In this thesis, I use a combination of simulations and empirical data to demonstrate that a small set of structural and functional principles - the basic tenets of predictive coding theory - succinctly accounts for a very wide range of properties in the language processing system. Predictive coding approximates hierarchical Bayesian inference via a biologically plausible mechanism of competition whose unique properties (i) allow it to capture important asymmetries in bottom-up and top-down processing and (ii) offer a critical insight into the functional relationship between behavioral and neural measures of word processing. In addition to accounting for well-known properties of the language processing system, this mechanism of competition allows us to formulate and test a novel empirical prediction - that N400 attenuation can be observed in the presence of behavioral interference - which challenges a widely held assumption that N400 attenuation is essentially synonymous with facilitated processing. Importantly, the computational model that we used to simulate the above psycholinguistic phenomena was tightly constrained by predictive coding principles and the particular class of algorithm we employed (PC/BC-DIM; Spratling, De Meyer, & Kompass 2009), emphasizing how a fundamental, biologically plausible perceptual mechanism that is shared across the cortex can also give rise to psycholinguistic phenomena. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]