A Biologically Inspired Computational Model of Language Cognition

ARTICLE 1. Introduction and Background Signifi cant progress had been made about how the brain works, from the molecular to the functional level, in the past few decades. But how can researchers, often get trained in a particular neuroscience discipline to understand and use all that data to develop the right kind of hypotheses to test? We have to develop novel computational models to tackle this challenge. It might be possible to develop software programs to mimic the behavior of the brain based on the results of proven scientifi c studies. Computational modeling is the only inherently dynamic way to help us to specify that function precisely. It not only provides some new e xplanations for the nerve physiology processes occurring in our brain, but also provides new ideas for the artifi cial cognitive systems [1,2]. What is needed is a formal way to systematically relate multiple data sets, thus bridging the function of brain and computational models. Functional Magnetic Resonance Imaging (fMRI) provides a high resolution volumetric mapping of the haemodynamic response of the brain, which can be correlated with neural activity, thereby allowing the spatially localized characteristics of brain activity to be observed. It is a new trend to use fMRI studies to confi rm and improve cognitive computational models. Hickok and Poeppel [4] provided a dual-stream model of speech processing. The approximate anatomical locations of the dual-stream model components are illustrated in Figure 1. Regions shaded green depicted areas on the dorsal surface of the superior temporal gyrus that are proposed to be involved in spectrotemporal analysis. Regions shaded yellow in the posterior half of the STS are implicated in phonological-level processes. Regions shaded pink represent the ventral stream, which is bilaterally organized with a weak left-hemisphere bias. The more posterior regions of the ventral stream, posterior middle and inferior portions of the temporal lobes correspond to the lexical interface, which links phonological and semantic information, whereas the more anterior locations correspond to the proposed