Alexander P. Leff

Spatial normalization of brain images with focal lesions using cost function masking.

In studies of patients with focal brain lesions, it is often useful to coregister an image of the patients brain to that of another subject or a standard template. We refer to this process as spatial normalization. Spatial normalization can improve the presentation and analysis of lesion location in neuropsychological studies; it can also allow other data, for example from functional imaging, to be compared to data from other patients or normal controls. In functional imaging, the standard procedure for spatial normalization is to use an automated algorithm, which minimizes a measure of difference between image and template, based on image intensity values. These algorithms usually optimize both linear (translations, rotations, zooms, and shears) and nonlinear transforms. In the presence of a focal lesion, automated algorithms attempt to reduce image mismatch between template and image at the site of the lesion. This can lead to significant inappropriate image distortion, especially when nonlinear transforms are used. One solution is to use cost-function masking-masking the areas used in the calculation of image difference-to exclude the area of the lesion, so that the lesion does not bias the transformations. We introduce and evaluate this technique using normalizations of a selection of brains with focal lesions and normal brains with simulated lesions. Our results suggest that cost-function masking is superior to the standard approach to this problem, which is affine-only normalization; we propose that cost-function masking should be used routinely for normalizations of brains with focal lesions.

Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data.

Spatial normalization of lesioned brains: performance evaluation and impact on fMRI analyses.

A key component of group analyses of neuroimaging data is precise and valid spatial normalization (i.e., inter-subject image registration). When patients have structural brain lesions, such as a stroke, this process can be confounded by the lack of correspondence between the subject and standardized template images. Current procedures for dealing with this problem include regularizing the estimate of warping parameters used to match lesioned brains to the template, or “cost function masking”; both these solutions have significant drawbacks. We report three experiments that identify the best spatial normalization for structurally damaged brains and establish whether differences among normalizations have a significant effect on inferences about functional activations. Our novel protocols evaluate the effects of different normalization solutions and can be applied easily to any neuroimaging study. This has important implications for users of both structural and functional imaging techniques in the study of patients with structural brain damage.

Speech Facilitation by Left Inferior Frontal Cortex Stimulation

Summary Electrophysiological studies in humans and animals suggest that noninvasive neurostimulation methods such as transcranial direct current stimulation (tDCS) can elicit long-lasting [1], polarity-dependent [2] changes in neocortical excitability. Application of tDCS can have significant and selective behavioral consequences that are associated with the cortical location of the stimulation electrodes and the task engaged during stimulation [3–8]. However, the mechanism by which tDCS affects human behavior is unclear. Recently, functional magnetic resonance imaging (fMRI) has been used to determine the spatial topography of tDCS effects [9–13], but no behavioral data were collected during stimulation. The present study is unique in this regard, in that both neural and behavioral responses were recorded using a novel combination of left frontal anodal tDCS during an overt picture-naming fMRI study. We found that tDCS had significant behavioral and regionally specific neural facilitation effects. Furthermore, faster naming responses correlated with decreased blood oxygen level-dependent (BOLD) signal in Brocas area. Our data support the importance of Brocas area within the normal naming network and as such indicate that Brocas area may be a suitable candidate site for tDCS in neurorehabilitation of anomic patients, whose brain damage spares this region.

Lesion identification using unified segmentation-normalisation models and fuzzy clustering

In this paper, we propose a new automated procedure for lesion identification from single images based on the detection of outlier voxels. We demonstrate the utility of this procedure using artificial and real lesions. The scheme rests on two innovations: First, we augment the generative model used for combined segmentation and normalization of images, with an empirical prior for an atypical tissue class, which can be optimised iteratively. Second, we adopt a fuzzy clustering procedure to identify outlier voxels in normalised gray and white matter segments. These two advances suppress misclassification of voxels and restrict lesion identification to gray/white matter lesions respectively. Our analyses show a high sensitivity for detecting and delineating brain lesions with different sizes, locations, and textures. Our approach has important implications for the generation of lesion overlap maps of a given population and the assessment of lesion-deficit mappings. From a clinical perspective, our method should help to compute the total volume of lesion or to trace precisely lesion boundaries that might be pertinent for surgical or diagnostic purposes.

The left superior temporal gyrus is a shared substrate for auditory short-term memory and speech comprehension: evidence from 210 patients with stroke

Competing theories of short-term memory function make specific predictions about the functional anatomy of auditory short-term memory and its role in language comprehension. We analysed high-resolution structural magnetic resonance images from 210 stroke patients and employed a novel voxel based analysis to test the relationship between auditory short-term memory and speech comprehension. Using digit span as an index of auditory short-term memory capacity we found that the structural integrity of a posterior region of the superior temporal gyrus and sulcus predicted auditory short-term memory capacity, even when performance on a range of other measures was factored out. We show that the integrity of this region also predicts the ability to comprehend spoken sentences. Our results therefore support cognitive models that posit a shared substrate between auditory short-term memory capacity and speech comprehension ability. The method applied here will be particularly useful for modelling structure–function relationships within other complex cognitive domains.

Noun imageability and the temporal lobes

We used positron emission tomography to investigate brain activity in response to hearing or reading nouns of varying imageability. Three experiments were performed. Activity increased with noun imageability in the left mid-fusiform gyrus, the lateral parahippocampal area in humans, and in the rostral medial temporal lobes close to or within perirhinal cortex. The left mid-fusiform activation has been observed in previous imaging studies of single word processing. Its functional significance was variously attributed to semantic processing, visual imagery, encoding episodic memories, or the integration of lexical inputs from different sensory modalities. These hypotheses are not mutually exclusive. The more rostral medial lobe response to noun imageability has not been observed previously. However, lesions in perirhinal cortex impair knowledge about objects in non-human primates, and bilateral rostral ventromedial temporal lobe potentials in response to object nouns were observed with human intracranial recordings. Imageable (object) nouns are learnt with reference to sensory experiences of living and non-living objects, whereas acquisition of the meaning of low imageable (abstract) nouns is more dependent on their context within sentences. Parahippocampal and perirhinal cortices are reciprocally connected with, respectively, second and third order sensory association cortices. We conclude that access to the representations of word meaning is dependent on heteromodal temporal lobe cortex, and that during the acquisition of object nouns one route is established through ventromedial temporal cortical regions that have reciprocal connections with all sensory association cortices.

Identification of higher brain centres that may encode the cardiorespiratory response to exercise in humans

1 Positron emission tomography (PET) was used to identify the neuroanatomical correlates underlying ‘central command’ during imagination of exercise under hypnosis, in order to uncouple central command from peripheral feedback. 2 Three cognitive conditions were used: condition I, imagination of freewheeling downhill on a bicycle (no change in heart rate, HR, or ventilation, V̇I): condition II, imagination of exercise, cycling uphill (increased HR by 12 % and V̇I by 30 % of the actual exercise response): condition III, volitionally driven hyperventilation to match that achieved in condition II (no change in HR). 3 Subtraction methodology created contrast A (II minus I) highlighting cerebral areas involved in the imagination of exercise and contrast B (III minus I) highlighting areas activated in the direct volitional control of breathing (n= 4 for both; 8 scans per subject). End‐tidal PCO2 (PET,CO2) was held constant throughout PET scanning. 4 In contrast A, significant activations were seen in the right dorso‐lateral prefrontal cortex, supplementary motor areas (SMA), the right premotor area (PMA), superolateral sensorimotor areas, thalamus, and bilaterally in the cerebellum. In contrast B, significant activations were present in the SMA and in lateral sensorimotor cortical areas. The SMA/PMA, dorso‐lateral prefrontal cortex and the cerebellum are concerned with volitional/motor control, including that of the respiratory muscles. 5 The neuroanatomical areas activated suggest that a significant component of the respiratory response to ‘exercise’, in the absence of both movement feedback and an increase in CO2 production, can be generated by what appears to be a behavioural response.

Cognitive Control and the Salience Network: An Investigation of Error Processing and Effective Connectivity

The Salience Network (SN) consists of the dorsal anterior cingulate cortex (dACC) and bilateral insulae. The network responds to behaviorally salient events, and an important question is how its nodes interact. One theory is that the dACC provides the earliest cortical signal of behaviorally salient events, such as errors. Alternatively, the anterior right insula (aRI) has been proposed to provide an early cognitive control signal. As these regions frequently coactivate, it has been difficult to disentangle their roles using conventional methods. Here we use dynamic causal modeling and a Bayesian model evidence technique to investigate the causal relationships between nodes in the SN after errors. Thirty-five human subjects performed the Simon task. The task has two conditions (congruent and incongruent) producing two distinct error types. Neural activity associated with errors was investigated using fMRI. Subjects made a total of 1319 congruent and 1617 incongruent errors. Errors resulted in robust activation of the SN. Dynamic causal modeling analyses demonstrated that input into the SN was most likely via the aRI for both error types and that the aRI was the only region intrinsically connected to both other nodes. Only incongruent errors produced behavioral adaptation, and the strength of the connection between the dACC and the left insulae correlated with the extent of this behavioral change. We conclude that the aRI, not the dACC, drives the SN after errors on an attentionally demanding task, and that a change in the effective connectivity of the dACC is associated with behavioral adaptation after errors.

Recovery and treatment of aphasia after stroke: functional imaging studies

Purpose of reviewIn this review of papers published between May 2006 and May 2007, we discuss functional neuroimaging studies of recovery and treatment of patients with aphasia after stroke. Recent findingsStudies of recovery of aphasia have highlighted the importance of right inferior frontal gyrus activation, especially early after stroke, when it correlates with language recovery. In contrast, in the later stages after stroke left hemisphere activations predict chronic aphasia; speech production recovery appears to depend on left frontal activation, whereas speech comprehension depends on left temporal activation. There have been few studies of treatment of aphasia, but preliminary evidence suggests that treatment of speech production difficulties, even years after stroke, may be effective and deserves further study. SummaryRecent studies of aphasia recovery allow a deeper appreciation of the changing neuronal activation patterns associated with time after stroke. The distinction between neuronal reorganization that does and does not sustain recovery in the chronic phase after stroke, either spontaneous or in response to treatment, remains controversial and further studies are necessary. Clinical diagnosis and treatment of aphasia requires many more longitudinal studies with larger patient numbers and more detailed behavioural and lesion characterization of stroke patients.