Understanding the nature of consciousness and qualia using artificial intelligence
Mahboobeh Parsapoor
McGill University, Canada
: J Addict Behav Ther Rehabil
Abstract
One of the big challenges in the field of cognitive neuroscience understands consciousness and its building blocks. The fact is that understanding consciousness can help cognitive neuroscientists understand the underlying procedure of the human brain to form a personal view of the world. It also can assist neuroscientists to figure out how the human brain process information, extract valuable message, form memory and expand knowledge. To do so, cognitive neuro-scientist have defined the terminology qualia and introduced it as a building block of consciousness. It has been stated that information messages which is extracted from basic sensory input as light, voice, etc. and represent it as information messages the basis of qualia is the basis of qualia. Qualia have been defined by philosophers and neuroscientists to explain introspectively accessible phenomenal aspects of our mental lives. However, the existence of qualia has been the sourse of conflicts between cognitive neuroscientists. The existence of their bearers”; 3) “How qualia relate to the physical world both inside and out- side the head”. In contrast, some scientists have agreed on existence of qualia and offered the following statements, 1) Does the perceptual knowledge of human have a material character of its own?; 2) Does it have some physical impacts, in particular on the brain ; 3) If it is what is the order of such impact? 4) Finally, how the brain can regulate those impacts. In our research, we have decided to take advantage of artificial intelligence (AI) in particular machine learning and deep learning to prove the existence of qualia. To do so, we have set up some experimental studies and recorded the electroencephalogram (EEG) of participants in the studies, and then we apply MLs to classify the data sets. of qualia has been denied on the basis of the following question: 1)”Which mental states have qualia”; 2) “Whether qualia are intrinsic qualities.
Biography
Mahboobeh Parsapoor has a licentiate degree of information technology from Halmstad University where she has been a member of Center for Research on Embedded Systems (CERES) and she focused on developing a new type of data-driven models that is referred to as brain emotional learning inspired models (BELIMs). She is interested in conducting research on various topics include: computational intelligence, nonlinear system identification and classification, wireless communication and has published several articles in these subjects. She is in the reviewer panel of IEEE communication letter and Neural Networks Journal.
E-mail: mahboobeh.parsapoor@mail.mcgill.ca
