# Monitoring Brain State and Behavioral Performance during Repetitive Visual Stimulation
###### Abstract  
We tested whether changes in prestimulus neural activity predict behavioral performance (decision time and errors) during a prolonged visual task. The task was to classify ambiguous stimuli--Necker cubes; manipulating the degree of ambiguity from low ambiguity (LA) to high ambiguity (HA) changed the task difficulty. First, we assumed that the observer's state changes over time, which leads to a change in the prestimulus brain activity. Second, we supposed that the prestimulus state produces a different effect on behavioral performance depending on the task demands. Monitoring behavioral responses, we revealed that the observer's decision time decreased for both LA and HA stimuli during the task performance. The number of perceptual errors lowered for HA, but not for LA stimuli. EEG analysis revealed an increase in the prestimulus 9-11 Hz EEG power with task time. Finally, we found associations between the behavioral and neural estimates. The prestimulus EEG power negatively correlated with the decision time for LA stimuli and the erroneous responses rate for HA stimuli. The obtained results confirm that monitoring prestimulus EEG power enables predicting perceptual performance on the behavioral level. The observed different time-on-task effects on the LA and HA stimuli processing may shed light on the features of ambiguous perception. m 2021 11 11544 110.10.  
when the sensory information quality was low [4]. Therefore, the observer must concentrate to gather more information to make the right decision, relying on personal experience to extrapolate limited information or unresolve its ambiguity. The conditions under which the observer receives and processes information are important as well. For example, high-speed driving on a rainy night requires the very fast processing of low-quality information. Performing monotonous tasks with increased responsibility (e.g., flight or power plant operators) also requires maintaining high performance and emergence preparedness. In these stressful conditions, the influence of exogenous and endogenous factors on the likelihood of perceptual errors should be considered. Therefore, knowing and monitoring these factors can help predict perceptual errors and reduce their probability. Furthermore, human condition monitoring (endogenous factor) is a task for passive brain-computer interfaces (BCIs) [5]. Unlike the traditional active BCI, which issues control commands through mental intent, passive BCIs continuously monitor the brain state during extended periods of cognitive activity and signal if it deviates from the normal state [6]. To control the quality of received information and its processing, the BCI must track both exogenous and endogenous components. Thus, the BCI must meet the task requirements (exogenous factor) along with the neural activity (endogenous factor). Moreover, objective assessments of the task requirements may depend on the amount of information, its ambiguity, and multimodality. Subjective estimates can be derived from the observer's reaction, such as response time, eye movements, and other behavioral indicators [7]. To take into account all these processes, it is necessary to move from a passive to a reactive BCI. The latter uses stimuli and analyzes the brain state through time intervals assigned to them [8]. Following this concept, a reactive BCI should analyze the brain state while performing a task. This will provide information on the influence of endogenous and exogenous factors on the speed and quality of information processing. The further development of BCIs aims not only at the detection, but also the prediction of the human states. These BCIs will give rise to the artificial intelligence systems that assist or alarm when detecting a high probability of critical errors. Developing such systems requires finding the associations between the current state of the BCI operator and their performance in solving ongoing tasks. A bulk of literature associates changes in the human condition with their behavioral performance in ongoing tasks.