Online research in philosophy

Perruchet & Vinter do not fully resolve issues about the role of consciousness and the unconscious in cognition and learning, and it is doubtful that consciousness has been computationally implemented. The cascade-correlation (CC) connectionist model develops high-order feature detectors as it learns a problem. We describe an extension, knowledge-based cascade-correlation (KBCC), that uses knowledge to learn in a hierarchical fashion.

Most consciousness researchers, almost no matter what their views of the metaphysics of consciousness, can agree that the first step in a science of consciousness is the search for the neural correlate of consciousness (the NCC). The reason for this agreement is that the notion of ‘correlation’ doesn’t by itself commit one to any particular metaphysical view about the relation between (neural) matter and consciousness. For example, some might treat the correlates as causally related, while others might view the correlation as evidence for identity between conscious states and brain states. The common ground therefore seems to be that the scientific search for the NCC is largely independent of the metaphysics of consciousness.