Reduced Gray Matter Volume and Cortical Thickness in Patients With Small-Fiber Neuropathy.

Small-fiber neuropathy (SFN) is defined by degeneration or dysfunction of peripheral sensory nerve endings. Central correlates have been identified on the level of gray matter volume (GMV) and cortical thickness (CT) changes. However, across SFN etiologies knowledge about a common structural brain signature is still lacking. Therefore, we recruited 26 SFN patients and 25 age- and sex-matched healthy controls to conduct voxel-based- and surface-based morphometry. Across all patients, we found reduced GMV in widespread frontal regions, left caudate, insula and superior parietal lobule. Surface-based morphometry analysis revealed reduced CT in the right precentral gyrus of SFN patients. In a region-based approach, patients had reduced GMV in the left caudate. Since pathogenic gain-of-function variants in voltage-gated sodium channels (Nav) have been associated with SFN pathophysiology, we explored brain morphological patterns in a homogenous subsample of patients carrying rare heterozygous missense variants. Whole brain- and region-based approaches revealed GMV reductions in the bilateral caudate for Nav variant carriers. Further research is needed to analyze the specific role of Nav variants for structural brain alterations. Together, we conclude that SFN patients have specific GMV and CT alterations, potentially forming potential new central biomarkers for this condition. Our results might help to better understand underlying or compensatory mechanisms of chronic pain perception in the future. PERSPECTIVE: This study reveals structural brain changes in small-fiber neuropathy (SFN) patients, particularly in frontal regions, caudate, insula, and parietal lobule. Notably, individuals with SFN and specific Nav variants exhibit bilateral caudate abnormalities. These findings may serve as potential central biomarkers for SFN and provide insights into chronic pain perception mechanisms.

Neural correlates of multisensory integration in the human brain: an ALE meta-analysis.

Previous fMRI research identified superior temporal sulcus as central integration area for audiovisual stimuli. However, less is known about a general multisensory integration network across senses. Therefore, we conducted activation likelihood estimation meta-analysis with multiple sensory modalities to identify a common brain network. We included 49 studies covering all Aristotelian senses i.e., auditory, visual, tactile, gustatory, and olfactory stimuli. Analysis revealed significant activation in bilateral superior temporal gyrus, middle temporal gyrus, thalamus, right insula, and left inferior frontal gyrus. We assume these regions to be part of a general multisensory integration network comprising different functional roles. Here, thalamus operate as first subcortical relay projecting sensory information to higher cortical integration centers in superior temporal gyrus/sulcus while conflict-processing brain regions as insula and inferior frontal gyrus facilitate integration of incongruent information. We additionally performed meta-analytic connectivity modelling and found each brain region showed co-activations within the identified multisensory integration network. Therefore, by including multiple sensory modalities in our meta-analysis the results may provide evidence for a common brain network that supports different functional roles for multisensory integration.

A neural mechanism underlying predictive visual motion processing in patients with schizophrenia.

Psychotic symptoms may be traced back to sensory sensitivity. Thereby, visual motion (VM) processing particularly has been suggested to be impaired in schizophrenia (SCZ). In healthy brains, VM underlies predictive processing within hierarchically structured systems. However, less is known about predictive VM processing in SCZ. Therefore, we performed fMRI during a VM paradigm with three conditions of varying predictability, i.e., Predictable-, Random-, and Arbitrary motion. The study sample comprised 17 SCZ patients and 23 healthy controls. We calculated general linear model (GLM) analysis to assess group differences in VM processing across motion conditions. Here, we identified significantly lower activity in right temporoparietal junction (TPJ) for SCZ patients. Therefore, right TPJ was set as seed for connectivity analyses. For patients, across conditions we identified increased connections to higher regions, namely medial prefrontal cortex, or paracingulate gyrus. Healthy subjects activated sensory regions as area V5, or superior parietal lobule. Reduced TPJ activity may reflect both a failure in the bottom-up flow of visual information and a decrease of signal processing as consequence of increased top-down input from frontal areas. In sum, these altered neural patterns provide a framework for future studies focusing on predictive VM processing to identify potential biomarkers of psychosis.