One in a series of talks from the 2019 Models of Consciousness conference. Inês Hipólito
University of Wollongong
Building on the modular architecture of mind (Fodor 1983), Modularity Networks is claimed as a theory well equipped to explain neural connectivity and reuse (Stanley et al.; 2019, Zerrili 2019). This paper takes the case of the oculomotor system to show that even if Modularity Network’s tools are useful to describe brain’s functional connectivity, they are limited in explaining why such connections are formed and dynamic. To show this, section 1 starts by laying down the reasons for adopting Modularity Networks as well suited for explaining neural connectivity. Section 2 introduces the oculomotor system as a dynamic integration of action and vision. Section 3 argues that however valuable in describing the functional connectivity of the oculomotor system, Modularity Networks fails to explain why such connections are formed and dynamic (dependent on activity). This failure is made evident by acknowledging a fundamental distinction in the metaphysics of inference. The nature of inference is taken differently in functional connectivity as a description of inference as opposed to effective connectivity as an explanation of inference (Friston 2011). Section 4 introduces Dynamic Causal Modelling (DCM) as a better resource to capture effective connectivity. It allows explaining how and why brain connections, as generative models of cognitive integration, are dependent on the dynamic activity within the environment. This conclusion speaks against modular arguments for encapsulation, innateness and specificity of cognitive organisation.
Filmed at the Models of Consciousness conference, University of Oxford, September 2019. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/