The dynamic allocation of attention to emotion: Simultaneous and independent evidence from the late positive potential and steady state visual evoked potentials

2013 ◽  
Vol 92 (3) ◽  
pp. 447-455 ◽  
Author(s):  
Greg Hajcak ◽  
Annmarie MacNamara ◽  
Dan Foti ◽  
Jamie Ferri ◽  
Andreas Keil
1996 ◽  
Vol 99 (4) ◽  
pp. 327
Author(s):  
V. Radivojević ◽  
M. Car ◽  
M. Rajković ◽  
. Martinović ◽  
N. Krstić

2013 ◽  
Vol 44 (1) ◽  
pp. 146-149 ◽  
Author(s):  
Yu-Yi Chien ◽  
Fang-Cheng Lin ◽  
Ching-Chi Chou ◽  
John K. Zao ◽  
Heng-Yuan Kuo ◽  
...  

2021 ◽  
Author(s):  
Ge Zhang ◽  
Yan Cui ◽  
Yangsong Zhang ◽  
Hefei Cao ◽  
Guanyu Zhou ◽  
...  

AbstractPeriodic visual stimulation can induce stable steady-state visual evoked potentials (SSVEPs) distributed in multiple brain regions and has potential applications in both neural engineering and cognitive neuroscience. However, the underlying dynamic mechanisms of SSVEPs at the whole-brain level are still not completely understood. Here, we addressed this issue by simulating the rich dynamics of SSVEPs with a large-scale brain model designed with constraints of neuroimaging data acquired from the human brain. By eliciting activity of the occipital areas using an external periodic stimulus, our model was capable of replicating both the spatial distributions and response features of SSVEPs that were observed in experiments. In particular, we confirmed that alpha-band (8-12 Hz) stimulation could evoke stronger SSVEP responses; this frequency sensitivity was due to nonlinear resonance and could be modulated by endogenous factors in the brain. Interestingly, the stimulus-evoked brain networks also exhibited significant superiority in topological properties near this frequency-sensitivity range, and stronger SSVEP responses were demonstrated to be supported by more efficient functional connectivity at the neural activity level. These findings not only provide insights into the mechanistic understanding of SSVEPs at the whole-brain level but also indicate a bright future for large-scale brain modeling in characterizing the complicated dynamics and functions of the brain.


2015 ◽  
Vol 12 (2) ◽  
pp. 026012 ◽  
Author(s):  
Laura Acqualagna ◽  
Sebastian Bosse ◽  
Anne K Porbadnigk ◽  
Gabriel Curio ◽  
Klaus-Robert Müller ◽  
...  

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