scholarly journals Neural dynamics for facial threat processing as revealed by gamma band synchronization using MEG

NeuroImage ◽  
2007 ◽  
Vol 34 (2) ◽  
pp. 839-847 ◽  
Author(s):  
Qian Luo ◽  
Tom Holroyd ◽  
Matthew Jones ◽  
Talma Hendler ◽  
James Blair
2011 ◽  
Vol 3 (1) ◽  
pp. 62-68 ◽  
Author(s):  
Frances A. Maratos ◽  
Carl Senior ◽  
Karin Mogg ◽  
Brendan P. Bradley ◽  
Gina Rippon

2021 ◽  
Author(s):  
Caitlin V. Hall ◽  
Ben J. Harrison ◽  
Kartik K. Iyer ◽  
Hannah S. Savage ◽  
Martha Zakrzewski ◽  
...  

AbstractThere is growing recognition that the composition of the gut microbiota influences behaviour, including responses to threat. The cognitive-interoceptive appraisal of threat-related stimuli relies on dynamic neural computations between the anterior insular (AIC) and the dorsal anterior cingulate (dACC) cortices. If, to what extent, and how microbial consortia influence the activity of this cortical threat processing circuitry is unclear. We addressed this question by combining a threat processing task, neuroimaging, 16S rRNA profiling, and computational modelling in healthy participants. Results showed interactions between high-level ecological indices with threat-related AIC-dACC neural dynamics. At finer taxonomic resolutions, the abundance of Ruminococcus was differentially linked to connectivity between, and activity within the AIC and dACC during threat updating. Functional inference analysis provides a strong rationale to motivate future investigations of microbiota-derived metabolites in the observed relationship with threat-related brain processes.


2021 ◽  
Author(s):  
Caitlin V. Hall ◽  
Ben J. Harrison ◽  
Kartik K. Iyer ◽  
Hannah S. Savage ◽  
Martha Zakrzewski ◽  
...  

2009 ◽  
Vol 40 (01) ◽  
Author(s):  
G Leicht ◽  
S Karch ◽  
I Giegling ◽  
V Kirsch ◽  
HJ Möller ◽  
...  
Keyword(s):  

2020 ◽  
Author(s):  
Amandine Lassalle ◽  
Michael X Cohen ◽  
Laura Dekkers ◽  
Elizabeth Milne ◽  
Rasa Gulbinaite ◽  
...  

Background: People with an Autism Spectrum Condition diagnosis (ASD) are hypothesized to show atypical neural dynamics, reflecting differences in neural structure and function. However, previous results regarding neural dynamics in autistic individuals have not converged on a single pattern of differences. It is possible that the differences are cognitive-set-specific, and we therefore measured EEG in autistic individuals and matched controls during three different cognitive states: resting, visual perception, and cognitive control.Methods: Young adults with and without an ASD (N=17 in each group) matched on age (range 20 to 30 years), sex, and estimated Intelligence Quotient (IQ) were recruited. We measured their behavior and their EEG during rest, a task requiring low-level visual perception of gratings of varying spatial frequency, and the “Simon task” to elicit activity in the executive control network. We computed EEG power and Inter-Site Phase Clustering (ISPC; a measure of connectivity) in various frequency bands.Results: During rest, there were no ASD vs. controls differences in EEG power, suggesting typical oscillation power at baseline. During visual processing, without pre-baseline normalization, we found decreased broadband EEG power in ASD vs. controls, but this was not the case during the cognitive control task. Furthermore, the behavioral results of the cognitive control task suggest that autistic adults were better able to ignore irrelevant stimuli.Conclusions: Together, our results defy a simple explanation of overall differences between ASD and controls, and instead suggest a more nuanced pattern of altered neural dynamics that depend on which neural networks are engaged.


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