A selective diffusion model of brain network activity

Author(s):  
Daniel Graham ◽  
Yan Hao
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kosuke Takagi

AbstractEnergy constraints are a fundamental limitation of the brain, which is physically embedded in a restricted space. The collective dynamics of neurons through connections enable the brain to achieve rich functionality, but building connections and maintaining activity come at a high cost. The effects of reducing these costs can be found in the characteristic structures of the brain network. Nevertheless, the mechanism by which energy constraints affect the organization and formation of the neuronal network in the brain is unclear. Here, it is shown that a simple model based on cost minimization can reproduce structures characteristic of the brain network. With reference to the behavior of neurons in real brains, the cost function was introduced in an activity-dependent form correlating the activity cost and the wiring cost as a simple ratio. Cost reduction of this ratio resulted in strengthening connections, especially at highly activated nodes, and induced the formation of large clusters. Regarding these network features, statistical similarity was confirmed by comparison to connectome datasets from various real brains. The findings indicate that these networks share an efficient structure maintained with low costs, both for activity and for wiring. These results imply the crucial role of energy constraints in regulating the network activity and structure of the brain.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory Simchick ◽  
Kelly M. Scheulin ◽  
Wenwu Sun ◽  
Sydney E. Sneed ◽  
Madison M. Fagan ◽  
...  

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.


Stroke ◽  
2021 ◽  
Author(s):  
Olga Boukrina ◽  
Mateusz Kowalczyk ◽  
Yury Koush ◽  
Yekyung Kong ◽  
A.M. Barrett

Background and Purpose: Delirium, an acute reduction in cognitive functioning, hinders stroke recovery and contributes to cognitive decline. Right-hemisphere stroke is linked with higher delirium incidence, likely, due to the prevalence of spatial neglect (SN), a right-brain disorder of spatial processing. This study tested if symptoms of delirium and SN after right-hemisphere stroke are associated with abnormal function of the right-dominant neural networks specialized for maintaining attention, orientation, and arousal. Methods: Twenty-nine participants with right-hemisphere ischemic stroke undergoing acute rehabilitation completed delirium and SN assessments and functional neuroimaging scans. Whole-brain functional connectivity of 4 right-hemisphere seed regions in the cortical-subcortical arousal and attention networks was assessed for its relationship to validated SN and delirium severity measures. Results: Of 29 patients, 6 (21%) met the diagnostic criteria for delirium and 16 (55%) for SN. Decreased connectivity of the right basal forebrain to brain stem and basal ganglia predicted more severe SN. Increased connectivity of the arousal and attention network regions with the parietal, frontal, and temporal structures in the unaffected hemisphere was also found in more severe delirium and SN. Conclusions: Delirium and SN are associated with decreased arousal network activity and an imbalance of cortico-subcortical hemispheric connectivity. Better understanding of neural correlates of poststroke delirium and SN will lead to improved neuroscience-based treatment development for these disorders.


2021 ◽  
Vol 11 (12) ◽  
pp. 1591
Author(s):  
Hai Xue ◽  
Qiong Wu ◽  
Zhijun Yang ◽  
Bo Wang ◽  
Xingchao Wang ◽  
...  

Cognitive impairments and social-function deficits are severe complaints in neurofibromatosis type 1 (NF1) patients. Empathetic pain perception may be disrupted in NF1 patients because of high-level cognitive deficits. This study investigated the empathy profiles of adult patients with NF1, especially concerning whether explicit and implicit empathetic pain perception are abnormal in this population. We examined empathetic pain perception through a paradigm based on perceiving another person’s pain; in this task, patients were required to make judgments about the presence of pain or the laterality of the body part, as shown in a picture. Twenty NF1 patients without obvious social or communication difficulties completed the task, and the results were compared with results from the normal controls (NCs). Regarding explicit empathetic pain processing, i.e., judging the presence of “pain” or “no pain”, there were no significant differences between patients and controls in accuracy or reaction time. However, in implicit empathetic processing, i.e., judging the laterality of “pain” or “no-pain” pictures, NF1 patients had significantly lower accuracy (p = 0.038) and significantly higher reaction times (p = 0.004) than the NCs. These results were consistent with those of a previous study showing that high-level cognitive deficits were prominent in NF1 patients when performing challenging tasks. The mechanisms and related brain network activity underlying these deficits should receive attention in the future.


2018 ◽  
Vol 2 (suppl_1) ◽  
pp. 402-402
Author(s):  
J Zhou ◽  
O Lo ◽  
M Halko ◽  
R Harrison ◽  
L Lipsitz ◽  
...  

2018 ◽  
Vol 129 (4) ◽  
pp. e12
Author(s):  
M. Bartoň ◽  
I. Rektorová ◽  
S. Rapcsak

2020 ◽  
Vol 30 (2) ◽  
pp. 267-286 ◽  
Author(s):  
Tim D. van Balkom ◽  
Odile A. van den Heuvel ◽  
Henk W. Berendse ◽  
Ysbrand D. van der Werf ◽  
Chris Vriend

2019 ◽  
Vol 61 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Pei-Wen Zhu ◽  
You Chen ◽  
Ying-Xin Gong ◽  
Nan Jiang ◽  
Wen-Feng Liu ◽  
...  

Background Neuroimaging studies revealed that trigeminal neuralgia was related to alternations in brain anatomical function and regional function. However, the functional characteristics of network organization in the whole brain is unknown. Purpose The aim of the present study was to analyze potential functional network brain-activity changes and their relationships with clinical features in patients with trigeminal neuralgia via the voxel-wise degree centrality method. Material and Methods This study involved a total of 28 trigeminal neuralgia patients (12 men, 16 women) and 28 healthy controls matched in sex, age, and education. Spontaneous brain activity was evaluated by degree centrality. Correlation analysis was used to examine the correlations between behavioral performance and average degree centrality values in several brain regions. Results Compared with healthy controls, trigeminal neuralgia patients had significantly higher degree centrality values in the right lingual gyrus, right postcentral gyrus, left paracentral lobule, and bilateral inferior cerebellum. Receiver operative characteristic curve analysis of each brain region confirmed excellent accuracy of the areas under the curve. There was a positive correlation between the mean degree centrality value of the right postcentral gyrus and VAS score (r = 0.885, P < 0.001). Conclusions Trigeminal neuralgia causes abnormal brain network activity in multiple brain regions, which may be related to underlying disease mechanisms.


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