@misc{ShirzhiyanKeihaniFarahietal., author = {Shirzhiyan, Zahra and Keihani, Ahmadreza and Farahi, Morteza and Shamsi, Elham and GolMohammadi, Mina and Mahnam, Amin and Haidari, Mohsen Reza and Jafari, Amir Homayoun}, title = {Toward New Modalities in VEP-Based BCI Applications Using Dynamical Stimuli: Introducing Quasi-Periodic and Chaotic VEP-Based BCI}, series = {Frontiers in Neuroscience}, volume = {14}, journal = {Frontiers in Neuroscience}, issn = {1662-453X}, doi = {10.3389/fnins.2020.534619}, abstract = {Visual evoked potentials (VEPs) to periodic stimuli are commonly used in brain computer interfaces for their favorable properties such as high target identification accuracy, less training time, and low surrounding target interference. Conventional periodic stimuli can lead to subjective visual fatigue due to continuous and high contrast stimulation. In this study, we compared quasi-periodic and chaotic complex stimuli to common periodic stimuli for use with VEP-based brain computer interfaces (BCIs). Canonical correlation analysis (CCA) and coherence methods were used to evaluate the performance of the three stimulus groups. Subjective fatigue caused by the presented stimuli was evaluated by the Visual Analogue Scale (VAS). Using CCA with the M2 template approach, target identification accuracy was highest for the chaotic stimuli (M = 86.8, SE = 1.8) compared to the quasi-periodic (M = 78.1, SE = 2.6, p = 0.008) and periodic (M = 64.3, SE = 1.9, p = 0.0001) stimulus groups. The evaluation of fatigue rates revealed that the chaotic stimuli caused less fatigue compared to the quasi-periodic (p = 0.001) and periodic (p = 0.0001) stimulus groups. In addition, the quasi-periodic stimuli led to lower fatigue rates compared to the periodic stimuli (p = 0.011). We conclude that the target identification results were better for the chaotic group compared to the other two stimulus groups with CCA. In addition, the chaotic stimuli led to a less subjective visual fatigue compared to the periodic and quasi-periodic stimuli and can be suitable for designing new comfortable VEP-based BCIs.}, language = {en} } @misc{ShirzhiyanGlasauer, author = {Shirzhiyan, Zahra and Glasauer, Stefan}, title = {Dual-task modulation of neural activity related to perception of time}, series = {Abstract NWG Meeting G{\"o}ttingen 2021}, volume = {2021}, journal = {Abstract NWG Meeting G{\"o}ttingen 2021}, address = {G{\"o}ttingen}, language = {en} } @misc{ShirzhiyanGlasauer, author = {Shirzhiyan, Zahra and Glasauer, Stefan}, title = {Late CNV-P2 amplitude as neural index of time interval perception}, series = {Bernstein Conference 2021, September 21 - 23, 2021}, volume = {2021}, journal = {Bernstein Conference 2021, September 21 - 23, 2021}, doi = {10.12751/nncn.bc2021.p153}, language = {de} } @misc{ShirzhiyanGlasauer, author = {Shirzhiyan, Zahra and Glasauer, Stefan}, title = {Neural correlates of perceptual biases in duration perception}, series = {bioRxiv}, journal = {bioRxiv}, editor = {Glasauer, Stefan}, publisher = {Cold Spring Harbor Laboratory}, address = {Cold Spring Harbor}, doi = {10.1101/2025.09.13.675931}, pages = {1 -- 48}, abstract = {How we perceive a current event depends not only on its immediate context, but also on how our internal expectations are shaped by prior experience. In time perception, these expectations manifest as systematic biases, namely sequential dependence, where the current percept is influenced by the previous stimulus, and central tendency, the overestimation of short durations and underestimation of long ones. Both perceptual biases, corresponding to individual beliefs about stimulus generation, can vary substantially between participants. However, the neural correlates of these individual beliefs and their effects are unknown. Here, we investigate how these biases and their individual variations are reflected in neural responses in a duration reproduction task. Our EEG results show that in the frontocentral region, the Contingent Negative Variation (CNV) while experiencing the current stimulus depends on the previous stimulus regardless of whether sequential dependence is high or low. In contrast, in the right parietal region, CNV significantly correlated with the amount of sequential dependence. Central tendency was associated with frontocentral CNV amplitude and post-stimulus P2 components. A Bayesian model of time perception reproduced the observed neural dynamics, suggesting that internal estimates and expectations of stimulus offset are reflected in EEG responses. Our results demonstrate that both forms of perceptual bias, sequential dependence and central tendency, are reflected in neural activity while experiencing the ongoing stimulus, suggesting that both biases directly affect the measurement of time.}, language = {en} }