Biology subjects

Mariani, B.

Publications and source records attributed to Mariani, B..

7 recordsLinked to original sources

bioRxiv2026

Towards a scalable effective connectivity estimation in fMRI

Characterizing directed connections between brain regions is fundamental for understanding the brains network organization and how it supports cognitive processes. However, a reliable methodology allowing assessment of effective connectivity (EC) at the whole-brain level and across high-resolution parcellations has remained elusive. This limitation reflects a trade-off between model detail and scalability. Mechanistic approaches such as Dynamic Causal Modeling (DCM) provide a principled description of directed interactions but become impractical for large parcellations, whereas scalable methods based on linear-system inversion often fail to reliably recover key features of the underlying effective connectivity. Here, using data from the Human Connectome Project S1200 release, we show that the multivariate Ornstein-Uhlenbeck (mOU) approach for EC estimation can be adapted to yield EC estimates that are in broad agreement with those of an advanced DCM, at least when the spatial variability of the hemodynamic response falls within the physiological range characteristic of the healthy adult brain. Furthermore, thanks to its low computational cost, mOU can be easily scaled up to large neuroimaging cohorts and high-resolution parcellations. High-resolution, mOU-based EC outperforms functional connectivity for single-subject connectome fingerprinting. In addition, it enables a high-resolution characterization of the brains hierarchical organization and modular architecture by identifying directed interactions within and between communities and revealing driver and receiver regions. Overall, our methodology provides a reliable and scalable EC estimation pipeline of wide applicability to cognitive and network neuroscience.

neuroscience↗

bioRxiv2026

Brain-tuning near criticality in newborns by prenatal experience with language

Language development starts early, possibly even in the womb. Recent results suggest that newborns neural responses to speech in the prenatally heard language are already different from those to unfamiliar languages. However, the neural dynamics of how these differential responses emerge remains little understood. Here, we hypothesize that they are supported by a functional tuning to criticality--a state that maximizes information transmission, dynamic range, and flexibility--, induced in newborns by the prenatally experienced language. To test this hypothesis, we study resting-state brain activity before and after stimulation with naturally spoken sentences in the prenatal language, French, in a rhythmically similar unfamiliar language, Spanish, as well as in a rhythmically different unfamiliar language, English. We show that the native language elicits brain tuning near criticality, balancing network activity and enhancing temporal correlations. Importantly, we find that the network state is not sensitive to the rhythmically different language, and only partially responds to the rhythmically similar language. These results indicate a stimulus-driven tuning to criticality in newborns, a potential foundation for early neuroplasticity, which relies on prenatal experience and may respond to early functional and developmental needs.

neuroscience↗

bioRxiv2025

The somatosensory barrel cortex controls the spindlethalamocortical oscillation by frequency locking

The sleep spindle is a characteristic oscillation typically observed in NREM sleep and anesthesia. It is generated by a closed-loop thalamocortical circuit that is allegedly contributing to thalamocortical gating, sensory processing and memory consolidation. Yet, the circuit intricacy in terms of electrophysiological neuronal properties and connectivity has so far contributed to hinder a clear understanding of its regulation and function. In this study, we experimentally demonstrate that, when driven by the somatosensory cortex, the spindle circuit behaves as a macroscopic single-frequency self-sustained oscillator. We frequency-modulated cortical inputs to the thalamocortical spindle circuit by periodic microstimulation of the barrel cortex in the anesthetized rat. Cortical spindles exhibited synchronization by frequency locking and not resonance, displaying a characteristic Arnold tongue, a hallmark of the self-sustained oscillator. With a rate model of the barrel cortex-thalamus circuit reproducing the oscillator behavior we show that frequency-locking can govern synchronization under whisking. Significance statementTemporal coordination across neurons (neural synchronization) is believed to be a fundamental mechanism underlying brain information processing. Neural synchornization generates oscillatory signals such as waxing and waning, approximately 10 Hz oscillations occurring during sleep and anaesthesia and known as brain spindles. Spindles are generated by a closed-loop circuit between thalamus and cortex but their function remains unknown. We demonstrate that, similarly to a methronome that adjusts its frequency to the one of an external forcing oscillator, the spindle circuit is controlled by the sensory cortex according to a frequency-locking mechanism. We suggest that frequency-locking within the thalmocortical circuitry represents a flexible frequency-adjustable mechanism tuning the processing of sensory inputs by neural synchronization.

neuroscience↗

bioRxiv2025

Whisker stimulation reinforces a resting-state network in the barrel cortex: nested oscillations and avalanches

The cerebral cortex operates in a state of restless activity, even in the absence of external stimuli. Collective neuronal activities, such as neural avalanches and synchronized oscillations, are also found under rest conditions, and these features have been suggested to support sensory processing, brain readiness for rapid responses, and computational efficiency. The rat barrel cortex and thalamus circuit, with its somatotopic organization for processing sensory inputs from the whiskers, provides a powerful system to explore such interplay. To characterize these resting state circuits, we perform simultaneous multi-electrode recordings in rats barrel cortex and thalamus. During spontaneous activity, oscillations with frequencies centered around 11 Hz are detected concomitantly with slow oscillations below 4 Hz, as well as power-law distributed avalanches. The phase of the lower-frequency oscillation appears to modulate the higher-frequency amplitude, and it has a role in gating avalanche occurrences. We then record neural activity during controlled whisker movements and observe that the 11 Hz barrel circuit active at rest is indeed the one involved in response to whisker stimulation. We finally show how a thalamic-driven firing-rate model can describe the entire phenomenology observed at resting state and predict the response of the barrel cortex to controlled whisker movement, suggesting that the same intrinsic dynamics underlying resting-state activity also shape sensory responses. Author SummaryThe brain is active even in the absence of external stimuli, generating complex patterns of activity that are thought to prepare it for processing incoming information. Two prominent features of this spontaneous activity are rhythmic oscillations and neuronal avalanches--bursts of activity that span a wide range of sizes and durations. However, how these patterns relate to actual sensory processing remains unclear. In this study, we investigated the rat barrel cortex, a well-characterized system for processing tactile information from whiskers. By combining electrophysiological recordings and computational modeling, we found that specific transient oscillations centered around 11 Hz are present during rest and become significantly stronger when the whiskers are stimulated. At the same time, spontaneous activity displays a rich dynamical regime with neuronal avalanches, whose timing is modulated by slower brain rhythms. Importantly, we show that a simple thalamus-driven computational model can reproduce these observations. We thus provide a minimal yet powerful model that suggests that the same rich, intrinsic dynamics underlying resting-state activity also shape sensory responses. Our results support the idea that spontaneous brain activity is not idle, but instead reflects an organized dynamical regime that facilitates efficient processing of sensory inputs.

neuroscience↗

bioRxiv2023

Prenatal experience with language shapes the brain

Human infants acquire language with striking ease compared to adults, but the neural basis of their remarkable brain plasticity for language remains little understood. Applying a scaling analysis of neural oscillations for the first time to address this question, we show that newborns electrophysiological activity exhibits increased long-range temporal correlations after stimulation with speech, particularly in the prenatally heard language, indicating the early emergence of brain specialization for the native language.

neuroscience↗

bioRxiv2022

Criticality and network structure drive emergent oscillations in a stochastic whole-brain model

Understanding the relation between the structure of brain networks and its functions is a fundamental open question. Simple models of neural activity based on real anatomical networks have proven to be effective in describing features of whole-brain spontaneous activity when tuned at their critical point. In this work, we show that indeed structural networks are a crucial ingredient in the emergence of collective oscillations in a whole-brain stochastic model at criticality. We study analytically a stochastic Greenberg-Hastings cellular automaton in the mean-field limit, showing that it undergoes an abrupt phase transition with a bistable region. In particular, no global oscillations emerge in this limit. Then, we show that by introducing a network structure in the homeostatic normalization regime, the bistability may be disrupted, and the transition may become smooth. Concomitantly, through an interplay between the network topology and weights, a large peak in the power spectrum appears around the transition point, signaling the emergence of collective oscillations. Hence, both the structure of brain networks and criticality are fundamental in driving the collective responses of whole-brain stochastic models.

neuroscience↗

bioRxiv2021

Beyond resting state neuronal avalanches in the somatosensory barrel cortex

Since its first experimental signatures, the so called critical brain hypothesis has been extensively studied. Yet, its actual foundations remain elusive. According to a widely accepted teleological reasoning, the brain would be poised to a critical state to optimize the mapping of the noisy and ever changing real-world inputs, thus suggesting that primary sensory cortical areas should be critical. We investigated whether a single barrel column of the somatosensory cortex of the anesthetized rat displays a critical behavior. Neuronal avalanches were recorded across all cortical layers in terms of both spikes and population local field potentials, and their behavior during spontaneous activity compared to the one evoked by a controlled single whisker deflection. By applying a maximum likelihood statistical method based on timeseries undersampling to fit the avalanches distributions, we show that neuronal avalanches are power law distributed for both spikes and local field potentials during spontaneous activity, with exponents that are spread along a scaling line. Instead, after the tactile stimulus, activity switches to an across-layers synchronization mode that appears to dominate during cortical representation of the single sensory input.

neuroscience↗