arXiv subjects

Giacomo Mazzamuto

Publications and source records attributed to Giacomo Mazzamuto.

9 recordsLinked to original sources

arXiv2024

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

q-bio.OT↗

arXiv2023

Breakdown of self-similarity in light transport

Transport processes underpin a multitude of phenomena, ranging from the propagation of atoms on lattices, to the mobility patterns of microorganisms and earthquakes, to name a few. The dynamics of these processes is very rich and key to understanding the complex nature of the underlying physics, but the way in which we classify them is often too simplistic to fully reflect this complexity. Here, we report on the experimental observation of a breakdown of self-similar propagation for light inside a scattering medium - a transport regime exhibiting different scaling rates for each spatial moment of the associated probability distribution. Notably, we show that this phenomenon arises for light waves even in the simple case of isotropic and homogeneous disorder, and can be controlled by tuning the turbidity of the system. These results support the idea that the traditional dichotomy between normal and anomalous diffusion is reductive and that a richer framework should be constructed based on the concept of self-similarity as this class of transport regimes may be far more common that it is currently believed. In addition, this insight can help understand scenarios where transport is dominated by rare propagation events, as in non-linear and active media, or more generally in other fields of research.

physics.optics↗

arXiv2021

Fast whole-brain imaging of seizures in zebrafish larvae by two-photon light-sheet microscopy

Light-sheet fluorescence microscopy (LSFM) enables real-time whole-brain functional imaging in zebrafish larvae. Conventional one photon LSFM can however induce undesirable visual stimulation due to the use of visible excitation light. The use of two-photon (2P) excitation, employing near-infrared invisible light, provides unbiased investigation of neuronal circuit dynamics. However, due to the low efficiency of the 2P absorption process, the imaging speed of this technique is typically limited by the signal-to-noise-ratio. Here, we describe a 2P LSFM setup designed for non-invasive imaging that enables quintuplicating state-of-the-art volumetric acquisition rate of the larval zebrafish brain (5 Hz) while keeping low the laser intensity on the specimen. We applied our system to the study of pharmacologically-induced acute seizures, characterizing the spatial-temporal dynamics of pathological activity and describing for the first time the appearance of caudo-rostral ictal waves (CRIWs).

q-bio.QM↗

arXiv2020

Semantic Segmentation of Neuronal Bodies in Fluorescence Microscopy Using a 2D+3D CNN Training Strategy with Sparsely Annotated Data

Semantic segmentation of neuronal structures in 3D high-resolution fluorescence microscopy imaging of the human brain cortex can take advantage of bidimensional CNNs, which yield good results in neuron localization but lead to inaccurate surface reconstruction. 3D CNNs, on the other hand, would require manually annotated volumetric data on a large scale and hence considerable human effort. Semi-supervised alternative strategies which make use only of sparse annotations suffer from longer training times and achieved models tend to have increased capacity compared to 2D CNNs, needing more ground truth data to attain similar results. To overcome these issues we propose a two-phase strategy for training native 3D CNN models on sparse 2D annotations where missing labels are inferred by a 2D CNN model and combined with manual annotations in a weighted manner during loss calculation.

eess.IV↗

arXiv2019

Photonic bands, superchirality, and inverse design of a chiral minimal metasurface

Photonic band structures are a typical fingerprint of periodic optical structures, and are usually observed in spectroscopic quantities such as transmission, reflection and absorption. Here we show that also the chiro-optical response of a metasurface constituted by a lattice of non-centrosymmetric, L-shaped holes in a dielectric slab shows a band structure, where intrinsic and extrinsic chirality effects are clearly recognized and connected to localized and delocalized resonances. Superchiral near-fields can be excited in correspondence to these resonances, and anomalous behaviors as a function of the incidence polarization occur. Moreover, we introduce a singular value decomposition (SVD) approach to show that the above mentioned effects are connected to specific fingerprints of the SVD spectra. Finally, we demonstrate by means of an inverse design technique that the metasurface based on an L-shaped hole array is a minimal one. Indeed, its unit cell geometry depends on the smallest number of parameters needed to implement arbitrary transmission matrices compliant with the general symmetries for 2d-chiral structures. These observations enable more powerful wave operations in a lossless photonic environment.

physics.optics↗

arXiv2017

CELES: CUDA-accelerated simulation of electromagnetic scattering by large ensembles of spheres

CELES is a freely available MATLAB toolbox to simulate light scattering by many spherical particles. Aiming at high computational performance, CELES leverages block-diagonal preconditioning, a lookup-table approach to evaluate costly functions and massively parallel execution on NVIDIA graphics processing units using the CUDA computing platform. The combination of these techniques allows to efficiently address large electrodynamic problems ($>10^4$ scatterers) on inexpensive consumer hardware. In this paper, we validate near- and far-field distributions against the well-established multi-sphere $T$-matrix (MSTM) code and discuss the convergence behavior for ensembles of different sizes, including an exemplary system comprising $10^5$ particles.

physics.comp-ph↗

arXiv2015

Deducing effective light transport parameters in optically thin systems

We present an extensive Monte Carlo study on light transport in optically thin slabs, addressing both axial and transverse propagation. We completely characterize the so-called ballistic-to-diffusive transition, notably in terms of the spatial variance of the transmitted/reflected profile. We test the validity of the prediction cast by diffusion theory, that the spatial variance should grow independently of absorption and, to a first approximation, of the sample thickness and refractive index contrast. Based on a large set of simulated data, we build a freely available look-up table routine allowing reliable and precise determination of the microscopic transport parameters starting from robust observables which are independent of absolute intensity measurements. We also present the Monte Carlo software package that was developed for the purpose of this study.

physics.optics↗

arXiv2015

Diffusion of light in semitransparent media

Light diffusion is usually associated with thick, opaque media. Indeed, multiple scattering is necessary for the onset of the diffusive regime and such condition is generally not met in almost transparent media. Nonetheless, at long enough times, transport in an infinite thin slab is still determined by a multiple scattering process whose complete characterization is lacking. In this paper we show that, after a short transient, the mean square width of the transmitted intensity still exhibits a simple linear increase with time as predicted by diffusion theory, even at optical thickness as low as one. Interestingly, such linear growth is predicted not to depend neither on the slab thickness nor on its refractive index contrast, yet the accuracy of this simple approximation in the ballistic-to-diffusive regime hasn't been investigated so far. By means of Monte Carlo simulations, we find clear evidence that boundary conditions play an active role in redefining the very asymptotic value of the diffusion coefficient by directly modifying the statistical distributions underlying light transport in such media. In this respect, we demonstrate the need to distinguish between a set of intrinsic and effective transport parameters, whose relation and interplay with boundary conditions remains to be fully understood.

physics.optics↗

arXiv2015

Key components for nano-assembled plasmon-excited single molecule non-linear devices

Tremendous enhancement of light-matter interaction in plasmon-excited molecular hybrid devices allows for non-linearities on the level of single emitters and few photons. This promises a plethora of novel applications like single photon transistors. Nevertheless, building the components of such devices is technologically extremely challenging. We tackle this task by lithographically fabricating on-chip plasmonic waveguides, efficiently connected to far-field in- and out-coupling ports via low-loss dielectric waveguides. Furthermore, a nano-assembling technology is developed, enabling the controlled coupling of single organic emitters to the plasmonic waveguides. Dibenzoterrylene fluorescent molecules hosted in anthracene crystals are investigated for this purpose. Here we present all key-components and technologies for a plasmon-excited single molecule non-linear device.

physics.optics↗