Connectionist networks are robust. They are resistant to noise. They gracefully degrade when they are damaged. They gracefully degrade when they are overloaded with information. Connectionist networks are based loosely on brains.
Control is distributed.
Computation is handled by massively connected, simple processors which repeatedly update on the basis of weighted inputs. Learning consists in enhancing or inhibiting on the basis of local information the degree to which signals are transmitted between processors. Memories are distributed. They are graded. They are context-dependent.