Recent developments in artificial intelligence (AI) have revived the possibility that we could endow machines with all the higher-order cognitive functions that characterize the mind of non-human and human primates. Much of this optimism derives from the achievements of contemporary artificial neural networks, which are equal to or even outperform humans in mundane and computationally demanding tasks like image classification. This progress was feasible through the implementation of processes like input-output functions, recurrent connectivity, and modifiable synaptic weights, all originally inspired from realistic brain operations. However, these computations do not require conscious processing and therefore reflect operations that unfold unconsciously. In order to implement artificial consciousness, it is first necessary to gain a detailed understanding of the biologically evolved neural circuits supporting this function. This is the objective of the current project. Together with our international collaborators, we will probe brain signals at different observational scales, from the micro to the meso and macro-scale, in order to disentangle the complexity of neural activity that mediates consciousness.