently, the focus of this study is to investigate if the use of MRI images, specifically texture and frequency attributes along with a feedforward ANN model, can lead to the classification of individuals with AD. Moreover, this study compared the use of a single view versus a multi-view of MRI images and their performance. The frequency, texture, and MRI views in combination with the feedforward artificial neural network were tested to determine if they were comparable to the clinician’s performance. The clinician’s performances used were 78 percent accuracy, 87 percent sensitivity, 71 percent specificity, and 78 percent precision from a study with 1,073 individuals. The study found that the use of the Discrete Wavelet Transform (DWT) and Fourier Transform (FT) low frequency give comparable results to the clinicians; however, the FT outperformed the clinicians with an accuracy of 85 percent, precision of 87 percent, sensitivity of 90 percent and specificity of 75 percent. In the case of texture, a single texture feature, and the combination of two or more features gave results comparable to the clinicians. However, the Gray level co-occurrence matrix (GLCOM), which is the combination of texture features, was the highest performing texture method with 82 percent accuracy, 86 percent sensitivity, 76 percent specificity, and 86 percent precision. Combination CII (energy and entropy) outperformed all other combinations with 78 percent accuracy, 88 percent sensitivity, 72 percent specificity, and 78 percent precision. Additionally, a combination of views can increase performance for certain texture attributes; however, the axial view outperformed the sagittal and coronal views in the case of frequency attributes. In conclusion, this study found that both texture and frequency characteristics in combinations with a feedforward backpropagation neural network can perform at the level of the clinician and even higher depending on the attribute and the view or combination of views used.

<p>  </p> <p>Understanding the mechanical properties of peripheral nerves is essential for chronically implanted device design. The work in this thesis aimed to understand the relationship between local deformation responses to global strain changes in peripheral nerves. A custom-built mechanical testing rig and sample holder enabled an improved cyclical uniaxial tensile testing environment on rabbit sciatic nerves (N=5). A speckle was placed on the surface of the nerve and recorded with a microscope camera to track local deformations. The development of a semi-automated digital image processing algorithm systematically measured local speckle dimension and nerve diameter changes. Combined with the measured force response, local and global strain values constructed a stress-strain relationship and corresponding elastic modulus. Preliminary exploration of models such as Fung and 2-Term Mooney-Rivlin confirmed the hyperelastic nature of the nerve. The results of strain analysis show that, on average, local strain levels were approximately five times smaller than globally measured strains; however, the relationship was dependent on global strain magnitude. Elastic modulus values corresponding to ~9% global strains were 2.070 ± 1.020 MPa globally and 10.15 ± 4 MPa locally. Elastic modulus values corresponding to ~6% global strains were 0.173 ± 0.091 MPa globally and 1.030 ± 0.532 MPa locally.   </p>

<p>Small nematode model organisms such as <em>Caenorhabditis elegans</em> are widely used in the fields of neurobiology, toxicology, drug discovery, etc. They are advantageous due to their fully characterized genomic and cellular system. Traditional screening methods involve the exposure of animals to chemicals/drugs inside multiwell-plates while its effects on growth, movement and other cellular/sub-cellular processes are monitored by visual inspection. Yet, these methods are time-consuming, low-throughput, expensive, tedious, difficult to control, hard to modulate instantaneously, prone to subjectivity and not suitable for movement-based behavioural assays. Hence, a method to induce and to quantify movement on-demand in a rapid, sensitive, precise and reversible manner would greatly facilitate biological studies. In this thesis, microfluidic engineering approaches have been utilized in nematode-based assays due to their potential to obtain high precision measurements in a low-cost, rapid and automated manner. Movement response of worms to a diverse range of electric signals has been quantitatively characterized. DC and pulse-DC electric fields have been shown to stimulate worms’ swimming towards the negative electrode inside a microchannel (electrotaxis). AC electric fields were used to inhibit movement on-demand. Animals’ movement has been characterized in terms of speed and range of motion, body-bend frequency and turning time. Electrotaxis was shown to be mediated by neuronal activities and correlations between animal’s behaviour and neuronal signalling has also been demonstrated. Using this basic understanding, multiple microfluidic components such as position sensors and electric immobilizers have been developed. Electrotaxis has then been applied as a technique to sort worms in accordance to their size/age and phenotype as well as to perform drug screening at a single-animal level. Integration of the techniques and components developed during this research is expected to have a significant impact on the development of an integrated microfluidic platform for high throughput automated behavioural screening of nematodes with applications in drug discovery, toxicology, neurobiology and genetics.</p> / Doctor of Philosophy (PhD)

The current research work aims at the development of Biomedical Neuroengineering tools (Biotechnologies) for the in-depth functional study, rapid diagnosis, continuous monitoring and well-timed management of acute and chronic brain disorders, of individuals that are subjected to or suffer from any kind of systemic hypoxaemia or more localized brain hypoxia; as well as the functional assessment and continuous control of adaptability during the training of “altinauts” and generally of individuals that practice activities and function within environments of increased visual-cognitive-motor response demands (a type of brain “stress test”). For this purpose, we subject the entire visuocognitive system, from the elementary sensory to the most complex cognitive level, to an experimental test of categorical discrimination of complex visuocognitive stimuli, following ultra-rapid visual stimulation that leads to a motor response upon categorization of targets (images of animals elicit productive responses) and to its suppression upon categorization of nontargets (images of nonanimals elicit inhibitory responses). The oscillatory electro-physiological responses that are concurrently recorded at the occipital-temporal-parietal brain areas are analyzed in the time-domain (<20Hz) and in the joint time-frequency domain broadband (1-60Hz) with the Continuous Wavelet Transform that optimizes the multiresolution analysis of the high frequency (≥20Hz) γ-band oscillatory activity. This visuocognitive categorization test takes place in normoxaemic as well as hypoxaemic conditions (monitored reduction in the blood oxygen saturation from ≥97% to around 80% under conditions of hypobaric hypoxia within a hypobaric chamber), in order to assess electrophysiological markers that can detect and capture in the most sensitive and dynamic way even so transient, short-living and rather mild changes in brain function. The statistical parametric analysis of the time-frequency maps and the generalized, statistically safer, method of analysis of variance have established as the most sensitive and reliable the following markers: the major deflections of the evoked potentials, the phase-coherence factor of the oscillations across single-trials and the elicited energy of the evoked/phase-locked and the induced/total oscillatory activity. These electrophysiological markers in conjunction with psychometric tests allow for the investigation of the stages/levels of the decline as well as of the compensatory reserves in the visual-perceptive and cognitive-mental brain functions in order to determine the functional sensitivity thresholds of different brain functions to hypoxia. They open up the way for the functional characterization, the diagnosis and monitoring of brain insults or other acute and chronic pathological brain conditions. / Η παρούσα ερευνητική εργασία στοχεύει στην ανάπτυξη εργαλείων Βιοϊατρικής Νευρομηχανικής (Βιοτεχνολογίες) για την σε βάθος λειτουργική μελέτη, ταχεία διάγνωση, συνεχή παρακολούθηση και έγκαιρη αντιμετώπιση οξέων και χρόνιων εγκεφαλικών διαταραχών, ατόμων που υπόκεινται σε ή πάσχουν από οιαδήποτε μορφή συστηματικής υποξαιμίας ή πιο εντοπισμένης εγκεφαλικής υποξίας, καθώς και για την λειτουργική αξιολόγηση και το συνεχή έλεγχο της προσαρμοστικότητας κατά την εξάσκηση των «υψιβατών», και γενικότερα ατόμων που ασκούν δραστηριότητες και λειτουργούν μέσα σε περιβάλλοντα αυξημένων οπτικο-γνωστικο-κινητικών απαιτήσεων (ένα είδος «στρες τεστ» για τον εγκέφαλο). Για το σκοπό αυτό υποβάλλουμε ολόκληρο το οπτικογνωστικό σύστημα, από το στοιχειώδες αισθητηριακό έως το πιο πολύπλοκο νοητικό επίπεδο, σε μια πειραματική δοκιμασία κατηγορικής διάκρισης σύνθετων οπτικογνωστικών ερεθισμάτων, μετά από υπερταχεία οπτική διέγερση που οδηγεί στην έκλυση κινητικής απάντησης κατά την κατηγοριοποίηση στόχων (εικόνες «ζώων» εκλύουν παραγωγικές αποκρίσεις) και στην καταστολή της κατά την κατηγοριοποίηση μη-στόχων (εικόνες «μη-ζώων» εκλύουν ανασταλτικές αποκρίσεις). Οι ταλαντωτικές ηλεκτροφυσιολογικές αποκρίσεις που συγχρόνως καταγράφονται στις ινιακές-κροταφικές-βρεγματικές περιοχές του εγκεφάλου αναλύονται στο πεδίο του χρόνου (<20Hz) και στο συζευγμένο χρονοφασματικό πεδίο ευρυζωνικά (1-60Hz) με το συνεχή μετασχηματισμό του κυματίου που βελτιστοποιεί την πολυφασματική ανάλυση της υψίσυχνης (≥20Hz) γ-ταλαντωτικής δραστηριότητας. Αυτή η δοκιμασία οπτικογνωστικής κατηγοριοποίησης λαμβάνει χώρα τόσο σε νορμοξαιμικές όσο και υποξαιμικές συνθήκες (ελεγχόμενη μείωση στον κορεσμό του αίματος σε οξυγόνο από ≥97% γύρω στο 80% για 15 λεπτά κάτω από συνθήκες υποβαρικής υποξίας μέσα σε υποβαρικό θάλαμο), προκειμένου να ελέγξουμε ηλεκτροφυσιολογικούς δείκτες που μπορούν να ανιχνεύσουν και να συλλάβουν με τον πιο ευαίσθητο και δυναμικό τρόπο ακόμη και τόσο βραχύβιες και σχετικά ήπιες μεταβολές της εγκεφαλικής λειτουργίας. Η στατιστική παραμετρική ανάλυση των χρονοφασματικών χαρτών και η γενικευμένη, στατιστικά πιο ασφαλής, μέθοδος ανάλυσης των διακυμάνσεων ανέδειξαν ως πλέον ευαίσθητους και αξιόπιστους τους ακόλουθους δείκτες: τις κύριες αιχμές των προκλητών δυναμικών, τον παράγοντα φασικής συνάφειας των ταλαντώσεων μεταξύ των μοναδιαίων καταγραφών και την εκλυόμενη ενέργεια των προκλητών/φασικά-κλειδωμένων και επαγόμενων/ολικών ταλαντώσεων. Οι ηλεκτροφυσιολογικοί αυτοί δείκτες σε συνδυασμό με ψυχομετρικές δοκιμασίες επιτρέπουν τη διερεύνηση των σταδίων/επιπέδων κάμψης καθώς και των αποθεμάτων αντιρρόπησης των οπτικο-αντιληπτικών και γνωστικών-νοητικών λειτουργιών του εγκεφάλου για τον καθορισμό των λειτουργικών ουδών ευαισθησίας διάφορων εγκεφαλικών λειτουργιών στην υποξία. Ανοίγουν μάλιστα το δρόμο. για το λειτουργικό χαρακτηρισμό, τη διάγνωση και την παρακολούθηση εγκεφαλικών προσβολών ή άλλων οξέων και χρόνιων παθολογικών καταστάσεων του εγκεφάλου.