Tobias Schmidt-Wilcke

Understanding encoded languages, such as written script or Morse code, requires nonlexical and lexical processing components that act in a parallel and interactive fashion. Decoding written script—as for example in reading—is typically very fast, making the investigation of the lexical and nonlexical components and their underlying neural mechanisms challenging. In the current study, we aimed to accomplish this problem by using Morse code as a model for language decoding. The decoding of Morse code is slower and thus allows a better and more fine‐grained investigation of the lexical and nonlexical components of language decoding. In the current study, we investigated the impact of various components of nonlexical decoding of Morse code using magnetoencephalography. For this purpose, we reconstructed the time–frequency responses below 40 Hz in brain regions significantly involved in Morse code decoding and word comprehension that were identified in a previous study. Event‐related reduction in beta‐ and alpha‐band power were found in left inferior frontal cortex and angular gyrus, respectively, while event‐related theta‐band power increase was found at frontal midline. These induced oscillations reflect working‐memory encoding, long‐term memory retrieval as well as demanding cognitive control, respectively. In sum, by using Morse code and MEG, we were able to identify a cortical network underlying language decoding in a time‐ and frequency‐resolved manner.

Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging–based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R ² = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder clinically characterized by muscle atrophy and progressive paralysis. In addition to the classical ALS affecting both the upper and lower motoneurons (UMN and LMN), other subtypes with the predominant (or even exclusive) affection of the UMN or LMN have been identified. This work sought to detect specific patterns of cortical brain atrophy in the UMN and LMN phenotypes to distinguish these two forms from the healthy state. Methods: Using high-resolution structural MRI and cortical thickness analysis, 38 patients with a diagnosis of ALS and predominance of either the UMN (n = 20) or the LMN (n = 18) phenotype were investigated. Results: Significant cortical thinning in the temporal lobe was found in both the ALS groups. Additionally, UMN patients displayed a significant thinning of the cortical thickness in the pre- and postcentral gyrus, as well as the paracentral lobule. By applying multivariate analyses based on the cortical thicknesses of 34 brain regions, ALS patients with either a predominant UMN or LMN phenotype were distinguished from healthy controls with an accuracy of 94% and UMN from LMN patients with an accuracy of 75%. Conclusions: These findings support previous hypothesis that neural degeneration in ALS is not confined to the sole motor regions. In addition, the amount of cortical thinning in the temporal lobe helps to distinguish ALS patients from healthy controls, that is, to support or discourage the diagnosis of ALS, while the cortical thickness of the precentral gyrus specifically helps to distinguish the UMN from the LMN phenotype.

Pain thresholds vary considerably across individuals and are influenced by a number of behavioral, genetic and neurobiological factors. However, the neurobiological underpinnings that account for individual differences remain to be fully elucidated. In this study, we used voxel‐based morphometry (VBM) and graph theory, specifically the local clustering coefficient (CC) based on resting‐state connectivity, to identify brain regions, where regional gray matter volume and network properties predicted individual pain thresholds. As a main finding, we identified a cluster in the left posterior insular cortex (IC) reaching into the left parietal operculum, including the secondary somatosensory cortex, where both regional gray matter volume and the local CC correlated with individual pain thresholds. We also performed a resting‐state functional connectivity analysis using the left posterior IC as seed region, demonstrating that connectivity to the pre‐ as well as postcentral gyrus bilaterally; that is, to the motor and primary sensory cortices were correlated with individual pain thresholds. To our knowledge, this is the first study that applied VBM in combination with voxel‐based graph theory in the context of pain thresholds. The co‐location of the VBM and the local CC cluster provide first evidence that both structure and function map to the same brain region while being correlated with the same behavioral measure; that is, pain thresholds. The study highlights the importance of the posterior IC, not only for pain perception in general, but also for the determination of individual pain thresholds.

Resembling letter-by-letter translation, Morse code can be used to investigate various linguistic components by slowing down the cognitive process of language decoding. Using fMRI and Morse code, we investigated patterns of brain activation associated with decoding three-letter words or non-words and making a lexical decision. Our data suggest that early sublexical processing is associated with activation in brain regions that are involved in sound-patterns to phoneme conversion (inferior parietal lobule), phonological output buffer (inferior frontal cortex: pars opercularis) as well as phonological and semantic top-down predictions (inferior frontal cortex: pars triangularis). In addition, later lexico-semantic processing of meaningful stimuli is associated with activation of the phonological lexicon (angular gyrus) and the semantic system (default mode network). Overall, our data indicate that sublexical and lexico-semantic analyses comprise two cognitive processes that rely on neighboring networks in the left frontal cortex and parietal lobule.

Most of the occupational exposure limits (OELs) are based on local irritants. However, exposure to much lower concentrations of irritant substances can also lead to health complaints from workers. Exposure to irritants is often accompanied by strong unpleasant odors, and strong odors might have distracting effects and hence pose a safety risk. The findings obtained in human exposure studies with chemically sensitive, stressed, or anxious persons suggest that their ability to direct attention away from the odorous exposure and to focus on a cognitive task is reduced. In addition, after repeated odor exposure, these persons show signs of sensitization, i.e., difficulties in ignoring or getting used to the exposure. The question arises as to whether certain health conditions are accompanied by a change in sensitivity to odors and irritants, so that these persons are potentially more distracted by odors and irritants and therefore more challenged in working memory tasks than nonsusceptible persons. In our study, susceptible persons with sensory airway hyperreactivity (“capsaicin-sensitive”) respond more strongly to mechanical skin stimuli than controls and show altered network connectivity. Capsaicin-sensitive subjects have a lower pain threshold and thus are more sensitive to mechanical skin stimuli. The intrinsic functional connectivity of their saliency network is higher, and the lower the GABAergic tone of the thalamus, the higher their pain sensitivity to mechanical stimuli. It seems that the increased communication between resting-state networks promotes a stronger perception of the sensory input signal. The results can be used to inform about actual risks (i.e., attention diversion and increased risk of accidents) and “pseudo” risks such as odor perception without a negative impact on one’s well-being. This way, uncertainties that still prevail in the health assessment of odorous and sensory irritating chemicals could be reduced.

We took advantage of magnetic resonance imaging (MRI) and spectroscopy (MRS) as non-invasive methods to quantify brain iron and neurometabolites, which were analyzed along with other predictors of motor dysfunction in Parkinson’s disease (PD). Tapping hits, tremor amplitude, and the scores derived from part III of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS3 scores) were determined in 35 male PD patients and 35 controls. The iron-sensitive MRI relaxation rate R2* was measured in the globus pallidus and substantia nigra. γ-aminobutyric acid (GABA)-edited and short echo-time MRS was used for the quantification of neurometabolites in the striatum and thalamus. Associations of R2*, neurometabolites, and other factors with motor function were estimated with Spearman correlations and mixed regression models to account for repeated measurements (hands, hemispheres). In PD patients, R2* and striatal GABA correlated with MDS-UPDRS3 scores if not adjusted for age. Patients with akinetic-rigid PD subtype (N = 19) presented with lower creatine and striatal glutamate and glutamine (Glx) but elevated thalamic GABA compared to controls or mixed PD subtype. In PD patients, Glx correlated with an impaired dexterity when adjusted for covariates. Elevated myo-inositol was associated with more tapping hits and lower MDS-UPDRS3 scores. Our neuroimaging study provides evidence that motor dysfunction in PD correlates with alterations in brain iron and neurometabolites.