Biology subjects

Di Liberto, G.

Publications and source records attributed to Di Liberto, G..

10 recordsLinked to original sources

bioRxiv2026

Bridging the neural synchronization to linguistic structures and natural speech comprehension

Speech comprehension involves the inference of abstract information from continuous acoustic signals. Prior work suggests that electrophysiological activity is synchronized with abstract linguistic structures (phrases and sentences) during the processing of isochronous syllable sequences. It is yet unclear whether this prior evidence generalizes to natural speech comprehension, which requires the flexible processing of continuous speech, where syllables and other types of linguistic units are anisochronous. Our magnetoencephalography experiment investigated neural synchronization to acoustic (syllables) and abstract units (phrases and sentences) using continuous speech ranging from artificial isochronous to more natural anisochronous. We find that neural synchronization to phrases and sentences, but not syllables, is resilient to naturalistic anisochrony. This suggests that linguistic structure processing reflects endogenous inferences that are fundamentally distinct from the exogenous processing of syllables driven by speech acoustics. Lateralization and linear regression results extend this functional dissociation as hemispheric asymmetry: stimulus-independent leftward lateralization for linguistic structure processing but stimulus-driven rightward lateralization (or bilaterality) for both syllable and acoustic processing. Our findings provide a more realistic characterization of the flexible neural mechanisms supporting the efficient comprehension of natural speech.

neuroscience↗

bioRxiv2024

Interleukin-33 from oligodendrocytes sustains effector differentiation of tissue-resident CD8+ T cells and is a druggable target in CNS autoimmune disease

In chronic inflammatory disorders of the central nervous system (CNS), tissue-resident self-reactive T cells perpetuate disease. The specific tissue factors governing the persistence and continuous differentiation of these cells remain undefined but could represent attractive therapeutic targets. In a model of chronic CNS autoimmunity, we find that oligodendrocyte-derived interleukin-33 (IL-33), an alarmin, is key for locally regulating the pathogenicity of self-reactive CD8+ T cells. The selective ablation of IL-33 from neo-self-antigen-expressing oligodendrocytes mitigates CNS disease. In this context, fewer self-reactive CD8+ T cells persist in the inflamed CNS, and the remaining cells are largely locked into a stem-like precursor program, failing to form TCF-1low effector progeny. Importantly, interventional IL-33 blockade by locally administered somatic gene therapy reduces T cell infiltrates and improves the disease course. Our study identifies oligodendrocyte-derived IL-33 as a druggable tissue factor regulating the differentiation and survival of self-reactive CD8+ T cell in the inflamed CNS. This finding introduces tissue factors as a novel category of immune targets for treating chronic CNS autoimmune diseases.

immunology↗

bioRxiv2024

Robust assessment of the cortical encoding of word-level expectations using the temporal response function

Speech comprehension involves detecting words and interpreting their meaning according to the preceding semantic context. This process is thought to be underpinned by a predictive neural system that uses that context to anticipate upcoming words. Recent work demonstrated that such a predictive process can be probed from neural signals recorded during ecologically-valid speech listening tasks by using linear lagged models, such as the temporal response function. This is typically done by extracting stimulus features, such as the estimated word-level surprise, and relate such features to the neural signal. While modern large language models (LLM) have led to a substantial leap forward on how word-level features and predictions are modelled, there has been little progress made towards the metrics used for evaluating how well a model is relating stimulus features and neural signals. In fact, previous studies relied on evaluation metrics that were designed for studying continuous univariate sound features, such as the sound envelope, without considering the different requirements of word-level features, which are discrete and sparse in nature. As a result, studies probing lexical prediction mechanisms in ecologically-valid experiments typically exhibit small effect-sizes, severely limiting the type of observations that can be drawn and leaving considerable uncertainty on how exactly our brains build lexical predictions. First, the present study discusses and quantifies these limitations on both simulated and actual electroencephalography signals capturing responses to a speech comprehension task. Second, we tackle the issue by introducing two assessment metrics for the neural encoding of lexical surprise that substantially improve the state-of-the-art. The new metrics were tested on both the simulated and actual electroencephalography datasets, demonstrating effect-sizes over 140% larger than those for the vanilla temporal response function evaluation.

neuroscience↗

bioRxiv2024

KIR3DL1 and Tox identify clonally expanded encephalitogenic neuron-specific CD8+ T cells in autoimmune encephalitis

Autoreactive CD8+ T cells are the principal suspects in autoimmune encephalitis (AIE) with antibodies targeting intracellular neuronal antigens So far, the search for neuron-autoreactive CD8+ T cells has been focused on a few autoantigens and did not yield convincing results. Here, we leveraged natural antigen presentation by hiPSC-derived neurons to look at the global autoreactive CD8+ T cell response, independently of pre-conceived hypothesis of the autoantigens involved in the disease. This unbiased approach allowed for the identification of rare polyclonal neuron-reactive CD8+ T cells in healthy donors, and contrastingly, expanded clonotypes in two patients with anti-Ri AIE. Detailed ex vivo phenotypic characterization of these clonotypes revealed a specific transcriptional program suggestive of a pathogenic potential. In particular, this subset can be identified by the expression of KIR3DL1 and TOX. Strikingly, we could also demonstrate that CD8+ T cells found in the brain of an anti-Ri AIE patient display a similar phenotype associated with cytotoxicity and encephalitogenic features.

immunology↗

bioRxiv2024

Real-time control of a hearing instrument with EEG-based attention decoding

Enhancing speech perception in everyday noisy acoustic environments remains an outstanding challenge for hearing aids. Speech separation technology is improving rapidly, but hearing devices cannot fully exploit this advance without knowing which sound sources the user wants to hear. Even with high-quality source separation, the hearing aid must know which speech streams to enhance and which to suppress. Advances in EEG-based decoding of auditory attention raise the potential of neurosteering, in which a hearing instrument selectively enhances the sound sources that a hearing-impaired listener is focusing their attention on. Here, we present and discuss a real-time brain-computer interface (BCI) system that combines a stimulus-response model based on canonical correlation analysis (CCA) for real-time EEG attention decoding, coupled with a multi-microphone hardware platform enabling low-latency real-time speech separation through spatial beamforming. We provide an overview of the system and its various components, discuss prospects and limitations of the technology, and illustrate its application with case studies of listeners steering acoustic feedback of competing speech streams via real-time attention decoding. A software implementation code of the system is publicly available for further research and explorations.

neuroscience↗

bioRxiv2023

Cortical over-representation of phonetic onsets of ignored speech in hearing impaired individuals

Hearing impairment alters the sound input received by the human auditory system, reducing speech comprehension in noisy multi-talker auditory scenes. Despite such challenges, attentional modulation on the envelope tracking in multi-talker scenarios is comparable between normal hearing (NH) and hearing impaired (HI) participants, with previous research suggesting an over-representation of the speech envelopes in HI individuals (see, e.g., Fuglsang et al. 2020 and Presacco et al. 2019), even though HI participants reported difficulties in performing the task. This result raises an important question: What speech-processing stage could reflect the difficulty in attentional selection, if not envelope tracking? Here, we use scalp electroencephalography (EEG) to test the hypothesis that such difficulties are underpinned by an over-representation of phonological-level information of the ignored speech sounds. To do so, we carried out a re-analysis of an EEG dataset where EEG signals were recorded as HI participants fitted with hearing aids attended to one speaker (target) while ignoring a competing speaker (masker) and spatialised multi-talker background noise. Multivariate temporal response function analyses revealed that EEG signals reflect stronger phonetic-feature encoding for target than masker speech streams. Interestingly, robust EEG encoding of phoneme onsets emerged for both target and masker streams, in contrast with previous work on NH participants and in line with our hypothesis of an over-representation of the masker. Stronger phoneme-onset encoding emerged for the masker, pointing to a possible neural basis for the higher distractibility experienced by HI individuals. Significance StatementThis study investigated the neural underpinnings of attentional selection in multi-talker scenarios in hearing-impaired participants. The impact of attentional selection on phonological encoding was assessed with electroencephalography (EEG) in an immersive multi-talker scenario. EEG signals encoded the phonetic features of the target (attended) speech more strongly than those of the masker (ignored) speech; but interestingly, they encoded the phoneme onsets of both target and masker speech. This suggests that the cortex of hearing-impaired individuals may over-represent higher-level features of ignored speech sounds, which could contribute to their higher distractibility in noisy environments. These findings provide insight into the neural mechanisms underlying speech comprehension in hearing-impaired individuals and could inform the development of novel approaches to improve speech perception in noisy environments.

neuroscience↗

bioRxiv2023

Soluble LIGHT (TNFSF14) activates endothelial cells, thereby priming the first vessel-occlusive events in acute sickle cell disease

In sickle cell disease (SCD), the red blood cells carry a mutated form of hemoglobin (HbS) leading to altered shape and deformability. The mutation causes abnormal hemorheological properties, mechanical hemolysis, and adhesion. The chronic vascular inflammation observed in SCD and hemolysis-related endothelium activation may trigger the vaso-occlusion of blood vessels. The prothrombotic and pro-inflammatory LIGHT/TNFSF14 is a tumor necrosis factor (TNF)- superfamily cytokine implicated in various inflammatory diseases. It is expressed by various immune cells and is considered an actor in T cell-mediated immunity and immune cell recruitment. LIGHT has also been shown to activate endothelial cells (ECs) strongly. LIGHT levels are high in the plasma of SCD patients, and platelets are a major source of its circulating form. We studied a cohort of 82 homozygous adult patients with SCD (n=108 samples) to determine whether LIGHT levels were linked to the clinical state of patients included in the Basal steady state or during an Acute crisis. Soluble LIGHT levels were high in the plasma of SCD patients during acute phases of the disease, particularly during painful occlusive crises. LIGHT levels were associated with Hb levels and inflammatory markers (mainly interferon-{gamma} and tumor necrosis factor-, specifically in acute SCD patients). Our findings confirm that LIGHT is a strong activator of cultured ECs, inducing a type II inflammatory cytokine profile and the expression of adhesion molecules. Using a physiological flow adhesion test on biochips, we showed that the LIGHT-induced activation of ECs led to the adhesion of both sickle platelets (but not their AA counterparts), and in a less extend sickle RBCs to activated HUVECs, potentially constituting the first step in vaso-occlusion. Indeed, the pretreatment of HUVECs with neutralizing polyclonal Abs against LIGHT, but not the non-specific counterpart, showed a reversal of both the inflammation process activated by LIGHT treatment and platelet adhesion to endothelial cells. Soluble LIGHT appears to be a promising therapeutic target for preventing adverse occlusive events in SCD through the blockade of its receptor, to prevent the adhesion of blood cell components to the endothelium. Future studies should consider whether soluble LIGHT contributes to other clinical complications in SCD. HIGHLIGHTSO_LIIn patients with SCD, plasma LIGHT is mainly secreted during acute phases, including VOCs. C_LIO_LIBoth Hb levels and IFN{gamma} levels are correlated with plasma LIGHT with SCD patients in acute phase disease. C_LIO_LIThe LIGHT-induced activation of endothelial cells leads to the flow adherence of both sickle (SS) platelets and red blood cells. C_LIO_LIBoth endothelial priming by LIGHT and platelet adherence are abolished by anti-LIGHT polyclonal Abs. C_LI

cell biology↗

bioRxiv2020

Delta- and theta-band cortical tracking and phase-amplitude coupling to sung speech by infants

The amplitude envelope of speech carries crucial low-frequency acoustic information that assists linguistic decoding at multiple time scales. Neurophysiological signals are known to track the amplitude envelope of adult-directed speech (ADS), particularly in the theta-band. Acoustic analysis of infant-directed speech (IDS) has revealed significantly greater modulation energy than ADS in an amplitude-modulation (AM) band centered on [~]2 Hz. Accordingly, cortical tracking of IDS by delta-band neural signals may be key to language acquisition. Speech also contains acoustic information within its higher-frequency bands (beta, gamma). Adult EEG and MEG studies reveal an oscillatory hierarchy, whereby low-frequency (delta, theta) neural phase dynamics temporally organize the amplitude of high-frequency signals (phase amplitude coupling, PAC). Whilst consensus is growing around the role of PAC in the matured adult brain, its role in the development of speech processing is unexplored. Here, we examined the presence and maturation of low-frequency (<12 Hz) cortical speech tracking in infants by recording EEG longitudinally from 60 participants when aged 4-, 7- and 11-months as they listened to nursery rhymes. After establishing stimulus-related neural signals in delta and theta, cortical tracking at each age was assessed in the delta, theta and alpha [control] bands using a multivariate temporal response function (mTRF) method. Delta-beta, delta-gamma, theta-beta and theta-gamma phase-amplitude coupling (PAC) was also assessed. Significant delta and theta but not alpha tracking was found. Significant PAC was present at all ages, with both delta and theta -driven coupling observed. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/329326v4_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@c7c7feorg.highwire.dtl.DTLVardef@1afa39org.highwire.dtl.DTLVardef@121d616org.highwire.dtl.DTLVardef@6e7c7b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LILongitudinal EEG study in which 4, 7- & 11-month infants listened to nursery rhymes C_LIO_LIWe demonstrate cortical speech tracking via delta & theta neural signals (mTRF) C_LIO_LIPeriodogram (PSD) analysis revealed stimulus related delta & theta PSD peaks C_LIO_LIDelta and theta driven phase amplitude coupling (PAC) was found at all ages C_LIO_LIGamma frequency amplitudes displayed stronger PAC to low frequency phases than beta C_LI

neuroscience↗

bioRxiv2020

Neural representation of linguistic feature hierarchy reflects second-language proficiency

Acquiring a new language requires a simultaneous and gradual learning of multiple levels of linguistic attributes. Here, we investigated how this process changes the neural encoding of natural speech by assessing the encoding of the linguistic feature hierarchy in second-language listeners. Electroencephalography (EEG) signals were recorded during English story listening from native Mandarin speakers with varied English proficiency and from native English speakers. We measured the temporal response functions (TRF) for acoustic, phonemic, phonotactic, and semantic features in individual participants and found a main effect of proficiency on the linguistic encoding. This effect of second-language proficiency was particularly prominent on the neural encoding of phonemes, showing stronger encoding of "new" phonemic contrasts (i.e. English contrasts that do not exist in Mandarin) with increasing proficiency. Overall, we found that linguistic feature representation in nonnative listeners progressively converged to that of native listeners with proficiency, which enabled accurate decoding of language proficiency. This detailed view advances our understanding of the cortical processing of linguistic information in second-language learners and provides an objective measure of language proficiency.

neuroscience↗

bioRxiv2017

Decoding the auditory brain with canonical component analysis

The relation between a stimulus and the brain response that it evokes can shed light on perceptual processes within the brain. It can also be harnessed to control external devices for Brain Computer Interface (BCI) applications. While the classic event-related potential (ERP) is appropriate for isolated stimuli, more sophisticated \"decoding\" strategies are needed to address ongoing stimuli such as speech, music or environmental sounds. Here we describe an approach based on Canonical Correlation Analysis (CCA) that finds the optimal transform to apply to both stimulus and response to reveal correlations between the two. Compared to prior methods based on forward or backward models for stimulus-response mapping, CCA finds significantly higher correlation scores, thus providing increased sensitivity to relatively small effects, and supports classifier schemes that yield higher classification scores. CCA strips the brain response of variance unrelated to the stimulus, and the stimulus representation of variance that does not affect the response, and thus improves our observation of the relation between stimulus and response.

neuroscience↗