scholarly journals Stimulus transformation into motor action: Dynamic graph analysis reveals a posterior‐to‐anterior shift in brain network communication of older subjects

2020 ◽  
Author(s):  
Nils Rosjat ◽  
Bin A. Wang ◽  
Liqing Liu ◽  
Gereon R. Fink ◽  
Silvia Daun
Keyword(s):  
Brain Network ◽  
Network Communication ◽  
Graph Analysis ◽  
Dynamic Graph ◽  
Motor Action ◽  
Stimulus Transformation ◽  
Older Subjects

scholarly journals Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects

2020 ◽  
Author(s):  
Nils Rosjat ◽  
Bin A. Wang ◽  
Liqing Liu ◽  
Gereon R. Fink ◽  
Silvia Daun
Keyword(s):  
Age Groups ◽  
Brain Network ◽  
Hemispheric Lateralization ◽  
Dynamic Graph ◽  
Movement Initiation ◽  
Motor Action ◽  
Low Frequencies ◽  
Functional Changes ◽  
Age Related ◽  
Older Subjects

AbstractCognitive performance slows down with increasing age. This includes cognitive processes that are essential for the performance of a motor act, such as the slowing down in response to an external stimulus. The objective of this study was to identify aging-associated functional changes in the brain networks that are involved in the transformation of external stimuli into motor action. To investigate this topic, we employed dynamic graphs based on phase-locking of Electroencephalography signals recorded from healthy younger and older subjects while performing a simple visually-cued finger-tapping task. The network analysis yielded specific age-related network structures varying in time in the low frequencies (2-7 Hz), which are closely connected to stimulus processing, movement initiation and execution in both age groups. The networks in older subjects, however, contained several additional, particularly interhemispheric, connections and showed an overall increased coupling density. Cluster analyses revealed reduced variability of the subnetworks in older subjects, particularly during movement preparation. In younger subjects, occipital, parietal, sensorimotor and central regions were - temporally arranged in this order - heavily involved in hub nodes. Whereas in older subjects, a hub in frontal regions preceded the noticeably delayed occurrence of sensorimotor hubs, indicating different neural information processing in older subjects.All observed changes in brain network organization, which are based on neural synchronization in the low frequencies, provide a possible neural mechanism underlying previous fMRI data, which report an overactivation, especially in the prefrontal and pre-motor areas, associated with a loss of hemispheric lateralization in older subjects.

Volume-based large dynamic graph analysis supported by evolution provenance

2019 ◽  
Vol 78 (23) ◽  
pp. 32939-32965 ◽  
Author(s):  
Valentin Bruder ◽  
Houssem Ben Lahmar ◽  
Marcel Hlawatsch ◽  
Steffen Frey ◽  
Michael Burch ◽  
...  
Keyword(s):  
Graph Analysis ◽  
Dynamic Graph

The hippocampus: hub of brain network communication for memory

2011 ◽  
Author(s):  
Francesco P. Battaglia ◽  
Karim Benchenane ◽  
Anton Sirota ◽  
Cyriel M.A. Pennartz ◽  
Sidney I. Wiener
Keyword(s):  
Brain Network ◽  
Network Communication

scholarly journals Compile- and run-time approaches for the selection of efficient data structures for dynamic graph analysis

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Benjamin Schiller ◽  
Clemens Deusser ◽  
Jeronimo Castrillon ◽  
Thorsten Strufe
Keyword(s):  
Data Structures ◽  
Graph Analysis ◽  
Dynamic Graph ◽  
Efficient Data ◽  
Run Time ◽  
Efficient Data Structures ◽  
Selection Of

scholarly journals Light-sheet imaging and graph analysis of antidepressant action in the larval zebrafish brain network

2019 ◽  
Author(s):  
Jessica Burgstaller ◽  
Elena Hindinger ◽  
Joseph Donovan ◽  
Marco Dal Maschio ◽  
Andreas M. Kist ◽  
...  
Keyword(s):  
Glucocorticoid Receptor ◽  
Brain Activity ◽  
Activity Patterns ◽  
Drug Effects ◽  
Light Sheet ◽  
Brain Network ◽  
Therapeutic Interventions ◽  
Stress Axis ◽  
Graph Analysis ◽  
Neuropsychiatric Diseases

AbstractThe zebrafish is increasingly being employed as an experimental platform to model neuropsychiatric diseases and to screen for novel neuro-active compounds. While the superb genetic and optical access that this system offers has long been recognized, these features have not been fully exploited to investigate disease mechanisms and possible therapeutic interventions. Here we introduce a light-sheet imaging and graph-theoretical analysis pipeline to determine the effects of the known or suspected antidepressant compounds fluoxetine, ketamine and cycloserine on brain-wide neural activity patterns. We imaged the brains of both wildtype fish and grs357 mutants, which harbor a missense mutation that abolishes glucocorticoid receptor transcriptional activity. The grs357 mutation results in a chronically elevated stress axis together with behavioral endophenotypes of depression. Consistent with broad expression of the glucocorticoid receptor throughout the brain, we show that the mutant fish exhibit an altered correlational structure of resting-state brain activity. Intriguingly, in grs357 mutant fish, an increased ‘modularity’, which represents the degree of segregation of the network into highly clustered modules, was restored by acute fluoxetine administration to wildtype levels. Ketamine and cycloserine also normalized specific parameters of the graph. Fluoxetine altered network function in the same direction in mutant and wildtype, while ketamine and cycloserine had effects that were opposite for the two genotypes. We propose that light-sheet imaging, followed by graph analysis, is a content-rich and scalable first-pass approach for studying the neural consequences of drug effects and drug x genotype interactions in zebrafish models of psychiatric disorders.

scholarly journals Brain network connectivity differs in early-onset neurodegenerative dementia

Neurology ◽  
2017 ◽  
Vol 89 (17) ◽  
pp. 1764-1772 ◽  
Author(s):  
Massimo Filippi ◽  
Silvia Basaia ◽  
Elisa Canu ◽  
Francesca Imperiale ◽  
Alessandro Meani ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Early Onset ◽  
Network Architecture ◽  
Parietal Lobe ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Functional Network ◽  
Graph Analysis ◽  
Functional Brain ◽  
Functional Brain Network

Objective:To investigate functional brain network architecture in early-onset Alzheimer disease (EOAD) and behavioral variant frontotemporal dementia (bvFTD).Methods:Thirty-eight patients with bvFTD, 37 patients with EOAD, and 32 age-matched healthy controls underwent 3D T1-weighted and resting-state fMRI. Graph analysis and connectomics assessed global and local functional topologic network properties, regional functional connectivity, and intrahemispheric and interhemispheric between-lobe connectivity.Results:Despite similarly extensive cognitive impairment relative to controls, patients with EOAD showed severe global functional network alterations (lower mean nodal strength, local efficiency, clustering coefficient, and longer path length), while patients with bvFTD showed relatively preserved global functional brain architecture. Patients with bvFTD demonstrated reduced nodal strength in the frontoinsular lobe and a relatively focal altered functional connectivity of frontoinsular and temporal regions. Functional connectivity breakdown in the posterior brain nodes, particularly in the parietal lobe, differentiated patients with EOAD from those with bvFTD. While EOAD was associated with widespread loss of both intrahemispheric and interhemispheric functional correlations, bvFTD showed a preferential disruption of the intrahemispheric connectivity.Conclusions:Disease-specific patterns of functional network topology and connectivity alterations were observed in patients with EOAD and bvFTD. Graph analysis and connectomics may aid clinical diagnosis and help elucidate pathophysiologic differences between neurodegenerative dementias.

Altered structural connectivity of pain-related brain network in burning mouth syndrome—investigation by graph analysis of probabilistic tractography

2017 ◽  
Vol 59 (5) ◽  
pp. 525-532 ◽  
Author(s):  
Akihiko Wada ◽  
Takashi Shizukuishi ◽  
Junko Kikuta ◽  
Haruyasu Yamada ◽  
Yusuke Watanabe ◽  
...  
Keyword(s):  
Structural Connectivity ◽  
Brain Network ◽  
Burning Mouth Syndrome ◽  
Graph Analysis ◽  
Probabilistic Tractography ◽  
Burning Mouth
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