In this study, we analyzed the effect of the ambiguity of the previous visual stimulus on the response time taken to process the current visual stimulus. Our experimental paradigm included the repeated presentation of ambiguous Necker cubes images with varying degrees of ambiguity. We studied the response time and the time-frequency features of EEG signals, reflecting the influence of the “sensory prehistory” on the current stimulus processing.
The design of visual decision-making task with uncertainty was proposed. Set of experiments was conducted in accordance with this design and obtained EEG dataset was analyzed. Analysis of EEG characteristics in time, frequency and space domains allowed to introduce certain features that can be used to separate right and wrong outcomes in the task prior actual subject's response.
In this study, we analyzed the behavioral characteristics of the subjects (response time to visual stimuli and the correctness of interpretation), as well as brain activity at the sensory level when classifying repeatedly presented ambiguous images. We showed that the reaction time decreased for both LA and HA stimuli with the task completion time. In addition, the distribution of perception errors decreased for HA stimuli, but not for LA stimuli. At the sensory level, we found an increase in EEG power in the frequency range of 9-11 Hz with an increase in the task execution time.
The perception of visual information includes such stages as the initial processing of sensory input and the interpretation of the received information (decision-making). The uncertainty of visual stimuli affects the neural activity during both sensory-processing and the decision-making stages. Here we analyzed spatial and temporal properties of the neural activity in the β-frequency band during the processing of ambiguous bistable stimuli. We tested how the stimulus ambiguity influenced the perceptual decision-making process.
It is known that brain performs cognitive functions through the activation of a distributed cortical network, which includes remote cortical regions. With this in mind we have analyzed the spatio-temporal cortical activity based on multichannel EEG recordings during accomplishing cognitive task. As the result, we have revealed typical spatio-temporal structures related to the different levels of cognitive task complexity.
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