scholarly journals Static and dynamic measures of human brain connectivity predict complementary aspects of human cognitive performance

2017 ◽  
Author(s):  
Aurora I. Ramos-Nuñez ◽  
Simon Fischer-Baum ◽  
Randi Martin ◽  
Qiuhai Yue ◽  
Fengdan Ye ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Brain Network ◽  
Predicting Performance ◽  
Brain Network Connectivity ◽  
Two Measures ◽  
And Performance ◽  
Dynamic Measures ◽  
The Relationship

AbstractIn cognitive network neuroscience, the connectivity and community structure of the brain network is related to cognition. Much of this research has focused on two measures of connectivity – modularity and flexibility – which frequently have been examined in isolation. By using resting state fMRI data from 52 young adults, we investigate the relationship between modularity, flexibility and performance on cognitive tasks. We show that flexibility and modularity are highly negatively correlated. However, we also demonstrate that flexibility and modularity make unique contributions to explain task performance, with modularity predicting performance for simple tasks and flexibility predicting performance on complex tasks that require cognitive control and executive functioning. The theory and results presented here allow for stronger links between measures of brain network connectivity and cognitive processes.

scholarly journals Electrocorticography and stereo EEG provide distinct measures of brain connectivity: Implications for network models

2020 ◽  
Author(s):  
John M. Bernabei ◽  
T. Campbell Arnold ◽  
Preya Shah ◽  
Andrew Revell ◽  
Ian Z. Ong ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Network Models ◽  
Brain Network ◽  
Seizure Freedom ◽  
Epileptogenic Zone ◽  
Depth Electrodes ◽  
Brain Network Connectivity ◽  
Patients With Epilepsy

AbstractBrain network models derived from graph theory have the potential to guide functional neurosurgery, and to improve rates of post-operative seizure freedom for patients with epilepsy. A barrier to applying these models clinically is that intracranial EEG electrode implantation strategies vary by center, region and country, from cortical grid & strip electrodes, to purely stereotactic depth electrodes, to a mixture of both. To determine whether models derived from one type of study are broadly applicable to others, we investigate the differences in brain networks mapped by electrocortiography (ECoG) and stereoelectroencephalography (SEEG) in a matched cohort of patients who underwent epilepsy surgery. We show that ECoG and SEEG map broad network structure differently, and demonstrate substantial disparity in the ability of node strength to localize the epileptogenic zone in SEEG compared to ECoG. We demonstrate that eliminating white matter contacts and reducing network nodes to anatomical regions of interest rather than individual contacts improves the ability of these models to distinguish between epileptogenic and non-epileptogenic regions in SEEG. Our findings suggest that effectively applying computational models to localize epileptic networks requires accounting for the effects of spatial sampling, particularly when analyzing both ECoG and SEEG recordings in the same cohort. Finally, we share all code and data in this study, aiming for our findings to accelerate research in brain network connectivity in epilepsy and beyond.

scholarly journals Scaling principles of white matter brain connectivity

2021 ◽  
Author(s):  
Dirk Jan Ardesch ◽  
Lianne H. Scholtens ◽  
Siemon C. de Lange ◽  
Lea Roumazeilles ◽  
Alexandre A. Khrapitchev ◽  
...  
Keyword(s):  
White Matter ◽  
Corpus Callosum ◽  
Right Hemisphere ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Network ◽  
Primate Species ◽  
Scaling Relationships ◽  
Brain Network Connectivity ◽  
Brain Circuitry

Brains come in many shapes and sizes. Nature has endowed big-brained primate species like humans with a proportionally large cerebral cortex. White matter connectivity - the brain's infrastructure for long-range communication - might not always scale at the same pace as the cortex. We investigated the consequences of this allometric scaling for white matter brain network connectivity. Structural T1 and diffusion MRI data were collated across fourteen primate species, describing a comprehensive 350-fold range in brain volume. We report volumetric scaling relationships that point towards a restriction in macroscale connectivity in larger brains. Building on previous findings, we show cortical surface to outpace white matter volume and the corpus callosum, suggesting the emergence of a white matter 'bottleneck' of lower levels of connectedness through the corpus callosum in larger brains. At the network level, we find a potential consequence of this bottleneck in shaping connectivity patterns, with homologous regions in the left and right hemisphere showing more divergent connectivity in larger brains. Our findings show conserved scaling relationships of major brain components and their consequence for macroscale brain circuitry, providing a comparative framework for expected connectivity architecture in larger brains such as the human brain.

scholarly journals Is brain circuitry linked with early symptoms of autism spectrum disorder?

2020 ◽  
Keyword(s):  
Autism Spectrum Disorder ◽  
San Diego ◽  
Network Connectivity ◽  
Autism Spectrum ◽  
Brain Network ◽  
Spectrum Disorder ◽  
Early Symptoms ◽  
Brain Network Connectivity ◽  
Brain Circuitry ◽  
The Relationship

Researchers in San Diego, USA, have studied the relationship between brain network connectivity and emerging autism spectrum disorder (ASD) symptoms in toddlers aged 17-45 months with (n=24) or without (n=23) ASD.

scholarly journals Brain Network Connectivity in Adolescents At Risk for Alcohol Use Problems

2020 ◽  
Author(s):  
Simon T. E. Baker ◽  
Murat Yücel ◽  
Alex Fornito ◽  
Andrew Zalesky ◽  
Sarah Whittle ◽  
...  
Keyword(s):  
Family History ◽  
Alcohol Use ◽  
Brain Connectivity ◽  
Structural Connectivity ◽  
Mean Diffusivity ◽  
Network Connectivity ◽  
Brain Network ◽  
Increased Risk ◽  
Brain Network Connectivity ◽  
History Of

AbstractImaging studies of young people with a family history of alcohol use disorder (AUD) have found structural and/or functional differences within and between anatomically distributed and functionally specialised systems throughout the brain. Differences in brain connectivity among adolescents with a family history of AUD may account for the increased risk of later alcohol use problems; however, to date, no prospective studies have directly examined this hypothesis across the entire connectome in a regionally unbiased way. Our analysis included 52 adolescents (Mage = 16.5 years ± 0.6 SD) assessed with diffusion-weighted magnetic resonance imaging, of whom 20 had a family history of AUD and 32 did not. All participants were followed-up 2.3 years later and completed a questionnaire measuring past year alcohol use and alcohol-related harms. Subject-specific connectomic maps of structural connectivity were constructed using two parcellation schemes (82-node anatomical and 530-node random) and five measures of connectivity weight (streamline count, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity), and a connectome-wide network-based statistic analysis was used to compare group differences at each and every connection between adolescents with and without a family history of AUD. Baseline connectivity measures did not differentiate these groups, and we did not find an association between baseline connectivity measures and alcohol outcomes at follow-up. These findings suggest that atypical inter-regional structural connectivity may not contribute to the risk of developing alcohol use problems in this particular age group, or during this particular period of development.

scholarly journals Altered functional connectivity is related to impaired cognition in left unilateral asymptomatic carotid artery stenosis patients

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shihao He ◽  
Ran Duan ◽  
Ziqi Liu ◽  
Cai Zhang ◽  
Tian Li ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Short Term Memory ◽  
Network Connectivity ◽  
Brain Network ◽  
Short Term ◽  
Asymptomatic Carotid ◽  
Term Memory ◽  
Brain Network Connectivity ◽  
Asymptomatic Carotid Artery Stenosis ◽  
The Relationship

Abstract Background Asymptomatic carotid artery stenosis (aCAS) impairs haemodynamic and cognitive functions; however, the relationship between these changes and brain network connectivity remains largely unknown. This study aimed to determine the relationship between functional connectivity and neurocognition in patients with aCAS. Methods We compared functional status in 14 patients with aCAS and 15 healthy controls using resting state functional magnetic resonance imaging sequences. The subjects underwent a full range of neuropsychological tests and a graphical theoretical analysis of their brain networks. Results Compared with controls, patients with aCAS showed significant decline in neuropsychological functions, particularly short-term memory (word-memory, p = .046 and picture-memory, p = .014). Brain network connectivity was lower in patients with aCAS than in the controls, and the decline of functional connectivity in aCAS patients was mainly concentrated in the left and right inferior frontal gyri, temporal lobe, left cingulate gyrus, and hippocampus. Decreased connectivity between various brain regions was significantly correlated with impaired short-term memory. Patients with aCAS showed cognitive impairment independent of known vascular risk factors for vascular cognitive impairment. The cognitive defects were mainly manifested in the short-term memory of words and pictures. Conclusions This study is the first of its kind to identify an association between disruption of functional connections in left carotid stenosis and impairment of short-term memory. The findings suggest that alterations in network connectivity may be an essential mechanism underlying cognitive decline in aCAS patients. Clinical trial registration-URL Unique identifier: 04/06/2019, ChiCTR1900023610.

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