Topic: information integration

In this talk, I’ll introduce the formal concept of a (pre)sheaf as data attached to a topological space. Sheaves capture the notion of patching local sources of information to form a global whole, e.g., the binding of visual features such as colour and shape. The formal theory appears to be closely related to the foundational properties asserted by the Information Integration Theory (IIT) for phenomenology. A comparison is intended to engender discussion on ways that phenomenology may benefit from a sheaf theory, or (more generally) a category theory approach.

Integrating information is particularly crucial when decisions contain complex information. In decision neuroscience, it has been widely studied how overall decision value is encoded in the brain, but how information is integrated prior to encoding overall value remains largely unclear. Recently, our neuroimaging study has shown that the lateral frontopolar cortex (FPl), a uniquely well-developed region in the human brain, engaged specifically in complex choice but not in simple choice (Law et al., 2023). Aided by an artificial neural network, we found that FPl involved a parallel processing t