Biology subjects

Tassi, L.

Publications and source records attributed to Tassi, L..

7 recordsLinked to original sources

bioRxiv2026

Different spatial profiles of aberrant N-glycans in pediatric and adult MOGHE brain tissue

Mild malformation of cortical development with oligodendroglial hyperplasia in epilepsy (MOGHE) is a recently recognized epilepsy-associated lesion frequently linked to brain-restricted somatic variants in SLC35A2, a gene encoding the Golgi UDP-galactose transporter. Although previous studies demonstrated altered glycosylation in SLC35A2-mutated MOGHE tissue, the spatial relationship between glycosylation defects and histopathological abnormalities remains poorly understood. We applied matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) using formalin-fixed paraffin-embedded brain tissue from six histologically confirmed MOGHE cases (three pediatric and three adult) and three temporal lobe epilepsy with hippocampal sclerosis (TLE-HS). We spatially evaluated N-glycan profiles across diagnostic tissue groups, with particular attention to molecular differences between lesional and perilesional regions and to recurrent abundance trends. All MOGHE cases harboured somatic SLC35A2 variants. Histologically, oligodendroglial hyperplasia and heterotopic neurons were present in all cases, while patchy hypomyelination was restricted to pediatric cases. Unsupervised spatial segmentation, integrated with neuropathological evaluation, revealed marked molecular heterogeneity in pediatric MOGHE. In these cases, lesional and perilesional regions were clearly distinguishable in both white matter (WM) and overlying grey matter (GM) boundaries patterns, whereas adult MOGHE and TLE-HS mainly showed a clearcut separation between WM and GM. Spatial analysis confirmed enrichment of the previously reported aberrant N-glycan species m/z 2094 and, to a lesser extent, m/z 2297 within MOGHE tissue, particularly in pediatric lesional WM. Notably, the distribution of m/z 2094 closely overlapped with areas of hypomyelination. Quantitative trajectory analysis of 151 detected N-glycan ions identified recurrent abundance profiles. Three representative spatial patterns emerged: pediatric lesion-enriched, pediatric perilesion-enriched, and TLE-HS-enriched profiles. Pediatric lesions were characterized by increased abundance of multiantennary glycans lacking terminal galactose residues and reduced abundance of galactosylated biantennary and multiantennary structures, consistent with defective UDP-galactose transport. In contrast, adult lesional and perilesional tissues exhibited largely overlapping glycomic profiles. These findings provide the first spatially resolved evidence that glycosylation abnormalities in SLC35A2-mutated MOGHE are closely associated with lesional pathology, particularly hypomyelination, and are substantially more pronounced in pediatric than adult cases. Spatial glycomics may therefore offer new insights into MOGHE pathophysiology and support the development of targeted therapeutic approaches aimed at correcting galactosylation defects.

neuroscience↗

bioRxiv2026

Frequency modulations of cortical synchronization in human cortex during wakefulness and sleep

Vigilance states are associated with reproducible reconfigurations of large-scale brain dynamics, reflected in changes in inter-areal phase synchronization and cross-frequency phase-amplitude coupling. Here, we characterized how these two forms of phase-based coordination jointly organize across sleep and wakefulness in the human brain at local and regional levels. We analysed phase-locking value (PLV) and phase-amplitude coupling (PAC) from intracranial stereo-electroencephalography (SEEG) recordings in 46 individuals with drug-resistant focal epilepsy, focusing on contacts outside the epileptogenic zone (non-epileptogenic zone, nEZ) to define physiological coupling profiles and comparing them with contacts within the EZ. For each subject, representative epochs of wakefulness, NREM sleep stages N2 and N3, and REM sleep were examined. Across vigilance states, large-scale phase synchronization exhibited distinct spectral fingerprints. Theta and sigma synchronization predominated during NREM sleep, beta synchronization increased during REM sleep, and theta interactions characterized wakefulness. PAC showed complementary state-dependent reorganizations: N3 was characterized by delta-driven modulation of broadband high-frequency activity; N2 additionally exhibited theta- and spindle-phase modulation of beta-gamma amplitudes; REM sleep showed reduced coupling; and wakefulness was marked by theta-to-beta interactions. Within vigilance states, epileptogenic regions displayed increased delta and gamma synchronization and enhanced delta-to-beta/gamma PAC, most prominently during N2 sleep and wakefulness, whereas differences between EZ and nEZ tissue were attenuated during REM sleep. Using partial least squares analysis, we further identified system-specific patterns of PLV-PAC covariation, with prominent involvement of temporal networks during NREM sleep and visual and limbic systems during REM sleep. Together, these findings delineate a frequency-specific, state-dependent architecture linking phase synchronization and phase-amplitude coupling in the human brain and describe how epileptogenic networks deviate from physiological coupling profiles across vigilance states.

neuroscience↗

bioRxiv2026

REM sleep reconfigures large-scale network dynamics: a link to its suppressive role in epilepsy

Converging evidence suggests that human brain activity operates near a critical-like regime in which balanced excitation and inhibition support efficient large-scale communication. The brains proximity to criticality may be dynamically reset across the sleep-wake cycle and altered by epilepsy, leading to aberrant oscillatory dynamics. Building on recent work demonstrating a tripartite interaction between networks synchronization, oscillatory amplitude bistability, and cross-frequency coupling in the human brain that seems to favour epileptic activity, we examined how this interaction, and its underlying large-scale dynamics are modulated across vigilance states. We analyzed overnight recordings from 20 patients with drug-resistant epilepsy undergoing presurgical evaluation and selected overall 20 minutes of continuous, artifact free stereo-electroencephalography (SEEG) spanning REM sleep, NREM stages N2 and N3, and eyes-closed resting wakefulness. Across states, we quantified phase synchronization, phase-amplitude coupling, bistability and their correlation. REM sleep was consistently associated with a reduction of these dynamics relative to NREM sleep and wakefulness. Importantly, the canonical correlation between these measures -- reflecting the strength of the tripartite interaction -- was significantly weaker during REM sleep. These findings indicate that vigilance states modulate this previously identified multiscale interaction in human brain networks and suggest that the reduced epileptogenicity of REM sleep can be associated with a disruption of coordinated synchronization, coupling, and bistable dynamics at the large-scale network level.

neuroscience↗

bioRxiv2022

NLP-based tools for localization of the Epileptogenic Zone in patients with drug-resistant focal epilepsy

BackgroundDrug-resistant focal epilepsy, defined by failure of two antiepileptic drugs, affects about 30% of patients with epilepsy. Epilepsy surgery may represent an alternative options for this population. However, defining the epileptogenic zone to be surgically removed requires highly specialised medical expertise as well as advanced technologies. The aim of this work is building a cost-effective support system based on text, in particular based on the semiological descriptions of the seizures (temporal vs extratemporal lobe; right vs left hemisphere), in order to predict the localization of seizure origin. MethodsAmong a population of 121 surgically treated and seizure-free drug-resistant patients suffering with focal epilepsy, recruited at the Niguarda Hospital in Milan, we extracted a total number of 509 descriptions of seizures. After a data pre-processing phase, we used natural language processing tools to build numerical representations of the seizures descriptions, both using embedding and countbased methods. We then used machine learning models performing a binary classification into right/left and temporal/extra-temporal. ResultsAll predictive models show a better performance when using the representations relying on embedding models respect to count-based ones. Between all the combinations of representations and classifiers, the best performance obtained in terms of F1-score is 84.7% {+/-} 0.6. DiscussionThis preliminary work reached encouraging results considering both localization tasks. The main advantage is that no specific knowledge about epilepsy is used to build the models, rendering our pipeline applicable also in other scenarios. The major limitation lies in the fact that the text is highly specific to the writer.

bioengineering↗

bioRxiv2021

White matter microstructure characterisation in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy. Parameters of microstructural abnormalities derived from diffusion tensor imaging(DTI) have been reported to be helpful in differentiating between Left and Right TLE (L-TLE and R-TLE) but few of them compared L-TLE and R-TLE with a voxelwise approach. In this study, a whole brain tract based spatial statistical analysis was performed on DTI, diffusion kurtosis and NODDI derived parameters of 88 subjects to identify specific white matter patterns of alteration in patient affected by L-TLE and R-TLE with respect to healthy controls. Our findings demonstrated the presence of specific patterns of white matter alterations, with L-TLE more widely affected both in cerebral and cerebellar regions. This result supports the need to consider patients separately, according to the side of their pathology.

neuroscience↗

bioRxiv2020

Automatic segmentation of dentate nuclei for microstructure assessment: example of application to temporal lobe epilepsy patients

Dentate nuclei (DNs) segmentation is helpful for assessing their potential involvement in neurological diseases. Once DNs have been segmented, it becomes possible to investigate whether DNs they are microstructurally affected, through analysis of quantitative MRI parameters, such as the ones derived from diffusion weighted imaging (DWI). This study, therefore, aimed to develop a fully automated segmentation method using the non-DWI (b0) images from a DWI dataset to obtain DN masks inherently registered with parameter maps. Three different automatic methods were applied to healthy subjects in order to segment the DNs: registration to SUIT (a spatially unbiased atlas template of the cerebellum and brainstem), OPAL (Optimized Patch Match for Label fusion) and CNN (Convolutional Neural Network). DNs manual segmentation was considered the gold standard. Results show that the segmentation obtained with SUIT has an average Dice Similarity Coefficient (DSC) of 0.4907{+/-}0.0793 between the automatic SUIT masks and the gold standard. A comparison with manual masks was also performed for OPAL (DSC = 0.7624 {+/-} 0.1786) and CNN (DSC = 0.8658 {+/-} 0.0255), showing a better performance when using CNN. OPAL and CNN were optimised on heathy subjects data with high spatial resolution from the Human Connectome Project. The three methods were further used to segment the DNs of a subset of subjects affected by Temporal Lobe Epilepsy (TLE). This subset was derived from a 3T MRI research study which included DWI data acquired with a coarser resolution. In TLE dataset, SUIT performed similarly to using the HCP dataset, with a DSC = 0.4145 {+/-} 0.1023. Using TLE data, OPAL performed worse than using HCP data: after changing the probability threshold the DSC was 0.4522 {+/-} 0.1178. CNN was able to extract the DNs using the TLE data without need for retraining and with a good DSC = 0.7368 {+/-} 0.0799. Statistical comparison of quantitative parameters derived from DWI analysis, as well as volumes of each DN, revealed altered and lateralised changes in TLE patients compared to healthy controls. The proposed CNN is therefore a viable option for accurate extraction of DNs from b0 images of DWI data with different resolutions and acquired at different sites.

bioengineering↗

bioRxiv2019

Stereotactic electroencephalography in humans reveals multisensory signal in early visual and auditory cortices

Unequivocally demonstrating the presence of multisensory signals at the earliest stages of cortical processing remains challenging in humans. In our study, we relied on the unique spatio-temporal resolution provided by intracranial stereotactic electroencephalographic (SEEG) recordings in patients with drug-resistant epilepsy to characterize the signal extracted from early visual (calcarine and pericalcarine) and auditory (Heschls gyrus and planum temporale) regions during a simple audio-visual oddball task. We provide evidences that both cross-modal responses (visual responses in auditory cortex or the reverse) and multisensory processing (alteration of the unimodal responses during bimodal stimulation) can be observed in intracranial event-related potentials (iERPs) and in power modulations of oscillatory activity at different temporal scales within the first 150 ms after stimulus onset. The temporal profiles of the iERPs are compatible with the hypothesis that MSI occurs by means of direct pathways linking early visual and auditory regions. Our data indicate, moreover, that MSI mainly relies on modulations of the low-frequency bands (foremost the theta band in the auditory cortex and the alpha band in the visual cortex), suggesting the involvement of feedback pathways between the two sensory regions. Remarkably, we also observed high-gamma power modulations by sounds in the early visual cortex, thus suggesting the presence of neuronal populations involved in auditory processing in the calcarine and pericalcarine region in humans.

neuroscience↗