Challenges in optics for Extremely Large Telescope instrumentation

We describe and summarize the optical challenges for future instrumentation for Extremely Large Telescopes (ELTs). Knowing the complex instrumental requirements is crucial for the successful design of 30-60m aperture telescopes. After all, the success of ELTs will heavily rely on its instrumentation and this, in turn, will depend on the ability to produce large and ultra-precise optical components like light-weight mirrors, aspheric lenses, segmented filters, and large gratings. New materials and manufacturing processes are currently under study, both at research institutes and in industry. In the present paper, we report on its progress with particular emphasize on volume-phase-holographic gratings, photochromic materials, sintered silicon-carbide mirrors, ion-beam figuring, ultra-precision surfaces, and free-form optics. All are promising technologies opening new degrees of freedom to optical designers. New optronic-mechanical systems will enable efficient use of the very large focal planes. We also provide exploratory descriptions of "old" and "new" optical technologies together with suggestions to instrument designers to overcome some of the challenges placed by ELT instrumentation.Comment: (Proc. OPTICON Key Technology Network Workshop, Rome 20-21 October 2005

Simulated switching of the resting state functional connectivity in mouse brain using a real mesoscale connectome

Capire come modellare l'attività del cervello a riposo, resting state, è il primo passo necessario per avvicinarsi a una reale comprensione della dinamica cerebrale. Sperimentalmente si osserva che, quando il cervello non è soggetto a stimoli esterni, particolari reti di regioni cerebrali presentano un'attività neuronale superiore alla media. Nonostante gli sforzi dei ricercatori, non è ancora chiara la relazione che sussiste tra le connessioni strutturali e le connessioni funzionali del sistema cerebrale a riposo, organizzate nella matrice di connettività funzionale. Recenti studi sperimentali mostrano la natura non stazionaria della connettività funzionale in disaccordo con i modelli in letteratura. Il modello implementato nella presente tesi per simulare l'evoluzione temporale del network permette di riprodurre il comportamento dinamico della connettività funzionale. Per la prima volta in questa tesi, secondo i lavori a noi noti, un modello di resting state è implementato nel cervello di un topo. Poco è noto, infatti, riguardo all'architettura funzionale su larga scala del cervello dei topi, nonostante il largo utilizzo di tale sistema nella modellizzazione dei disturbi neurologici. Le connessioni strutturali utilizzate per definire la topologia della rete neurale sono quelle ottenute dall'Allen Institute for Brain Science. Tale strumento fornisce una straordinaria opportunità per riprodurre simulazioni realistiche, poiché, come affermato nell'articolo che presenta tale lavoro, questo connettoma è il più esauriente disponibile, ad oggi, in ogni specie vertebrata. I parametri liberi del modello sono stati scelti in modo da inizializzare il sistema nel range dinamico ottimale per riprodurre il comportamento dinamico della connettività funzionale. Diverse considerazioni e misure sono state effettuate sul segnale BOLD simulato per meglio comprenderne la natura. L'accordo soddisfacente fra i centri funzionali calcolati nel network cerebrale simulato e quelli ottenuti tramite l'indagine sperimentale di Mechling et al., 2014 comprovano la bontà del modello e dei metodi utilizzati per analizzare il segnale simulato

Rôle du connectome structurel sur l'organisation fonctionnelle de l'état de repos : une étude computationnelle à grande échelle chez la souris

Il est possible d’aborder l'organisation fonctionnelle du cerveau en modélisant le cerveau comme un système dynamique, ce qui permet d'étudier comment l'architecture fonctionnelle dépend du squelette structurel sous-jacent. En combinant approches expérimentales et théoriques chez la souris, nous avons étudié de façon systématique comment le connectome structurel contraint le connectome fonctionnel.Dans une première partie nous avons généralisé à la souris le logiciel open source The Virtual Brain (Sanz-Leon et al., 2013, Melozzi et al., 2017).En utilisant les données d'IRM de diffusion (IRMd) de 19 souris, nous avons virtualisé leur cerveau pour générer un signal BOLD in silico que nous avons comparé aux données d'IRM fonctionnelle enregistrées chez les mêmes souris pendant la veille passive. Nous montrons que les prédictions du modèle basé sur le connectome dépendent strictement de la structure du réseau (Melozzi et al., en révision). Nous démontrons que les variations individuelles définissent une empreinte structurelle spécifique ayant un impact direct sur l'organisation fonctionnelle des cerveaux individuels. Ces résultats démontrent l’existence d’un lien causal entre le connectome structurel et le connectome fonctionnel.Finalement, nous confirmons certaines de nos conclusions en utilisant l’approche inverse: nous avons étudié s’il était possible de déduire le connectome structurel à partir du connectome fonctionnel en utilisant la méthode d'inférence Bayésienne (Melozzi et al., en préparation).Nos résultats aux futures études testant la causalité entre structure et fonction, au niveau du cerveau entier individuel, en conditions physiologique et pathologiqueThe connectome-based model approach aims to understand the functional organization of the brain by modeling the brain as a dynamical system and then studying how the functional architecture rises from the underlying structural skeleton. In this thesis, taking advantage of mice studies, we investigated the informative content of different structural features in explaining the functional ones.First, we extended the open-source software TVB (Leon et al., 2013), originally designed for humans, to accommodate the connectome-based model approach in mice (Melozzi et al., 2017).Using diffusionMRI (dMRI) data from 19 mice, we virtualised their brains to generate in silico fMRI that we compared to functional MRI data recorded in the same mice during passive wakefulness. We show that the predictions of the connectome-based model strictly depend on the structure of the underlying network (Melozzi et al., under review). We demonstrate that individual variations define a specific structural fingerprint with a direct impact upon the functional organization of individual brains. Comparing the predictive power of the tracer-based and the dMRI-based connectome we identify how the limitations of the dMRI method restrict our comprehension of the structural-functional relation. Together, these results strongly support the existence of a causal link between the structural and the functional connectomes.Finally, we infer the connectome form resting state dynamics by inferring the structural connectome using the Bayesian inference (Melozzi et al., in prep).Our results pave the way to future studies focusing on the causal link between structure and function at the individual brain level

Systematic comparison of the use of annular and Zernike circle polynomials for annular wavefronts

The theory of wavefront analysis of a noncircular wavefront is given and applied for a systematic comparison of the use of annular and Zernike circle polynomials for the analysis of an annular wavefront. It is shown that, unlike the annular coefficients, the circle coefficients generally change as the number of polynomials used in the expansion changes. Although the wavefront fit with a certain number of circle polynomials is identically the same as that with the corresponding annular polynomials, the piston circle coefficient does not represent the mean value of the aberration function, and the sum of the squares of the other coefficients does not yield its variance. The interferometer setting errors of tip, tilt, and defocus from a four-circle-polynomial expansion are the same as those from the annular-polynomial expansion. However, if these errors are obtained from, say, an 11-circle polynomial expansion, and are removed from the aberration function, wrong polishing will result by zeroing out the residual aberration function. If the common practice of defining the center of an interferogram and drawing a circle around it is followed, then the circle coefficients of a noncircular interferogram do not yield a correct representation of the aberration function. Moreover, in this case, some of the higher-order coefficients of aberrations that are nonexistent in the aberration function are also nonzero. Finally, the circle coefficients, however obtained, do not represent coefficients of the balanced aberrations for an annular pupil. The various results are illustrated analytically and numerically by considering an annular Seidel aberration function.Applied Science

Nuovo soggettario e DDC

The team of Italian National Bibliography (BNI) wanted the Dewey Classification be an important component of the Nuovo soggettario as the classification is able to represent a bridge towards indexing systems in other languages. Linking DDC numbers to the completely structured terms of the italian Nuovo Soggettario makes the maximum integration and interoperability between the two distinct indexing systems possible. The work was carried out using specific criteria and the problems that occurred derive from the different structure of the two tools and some language differences concerning terms and their meaning. One of the most pressing needs of the BNI team is to refine operative criteria in order to continue this project

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics

International audienc

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics

International audienc

Individual structural features constrain the mouse functional connectome

International audienceWhole brain dynamics intuitively depend upon the internal wiring of the brain; but to which extent the individual structural con-nectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure-function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine