Agents, nodes & resources: Universal naming system for a coordination middleware

La tesi si propone di sviluppare un modello, l'architettura e la tecnologia per il sistema di denominazione del Middleware Coordinato TuCSoN, compresi gli agenti, i nodi e le risorse. Identità universali che rappresentano queste entità, sia per la mobilità fisica sia per quella virtuale, per un Management System (AMS, NMS, RMS) distribuito; tale modulo si occupa anche di ACC e trasduttori, prevedendo questioni come la tolleranza ai guasti, la persistenza, la coerenza, insieme con il coordinamento disincarnata in rete, come accade con le tecnologie Cloud. All’interno dell’elaborato, per prima cosa si è fatta una introduzione andando a descrivere tutto ciò che è contenuto nell’elaborato in modo da dare una visione iniziale globale del lavoro eseguito. Di seguito (1° capitolo) si è descritta tutta la parte relativa alle conoscenze di base che bisogna avere per la comprensione dell’elaborato; tali conoscenze sono relative a TuCSoN (il middleware coordinato con cui il modulo progettato dovrà interfacciarsi) e Cassandra (sistema server distribuito su cui si appoggia la parte di mantenimento e salvataggio dati del modulo). In seguito (2° capitolo) si è descritto JADE, un middleware da cui si è partiti con lo studio per la progettazione del modello e dell’architettura del modulo. Successivamente (3° capitolo) si è andati a spiegare la struttura e il modello del modulo considerato andando ad esaminare tutti i dettagli relativi alle entità interne e di tutti i legami fra esse. In questa parte si è anche dettagliata tutta la parte relativa alla distribuzione sulla rete del modulo e dei suoi componenti. In seguito (4° capitolo) è stata dettagliata e spiegata tutta la parte relativa al sistema di denominazione del modulo, quindi la sintassi e l’insieme di procedure che l’entità consumatrice esterna deve effettuare per ottenere un “nome universale” e quindi anche tutti i passaggi interni del modulo per fornire l’identificatore all’entità consumatrice. Nel capitolo successivo (5° capitolo) si sono descritti tutti i casi di studio relativi alle interazioni con le entità esterne, alle entità interne in caso in cui il modulo sia o meno distribuito sulla rete, e i casi di studio relativi alle politiche, paradigmi e procedure per la tolleranza ai guasti ed agli errori in modo da dettagliare i metodi di riparazione ad essi. Successivamente (6° capitolo) sono stati descritti i possibili sviluppi futuri relativi a nuove forme di interazione fra le entità che utilizzano questo modulo ed alle possibili migliorie e sviluppi tecnologici di questo modulo. Infine sono state descritte le conclusioni relative al modulo progettato con tutti i dettagli in modo da fornire una visione globale di quanto inserito e descritto nell’elaborato.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Imagery of a moving object: the role of occipital cortex and human MT/V5+

Visual imagery – similar to visual perception – activates feature-specific and category-specific visual areas. This is frequently observed in experiments where the instruction is to imagine stimuli that have been shown immediately before the imagery task. Hence, feature-specific activation could be related to the short-term memory retrieval of previously presented sensory information. Here, we investigated mental imagery of stimuli that subjects had not seen before, eliminating the effects of short-term memory. We recorded brain activation using fMRI while subjects performed a behaviourally controlled guided imagery task in predefined retinotopic coordinates to optimize sensitivity in early visual areas. Whole brain analyses revealed activation in a parieto-frontal network and lateral–occipital cortex. Region of interest (ROI) based analyses showed activation in left hMT/V5+. Granger causality mapping taking left hMT/V5+ as source revealed an imagery-specific directed influence from the left inferior parietal lobule (IPL). Interestingly, we observed a negative BOLD response in V1–3 during imagery, modulated by the retinotopic location of the imagined motion trace. Our results indicate that rule-based motion imagery can activate higher-order visual areas involved in motion perception, with a role for top-down directed influences originating in IPL. Lower-order visual areas (V1, V2 and V3) were down-regulated during this type of imagery, possibly reflecting inhibition to avoid visual input from interfering with the imagery construction. This suggests that the activation in early visual areas observed in previous studies might be related to short- or long-term memory retrieval of specific sensory experiences.

Neural networks engaged in tactile object manipulation: patterns of expression among healthy individuals

Somatosensory object discrimination has been shown to involve widespread cortical and subcortical structures in both cerebral hemispheres. In this study we aimed to identify the networks involved in tactile object manipulation by principal component analysis (PCA) of individual subjects. We expected to find more than one network.

Specific attentional impairments and complex visual hallucinations in eye disease

OBJECTIVE: To test the prediction by the Perception and Attention Deficit (PAD) model of complex visual hallucinations that cognitive impairment, specifically in visual attention, is a key risk factor for complex hallucinations in eye disease. METHODS: Two studies of elderly patients with acquired eye disease investigated the relationship between complex visual hallucinations (CVH) and impairments in general cognition and verbal attention (Study 1) and between CVH, selective visual attention and visual object perception (Study 2). The North East Visual Hallucinations Inventory was used to classify CVH. RESULTS: In Study 1, there was no relationship between CVH (n=10/39) and performance on cognitive screening or verbal attention tasks. In Study 2, participants with CVH (n=11/31) showed poorer performance on a modified Stroop task (p<0.05), a novel imagery-based attentional task (p<0.05) and picture (p<0.05) but not silhouette naming (p=0.13) tasks. Performance on these tasks correctly classified 83% of the participants as hallucinators or non-hallucinators. CONCLUSIONS: The results suggest that, consistent with the PAD model, complex visual hallucinations in people with acquired eye disease are associated with visual attention impairment.

Theta Burst Stimulation Over the Right Broca's Homologue Induces Improvement of Naming in Aphasic Patients

Improvements of language production in aphasic patients have been reported following repeated 1-Hz transcranial magnetic stimulation over the nondamaged right hemisphere. Most studies examined aphasic patients in the chronic phase. The effect of transcranial magnetic stimulation application in acute or subacute patients has not been systematically studied. We aimed to evaluate whether continuous theta burst stimulation, an inhibitory protocol with a shorter application time than the common 1-Hz protocol, is able to improve naming performance in aphasic patients in different poststroke phases.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

Use Of Conspecific Gestural Cues To Solve An Object-Choice Task In Tufted Capuchin Monkeys (Cebus Apella)

Capuchin monkeys, Cebus sp., utilize a wide array of gestural displays in the wild, including facial displays such as lip-smacking and bare-teeth displays. In captivity, they have been shown to respond to the head orientation of humans, show sensitivity to human attentional states, as well as follow human gazes behind barriers. In this study, I investigated whether tufted capuchin monkeys (Cebus apella) would attend to and utilize the gestural cues of a conspecific to obtain a hidden reward. Two capuchins faced each other in separate compartments of an apparatus with an open field in between. The open field contained two cups with holes on one side such that only one monkey, a so-called cuing monkey, could see the reward inside one of the cups. I then moved the cups toward the other signal-receiving monkey and assessed whether it would utilize untrained cues provided by the cuing monkey to select the cup containing the reward. Two of four female capuchin monkeys learned to select the cup containing the reward significantly more often than chance. Neither of these two monkeys performed over chance spontaneously, however, and the other two monkeys never performed above chance despite many blocks of trials. Successful choices by two monkeys to obtain hidden rewards provided experimental evidence that capuchin monkeys attend to and utilize the gestural cues of conspecifics.