Repetitive Transcranial Magnetic Stimulation Over the Left Posterior Middle Temporal Gyrus Reduces Wrist Velocity During Emblematic Hand Gesture Imitation

Results from neuropsychological studies, and neuroimaging and behavioural experiments with healthy individuals, suggest that the imitation of meaningful and meaningless actions may be reliant on different processing routes. The left posterior middle temporal gyrus (pMTG) is one area that might be important for the recognition and imitation of meaningful actions. We studied the role of the left pMTG in imitation using repetitive transcranial magnetic stimulation (rTMS) and two-person motion-tracking. Participants imitated meaningless and emblematic meaningful hand and finger gestures performed by a confederate actor whilst both individuals were motion-tracked. rTMS was applied during action observation (before imitation) over the left pMTG or a vertex control site. Since meaningless action imitation has been previously associated with a greater wrist velocity and longer correction period at the end of the movement, we hypothesised that stimulation over the left pMTG would increase wrist velocity and extend the correction period of meaningful actions (i.e., due to interference with action recognition). We also hypothesised that imitator accuracy (actor-imitator correspondence) would be reduced following stimulation over the left pMTG. Contrary to our hypothesis, we found that stimulation over the pMTG, but not the vertex, during action observation reduced wrist velocity when participants later imitated meaningful, but not meaningless, hand gestures. These results provide causal evidence for a role of the left pMTG in the imitation of meaningful gestures, and may also be in keeping with proposals that left posterior temporal regions play a role in the production of postural components of gesture

Repetitive transcranial magnetic stimulation reveals a role for the left inferior parietal lobule in matching observed kinematics during imitation

Apraxia (a disorder of complex movement) suggests that the left inferior parietal lobule plays a role in kinematic or spatial aspects of imitation, which may be particularly important for meaningless (i.e., unfamiliar intransitive) actions. Mirror neuron theories indicate that the inferior parietal lobule is part of a frontoparietal system that can support imitation by linking observed and stored actions through visuomotor matching, and have less to say about different subregions of the left inferior parietal lobule, or how different types of action (i.e., meaningful or meaningless) are processed for imitation. We used repetitive transcranial magnetic stimulation (rTMS) to bridge this gap and better understand the roles of the left supramarginal gyrus and left angular gyrus in imitation. We also examined if these areas are differentially involved in meaningful and meaningless action imitation. We applied rTMS over the left supramarginal gyrus, left angular gyrus, or during a no-rTMS baseline condition, then asked participants to imitate a confederate’s actions whilst the arm and hand movements of both individuals were motion-tracked. rTMS over both the left supramarginal gyrus and the left angular gyrus reduced the velocity of participants' finger movements relative to the actor during imitation of finger gestures, regardless of action meaning. Our results support recent claims in apraxia and confirm a role for the left inferior parietal lobule in kinematic processing during gesture imitation, regardless of action meaning

Bayesian lesion-deficit inference with Bayes factor mapping: key advantages, limitations, and a toolbox.

Statistical lesion-symptom mapping is largely dominated by frequentist approaches with null hypothesis significance testing. They are popular for mapping functional brain anatomy but are accompanied by some challenges and limitations. The typical analysis design and the structure of clinical lesion data are linked to the multiple comparison problem, an association problem, limitations to statistical power, and a lack of insights into evidence for the null hypothesis. Bayesian lesion deficit inference (BLDI) could be an improvement as it collects evidence for the null hypothesis, i.e. the absence of effects, and does not accumulate α-errors with repeated testing. We implemented BLDI by Bayes factor mapping with Bayesian t-tests and general linear models and evaluated its performance in comparison to frequentist lesion-symptom mapping with a permutation-based family-wise error correction. We mapped the voxel-wise neural correlates of simulated deficits in an in-silico-study with 300 stroke patients, and the voxel-wise and disconnection-wise neural correlates of phonemic verbal fluency and constructive ability in 137 stroke patients. Both the performance of frequentist and Bayesian lesion-deficit inference varied largely across analyses. In general, BLDI could find areas with evidence for the null hypothesis and was statistically more liberal in providing evidence for the alternative hypothesis, i.e. the identification of lesion-deficit associations. BLDI performed better in situations in which the frequentist method is typically strongly limited, for example with on average small lesions and in situations with low power, where BLDI also provided unprecedented transparency in terms of the informative value of the data. On the other hand, BLDI suffered more from the association problem, which led to a pronounced overshoot of lesion-deficit associations in analyses with high statistical power. We further implemented a new approach to lesion size control, adaptive lesion size control, that, in many situations, was able to counter the limitations imposed by the association problem, and increased true evidence both for the null and the alternative hypothesis. In summary, our results suggest that BLDI is a valuable addition to the method portfolio of lesion-deficit inference with some specific and exclusive advantages: it deals better with smaller lesions and low statistical power (i.e. small samples and effect sizes) and identifies regions with absent lesion-deficit associations. However, it is not superior to established frequentist approaches in all respects and therefore not to be seen as a general replacement. To make Bayesian lesion-deficit inference widely accessible, we published an R toolkit for the analysis of voxel-wise and disconnection-wise data

Cortical Damage and Disconnection Contribute to Post-Stroke Sensorimotor Impairment

BACKGROUND. Stroke is a cerebrovascular event that causes permanent damage to brain regions and decreases in connectivity (disconnection) between brain regions. Most stroke survivors have permanent difficulties performing functional motor tasks, thus research into how damage and disconnection produce difficulties performing motor tasks can help guide post-stroke rehabilitation. Previous studies have examined the extent to which cortical damage produces motor impairments, but the extent to which disconnection produces motor impairments remains unclear. Furthermore, studies have focused on how motor impairments contribute to difficulties performing motor tasks, whereas the role of visuospatial impairments has received little attention. Neuroimaging techniques for quantifying stroke-induced damage and disconnection of brain networks are powerful tools for examining the neural mechanisms that underlie difficulties performing visuomotor tasks. OBJECTIVE. The purpose of the proposed research study is to examine the extent to which cortical damage and disconnection independently contribute to deficits in visuomotor task performance. HYPOTHESES. Three hypotheses will be tested. Hypothesis 1: Cortical damage and disconnection will be largely independent of each other. Hypothesis 2: Damage and disconnection involving two different (but partially overlapping) cortical networks will be associated with motor and visuospatial impairments. Hypothesis 3: Damage and disconnection of cortical motor and visuospatial networks will independently contribute to deficits in task performance. METHODS. The proposed study will examine 47 subjects with a single, unilateral stroke of the left middle cerebral artery at least six months before testing. Subjects will perform a bimanual, visuomotor task (Object Hit), which will be used to quantify Task Performance (Object Hits), Motor Impairment (Hand Speed Bias), and Visuospatial Impairment (Spatial Miss Bias). Magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) will be used to quantify Damage (Lesion Volume) and Disconnection (Connectivity Bias) of cortical visuomotor regions. These measures will be used to test the hypotheses of the proposed study

Using multi-level Bayesian lesion-symptom mapping to probe the body-part-specificity of gesture imitation skills

Past attempts to identify the neural substrates of hand and finger imitation skills in the left hemisphere of the brain have yielded inconsistent results. Here, we analyse those associations in a large sample of 257 left hemisphere stroke patients. By introducing novel Bayesian methods, we characterise lesion symptom associations at three levels: the voxel-level, the single-region level (using anatomically defined regions), and the region-pair level. The results are inconsistent across those three levels and we argue that each level of analysis makes assumptions which constrain the results it can produce. Regardless of the inconsistencies across levels, and contrary to past studies which implicated differential neural substrates for hand and finger imitation, we find no consistent voxels or regions, where damage affects one imitation skill and not the other, at any of the three analysis levels. Our novel Bayesian approach indicates that any apparent differences appear to be driven by an increased sensitivity of hand imitation skills to lesions that also impair finger imitation. In our analyses, the results of the highest level of analysis (region-pairs) emphasise a role of the primary somatosensory and motor cortices, and the occipital lobe in imitation. We argue that this emphasis supports an account of both imitation tasks based on direct sensor-motor connections, which throws doubt on past accounts which imply the need for an intermediate (e.g. body-part-coding) system of representation

Improving and validating methods in lesion behaviour mapping

The investigation of diseased brain is one of the major methods in cognitive neuroscience. This approach allows numerous insights both into human cognition and brain architecture. Most prominent is the method of lesion behaviour mapping, where inferences about functional brain architecture are drawn from focally lesioned brains. In the last 15 years, the state-of-the-art implementation of lesion behaviour mapping has been voxel-based lesion behaviour mapping, which is based on the framework of statistical parametric mapping. Recently, the validity of this method has been criticised and multivariate methods have been proposed to complement or even replace it. In my thesis, I aim to evaluate these different methodological approaches to lesion behaviour mapping and to provide guidelines on how lesion-brain inference should be drawn. In my first empirical work, I investigate the validity of voxel-based lesion behaviour mapping. It shows that previous studies overestimated biases inherent to the method, and that validity can be improved by the use of correction factors. The second empirical work deals with a recently developed method of multivariate lesion behaviour mapping. On the one hand, I clarify how this method can be used to obtain valid lesion-brain inference. On the other hand, I show that the method is not able to overcome all limitations of voxel-based lesion behaviour mapping. In my last work, I apply multivariate lesion behaviour mapping to investigate the neural correlates of higher motor cognition. This analysis is the first to identify a brain network to underlie apraxia, a disorder of higher motor cognition, which underlines the benefits of the new multivariate approach in brain networks