Language Processing as Cue Integration: Grounding the Psychology of Language in Perception and Neurophysiology

How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.

Despite intensive work on language-brain relations, and a fairly impressive accumulation of knowledge over the last several decades, there has been little progress in developing large-scale models of the functional anatomy of language that integrate neuropsychological, neuroimaging, and psycholinguistic data. Drawing on relatively recent developments in the cortical organization of vision, and on data from a variety of sources, we propose a new framework for understanding aspects of the functional anatomy of language which moves towards remedying this situation. The framework posits that early cortical stages of speech perception involve auditory fields in the superior temporal gyrus bilaterally (although asymmetrically). This cortical processing system then diverges into two broad processing streams, a ventral stream, which is involved in mapping sound onto meaning, and a dorsal stream, which is involved in mapping sound onto articulatory-based representations. The ventral stream projects ventro-laterally toward inferior posterior temporal cortex (posterior middle temporal gyrus) which serves as an interface between sound-based representations of speech in the superior temporal gyrus (again bilaterally) and widely distributed conceptual representations. The dorsal stream projects dorso-posteriorly involving a region in the posterior Sylvian fissure at the parietal-temporal boundary (area Spt), and ultimately projecting to frontal regions. This network provides a mechanism for the development and maintenance of "parity" between auditory and motor representations of speech. Although the proposed dorsal stream represents a very tight connection between processes involved in speech perception and speech production, it does not appear to be a critical component of the speech perception process under normal (ecologically natural) listening conditions, that is, when speech input is mapped onto a conceptual representation. We also propose some degree of bi-directionality in both the dorsal and ventral pathways. We discuss some recent empirical tests of this framework that utilize a range of methods. We also show how damage to different components of this framework can account for the major symptom clusters of the fluent aphasias, and discuss some recent evidence concerning how sentence-level processing might be integrated into the framework.

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.