Cathy J. Price

The anatomy of language: contributions from functional neuroimaging.

This article illustrates how functional neuroimaging can be used to test the validity of neurological and cognitive models of language. Three models of language are described: the 19th Century neurological model which describes both the anatomy and cognitive components of auditory and visual word processing, and 2 20th Century cognitive models that are not constrained by anatomy but emphasise 2 different routes to reading that are not present in the neurological model. A series of functional imaging studies are then presented which show that, as predicted by the 19th Century neurologists, auditory and visual word repetition engage the left posterior superior temporal and posterior inferior frontal cortices. More specifically, the roles Wernicke and Broca assigned to these regions lie respectively in the posterior superior temporal sulcus and the anterior insula. In addition, a region in the left posterior inferior temporal cortex is activated for word retrieval, thereby providing a second route to reading, as predicted by the 20th Century cognitive models. This region and its function may have been missed by the 19th Century neurologists because selective damage is rare. The angular gyrus, previously linked to the visual word form system, is shown to be part of a distributed semantic system that can be accessed by objects and faces as well as speech. Other components of the semantic system include several regions in the inferior and middle temporal lobes. From these functional imaging results, a new anatomically constrained model of word processing is proposed which reconciles the anatomical ambitions of the 19th Century neurologists and the cognitive finesse of the 20th Century cognitive models. The review focuses on single word processing and does not attempt to discuss how words are combined to generate sentences or how several languages are learned and interchanged. Progress in unravelling these and other related issues will depend on the integration of behavioural, computational and neurophysiological approaches, including neuroimaging.

Detecting Activations in PET and fMRI: Levels of Inference and Power

This paper is about detecting activations in statistical parametric maps and considers the relative sensitivity of a nested hierarchy of tests that we have framed in terms of the level of inference (voxel level, cluster level, and set level). These tests are based on the probability of obtaining c, or more, clusters with k, or more, voxels, above a threshold u. This probability has a reasonably simple form and is derived using distributional approximations from the theory of Gaussian fields. The most important contribution of this work is the notion of set-level inference. Set-level inference refers to the statistical inference that the number of clusters comprising an observed activation profile is highly unlikely to have occurred by chance. This inference pertains to the set of activations reaching criteria and represents a new way of assigning P values to distributed effects. Cluster-level inferences are a special case of set-level inferences, which obtain when the number of clusters c = 1. Similarly voxel-level inferences are special cases of cluster-level inferences that result when the cluster can be very small (i.e., k = 0). Using a theoretical power analysis of distributed activations, we observed that set-level inferences are generally more powerful than cluster-level inferences and that cluster-level inferences are generally more powerful than voxel-level inferences. The price paid for this increased sensitivity is reduced localizing power: Voxel-level tests permit individual voxels to be identified as significant, whereas cluster-and set-level inferences only allow clusters or sets of clusters to be so identified. For all levels of inference the spatial size of the underlying signal f (relative to resolution) determines the most powerful thresholds to adopt. For set-level inferences if f is large (e.g., fMRI) then the optimum extent threshold should be greater than the expected number of voxels for each cluster. If f is small (e.g., PET) the extent threshold should be small. We envisage that set-level inferences will find a role in making statistical inferences about distributed activations, particularly in fMRI.

A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading

The anatomy of language has been investigated with PET or fMRI for more than 20 years. Here I attempt to provide an overview of the brain areas associated with heard speech, speech production and reading. The conclusions of many hundreds of studies were considered, grouped according to the type of processing, and reported in the order that they were published. Many findings have been replicated time and time again leading to some consistent and undisputable conclusions. These are summarised in an anatomical model that indicates the location of the language areas and the most consistent functions that have been assigned to them. The implications for cognitive models of language processing are also considered. In particular, a distinction can be made between processes that are localized to specific structures (e.g. sensory and motor processing) and processes where specialisation arises in the distributed pattern of activation over many different areas that each participate in multiple functions. For example, phonological processing of heard speech is supported by the functional integration of auditory processing and articulation; and orthographic processing is supported by the functional integration of visual processing, articulation and semantics. Future studies will undoubtedly be able to improve the spatial precision with which functional regions can be dissociated but the greatest challenge will be to understand how different brain regions interact with one another in their attempts to comprehend and produce language.

The anatomy of language: a review of 100 fMRI studies published in 2009

In this review of 100 fMRI studies of speech comprehension and production, published in 2009, activation is reported for: prelexical speech perception in bilateral superior temporal gyri; meaningful speech in middle and inferior temporal cortex; semantic retrieval in the left angular gyrus and pars orbitalis; and sentence comprehension in bilateral superior temporal sulci. For incomprehensible sentences, activation increases in four inferior frontal regions, posterior planum temporale, and ventral supramarginal gyrus. These effects are associated with the use of prior knowledge of semantic associations, word sequences, and articulation that predict the content of the sentence. Speech production activates the same set of regions as speech comprehension but in addition, activation is reported for: word retrieval in left middle frontal cortex; articulatory planning in the left anterior insula; the initiation and execution of speech in left putamen, pre‐SMA, SMA, and motor cortex; and for suppressing unintended responses in the anterior cingulate and bilateral head of caudate nuclei. Anatomical and functional connectivity studies are now required to identify the processing pathways that integrate these areas to support language.

Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics

There is a growing appreciation of the importance of nonlinearities in evoked responses in fMRI, particularly with the advent of event-related fMRI. These nonlinearities are commonly expressed as interactions among stimuli that can lead to the suppression and increased latency of responses to a stimulus that are incurred by a preceding stimulus. We have presented previously a model-free characterization of these effects using generic techniques from nonlinear system identification, namely a Volterra series formulation. At the same time Buxton et al. (1998) described a plausible and compelling dynamical model of hemodynamic signal transduction in fMRI. Subsequent work by Mandeville et al. (1999) provided important theoretical and empirical constraints on the form of the dynamic relationship between blood flow and volume that underpins the evolution of the fMRI signal. In this paper we combine these system identification and model-based approaches and ask whether the Balloon model is sufficient to account for the nonlinear behaviors observed in real time series. We conclude that it can, and furthermore the model parameters that ensue are biologically plausible. This conclusion is based on the observation that the Balloon model can produce Volterra kernels that emulate empirical kernels. To enable this evaluation we had to embed the Balloon model in a hemodynamic input-state-output model that included the dynamics of perfusion changes that are contingent on underlying synaptic activation. This paper presents (i) the full hemodynamic model (ii), how its associated Volterra kernels can be derived, and (iii) addresses the models validity in relation to empirical nonlinear characterizations of evoked responses in fMRI and other neurophysiological constraints.

A voxel-based morphometry study of semantic dementia : Relationship between temporal lobe atrophy and semantic memory

The cortical anatomy of 6 patients with semantic dementia (the temporal lobe variant of frontotemporal dementia) was contrasted with that of a group of age‐matched normal subjects by using voxel‐based morphometry, a technique that identifies changes in gray matter volume on a voxel‐by‐voxel basis. Among the circumscribed regions of neuronal loss, the left temporal pole (Brodmann area 38) was the most significantly and consistently affected region. Cortical atrophy in the left hemisphere also involved the inferolateral temporal lobe (Brodmann area 20/21) and fusiform gyrus. In addition, the right temporal pole (Brodmann area 38), the ventromedial frontal cortex (Brodmann area 11/32) bilaterally, and the amygdaloid complex were affected, but no significant atrophy was measured in the hippocampus, entorhinal, or caudal perirhinal cortex. The degree of semantic memory impairment across the 6 cases correlated significantly with the extent of atrophy of the left anterior temporal lobe but not with atrophy in the adjacent ventromedial frontal cortex. These results confirm that the anterior temporal lobe is critically involved in semantic processing, and dissociate its function from that of the adjacent frontal region. Ann Neurol 2000; 47:36–45

ALE meta-analysis: Controlling the false discovery rate and performing statistical contrasts

Activation likelihood estimation (ALE) has greatly advanced voxel‐based meta‐analysis research in the field of functional neuroimaging. We present two improvements to the ALE method. First, we evaluate the feasibility of two techniques for correcting for multiple comparisons: the single threshold test and a procedure that controls the false discovery rate (FDR). To test these techniques, foci from four different topics within the literature were analyzed: overt speech in stuttering subjects, the color‐word Stroop task, picture‐naming tasks, and painful stimulation. In addition, the performance of each thresholding method was tested on randomly generated foci. We found that the FDR method more effectively controls the rate of false positives in meta‐analyses of small or large numbers of foci. Second, we propose a technique for making statistical comparisons of ALE meta‐analyses and investigate its efficacy on different groups of foci divided by task or response type and random groups of similarly obtained foci. We then give an example of how comparisons of this sort may lead to advanced designs in future meta‐analytic research. Hum Brain Mapp 25:155–164, 2005.

Voxel-based morphometry of the human brain: Methods and applications

In recent years, a whole-brain unbiased objective technique, known as voxel-based morphometry (VBM), has been developed to characterise brain differences in vivo using structural magnetic resonance images. The present review provides a brief description of VBM and then focuses on exemplar applications in healthy and diseased subjects. The procedure involves normalising high-resolution structural magnetic resonance images to a standard template in stereotactic space. Normalised images are then segmented into gray and white matter and smoothed using an isotropic Gaussian kernel. Finally, a series of voxel-wise comparisons of gray and white matter in different groups of subjects are performed, using Random Field theory to correct for multiple comparisons. VBM has been useful in characterizing subtle changes in brain structure in a variety of diseases associated with neurological and psychiatric dysfunction. These include schizophrenia, developmental and congenital disorders, temporal lobe epilepsy and even cluster headache. In addition, VBM has been successful in identifying gross structural abnormalities, such as those observed in herpes simplex encephalitis, multiple sclerosis and Alzheimers disease. Studies of normal subjects, on the other hand, have focussed on the impact of learning and practice on brain structure. These studies have led to the finding that environmental demands may be associated with changes in gray and white matter. For instance, it has been reported that the structure of the brain alters when human beings learn to navigate, read music, speak a second language and even perform a complex motor task such as juggling. We conclude the present review by discussing the potential limitations of the technique.

Neurolinguistics: Structural plasticity in the bilingual brain

Humans have a unique ability to learn more than one language — a skill that is thought to be mediated by functional (rather than structural) plastic changes in the brain. Here we show that learning a second language increases the density of grey matter in the left inferior parietal cortex and that the degree of structural reorganization in this region is modulated by the proficiency attained and the age at acquisition. This relation between grey-matter density and performance may represent a general principle of brain organization.

The trouble with cognitive subtraction

In this paper we present a critique of pure insertion. Pure insertion represents an implicit assumption behind many (but not all) studies that employ cognitive subtraction. The main contention is that pure insertion is not valid in relation to the neuronal instantiation of cognitive processes. Pure insertion asserts that there are no interactions among the cognitive components of a task. It is possible to evaluate and refute this assumption by testing explicitly for interactions using factorial experimental designs. It is proposed that factorial designs are more powerful than subtraction designs in characterizing cognitive neuroanatomy, precisely because they allow for interactions and eschew notions like pure insertion. In particular we suggest that the effect of a cognitive component (i.e., an effect that is independent of other components) is best captured by the main (activation) effect of that component and that the integration among components (i.e., the expression of one cognitive process in the context of another) can be assessed with the interaction terms. In this framework a complete characterization of cognitive neuroanatomy includes both regionally specific activations and regionally specific interactions. To illustrate our point we have used a factorial experimental design to show that inferotemporal activations, due to object recognition, are profoundly modulated by phonological retrieval of the objects name. This interaction implicates the inferotemporal regions in phonological retrieval, during object naming, despite the fact that phonological retrieval does not, by itself, activate this region.