Consciousness: converging insights from connectionist modeling and neuroscience.

Connectionist models of cognitive development: where next?

Over the past two decades, connectionist models have generated a lively debate regarding the underlying mechanisms of cognitive development. This debate has in turn led to important empirical research that might not have occurred otherwise. More recently, advances in developmental neuroscience present a new set of challenges for modelers. In this article, I review some of the insights that have...

Computational modeling of dynamic decision making using connectionist networks

In this research connectionist modeling of decision making has been presented. Important areas for decision making in the brain are thalamus, prefrontal cortex and Amygdala. Connectionist modeling with 3 parts representative for these 3 areas is made based the result of Iowa Gambling Task. In many researches Iowa Gambling Task is used to study emotional decision making. In these kind of decisio...

Consciousness and the Prefrontal Parietal Network: Insights from Attention, Working Memory, and Chunking

Consciousness has of late become a "hot topic" in neuroscience. Empirical work has centered on identifying potential neural correlates of consciousness (NCCs), with a converging view that the prefrontal parietal network (PPN) is closely associated with this process. Theoretical work has primarily sought to explain how informational properties of this cortical network could account for phenomena...

NBIC, THE CONVERGING TECHNOLOGIES

Consciousness: perspectives from symbolic and connectionist AI.

While consciousness has not been a major concern of most AI researchers, some theorists have tried to explore how computational models might explain consciousness. I explore how far computational models might go in explaining consciousness, focusing on three aspects of conscious mental states: their intrinsic intentionality, the awareness a subject has of the contents of these intentional state...