Biology subjects

Lombardi, F.

Publications and source records attributed to Lombardi, F..

7 recordsLinked to original sources

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↗

bioRxiv2026

The scaling behavior of hippocampal activity in sleep/rest predicts spatial memory performance

In the hippocampus, reactivation of spatial memories during sleep enhances consolidation and recall. However, network dynamics may independently influence memory retention. We applied the Phenomenological Renormalization Group to CA1 neuronal activity in rats during sleep/rest epochs surrounding a spatial learning task. The scaling exponent of activity variance (), assessed either before or after learning, predicted subsequent recall performance independently of reactivation. The prediction model was transferable across subjects, suggesting that it is a robust biomarker of learning ability. Single-cell features, such as burst propensity and intrinsic timescales, correlated with and memory, predicted retention even when controlling for these factors. Our results identified a link between scale-free circuit dynamics and memory stabilization, suggesting that the tuning of the underlying dynamical regime near criticality is a key determinant of memory longevity. Targeted modulation of these collective states could offer new avenues for memory enhancement.

neuroscience↗

bioRxiv2024

Generation and benchmarking of a collection of hiPSC lines from Schizophrenia Patients with Diverse Clinical Profiles

Limited therapeutic advancements in Schizophrenia (SCZ) depend on the heterogeneous nature of the disorder, impacting drug development and clinical trials that assume uniform therapy response, neglecting individual genetic and epigenomic variability. Disease modeling using human induced pluripotent stem cells (hiPSCs) is ideally suited for precision medicine, enabling individualized treatment approaches. Here, we describe the generation of patient-specific lines from somatic cells of SCZ individuals with well-defined diverse clinical trajectories using a Sendai virus-based reprogramming system. Karyotypically and CGH-array validated, the generated hiPSCs expressed diagnostic markers and demonstrated functional pluripotency. Converting these hiPSCs into neural progenitor cells enables the identification of aberrant cellular phenotypes associated with specific pathologically relevant neural phenotypes. This collection of hiPSC lines serves as a platform for developing therapeutic compounds targeting neural populations, potentially addressing early-stage disease alterations.

neuroscience↗

bioRxiv2022

Scale-free avalanches in humans NREM sleep and their relationships with sleep macro and microstructure

Sleep plays a key role in preserving brain function, keeping the brain network in a state that ensures optimal computational capabilities. Empirical evidence indicates that such a state is consistent with criticality, where scale-free neuronal avalanches emerge. However, the relationship between sleep, emergent avalanches, and criticality remains poorly understood. Here we fully characterize the critical behavior of avalanches during sleep, and study their relationship with the sleep macro- and micro-architecture, in particular the cyclic alternating pattern (CAP). We show that avalanche size and duration distributions exhibit robust power laws with exponents approximately equal to -3/2 e -2, respectively. Importantly, we find that sizes scale as a power law of the durations, and that all critical exponents for neuronal avalanches obey robust scaling relations, which are consistent with the mean-field directed percolation universality class. Our analysis demonstrates that avalanche dynamics depends on the position within the NREM-REM cycles, with the avalanche density increasing in the descending phases and decreasing in the ascending phases of sleep cycles. Moreover, we show that, within NREM sleep, avalanche occurrence correlates with CAP activation phases, particularly A1, which are the expression of slow wave sleep propensity and have been proposed to be beneficial for cognitive processes. The results suggest that neuronal avalanches, and thus tuning to criticality, actively contribute to sleep development and play a role in preserving network function. Such findings, alongside characterization of the universality class for avalanches, open new avenues to the investigation of functional role of criticality during sleep with potential clinical application. Significance statementWe fully characterize the critical behavior of neuronal avalanches during sleep, and show that avalanches follow precise scaling laws that are consistent with the mean-field directed percolation universality class. The analysis provides first evidence of a functional relationship between avalanche occurrence, slow-wave sleep dynamics, sleep stage transitions and occurrence of CAP phase A during NREM sleep. Because CAP is considered one of the major guardians of NREM sleep that allows the brain to dynamically react to external perturbation and contributes to the cognitive consolidation processes occurring in sleep, our observations suggest that neuronal avalanches at criticality are associated with flexible response to external inputs and to cognitive processes, a key assumption of the critical brain hypothesis.

neuroscience↗

bioRxiv2022

Alpha rhythm induces attenuation-amplification dynamics in neural activity cascades

The alpha rhythm is a distinctive feature of the awake resting-state of the human brain. Recent evidence suggests that alpha plays an active role in information processing, modulating behavioral and cognitive performance. However, the functional role of alpha oscillations in the resting-state neuronal dynamics remains poorly understood. To address this question, we investigate collective neural activity during resting wake and NREM sleep, a physiologic state with marginal presence of alpha rhythm. We show that, during resting wake, alpha oscillations drive an alternation of attenuation and amplification bouts in neural activity. Our analysis indicates that inhibition is activated in pulses that last a single alpha cycle and gradually suppress neural activity, while excitation is successively enhanced over timescales of a few alpha cycles to amplify neural activity. Furthermore, we show that long-term, intermittent fluctuations in alpha amplitude--known as the "waxing and waning" phenomenon--are associated with an attenuation-amplification mechanism acting over the timescales of several seconds and described by a power law decay of the activity rate in the "waning" phase. Importantly, we do not observe such dynamics during NREM sleep. The results suggest that the alpha rhythm acts as a "pacemaker" for the alternation of inhibition and excitation bouts across multiple timescales, the "waxing and waning" being a long-term control mechanism of cortical excitability. The amplification regime observed beyond the timescales of the individual alpha cycle suggests in turn that alpha oscillations might modulate the intensity of neural activity not only through pulses of inhibition, as proposed in the pulsed inhibition hypothesis, but also by timely enhancing excitation (or dis-inhibition).

neuroscience↗

bioRxiv2020

European Primary Forest Database (EPFD) v2.0

Primary forests are scarce in Europe and continue to disappear at an alarming rate. Despite these losses, we know little about where such forests still occur. Here, we present an updated geodatabase and map of Europes known primary forests. Our geodatabase harmonizes 48 different datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). To assess the robustness of our geodatabase, we checked each patch for forest disturbance events using Landsat satellite-image time series (1985-2018). We estimate that 94% of the patches in our database did not experience significant disturbances that would alter their primary forest status in the last 30 year. Our database is the most comprehensive dataset on primary forests in Europe, and will be useful for biogeographic and ecological studies, and conservation planning to safeguard these unique forests.

ecology↗

bioRxiv2020

Long-range Temporal Correlations in the Broadband Resting state Activity of the Human Brain revealed by Neuronal Avalanches

Resting-state brain activity is characterized by the presence of neuronal avalanches showing absence of characteristic size. Such evidence has been interpreted in the context of criticality and associated with the normal functioning of the brain. At criticality, a crucial role is played by long-range power-law correlations. Thus, to verify the hypothesis that the brain operates close to a critical point and consequently assess deviations from criticality for diagnostic purposes, it is of primary importance to robustly and reliably characterize correlations in resting-state brain activity. Recent works focused on the analysis of narrow band electroencephalography (EEG) and magnetoencephalography (MEG) signal amplitude envelope, showing evidence of long-range temporal correlations (LRTC) in neural oscillations. However, this approach is not suitable for assessing long-range correlations in broadband resting-state cortical signals. To overcome such limitation, here we propose to characterize the correlations in the broadband brain activity through the lens of neuronal avalanches. To this end, we consider resting-state EEG and long-term MEG recordings, extract the corresponding neuronal avalanche sequences, and study their temporal correlations. We demonstrate that the broadband resting-state brain activity consistently exhibits long-range power-law correlations in both EEG and MEG recordings, with similar values of the scaling exponents. Importantly, although we observe that avalanche size distribution depends on scale parameters, scaling exponents characterizing long-range correlations are quite robust. In particular, they are independent of the temporal binning (scale of analysis), indicating that our analysis captures intrinsic characteristics of the underlying dynamics. Because neuronal avalanches constitute a fundamental feature of neural systems with universal characteristics, the proposed approach may serve as a general, systems- and experiment-independent procedure to infer the existence of underlying long-range correlations in extended neural systems, and identify pathological behaviors in the complex spatio-temporal interplay of cortical rhythms.

neuroscience↗