Auditory cortex hypoperfusion: a metabolic hallmark in Beta Thalassemia

Abstract Background Sensorineural hearing loss in beta-thalassemia is common and it is generally associated with iron chelation therapy. However, data are scarce, especially on adult populations, and a possible involvement of the central auditory areas has not been investigated yet. We performed a multicenter cross-sectional audiological and single-center 3Tesla brain perfusion MRI study enrolling 77 transfusion-dependent/non transfusion-dependent adult patients and 56 healthy controls. Pure tone audiometry, demographics, clinical/laboratory and cognitive functioning data were recorded. Results Half of patients (52%) presented with high-frequency hearing deficit, with overt hypoacusia (Pure Tone Average (PTA) > 25 dB) in 35%, irrespective of iron chelation or clinical phenotype. Bilateral voxel clusters of significant relative hypoperfusion were found in the auditory cortex of beta-thalassemia patients, regardless of clinical phenotype. In controls and transfusion-dependent (but not in non-transfusion-dependent) patients, the relative auditory cortex perfusion values increased linearly with age (p < 0.04). Relative auditory cortex perfusion values showed a significant U-shaped correlation with PTA values among hearing loss patients, and a linear correlation with the full scale intelligence quotient (right side p = 0.01, left side p = 0.02) with its domain related to communication skills (right side p = 0.04, left side p = 0.07) in controls but not in beta-thalassemia patients. Audiometric test results did not correlate to cognitive test scores in any subgroup. Conclusions In conclusion, primary auditory cortex perfusion changes are a metabolic hallmark of adult beta-thalassemia, thus suggesting complex remodeling of the hearing function, that occurs regardless of chelation therapy and before clinically manifest hearing loss. The cognitive impact of perfusion changes is intriguing but requires further investigations

Sex differences in the taste-evoked functional connectivity network

The central gustatory pathway encompasses multiple subcortical and cortical regions whose neural functional connectivity can be modulated by taste stimulation. While gustatory perception has been previously linked to sex, whether and how the gustatory network differently responds to basic tastes between men and women is unclear. Here, we defined the regions of the central gustatory network by a meta-analysis of 35 fMRI taste activation studies and then analyzed the taste-evoked functional connectivity between these regions in 44 subjects (19 women) in a separate 3 Tesla activation study where sweet and bitter solutions, at five concentrations each, were administered during scanning. From the meta-analysis, a network model was set up, including bilateral anterior, middle and inferior insula, thalamus, precentral gyrus, left amygdala, caudate and dorsolateral prefrontal cortex. Higher functional connectivity than in women was observed in men between the right middle insula and bilateral thalami for bitter taste. Men exhibited higher connectivity than women at low bitter concentrations and middle-high sweet concentrations between bilateral thalamus and insula. A graph-based analysis expressed similar results in terms of nodal characteristics of strength and centrality. Our findings add new insights into the mechanisms of taste processing by highlighting sex differences in the functional connectivity of the gustatory network as modulated by the perception of sweet and bitter tastes. These results shed more light on the neural origin of sex-related differences in gustatory perception and may guide future research on the pathophysiology of taste perception in humans

Explaining neural activity in human listeners with deep learning via natural language processing of narrative text

Deep learning (DL) approaches may also inform the analysis of human brain activity. Here, a state-of-art DL tool for natural language processing, the Generative Pre-trained Transformer version 2 (GPT-2), is shown to generate meaningful neural encodings in functional MRI during narrative listening. Linguistic features of word unpredictability (surprisal) and contextual importance (saliency) were derived from the GPT-2 applied to the text of a 12-min narrative. Segments of variable duration (from 15 to 90&nbsp;s) defined the context for the next word, resulting in different sets of neural predictors for functional MRI signals recorded in 27 healthy listeners of the narrative. GPT-2 surprisal, estimating word prediction errors from the artificial network, significantly explained the neural data in superior and middle temporal gyri (bilaterally), in anterior and posterior cingulate cortices, and in the left prefrontal cortex. GPT-2 saliency, weighing the importance of context words, significantly explained the neural data for longer segments in left superior and middle temporal gyri. These results add novel support to the use of DL tools in the search for neural encodings in functional MRI. A DL language model like the GPT-2 may feature useful data about neural processes subserving language comprehension in humans, including next-word context-related prediction

Intensity-related distribution of sweet and bitter taste fMRI responses in the insular cortex

The human gustatory cortex analyzes the chemosensory properties of tastants, particularly the quality, intensity, and affective valence, to determine whether a perceived substance should be ingested or rejected. Among previous studies, the spatial distribution of taste intensity-related activations within the human insula has been scarcely addressed. To spatially characterize a specialized or distributed nature of the cortical responses to taste intensities, a functional magnetic resonance imaging study was performed at 3 T in 44 healthy subjects where sweet and bitter tastants were administered at five increasing concentrations and cortex-based factorial and parametric analyses were performed. Two clusters in the right middle-posterior and left middle insula were found specialized for taste intensity processing, exhibiting a highly nonlinear profile across concentrations. Multiple clusters were found activated by sweet and bitter taste stimuli at most concentrations, in the anterior, middle-posterior, and inferior portion of the bilateral insula. Across these clusters, respectively, for the right and left insula, a superior-to-inferior and an anterior-to-posterior spatial gradient for high-to-low concentrations were observed for the most responsive intensity of both tastes. These findings may gather new insights regarding how the gustatory cortex is spatially organized during the perceptual processing of taste intensity for two basic tastants

Semantic fMRI neurofeedback:A Multi-Subject Study at 3 Tesla

Objective: Real-time fMRI neurofeedback is a non-invasive procedure allowing the self-regulation of brain functions via enhanced self-control of fMRI based neural activation. In semantic real-time fMRI neurofeedback, an estimated relation between multivariate fMRI activation patterns and abstract mental states is exploited for a multi-dimensional feedback stimulus via real-time representational similarity analysis (rt-RSA). Here, we assessed the performances of this framework in a multi-subject multi-session study on a 3T MRI clinical scanner. Approach: Eighteen healthy volunteers underwent two semantic real-time fMRI neurofeedback sessions on two different days. In each session, participants were first requested to engage in specific mental states while local fMRI patterns of brain activity were recorded during stimulated mental imagery of concrete objects (pattern generation). The obtained neural representations were to be replicated and modulated by the participants in subsequent runs of the same session under the guidance of a rt-RSA generated visual feedback (pattern modulation). Performance indicators were derived from the rt-RSA output to assess individual abilities in replicating (and maintaining over time) a target pattern. Simulations were carried out to assess the impact of the geometric distortions implied by the low-dimensional representation of patterns' dissimilarities in the visual feedback. Main results: Sixteen subjects successfully completed both semantic real-time fMRI neurofeedback sessions. Considering some performance indicators, a significant improvement between the first and the second runs, and within run increasing modulation performances were observed, whereas no improvements were found between sessions. Simulations confirmed that in a small percentage of cases visual feedback could be affected by metric distortions due to dimensionality reduction implicit to the rt-RSA approach. Significance: Our results proved the feasibility of the semantic real-time fMRI neurofeedback at 3T, showing that subjects can successfully modulate and maintain a target mental state, guided by rt-RSA derived feedback. Further development is needed to encourage future clinical applications

Automated search of control points in surface-based morphometry

Cortical surface-based morphometry is based on a semi-automated analysis of structural MRI images. In FreeSurfer, a widespread tool for surface-based analyses, a visual check of gray-white matter borders is followed by the manual placement of control points to drive the topological correction (editing) of segmented data. A novel algorithm combining radial sampling and machine learning is presented for the automated control point search (ACPS). Four data sets with 3 T MRI structural images were used for ACPS validation, including raw data acquired twice in 36 healthy subjects and both raw and FreeSurfer preprocessed data of 125 healthy subjects from public databases. The unedited data from a subgroup of subjects were submitted to manual control point search and editing. The ACPS algorithm was trained on manual control points and tested on new (unseen) unedited data. Cortical thickness (CT) and fractal dimensionality (FD) were estimated in three data sets by reconstructing surfaces from both unedited and edited data, and the effects of editing were compared between manual and automated editing and versus no editing. The ACPS-based editing improved the surface reconstructions similarly to manual editing. Compared to no editing, ACPS-based and manual editing significantly reduced CT and FD in consistent regions across different data sets. Despite the extra processing of control point driven reconstructions, CT and FD estimates were highly reproducible in almost all cortical regions, albeit some problematic regions (e.g. entorhinal cortex) may benefit from different editing. The use of control points improves the surface reconstruction and the ACPS algorithm can automate their search reducing the burden of manual editing

Vitamin C Acutely Affects Brain Perfusion and Mastication-Induced Perfusion Asymmetry in the Principal Trigeminal Nucleus

Prolonged mastication may induce an asymmetric modification of the local perfusion of the trigeminal principal nucleus. The aim of the present study was to evaluate the possible influence of vitamin C (vit. C) on such effect. Four groups of healthy volunteers underwent arterial spin labeling magnetic resonance imaging (ASL-MRI) to evaluate the local perfusion of the trigeminal nuclei after a vit. C-enriched lunch or a control lunch. Two ASL-MRI scans were acquired, respectively, before and after a 1 h-long masticating exercise or a 1 h long resting period. The results showed (i) an increased global perfusion of the brain in the vit. C-enriched lunch groups, (ii) an increased local perfusion of the right principal trigeminal nucleus (Vp) due to mastication, and (iii) a reduction of the rightward asymmetry of the Vp perfusion, due to mastication, after the vit C-enriched meal compared to the control meal. These results confirmed a long-lasting effect of prolonged mastication on Vp perfusion and also suggest a possible effect of vit. C on cerebral vascular tone regulation. Moreover, the data strongly draw attention on the side-to-side relation in Vp perfusion as a possible physiological parameter to be considered to understand the origin of pathological conditions like migraine

A group-level comparison of volumetric and combined volumetric-surface normalization for whole brain analyses of myelin and iron maps

Quantitative MRI (qMRI) provides surrogate brain maps of myelin and iron content. After spatial normalization to a common standard brain space, these may be used to detect altered myelination and iron accumulation in clinical populations. Here, volumetric and combined volumetric and surface-based (CVS) normalization were compared to identify which procedure would afford the greatest sensitivity to inter-regional differences (contrast), and the lowest inter-subject variability (under normal conditions), of myelin- and iron-related qMRI parameters, in whole-brain group-level studies. Ten healthy volunteers were scanned twice at 3 Tesla. Three-dimensional T1-weighted, T2-weighted and multi-parametric mapping sequences for brain qMRI were used to map myelin and iron content over the whole brain. Parameter maps were spatially normalized using volumetric (DARTEL) and CVS procedures. Tissue probability weighting and isotropic Gaussian smoothing were integrated in DARTEL for voxel-based quantification (VBQ). Contrasts, coefficients of variations and sensitivity to detecting differences in the parameters were estimated in standard space for each approach on region of interest (ROI) and voxel-by-voxel bases. The contrast between cortical and subcortical ROIs with respectively different myelin and iron content was higher following CVS, compared to DARTEL-VBQ, normalization. Across cortical voxels, the inter-individual variability of myelin and iron qMRI maps were comparable between CVS (with no smoothing) and DARTEL-VBQ (with smoothing). CVS normalization of qMRI maps preserves higher myelin and iron contrast than DARTEL-VBQ over the entire brain, while exhibiting comparable variability in the cerebral cortex without extra smoothing. Thus, CVS may prove useful for detecting small microstructural differences in whole-brain group-level qMRI studies