Biology subjects

Pestilli, F.

Publications and source records attributed to Pestilli, F..

26 records · Page 2Linked to original sources

bioRxiv2020

Visual information routes in the posterior dorsal and ventral face network studied with intracranial neurophysiology, and white matter tract endpoints

Occipito-temporal regions within the face network process perceptual and socio-emotional information, but the dynamics and information flow between different nodes of this network is still debated. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other network regions. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes in the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. Overall, our data provide new insight on the timing of face and social cue processing in the occipito-temporal brain and anchor the superior temporal cortex in dynamic gaze processing.

animal behavior and cognition↗

bioRxiv2020

The visual white matter connecting human area prostriata and the thalamus is retinotopically organized

The human visual system is capable of processing visual information from fovea to the far peripheral visual field. Recent fMRI studies have shown a full and detailed retinotopic map in area prostriata, located ventro-dorsally and anterior to the calcarine sulcus along the parietooccipital sulcus with strong preference for peripheral and wide-field stimulation. Here, we report the anatomical pattern of white-matter connections between area prostriata and the thalamus encompassing the lateral geniculate nucleus (LGN). We observe a continuous and extended bundle of white matter fibers from which two subcomponents can be extracted: one passing ventrally parallel to the optic radiations (OR) and another passing dorsally circumventing the lateral ventricle. Interestingly, the loop travelling dorsally connects the thalamus with the central visual field representation of prostriata, while the other loop travelling more ventrally connects the LGN with the more peripheral visual field representation. This is consistent with a retinotopic segregation recently demonstrated in the OR, connecting the LGN and V1 in humans. Our results demonstrate for the first time a retinotopic segregation regarding the trajectory of a fiber bundle between the thalamus and an associative visual area.

neuroscience↗

bioRxiv2020

Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation

Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bundles from diffusion Magnetic Resonance Imaging (dMRI) data indirectly, by exploiting either the idea of connectivity between regions or the geometry of fiber paths obtained with tractography techniques, or, directly, through the information in volumetric data. Despite the remarkable improvement in automatic segmentation methods over the years, their segmentation quality is not yet satisfactory, especially when dealing with datasets with very diverse characteristics, such as different tracking methods, bundle sizes or data quality. In this work, we propose a novel, supervised streamline-based segmentation method, called Classifyber, which combines information from atlases, connectivity patterns, and the geometry of fiber paths into a simple linear model. With a wide range of experiments on multiple datasets that span from research to clinical domains, we show that Classifyber substantially improves the quality of segmentation as compared to other state-of-the-art methods and, more importantly, that it is robust across very diverse settings. We provide an implementation of the proposed method as open source code, as well as web service.

neuroscience↗

bioRxiv2019

Triple visual hemifield maps in optic chiasm hypoplasia

In humans, each hemisphere comprises an overlay of two visuotopic maps of the contralateral visual field, one from each eye. Is the capacity of the visual cortex limited to these two maps or are plastic mechanisms available to host more maps? Using an integrative approach of submillimeter fMRI, diffusion-weighted imaging and population receptive field mapping, we found three hemiretinal inputs to converge onto the left hemisphere in a rare individual with chiasma hypoplasia. This generates extremely atypical responses in striate and extrastriate cortices, specifically an overlay of three hemifield representations. Unexpectedly, the effects of this large abnormality on visual function in daily life are not easily detected. We conclude that developmental plasticity including the re-wiring of local intra- and cortico-cortical connections is pivotal to support the coexistence and functioning of three hemifield maps within one hemisphere.

neuroscience↗

bioRxiv2019

Quantifying nerve decussation abnormalities in the optic chiasm

ObjectiveThe human optic chiasm comprises partially crossing optic nerve fibres. Here we used diffusion MRI (dMRI) for the in-vivo identification of the abnormally high proportion of crossing fibres found in the optic chiasm of people with albinism.\n\nMethodsIn 9 individuals with albinism and 8 controls high-resolution 3T dMRI data was acquired and analyzed with a set of methods for signal modeling [Diffusion Tensor (DT) and Constrained Spherical Deconvolution (CSD)], tractography, and streamline filtering (LiFE, COMMIT, and SIFT2). The number of crossing and non-crossing streamlines and their weights after filtering entered ROC-analyses to compare the discriminative power of the methods based on the area under the curve (AUC). The dMRI results were cross-validated with fMRI estimates of misrouting in a subset of 6 albinotic individuals.\n\nResultsWe detected significant group differences in chiasmal crossing for both unfiltered DT (p=0.014) and CSD tractograms (p=0.0009) also reflected by AUC measures (for DT and CSD: 0.61 and 0.75, respectively), underlining the discriminative power of the approach. Estimates of crossing strengths obtained with dMRI and fMRI were significantly correlated for CSD (R2=0.83, p=0.012). The results show that streamline filtering methods in combination with probabilistic tracking, both optimized for the data at hand, can improve the detection of crossing in the human optic chiasm.\n\nConclusionsEspecially CSD-based tractography provides an efficient approach to detect structural abnormalities in the optic chiasm. The most realistic results were obtained with filtering methods with parameters optimized for the data at hand.\n\nSignificanceOur findings demonstrate a novel anatomy-driven approach for the individualized diagnostics of optic chiasm abnormalities.\n\nHighlightsO_LIDiffusion MRI is capable of detecting structural abnormalities of the optic chiasm.\nC_LIO_LIQuantification of crossing strength in optic chiasm is of promise for albinism diagnostics.\nC_LIO_LIOptic chiasm is a powerful test model for neuroimaging methods resolving crossing fibers.\nC_LI

neuroscience↗

bioRxiv2019

Tractostorm: Rater reproducibility assessment in tractography dissection of the pyramidal tract

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called \"virtual dissection\". Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. The contribution of this study is to provide the first large-scale, international, multi-center variability assessment of the \"virtual dissection\" of the pyramidal tract (PyT). Eleven (11) experts and thirteen (13) non-experts in neuroanatomy and \"virtual dissection\" were asked to perform 30 PyT segmentation and their results were compared using various voxel-wise and streamline-wise measures. Overall the voxel representation is always more reproducible than streamlines ({approx}70% and {approx}35% overlap respectively) and distances between segmentations are also lower for voxel-wise than streamline-wise measures ([3/4]3mm and [3/4]umm respectively). This needs to be seriously considered before using tract-based measures (e.g. bundle volume versus streamline count) for an analysis. We show and argue that future bundle segmentation protocols need to be designed to be more robust to human subjectivity. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction techniques in this era of open and collaborative science.

neuroscience↗

bioRxiv2018

Age-related macular degeneration affects the optic radiation white matter projecting to locations of retinal damage

PurposeWe investigated the impact of age-related macular degeneration (AMD) on visual acuity and the visual white matter.\n\nMethodsWe combined an adaptive cortical atlas and diffusion-weighted magnetic resonance imaging (dMRI) and tractography to separate optic radiation (OR) projections to different retinal eccentricities in human primary visual cortex. We exploited the known anatomical organization of the OR and clinically relevant data to segment the OR into three primary components projecting to fovea, mid- and far-periphery. We measured white matter tissue properties - (fractional anisotropy, linearity, planarity, sphericity) along the aforementioned three components of the optic radiation to compare AMD patients and controls.\n\nResultsWe found differences in white matter properties specific to OR white matter fascicles projecting to primary visual cortex locations corresponding to the location of retinal damage (fovea). Additionally, we show that the magnitude of white matter properties in AMD patients correlates with visual acuity. In sum, we demonstrate a specific relation between visual loss, anatomical location of retinal damage and white matter damage in AMD patients. Importantly, we demonstrate that these changes are so profound that can be detected using magnetic resonance imaging data with clinical resolution. The conserved mapping between retinal and white matter damage suggests that retinal neurodegeneration might be a primary cause of white matter degeneration in AMD patients.\n\nConclusionsThe results highlight the impact of eye disease on brain tissue, a process that may become an important target to monitor during the course of treatment.

neuroscience↗

bioRxiv2017

Multidimensional encoding of brain connectomes

The ability to map brain networks at the macroscale in living individuals is fundamental in efforts to chart the relation between human behavior, health and disease. We present a framework to encode structural brain connectomes and diffusion-weighted magnetic resonance data into multidimensional arrays (tensors). The framework overcomes current limitations in building connectomes; it prevents information loss by integrating the relation between connectome nodes, edges, fascicles and diffusion data. We demonstrate the utility of the framework for in vivo white matter mapping and anatomical computing. The framework reduces dramatically storage requirements for connectome evaluation methods, with up to 40x compression factors. We apply the framework to evaluate 1,980 connectomes, thirteen tractography methods, and three data sets. We describe a general equation to predicts connectome resolution (number of fascicles) given data quality and tractography model parameters. Finally, we provide open-source software implementing the method and data to reproduce the results.

neuroscience↗