Accumbal-thalamic connectivity and associated glutamate alterations in human cocaine craving: A state-dependent rs-fMRI and 1H-MRS study.

Craving is a core symptom of cocaine use disorder and a major factor for relapse risk. To date, there is no pharmacological therapy to treat this disease or at least to alleviate cocaine craving as a core symptom. In animal models, impaired prefrontal-striatal signalling leading to altered glutamate release in the nucleus accumbens appear to be the prerequisite for cocaine-seeking. Thus, those network and metabolic changes may constitute the underlying mechanisms for cocaine craving and provide a potential treatment target. In humans, there is recent evidence for corresponding glutamatergic alterations in the nucleus accumbens, however, the underlying network disturbances that lead to this glutamate imbalance remain unknown. In this state-dependent randomized, placebo-controlled, double-blinded, cross-over multimodal study, resting state functional magnetic resonance imaging in combination with small-voxel proton magnetic resonance spectroscopy (voxel size: 9.4 × 18.8 × 8.4 mm3) was applied to assess network-level and associated neurometabolic changes during a non-craving and a craving state, induced by a custom-made cocaine-cue film, in 18 individuals with cocaine use disorder and 23 healthy individuals. Additionally, we assessed the potential impact of a short-term challenge of N-acetylcysteine, known to normalize disturbed glutamate homeostasis and to thereby reduce cocaine-seeking in animal models of addiction, compared to a placebo. We found increased functional connectivity between the nucleus accumbens and the dorsolateral prefrontal cortex during the cue-induced craving state. However, those changes were not linked to alterations in accumbal glutamate levels. Whereas we additionally found increased functional connectivity between the nucleus accumbens and a midline part of the thalamus during the cue-induced craving state. Furthermore, obsessive thinking about cocaine and the actual intensity of cocaine use were predictive of cue-induced functional connectivity changes between the nucleus accumbens and the thalamus. Finally, the increase in accumbal-thalamic connectivity was also coupled with craving-related glutamate rise in the nucleus accumbens. Yet, N-acetylcysteine had no impact on craving-related changes in functional connectivity. Together, these results suggest that connectivity changes within the fronto-accumbal-thalamic loop, in conjunction with impaired glutamatergic transmission, underlie cocaine craving and related clinical symptoms, pinpointing the thalamus as a crucial hub for cocaine craving in humans.

Olfactory Loss and Brain Connectivity after COVID-19: Structural Follow-Up at One Year.

The structural connectivity from the primary olfactory cortex to the main secondary olfactory areas was previously reported as relatively increased in the medial orbitofrontal cortex in a cohort of 27 recently SARS-CoV-2-infected (COV+) subjects, of which 23/27 had clinically confirmed olfactory loss, compared to 18 control (COV-) normosmic subjects, who were not previously infected. To complement this finding, here we report the outcome of an identical high angular resolution diffusion MRI analysis on follow-up data sets collected in 18/27 COV+ subjects (10 males, mean age ± SD: 38.7 ± 8.1 years) and 10/18 COV- subjects (5 males, mean age ± SD: 33.1 ± 3.6 years) from the previous samples who repeated both the olfactory functional assessment and the MRI examination after ~1 year. By comparing the newly derived subgroups, we observed that the increase in the structural connectivity index of the medial orbitofrontal cortex was not significant at follow-up, despite 10/18 COV+ subjects were still found hyposmic after ~1 year from SARS-CoV-2 infection. We concluded that the relative hyperconnectivity of the olfactory cortex to the medial orbitofrontal cortex could be, at least in some cases, an acute or reversible phenomenon linked to the recent SARS-CoV-2 infection with associated olfactory loss.

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 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.

Negative correlation between word-level surprisal and intersubject neural synchronization during narrative listening.

Word-predictability measures, such as surprisal, have been used to show that linguistic prediction is an essential neural mechanism for successful comprehension. However, the neural dynamic of this mechanism may differ across individuals listening to the same narrative, revealing possible idiosyncrasies. Therefore, in this study, we investigated the ability of the surprisal measure to address the linguistic prediction in terms of the intersubject phase synchronization (ISPS) among healthy volunteers listening to a narrative during continuous functional Magnetic Resonance Imaging (fMRI) scanning. The data of twenty-seven participants, acquired in a previous study, were re-analyzed to estimate the ISPS associated with an audiobook listening, played forward and backward. Mean ISPS differences between playing conditions were first analyzed across the whole brain. ISPS time-series during the forward condition was explained with both a lexical-only and a semantics-weighted lexical surprisal model of the narrative word series to detect correlations between ISPS and word surprisal values. Compared to the backward condition, mean ISPS was significantly higher during forward condition in a broad network encompassing frontal, temporal, and parietal areas. The lexical-only model disclosed significant negative ISPS-surprisal correlations in the angular gyrus bilaterally, precuneus, left inferior parietal lobule, left middle frontal gyrus, left cerebellum, and left inferior frontal gyrus. The semantics-weighted surprisal model disclosed significant negative ISPS-surprisal correlations in the right angular gyrus, right precuneus, and left inferior frontal gyrus. Besides engaging language-related areas, narrative processing induces significant ISPS levels beyond the language network. The negative ISPS-surprisal correlations observed would signal divergent neural dynamics among individuals, leading to lower group synchronization, when the words to be integrated are characterized by higher surprisal levels. These results provide further support to the use of language models, such as the surprisal, to explain the neural processes of narrative comprehension and additional information into how the human brain exploits predictions during language comprehension.

Semantic fMRI neurofeedback: a multi-subject study at 3 tesla.

Objective.Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) is a non-invasive procedure allowing the self-regulation of brain functions via enhanced self-control of fMRI based neural activation. In semantic rt-fMRI-NF, 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 3 T MRI clinical scanner.Approach.Eighteen healthy volunteers underwent two semantic rt-fMRI-NF 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 rt-fMRI-NF 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 rt-fMRI-NF at 3 T, showing that subjects can successfully modulate and maintain a target mental state when guided by rt-RSA derived feedback. Further development is needed to encourage future clinical applications.

Towards semantic fMRI neurofeedback: navigating among mental states using real-time representational similarity analysis.

Objective. Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) is a non-invasive MRI procedure allowing examined participants to learn to self-regulate brain activity by performing mental tasks. A novel two-step rt-fMRI-NF procedure is proposed whereby the feedback display is updated in real-time based on high-level representations of experimental stimuli (e.g. objects to imagine) via real-time representational similarity analysis of multi-voxel patterns of brain activity.Approach. In a localizer session, the stimuli become associated with anchored points on a two-dimensional representational space where distances approximate between-pattern (dis)similarities. In the NF session, participants modulate their brain response, displayed as a movable point, to engage in a specific neural representation. The developed method pipeline is verified in a proof-of-concept rt-fMRI-NF study at 7 T involving a single healthy participant imagining concrete objects. Based on this data and artificial data sets with similar (simulated) spatio-temporal structure and variable (injected) signal and noise, the dependence on noise is systematically assessed.Main results. The participant in the proof-of-concept study exhibited robust activation patterns in the localizer session and managed to control the neural representation of a stimulus towards the selected target in the NF session. The offline analyses validated the rt-fMRI-NF results, showing that the rapid convergence to the target representation is noise-dependent.Significance. Our proof-of-concept study introduces a new NF method allowing the participant to navigate among different mental states. Compared to traditional NF designs (e.g. using a thermometer display to set the level of the neural signal), the proposed approach provides content-specific feedback to the participant and extra degrees of freedom to the experimenter enabling real-time control of the neural activity towards a target brain state without suggesting a specific mental strategy to the subject.

Visual cortex changes in children with sickle cell disease and normal visual acuity: a multimodal magnetic resonance imaging study.

The visual system is primarily affected in sickle cell disease (SCD), and eye examination is recommended starting in late childhood. So far, to our knowledge, all studies have focused on the retina, neglecting the changes that might be present in the cortical portion of the visual system. We performed a multimodal magnetic resonance imaging (MRI) evaluation of the visual cortex in 25 children with SCD (mean age: 12·3 ± 1·9 years) and 31 controls (mean age: 12·7 ± 1·6 years). At ophthalmologic examination, 3/25 SCD children had mild visual acuity deficits and 2/25 had mild tortuosity of the retinal vessels. None showed optic pathway infarcts at MRI or Transcranial Doppler abnormal blood velocities, and 6/25 disclosed posterior cerebral artery stenosis (five mild and one severe) at MR-angiography. Compared to controls, SCD children had increased posterior pericalcarine cortical thickness, with a different trajectory of cortical maturation and decreased connectivity within medial and ventral visual neural networks. Our findings suggest that SCD affects the development and the tuning of the visual cortex, leading to anatomical and functional changes in childhood even in the absence of retinopathy, and set the basis for future studies to determine if these changes can represent useful predictors of visual impairment in adulthood, biomarkers of disease progression or treatment response.

The neural substrate of noun morphological inflection: A rapid event-related fMRI study in Italian.

The present research investigated the neural correlates of nominal inflection and aimed at disclosing their possible link with the frequency distribution of noun inflectional features: grammatical gender, inflectional suffixes and inflectional classes. The properties of the Italian nominal system were exploited since it allows to explore exhaustively fine-grained phenomena in the inflectional processing. An event-related functional magnetic resonance imaging (fMRI) experiment was carried out where Italian masculine and feminine nouns were visually presented to 50 healthy participants in an overt inflectional task: the generation of the plural from the singular and vice versa. The grammatical gender and the citation form suffix of nouns were manipulated in a factorial design. Functional data showed that inflectional operations for nouns activate an extensive cortical network involving the left inferior and right superior frontal gyri, the left and right middle temporal gyri, the posterior cingulate cortex and the cerebellum. Activations were variably modulated by the distributional features of gender-dependent properties of nouns. Particularly, cortical activity increased during inflectional operations for small and/or scarcely consistent inflectional classes. These findings demonstrate the relevance of specific morphological (inflectional suffixes) and distributional features (size and consistency) shared by groups of words (inflectional classes) in a language, particularly when implementing cognitive operations required for language processing.

Semantics-weighted lexical surprisal modeling of naturalistic functional MRI time-series during spoken narrative listening.

Probabilistic language models are increasingly used to provide neural representations of linguistic features under naturalistic settings. Word surprisal models can be applied to continuous fMRI recordings during task-free listening of narratives, to detect regions linked to language prediction and comprehension. Here, to this purpose, a novel semantics-weighted lexical surprisal is applied to naturalistic fMRI data. FMRI was performed at 3 Tesla in 31 subjects during task-free listening to a 12-minute audiobook played in both original and word-reversed (control) version. Lexical-only and semantics-weighted lexical surprisal models were estimated for the original and control word series. The two series were alternatively chosen to build the predictor of interest in the first-level general linear model and were compared in the second-level (group) analysis. The addition of the surprisal predictor to the stimulus-related predictors significantly improved the fitting of the neural signal. In average, the semantics-weighted model yielded lower surprisal values and, in some areas, better fitting of the fMRI data compared to the lexical-only model. The two models produced both overlapping and distinct activations: while lexical-only surprisal activated secondary auditory areas in the superior temporal gyri and the cerebellum, semantics-weighted surprisal additionally activated the left inferior frontal gyrus. These results confirm the usefulness of surprisal models in the naturalistic fMRI analysis of linguistic processes and suggest that the use of semantic information may increase the sensitivity of a probabilistic language model in higher-order language-related areas, with possible implications for future naturalistic fMRI studies of language under normal and (clinically or pharmacologically) modified conditions.

Headache in beta-thalassemia: An Italian multicenter clinical, conventional MRI and MR-angiography case-control study.

OBJECTIVES: A strikingly increased headache prevalence was recently noted in Sri Lankan beta-thalassemia patients, raising several concerns regarding long-term neurological involvement in this condition. METHODS: We interviewed on headache occurrence and characteristics 102 Italian beta-thalassemia patients and 129 healthy controls. 3T-MRI, MR-angiography, MR-venography, cognitive and psychiatric findings were considered. RESULTS: Headache was diagnosed in 39/102 (38.2%) beta-thalassemia patients without significant phenotype-related differences and in 51/129 (39.5%) controls. Patients and controls did not differ significantly regarding episode number (5.9 ± 6.2 vs 5.4 ± 4.4 days/month), subjective severity-score (6.8 ± 1.4 vs 7.1 ± 1.3), age-at-onset (24.3 ± 13.0 vs 19.5 ± 9.6 years) and headache-subtype rate. No main demographic, clinical or laboratory data was associated with headache but female gender. Headache was not associated with white matter lesions (number or maximal diameter), intracranial aneurysms, intracranial artery stenoses or venous sinus thrombosis. Cognitive and psychiatric evaluations were worse in beta-thalassemia, however, headache did not correlate with full-scale Intelligence Quotient (75.4 ± 18.0 vs 76.7 ± 15.3, with and without headache, respectively) or Brief Psychiatric Rating Scale scores (29.1 ± 2.7 vs 28.5 ± 3.4). CONCLUSIONS: Among Italian beta-thalassemia patients, headache does not seem to be more common or severe than in the general population. In addition, patients with headache do not seem to present increased conventional MRI, MR-angiography and cognitive/psychiatric changes.

No evidence of increased cerebrovascular involvement in adult neurologically-asymptomatic ß-Thalassaemia. A multicentre multimodal magnetic resonance study.

Multi-factorial causes jeopardize brain integrity in ß-thalassaemia. Intracranial parenchymal and vascular changes have been reported among young ß-thalassaemia patients but conventional magnetic resonance imaging (MRI) findings are contradictory making early MRI and magnetic resonance angiography (MRA)/venography monitoring a matter of debate. This study prospectively investigated 75 neurologically asymptomatic ß-thalassaemia patients (mean-age 35·2 ± 10·7 years; 52/75 transfusion-dependent; 41/75 splenectomised) using a 3T magnetic resonance scanner; clinical, laboratory and treatment data were also collected. White matter ischaemic-like abnormalities, intracranial artery stenoses, aneurysms and sinus venous thrombosis were compared between patients and 56 healthy controls (mean-age 33·9 ± 10·8 years). No patient or control showed silent territorial or lacunar strokes, intracranial artery stenoses or signs of sinus thrombosis. White matter lesions were found both in patients (35/75, 46·7%) and controls (28/56, 50·0%), without differences in terms of number (4·0 ± 10·6 vs. 4·6 ± 9·1, P = 0·63), size and Fazekas' Score. Intracranial aneurysms did not differ between patients and controls for incidence rate (7/75, 9·3% vs. 5/56, 8·9%), size and site. Vascular and parenchymal abnormality rate did not differ according to treatments or clinical phenotype. According to this study, asymptomatic ß-thalassaemia patients treated according to current guidelines do not seem to carry an increased risk of brain and intracranial vascular changes, thus weakening recommendations for regular brain MRI monitoring.

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.

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.