scholarly journals Cross-species cortical alignment identifies different types of neuroanatomical reorganization in the temporal lobe of higher primates

2019 ◽  
Author(s):  
Nicole Eichert ◽  
Emma C. Robinson ◽  
Katherine L. Bryant ◽  
Saad Jbabdi ◽  
Mark Jenkinson ◽  
...  
Keyword(s):  
Temporal Lobe ◽  
Parietal Cortex ◽  
Connectivity Pattern ◽  
Arcuate Fasciculus ◽  
Computational Neuroanatomy ◽  
Brain Organization ◽  
Cortical Organization ◽  
Connectivity Patterns ◽  
Different Types ◽  
Brain Reorganization

AbstractEvolutionary modifications of the temporo-parietal cortex are considered to be a critical adaptation of the human brain. Cortical adaptations, however, can affect different aspects of brain architecture, including areal expansion or changes in connectivity profiles. We propose to distinguishing different types of brain reorganization using a computational neuroanatomy approach. We investigate the extent to which between-species alignment based on cortical myelin can predict changes in connectivity patterns across macaque, chimpanzee and human. We show that expansion and relocation of brain areas are sufficient to predict terminations of several white matter tracts in temporo-parietal cortex, including the middle and superior longitudinal fasciculus, but not of the arcuate fasciculus. This demonstrates that the arcuate fasciculus underwent additional evolutionary modifications affecting the connectivity pattern of the temporal lobe. The presented approach can flexibly be extended to include other features of cortical organization and other species, allowing direct tests of comparative hypotheses of brain organization.

scholarly journals Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Nicole Eichert ◽  
Emma C Robinson ◽  
Katherine L Bryant ◽  
Saad Jbabdi ◽  
Mark Jenkinson ◽  
...  
Keyword(s):  
Temporal Lobe ◽  
Parietal Cortex ◽  
Connectivity Pattern ◽  
Arcuate Fasciculus ◽  
Computational Neuroanatomy ◽  
Brain Organization ◽  
Cortical Organization ◽  
Connectivity Patterns ◽  
Different Types ◽  
Brain Architecture

Evolutionary adaptations of temporo-parietal cortex are considered to be a critical specialization of the human brain. Cortical adaptations, however, can affect different aspects of brain architecture, including local expansion of the cortical sheet or changes in connectivity between cortical areas. We distinguish different types of changes in brain architecture using a computational neuroanatomy approach. We investigate the extent to which between-species alignment, based on cortical myelin, can predict changes in connectivity patterns across macaque, chimpanzee, and human. We show that expansion and relocation of brain areas can predict terminations of several white matter tracts in temporo-parietal cortex, including the middle and superior longitudinal fasciculus, but not the arcuate fasciculus. This demonstrates that the arcuate fasciculus underwent additional evolutionary modifications affecting the temporal lobe connectivity pattern. This approach can flexibly be extended to include other features of cortical organization and other species, allowing direct tests of comparative hypotheses of brain organization.

scholarly journals Age of Speech Onset in Autism Relates to Structural Connectivity in the Language Network

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Elise B Barbeau ◽  
Denise Klein ◽  
Isabelle Soulières ◽  
Michael Petrides ◽  
Boris Bernhardt ◽  
...  
Keyword(s):  
Structural Connectivity ◽  
Autism Spectrum ◽  
White Matter Tract ◽  
Arcuate Fasciculus ◽  
Brain Organization ◽  
Autistic Group ◽  
Categorical Diagnosis ◽  
Onset Delays ◽  
Brain Reorganization ◽  
Language Network

Abstract Speech onset delays (SOD) and language atypicalities are central aspects of the autism spectrum (AS), despite not being included in the categorical diagnosis of AS. Previous studies separating participants according to speech onset history have shown distinct patterns of brain organization and activation in perceptual tasks. One major white matter tract, the arcuate fasciculus (AF), connects the posterior temporal and left frontal language regions. Here, we used anatomical brain imaging to investigate the properties of the AF in adolescent and adult autistic individuals with typical levels of intelligence who differed by age of speech onset. The left AF of the AS group showed a significantly smaller volume than that of the nonautistic group. Such a reduction in volume was only present in the younger group. This result was driven by the autistic group without SOD (SOD−), despite their typical age of speech onset. The autistic group with SOD (SOD+) showed a more typical AF as adults relative to matched controls. This suggests that, along with multiple studies in AS-SOD+ individuals, atypical brain reorganization is observable in the 2 major AS subgroups and that such reorganization applies mostly to the language regions in SOD− and perceptual regions in SOD+ individuals.

scholarly journals The Parietal Cortex in Sensemaking: The Dissociation of Multiple Types of Spatial Information

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Yanlong Sun ◽  
Hongbin Wang
Keyword(s):  
Parietal Cortex ◽  
Spatial Information ◽  
Mathematical Thinking ◽  
Hierarchical Organization ◽  
Levels Of Abstraction ◽  
Perceptual Analysis ◽  
Different Types ◽  
Sensemaking Process ◽  
Network Simulations ◽  
Different Levels

According to the data-frame theory, sensemaking is a macrocognitive process in which people try to make sense of or explain their observations by processing a number of explanatory structures called frames until the observations and frames become congruent. During the sensemaking process, the parietal cortex has been implicated in various cognitive tasks for the functions related to spatial and temporal information processing, mathematical thinking, and spatial attention. In particular, the parietal cortex plays important roles by extracting multiple representations of magnitudes at the early stages of perceptual analysis. By a series of neural network simulations, we demonstrate that the dissociation of different types of spatial information can start early with a rather similar structure (i.e., sensitivity on a common metric), but accurate representations require specific goal-directed top-down controls due to the interference in selective attention. Our results suggest that the roles of the parietal cortex rely on the hierarchical organization of multiple spatial representations and their interactions. The dissociation and interference between different types of spatial information are essentially the result of the competition at different levels of abstraction.

Magnetoencephalographic correlates of different types of aura in temporal lobe epilepsy

Epilepsia ◽  
2010 ◽  
Vol 51 (9) ◽  
pp. 1846-1851 ◽  
Author(s):  
Kenjiro Fukao ◽  
Yushi Inoue ◽  
Kazuichi Yagi
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Different Types

scholarly journals How the Statistical Validation of Functional Connectivity Patterns Can Prevent Erroneous Definition of Small-World Properties of a Brain Connectivity Network

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
J. Toppi ◽  
F. De Vico Fallani ◽  
G. Vecchiato ◽  
A. G. Maglione ◽  
F. Cincotti ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Adjacency Matrix ◽  
Brain Connectivity ◽  
Small World ◽  
Connectivity Pattern ◽  
Edge Density ◽  
Statistical Validation ◽  
Common Procedure ◽  
Connectivity Patterns ◽  
Definition Of

The application of Graph Theory to the brain connectivity patterns obtained from the analysis of neuroelectrical signals has provided an important step to the interpretation and statistical analysis of such functional networks. The properties of a network are derived from the adjacency matrix describing a connectivity pattern obtained by one of the available functional connectivity methods. However, no common procedure is currently applied for extracting the adjacency matrix from a connectivity pattern. To understand how the topographical properties of a network inferred by means of graph indices can be affected by this procedure, we compared one of the methods extensively used in Neuroscience applications (i.e. fixing the edge density) with an approach based on the statistical validation of achieved connectivity patterns. The comparison was performed on the basis of simulated data and of signals acquired on a polystyrene head used as a phantom. The results showed (i) the importance of the assessing process in discarding the occurrence of spurious links and in the definition of the real topographical properties of the network, and (ii) a dependence of the small world properties obtained for the phantom networks from the spatial correlation of the neighboring electrodes.

scholarly journals Author response: Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe

2020 ◽  
Author(s):  
Nicole Eichert ◽  
Emma C Robinson ◽  
Katherine L Bryant ◽  
Saad Jbabdi ◽  
Mark Jenkinson ◽  
...  
Keyword(s):  
Temporal Lobe ◽  
Author Response ◽  
Different Types

scholarly journals Body mass variations relate to fractionated functional brain hierarchies

2020 ◽  
Author(s):  
Bo-yong Park ◽  
Hyunjin Park ◽  
Filip Morys ◽  
Mansu Kim ◽  
Kyoungseob Byeon ◽  
...  
Keyword(s):  
Young Adults ◽  
Body Mass ◽  
Cell Types ◽  
Modular Architecture ◽  
Brain Organization ◽  
Functional Connectome ◽  
Genome Wide ◽  
Learning Techniques ◽  
Connectivity Patterns ◽  
Cerebellar Cell

AbstractVariations in body mass index (BMI) have been suggested to relate to atypical brain organization, yet connectome-level substrates of BMI and their neurobiological underpinnings remain unclear. Studying 325 healthy young adults, we examined association between functional connectome organization and BMI variations. We capitalized on connectome manifold learning techniques, which represent macroscale functional connectivity patterns along continuous hierarchical axes that dissociate low level and higher order brain systems. We observed an increased differentiation between unimodal and heteromodal association networks in individuals with higher BMI, indicative of an increasingly segregated modular architecture and a disruption in the hierarchical integration of different brain system. Transcriptomic decoding and subsequent gene enrichment analyses identified genes previously implicated in genome-wide associations to BMI and specific cortical, striatal, and cerebellar cell types. These findings provide novel insights for functional connectome substrates of BMI variations in healthy young adults and point to potential molecular associations.

Increased structural white and grey matter network connectivity compensates for functional decline in early multiple sclerosis

2016 ◽  
Vol 23 (3) ◽  
pp. 432-441 ◽  
Author(s):  
Vinzenz Fleischer ◽  
Adriane Gröger ◽  
Nabin Koirala ◽  
Amgad Droby ◽  
Muthuraman Muthuraman ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Grey Matter ◽  
Diffusion Tensor ◽  
Disease Onset ◽  
Structural Connectivity ◽  
Connectivity Pattern ◽  
Structural Adaptation ◽  
Theoretical Approaches ◽  
Connectivity Patterns ◽  
Clinical Impairment

Background: The pathology of multiple sclerosis (MS) consists of demyelination and neuronal injury, which occur early in the disease; yet, remission phases indicate repair. Whether and how the central nervous system (CNS) maintains homeostasis to counteract clinical impairment is not known. Objective: We analyse the structural connectivity of white matter (WM) and grey matter (GM) networks to understand the absence of clinical decline as the disease progresses. Methods: A total of 138 relapsing–remitting MS patients (classified into six groups by disease duration) and 32 healthy controls were investigated using 3-Tesla magnetic resonance imaging (MRI). Networks were analysed using graph theoretical approaches based on connectivity patterns derived from diffusion-tensor imaging with probabilistic tractography for WM and voxel-based morphometry and regional-volume-correlation matrix for GM. Results: In the first year after disease onset, WM networks evolved to a structure of increased modularity, strengthened local connectivity and increased local clustering while no clinical decline occurred. GM networks showed a similar dynamic of increasing modularity. This modified connectivity pattern mainly involved the cerebellum, cingulum and temporo-parietal regions. Clinical impairment was associated at later disease stages with a divergence of the network patterns. Conclusion: Our findings suggest that network functionality in MS is maintained through structural adaptation towards increased local and modular connectivity, patterns linked to adaptability and homeostasis.

scholarly journals Edges in brain networks: contributions to models of structure and function

2021 ◽  
pp. 1-63
Author(s):  
Joshua Faskowitz ◽  
Richard F Betzel ◽  
Olaf Sporns
Keyword(s):  
Network Models ◽  
Brain Network ◽  
Higher Order ◽  
Dynamic Information ◽  
Brain Organization ◽  
Network Nodes ◽  
Different Types ◽  
Definition Of ◽  
And Function ◽  
Specific Definition

Abstract Network models describe the brain as sets of nodes and edges that represent its distributed organization. So far, most discoveries in network neuroscience have prioritized insights that highlight distinct groupings and specialized functional contributions of network nodes. Importantly, these functional contributions are determined and expressed by the web of their interrelationships, formed by network edges. Here, we underscore the important contributions made by brain network edges for understanding distributed brain organization. Different types of edges represent different types of relationships, including connectivity and similarity among nodes. Adopting a specific definition of edges can fundamentally alter how we analyze and interpret a brain network. Furthermore, edges can associate into collectives and higher-order arrangements, describe time series, and form edge communities that provide insights into brain network topology complementary to the traditional node-centric perspective. Focusing on the edges, and the higher-order or dynamic information they can provide, discloses previously underappreciated aspects of structural and functional network organization.

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