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Pietrini, P.

Publications and source records attributed to Pietrini, P..

18 recordsLinked to original sources

Lack of vision shifts occipital dynamics toward a frontal-like regime and enhances top-down connectivity

The human occipital cortex is robustly repurposed for non-visual cognition after blindness, yet it remains unknown whether this functional reassignment is accompanied by a fundamental retuning of its intrinsic neural dynamics. Here, we recorded the electroencephalographic (EEG) responses to transcranial magnetic stimulation (TMS) of frontal and occipital areas to causally probe local cortical reactivity and large-scale effective connectivity in 16 blind individuals and 16 sighted controls. Direct perturbation of the occipital cortex revealed a profound shift in its intrinsic operating regime: compared with sighted participants, blind individuals exhibited faster, lower-amplitude TMS-evoked potentials that closely resembled the electrophysiological signature of the frontal cortex, which turned out to be comparable in the two populations. At the network level, source analyses further showed a specific enhancement of frontal-to-occipital effective connectivity, whereas occipital-to-frontal propagation remained unchanged. Importantly, among blind participants, faster occipital dynamics were associated with stronger frontal-driven occipital recruitment, directly linking local temporal retuning to enhanced top-down network influence. Together, these findings indicate that blindness reshapes both the intrinsic dynamics and large-scale integration of the occipital cortex. We propose that successful functional reassignment of the occipital cortex requires not only changes in cortical connectivity but also a tuning of the temporal operating regime toward a faster dynamics, enabling its embedding into distributed cognitive networks and providing a mechanistic framework for the functional reassignment of deafferented cortex.

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The semantics of dreams

Dreams are universal yet deeply personal experiences. While memory and personal concerns influence dream content, the impact of other individual, generalizable traits remains poorly understood. To address this gap, we built a multimodal dataset including dream and wakefulness reports, alongside demographic, psychometric, cognitive, and sleep-related measures in a large adult cohort. Natural language processing characterized the semantic features that quantitatively distinguish dream from wakefulness reports, with this distinction significantly modulated by individual-specific factors. Longitudinal and cross-sample analyses further demonstrated that major external events, such as the COVID-19 pandemic, affect dream content, leaving lasting traces. Overall, the findings highlight a dynamic interplay between stable individual traits and external events in shaping dream experiences, offering novel insights into the cognitive and emotional architecture of dreaming.

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Abstract, modality-specific and experience-dependent coding of affect in the human brain

Emotion and perception are tightly intertwined, as affective experiences often arise from the appraisal of sensory information. Nonetheless, whether the brain encodes emotional instances using a sensory-specific code or in a more abstract manner is unclear. Here, we answer this question by measuring the association between emotion ratings collected during a unisensory or multisensory presentation of a full-length movie and brain activity recorded in typically-developed, congenitally blind and congenitally deaf participants. Emotional instances are encoded in a vast network encompassing sensory, prefrontal, and temporal cortices. Within this network, the ventromedial prefrontal cortex stores a categorical representation of emotion independent of modality and experience, and the posterior superior temporal cortex maps valence using an abstract code. Sensory experience more than modality impacts how the brain organizes emotional information outside supramodal regions, suggesting the existence of a scaffold for the representation of emotional states where sensory inputs during development shape its functioning.

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Brain structure reflects empathy and psychopathy in incarcerated males

BackgroundReduced empathy is a hallmark of individuals with high (i.e., clinical) levels of psychopathy, who are overrepresented among incarcerated men. Yet, a comprehensive, well-powered mapping of cortical structure in relation to empathy and psychopathy is still lacking. MethodsIn 804 incarcerated adult men, we administered the Perspective Taking (IRI-PT) and Empathic Concern (IRI-EC) subscales of the Interpersonal Reactivity Index, the Psychopathy Checklist-Revised (PCL-R; with Interpersonal/Affective [F1] and Lifestyle/Antisocial [F2] factors), and T1-weighted MRI to quantify cortical thickness (CT), surface area (SA), and structural-covariance gradients. ResultsPCL-R F1 was uniquely negatively related to IRI-EC, while PCL-R F2 was uniquely negatively related to IRI-PT. Cortical structure was not related to the IRI subscales. In contrast, CT was related to PCL-R F1 (mostly positively), SA was related to both PCL-R factors (only positively), and both cortical indices demonstrated out-of-sample predictive utility for PCL-R F1. Compared to low-psychopathy men, high-psychopathy men had uniquely lower IRI-EC scores and increased SA (but not CT); across the cortex, effect sizes were largest in the paralimbic class and somatomotor network, while meta-analytic task-based activations further highlighted spatial overlap with (social-)affective/sensory regions. Finally, the total sample revealed canonical anterior-posterior structural-covariance gradients. In high-psychopathy men, the gradient of CT (but not SA) was globally compressed. ConclusionsHigh-psychopathy men had reduced empathic concern, increased SA, and a compressed macroscale organization of CT, suggesting specific co-occurring alterations in empathy and cortical structure. Future work should build upon these novel insights in both the general and incarcerated populations to inform the treatment of psychopathy.

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Distinct cortical responses to Auditory Statistics: pre-attentive discriminations based on local and global representations

The auditory system relies on both local and summary representations; acoustic local features exceeding system constraints are compacted into a set of summary statistics. Such compression is pivotal for sound-object recognition. Here, we assessed whether computations subtending local and statistical representations of sounds could be distinguished at the neural level. A computational auditory model was employed to extract auditory statistics from natural sound textures (i.e., fire, rain) and to generate synthetic exemplars where local and statistical properties were controlled. Twenty-four human participants were passively exposed to auditory streams while the EEG was recorded. Each stream could consist of short, medium, or long sounds to vary the amount of acoustic information. Short and long sounds were expected to engage local or summary statistics representations, respectively. Data revealed a clear dissociation. Compared to summary-based ones, auditory-evoked responses based on local information were selectively greater in magnitude in short sounds. Opposite patterns emerged for longer sounds. Neural oscillations revealed that local features and summary statistics rely on neural activity occurring at different temporal scales, faster (beta) or slower (theta-alpha). These dissociations emerged automatically without explicit engagement in a discrimination task. Overall, this study demonstrates that the auditory system developed distinct coding mechanisms to discriminate changes in the acoustic environment based on fine structure and summary representations. SIGNIFICANCE STATEMENTPrior to this study, it was unknown whether we could measure auditory discrimination based on local temporal features or spectrotemporal statistics properties of sounds from brain responses. Results show that the two auditory modes of sound discrimination (local and summary statistics) are automatically attuned to the temporal resolution (high or low) at which a change has occurred. In line with the temporal resolutions of auditory statistics, faster or slower neural oscillations (temporal scales) code sound changes based on local or summary representations. These findings expand our knowledge of some fundamental mechanisms underlying the function of the auditory system.

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A modality independent proto-organization of human multisensory areas

The processing of multisensory information is based upon the capacity of brain regions, such as the superior temporal cortex, to combine information across modalities. However, it is still unclear whether the representation of coherent auditory and visual events does require any prior audiovisual experience to develop and function. In three fMRI experiments, intersubject correlation analysis measured brain synchronization during the presentation of an audiovisual, audio-only or video-only versions of the same narrative in distinct groups of sensory-deprived (congenitally blind and deaf) and typically-developed individuals. The superior temporal cortex synchronized across auditory and visual conditions, even in sensory-deprived individuals who lack any audiovisual experience. This synchronization was primarily mediated by low-level perceptual features and relied on a similar modality-independent topographical organization of temporal dynamics. The human superior temporal cortex is naturally endowed with a functional scaffolding to yield a common representation across multisensory events.

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Auditory statistics development does not rely on vision, but the processing of sound local features is hampered by late-onset sight loss

The human auditory system relies on both detailed and summarized representations to recognize different sounds. As local features can exceed the storage capacity, average statistics are computed over time to generate more compact representations at the expense of temporal details availability. This study aimed to identify whether these fundamental sound analyses develop and function exclusively under the influence of the auditory system or interact with other modalities, such as vision. We employed a validated computational synthesis approach allowing to control directly statistical properties embedded in sounds. To address whether the two modes of auditory representation (local features processing and statistical averaging) are influenced by the availability of visual input in different phases of development, we tested samples of sighted controls (SC), congenitally blind (CB), and late-onset (> 10 years of age) blind (LB) individuals in two separate experiments which uncovered auditory statistics computations from behavioral performances. In experiment 1, performance relied on the availability of local features at specific time points; in experiment 2, performance benefited from computing average statistics over longer durations. As expected, when sound duration increased, detailed representation gave way to summary statistics in SC. In both experiments, the sample of CB individuals displayed a remarkably similar performance revealing that both local and global auditory processes are not altered by blindness since birth. Conversely, LB individuals performed poorly compared to the other groups when relying on local features, with no impact on statistical averaging. The dampening in the performance was not associated with the onset and duration of visual deprivation. Results provide clear evidence that vision is not necessary for the development of the auditory computations tested here. Remarkably, a functional interplay between acoustic details processing and vision emerges at later developmental phases. Findings are consistent with a model in which the efficiency of local auditory processing is vulnerable in case sight becomes unavailable. Ultimately results are in favor of a shared computational framework for auditory and visual processing of local features, which emerges in late development.

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Local increases in sleep-like activity predict the occurrence of emotion suppression failures

Emotion self-regulation relies both on cognitive and behavioral strategies implemented to modulate the subjective experience and/or the behavioral expression of a given emotion. While it is known that a network encompassing fronto-cingulate and parietal brain areas is engaged during successful emotion regulation, the functional mechanisms underlying failures in emotion suppression are still unclear. In order to investigate this issue, we analyzed video and high-density EEG recordings of nineteen healthy adult subjects during an emotion suppression (ES) and a free expression (FE) task performed on two consecutive days. Changes in facial expression during ES, but not FE, were preceded by local increases in sleep-like activity (1-4Hz) in in brain areas responsible for emotional suppression, including bilateral anterior insula and anterior cingulate cortex, and in right middle/inferior frontal gyrus (p<0.05, corrected). Moreover, shorter sleep duration the night prior to the ES experiment correlated with the number of behavioral errors (p=0.01) and tended to be associated with higher frontal sleep-like activity during emotion suppression failures (p=0.05). These results indicate that local sleep-like activity may represent the cause of emotion suppression failures in humans, and may offer a functional explanation for previous observations linking lack of sleep, changes in frontal activity and emotional dysregulation.

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Intersubject brain connectivity dynamics encode the stream of affect at multiple timescales

In everyday life the stream of affect results from the interaction between past experiences, expectations, and the unfolding of events. How the brain represents the relationship between time and affect has been hardly explored, as it requires modeling the complexity of everyday life in the laboratory setting. Movies condense into hours a multitude of emotional responses, synchronized across subjects and characterized by temporal dynamics alike real-world experiences. Here, we use time-varying intersubject brain synchronization and real-time behavioral reports to test whether connectivity dynamics track changes in affect during movie watching. Results show that polarity and intensity of experiences relate to connectivity of the default mode and control networks and converge in the right temporo-parietal cortex. We validate these results in two experiments including four independent samples, two movies, and alternative analysis workflows. Lastly, we reveal chronotopic connectivity maps within temporo-parietal and prefrontal cortex, where adjacent areas preferentially encode affect at specific timescales.

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Auditory features modelling demonstrates sound envelope representation in striate cortex

The striate cortex is no longer considered exclusively visual in its function. Proofs that its activity is modulated by acoustic inputs have accrued. By employing category-based and feature modeling approaches, here we characterized V1 activity (in absence of retinal input) during the processing of natural and synthetically derived sounds. First, we showed that distinct sound categories could be dissociated by the analysis of V1 multivoxel response patterns. Hence, we assessed whether a hallmark of sound neural representations is mapped in V1. In each sound category, we modeled sound envelopes and assessed whether these were represented at the single-voxel level in the striate cortex and, as a control, in the temporal cortex. The hierarchical organization of sound categories allowed to exert control over dimensions that could spuriously lead to sound envelope V1 mapping. Variations of sound amplitude over time were successfully decoded in V1 regardless of the category class. Results confirm that the human striate cortex receives acoustic category-based input and demonstrate that V1 is a genuine locus of sound envelope representation.

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Shape coding in occipito-temporal cortex relies on object silhouette, curvature and medial-axis

Object recognition relies on different transformations of the retinal input, carried out by the visual system, that range from local contrast to object shape and category. While some of those transformations are thought to occur at specific stages of the visual hierarchy, the features they represent are correlated (e.g., object shape and identity) and selectivity for the same feature overlaps in many brain regions. This may be explained either by collinearity across representations, or may instead reflect the coding of multiple dimensions by the same cortical population. Moreover, orthogonal and shared components may differently impact on distinctive stages of the visual hierarchy. We recorded functional MRI (fMRI) activity while participants passively attended to object images and employed a statistical approach that partitioned orthogonal and shared object representations to reveal their relative impact on brain processing. Orthogonal shape representations (silhouette, curvature and medial-axis) independently explained distinct and overlapping clusters of selectivity in occitotemporal (OTC) and parietal cortex. Moreover, we show that the relevance of shared representations linearly increases moving from posterior to anterior regions. These results indicate that the visual cortex encodes shared relations between different features in a topographic fashion and that object shape is encoded along different dimensions, each representing orthogonal features. New & NoteworthyThere are several possible ways of characterizing the shape of an object. Which shape description better describes our brain responses while we passively perceive objects? Here, we employed three competing shape models to explain brain representations when viewing real objects. We found that object shape is encoded in a multi-dimensional fashion and thus defined by the interaction of multiple features.

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Integrity of corpus callosum is essential for the cross-hemispheric propagation of sleep slow waves: a high-density EEG study in split-brain patients

The slow waves of NREM-sleep (0.5-4Hz) reflect experience-dependent plasticity and play a direct role in the restorative functions of sleep. Importantly, slow waves behave as traveling waves and their propagation is assumed to reflect the structural properties of white matter connections. Based on this assumption, the corpus callosum (CC) may represent the main responsible for cross-hemispheric slow wave propagation. To verify this hypothesis, here we studied a group of patients who underwent total callosotomy due to drug-resistant epilepsy. Overnight high-density (hd)-EEG recordings (256 electrodes) were performed in five totally callosotomized in-patients (CP; 40-53y, 2F), in three control non-callosotomized neurological in-patients (NP; 44-66y, 2F, 1M epileptic), and in an additional sample of 24 healthy adult subjects (HS; 20-47y, 13F). Data were inspected to select NREM-sleep epochs and artefactual or non-physiological activity was rejected. Slow waves were detected using an automated algorithm and their properties and propagation patterns were computed. For each slow wave parameter and for each patient, the relative z-score and the corresponding p-value were calculated with respect to the distribution represented by the HS-group. Group differences were considered significant only when a Bonferroni corrected P < 0.05 was observed in all the CP and in none of the NP. A regression-based adjustment was used to exclude potential confounding effects of age. Slow wave density, amplitude, slope and propagation speed did not differ across CP and HS. In all CP slow waves displayed a significantly reduced probability of cross-hemispheric propagation and a stronger inter-hemispheric asymmetry. Moreover, we found that the incidence of large slow waves tended to differ across hemispheres within individual NREM epochs, with a relative predominance of the right over the left hemisphere in both CP and HS. The absolute magnitude of this inter-hemispheric difference was significantly greater in CP relative to HS. This effect did not depend on differences in slow wave origin within each hemisphere across groups. Present results indicate that the integrity of the CC is essential for the cross-hemispheric traveling of sleep slow waves, supporting the assumption of a direct relationship between white matter structural integrity and cross-hemispheric slow wave propagation. Our findings also imply a prominent role of cortico-cortical connections, rather than cortico-subcortico-cortical loops, in slow wave cross-hemispheric synchronization. Finally, this data indicate that the lack of the CC does not lead to differences in sleep depth, in terms of slow wave generation/origin, across brain hemispheres.

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Visual imagery and visual perception induce similar changes in occipital slow waves of sleep

Previous studies have shown that regional slow wave activity (SWA) during NREM-sleep is modulated by prior experience and learning. While this effect has been convincingly demonstrated for the sensorimotor domain, attempts to extend these findings to the visual system have provided mixed results. Here we asked whether depriving subjects of external visual stimuli during daytime would lead to regional changes in slow waves during sleep and whether the degree of internal visual stimulation (spontaneous imagery) would influence such changes. In two 8h-long sessions spaced one-week apart, twelve healthy volunteers either were blindfolded while listening to audiobooks or watched movies (control condition), after which their sleep was recorded with high-density EEG. We found that during NREM-sleep the number of small, local slow waves in the occipital cortex decreased after listening with blindfolding relative to movie watching in a way that depended on the degree of visual imagery subjects reported during blindfolding: subjects with low visual imagery showed a significant reduction of occipital sleep slow waves, while those who reported a high degree of visual imagery did not. We also found a positive relationship between the reliance on visual imagery during blindfolding and audiobook listening and the degree of correlation in sleep SWA between visual areas and language-related areas. These preliminary results demonstrate that short-term alterations in visual experience may trigger slow wave changes in cortical visual areas. Furthermore, they suggest that plasticity-related EEG changes during sleep may reflect externally induced ( bottom-up) visual experiences, as well as internally generated ( top-down) processes.

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Emotionotopy: Gradients encode emotion dimensions in right temporo-parietal territories

Humans use emotions to decipher complex cascades of internal events. However, which mechanisms link descriptions of affective states to brain activity is unclear, with evidence supporting either local or distributed processing. A biologically favorable alternative is provided by the notion of gradient, which postulates the isomorphism between functional representations of stimulus features and cortical distance. Here, we use fMRI activity evoked by an emotionally charged movie and continuous ratings of the perceived emotion intensity to reveal the topographic organization of affective states. Results show that three orthogonal and spatially overlapping gradients encode the polarity, complexity and intensity of emotional experiences in right temporo-parietal territories. The spatial arrangement of these gradients allows the brain to map a variety of affective states within a single patch of cortex. As this organization resembles how sensory regions represent psychophysical properties (e.g., retinotopy), we propose emotionotopy as a principle of emotion coding.

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EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions

Functional connectivity (FC) estimation methods are extensively used in neuroimaging to measure brain inter-regional interactions. The weighted Phase Lag Index (wPLI) and the weighted Symbolic Mutual Information (wSMI) represent relatively robust exemplars of spectral (wPLI) and information-theoretic (wSMI) connectivity measures that recently gained increased popularity due to their relative immunity to volume conduction. wPLI and wSMI are posited to have different sensitivity to linear and nonlinear relationships between neural sources, but their performance has never been directly compared. Here, using simulated high-density (hd-)EEG data, we evaluated the accuracy of these two metrics for detecting distinct types of regional interdependencies characterised by different combinations of linear and nonlinear components. Our results demonstrate that while wPLI performs generally better at detecting functional couplings presenting a mixture of linear and nonlinear interdependencies, only wSMI is able to detect exclusively nonlinear interaction dynamics. To evaluate the potential impact of these differences on real experimental data, we computed wPLI and wSMI connectivity in hd-EEG recordings of 12 healthy adults obtained in wakefulness and deep (N3-)sleep. While both wPLI and wSMI revealed a relative decrease in alpha-connectivity during sleep relative to wakefulness, only wSMI identified a relative increase in theta-connectivity, while wPLI detected an increase in delta-connectivity, likely reflecting the occurrence of traveling slow waves. Overall, our findings indicate that wPLI and wSMI provide distinct but complementary information about functional brain connectivity, and that their combined use could advance our knowledge of neural interactions underlying different behavioural states.

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Common spatiotemporal processing of visual features shapes object representation

Biological vision relies on representations of the physical world at different levels of complexity. Relevant features span from simple low-level properties, as contrast and spatial frequencies, to object-based attributes, as shape and category. However, how these features are integrated into coherent percepts is still debated. Moreover, these dimensions often share common biases: for instance, stimuli from the same category (e.g., tools) may have similar shapes. Here, using magnetoencephalography, we revealed the temporal dynamics of feature processing in human subjects attending to pictures of items pertaining to different semantic categories. By employing Relative Weights Analysis, we mitigated collinearity between model-based descriptions of stimuli and showed that low-level properties (contrast and spatial frequencies), shape (medial-axis) and category are represented within the same spatial locations early in time: 100-150ms after stimulus onset. This fast and overlapping processing may result from independent parallel computations, with categorical representation emerging later than the onset of low-level feature processing, yet before shape coding. Categorical information is represented both before and after shape also suggesting a role for this feature in the refinement of categorical matching.

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Regional low-frequency oscillations in human rapid-eye movement sleep

Although the EEG slow wave of sleep is typically considered to be a hallmark of Non Rapid Eye Movement (NREM) sleep, recent work in mice has shown that slow waves can also occur in REM sleep. Here we investigated the presence and cortical distribution of low-frequency (1-4 Hz) oscillations in human REM sleep by analyzing high-density EEG sleep recordings obtained in 28 healthy subjects. We identified two clusters of low-frequency oscillations with distinctive properties: 1) a fronto-central cluster characterized by [~]2.5-3.0 Hz, relatively large, notched delta waves (so-called sawtooth waves) that tended to occur in bursts, were associated with increased gamma activity and rapid eye movements, and upon source modeling, displayed an occipito-temporal and a fronto-central component; and 2) a medial occipital cluster characterized by more isolated, slower (<2 Hz) and smaller waves that were not associated with rapid eye movements, displayed a negative correlation with gamma activity and were also found in NREM sleep. Thus, low-frequency oscillations are an integral part of REM sleep in humans, and the two identified subtypes (sawtooth and medial-occipital slow waves) may reflect distinct generation mechanisms and functional roles. Sawtooth waves, which are exclusive to REM sleep, share many characteristics with ponto-geniculo-occipital (PGO) waves described in animals and may represent the human equivalent or a closely related event while medio-occipital slow waves appear similar to NREM sleep slow waves.

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Foreground Enhancement and Background Suppression in Human Early Visual System During Passive Perception of Natural Images

One of the major challenges in visual neuroscience is represented by foreground-background segmentation. Data from nonhuman primates show that segmentation leads to two distinct, but associated processes: the enhancement of neural activity during figure processing (i.e., foreground enhancement) and the suppression of background-related activity (i.e., background suppression). To study foreground-background segmentation in ecological conditions, we introduce a novel method based on parametric modulation of low-level image properties followed by application of simple computational image-processing models. By correlating the outcome of this procedure with human fMRI activity measured during passive viewing of 334 natural images, we reconstruct easily interpretable \"neural images\" from seven visual areas: V1, V2, V3, V3A, V3B, V4 and LOC. Results show evidence of foreground enhancement for all tested regions, while background suppression specifically occurs in V4 and LOC. \"Neural images\" reconstructed from V4 and LOC revealed a preserved spatial resolution of foreground textures, indicating a richer representation of the salient part of natural images, rather than a simplistic model of object shape. Our results indicate that scene segmentation is an automatic process that occurs during natural viewing, even when individuals are not required to perform any particular task.

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