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Concept

Capacité crânienne

vignette|Comparaison, de gauche à droite, d'un cerveau de sanglier, de grand dauphin et d'humain. La capacité crânienne est une mesure du volume de l'intérieur de la boîte crânienne chez les vertébrés qui ont à la fois un crâne et un cerveau. L'unité de mesure la plus utilisée est le centimètre cube. Certains auteurs considèrent le volume du crâne comme un indicateur de la taille du cerveau, laquelle est à son tour utilisée pour indiquer approximativement l'intelligence potentielle de l'organisme. Une plus grande capacité crânienne n'est pas bien sûr toujours l'indication d'un organisme plus intelligent, puisqu'une capacité plus grande est requise pour contrôler le corps lorsqu'il est plus grand. Par conséquent la capacité crânienne comme mètre étalon de l’intelligence a été remplacé par le rapport masse du cerveau sur masse du corps. Cette notion a elle-même été remplacée par le quotient d'encéphalisation qui tient compte du fait que le nombre de neurones nécessaires pour faire fonct

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Mammifère

Les Mammifères (Mammalia) sont une classe d'animaux vertébrés caractérisés par la présence de fourrures (excepté pour certains mammifères marins), d'une oreille moyenne comportant trois os, d'un néo

Brain–body mass ratio

Brain–body mass ratio, also known as the brain–body weight ratio, is the ratio of brain mass to body mass, which is hypothesized to be a rough estimate of the intelligence of an animal, although fai

Évolution (biologie)

En biologie, l’évolution est la transformation du monde vivant au cours du temps, qui se manifeste par des changements phénotypiques des organismes à travers les générations. Ces changements général

Effects of eight neuropsychiatric copy number variants on human brain structure

Bogdan Draganski, Kuldeep Kumar, Lester Melie Garcia, Claudia Modenato, Borja Rodriguez Herreros

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen's d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions.

SPRINGERNATURE2021

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Methods for functional connectivity and morphometry in neonatal neuroimaging to study neurodevelopment.

Serafeim Loukas

Preterm birth is a major pediatric health problem that perturbs the genetically determined program of corticogenesis of the developing brain. As a consequence, prematurity has been strongly associated with adverse long-term neurodevelopmental outcome that may persist even into adulthood. Early characterization of the underlying neuronal mechanisms and early identification of infants at risk is of paramount importance since it allows better development of early therapeutic interventions aiming to prevent adverse outcomes through resilience. This dissertation aims to investigate the consequences of preterm birth on brain function and structure and their relation to adverse neurodevelopmental outcome, as well as to unveil the effect of an early music intervention on brain function. Research to date has mainly focused on the effect of early interventions on the long-term outcome but not on the effect of those interventions on brain function in preterm populations. Moreover, a clear consensus about the predictive utility of MRI volumetric data for long-term outcomes is still missing. This dissertation consists of three main parts. First, we investigate the effects of an early musical intervention in preterm infants using a task-based and resting-state fMRI paradigm. We explore brain effective connectivity changes during task and functional connectivity (FC) modulations at rest. We show that music exposure during hospitalization promotes brain auditory processing maturation. We find increased FC between the auditory cortex and regions involved in familiarity and music processing, such as the thalamus and caudate nucleus. Moreover, we report increased rs-FC in regions involved in associative memory and multisensory processing, such as the calcarine and angular gyrus with a dosage-dependent effect on this modulation. Secondly, we examine brain volumetric development and whether brain volumes are associated with cognitive and behavioural long-term outcomes. We find that perinatal risk factors, such as asphyxia and sepsis have an impact on brain tissue volume. We also find that cognitive and behavioural outcomes are strongly associated with parental SES and that brain tissue volumes at TEA have moderate predictive power. Next, inspired by studies that have characterized the progression of neurodegenerative diseases, we employ an advanced technique to unveil the sequence of biological events along the course of prematurity. Our novel findings might be of clinical use as they allow more targeted early interventions aiming to improve long-term outcomes. Finally, we propose a framework that enables the spectral graph theory analysis of the functional connectome at the voxel level. Our results indicate the presence of both functional gradients and community structure revealing fine-grained connectivity patterns. The proposed framework opens a new avenue for spectral graph theory research at the voxel level.

EPFL2021

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Fourier modeling of the BOLD response to a breath-hold task: Optimization and reproducibility

Patricia Figueiredo, João Pedro Forjaco Jorge, Inês Nunes de Sousa

Cerebrovascular reactivity (CVR) reflects the capacity of blood vessels to adjust their caliber in order to maintain a steady supply of brain perfusion, and it may provide a sensitive disease biomarker. Measurement of the blood oxygen level dependent (BOLD) response to a hypercapnia-inducing breath-hold (BH) task has been frequently used to map CVR noninvasively using functional magnetic resonance imaging (fMRI). However, the best modeling approach for the accurate quantification of CVR maps remains an open issue. Here, we compare and optimize Fourier models of the BOLD response to a BH task with a preparatory inspiration, and assess the test-retest reproducibility of the associated CVR measurements, in a group of 10 healthy volunteers studied over two fMRI sessions. Linear combinations of sine-cosine pairs at the BH task frequency and its successive harmonics were added sequentially in a nested models approach, and were compared in terms of the adjusted coefficient of determination and corresponding variance explained (VE) of the BOLD signal, as well as the number of voxels exhibiting significant BOLD responses, the estimated CVR values, and their test-retest reproducibility. The brain average VE increased significantly with the Fourier model order, up to the 3rd order. However, the number of responsive voxels increased significantly only up to the 2nd order, and started to decrease from the 3rd order onwards. Moreover, no significant relative underestimation of CVR values was observed beyond the 2nd order. Hence, the 2nd order model was concluded to be the optimal choice for the studied paradigm. This model also yielded the best test-retest reproducibility results, with intra-subject coefficients of variation of 12 and 16% and an intra-class correlation coefficient of 0.74. In conclusion, our results indicate that a Fourier series set consisting of a sine-cosine pair at the BH task frequency and its two harmonics is a suitable model for BOLD fMRI CVR measurements based on a BH task with preparatory inspiration, yielding robust estimates of this important physiological parameter. (C) 2016 Elsevier Inc. All rights reserved.

Elsevier2016

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BIO-311: Neuroscience

The course starts with fundamentals of electrical - and chemical signaling in neurons. Students then learn how neurons in the brain receive and process sensory information, and how other neurons control the behavior of an animal. Furthermore, memory, learning, and brain disorders will be introduced.

BIOENG-450: In silico neuroscience

"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies.

MICRO-513: Signal processing for functional brain imaging

Computational methods for the analysis of human brain imaging data