Two-photon minimal inertia scanning patterns for fast acquisition of calcium dynamics

Development of optical technologies aiming to reverse engineer neural circuits has been flourishing over the past two decades. Multi-Photon Laser Scanning Microscopy (MPLMS) together with the development of fast kinetic fluorescent calcium dyes has revolutionised the world of modern neuroscience. This technology enables mesoscale functional imaging in deep scattering brain tissues of large two (2D) and three dimensional (3D) neural networks. With single cell sensitivity in vitro as well as in vivo, it is one of the main contenders for deciphering higher brain functions. My approach in this thesis is to develop and test new scanning techniques for fast functional calcium imaging aiming to enhance the temporal precision of the acquisition. To avoid the slow and sequential "point" raster scanning nature of these Galvanometric Scanners (GSs) based microscopes, I developed new 2D and 3D scanning algorithms. These algorithms were developed in MATLAB with a simulation platform that models the main mechanical elements of the MPLSM. Both my 2D Adaptive Spiral Scanning (SSA) algorithm and my 3D Orbital Scanning Trajectory (OST) algorithm were developed to minimize the inertial slowdowns of the GSs and Electrical Tunable Lens (ETL) and therefore increase the temporal resolution of the acquisition. In 2D, I tested the SSA algorithm on in vitro hippocampal brain slices loaded with the synthetic calcium dye Cal520. To assess the performance of the scanning technique, I used the Cramer-Rao Bound (CRB) as a metric for signal quality. The CRB estimates the time of occurrence of an Action Potential (AP) from the calcium imaging data, taking into account the sampling frequency and the SNR of the acquisition. In this thesis, I show that the use of scanning strategies enables sampling rates one order of magnitude higher than traditional frame scanning in functional calcium imaging. I also show that frame scanning needs considerably higher SNR values than scanning strategies to reach the same temporal precision. In 3D, I implemented the scanning algorithms into the software and hardware of the MPLSM and recorded the trajectory of the focal point with a high-speed camera as a proof of principle. More analyses regarding the precision of the paths needs to be carried out in 3D for functional calcium imaging in vitro or in vivo. These software-based scanning strategies are attractive as they are inexpensive, easily transferable from one setup to another and enable fast functional calcium imaging with standard commercial MPSLMs. Finally, through this implementation of scanning strategies, I recorded multiple data sets of spontaneous and evoked activity in populations of Dentate Granular Cells (DGCs). This lead to the new beginning of a larger in vitro investigation at the microcircuit level on the functionality of the DG.Open Acces

Comparison of histological delineations of medial temporal lobe cortices by four independent neuroanatomy laboratories

The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and prone to the accumulation of certain neuropathologies such as Alzheimer's disease neurofibrillary tau tangles. The MTL cortex is composed of several subregions which differ in their functional and cytoarchitectonic features. As neuroanatomical schools rely on different cytoarchitectonic definitions of these subregions, it is unclear to what extent their delineations of MTL cortex subregions overlap. Here, we provide an overview of cytoarchitectonic definitions of the entorhinal and parahippocampal cortices as well as Brodmann areas (BA) 35 and 36, as provided by four neuroanatomists from different laboratories, aiming to identify the rationale for overlapping and diverging delineations. Nissl-stained series were acquired from the temporal lobes of three human specimens (two right and one left hemisphere). Slices (50 μm thick) were prepared perpendicular to the long axis of the hippocampus spanning the entire longitudinal extent of the MTL cortex. Four neuroanatomists annotated MTL cortex subregions on digitized slices spaced 5 mm apart (pixel size 0.4 μm at 20× magnification). Parcellations, terminology, and border placement were compared among neuroanatomists. Cytoarchitectonic features of each subregion are described in detail. Qualitative analysis of the annotations showed higher agreement in the definitions of the entorhinal cortex and BA35, while the definitions of BA36 and the parahippocampal cortex exhibited less overlap among neuroanatomists. The degree of overlap of cytoarchitectonic definitions was partially reflected in the neuroanatomists' agreement on the respective delineations. Lower agreement in annotations was observed in transitional zones between structures where seminal cytoarchitectonic features are expressed less saliently. The results highlight that definitions and parcellations of the MTL cortex differ among neuroanatomical schools and thereby increase understanding of why these differences may arise. This work sets a crucial foundation to further advance anatomically-informed neuroimaging research on the human MTL cortex

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.</p

An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms.

Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells

An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms.

Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells