Dissociation Between Attention and Consciousness During a Novel Task: an ERP Study

• Дата: 2015
• Автори: Davoodi, R., Moradi, M.H., Yoonessi, A.
• Формат: Стаття
• Мова: English
• Опубліковано: Інститут фізіології ім. О.О. Богомольця НАН України 2015
• Назва видання: Нейрофизиология
• Онлайн доступ: http://dspace.nbuv.gov.ua/handle/123456789/148181
• Назва журналу: Digital Library of Periodicals of National Academy of Sciences of Ukraine
• Цитувати: Dissociation Between Attention and Consciousness During a Novel Task: an ERP Study / R. Davoodi, M.H. Moradi, A. Yoonessi // Нейрофизиология. — 2015. — Т. 47, № 2. — С. 169-180. — Бібліогр.: 32 назв. — англ.

While consciousness and attention seem to be tightly connected, recent evidence has suggested that one of these processes can be present in the absence of the other. Recent researches showed that observers can pay attention to an invisible (unconscious) stimulus, and that a stimulus can be clearly perceived (seen) in the absence of attention. We have proposed a novel psychophysical task to explore neural correlates of top-down attention and consciousness. The task is meant to confirm that these two processes can occur independently of each other. EEG was recorded during realizations of the task and target-locked event-related potentials (ERPs) for masked and unmasked conditions were constructed. Time features corresponding to the P100, N150, and P300 components were extracted for each channel separately. Utilizing these features, we employed some common classifiers for classification of the fourfold state. Our task could separate attention and consciousness successfully through their neural correlates. The results indicate that some of the mentioned components changed when attention or consciousness occurs. By comparing difference waves in each condition separately, our results introduce new ERP correlates of attention and consciousness. We also revealed that parieto-occipital areas are the most relevant areas for dissociation between attention and consciousness. To our knowledge, this is the first time that these correlates are introduced in a separable mode, and that the classification accuracies are reported for this purpose.