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Dellavale, D.

Publications and source records attributed to Dellavale, D..

4 recordsLinked to original sources

Linking neuronal avalanches with oscillatory and broadband 1/f activities in the resting human brain

ObjectiveNarrowband oscillations (NOs) and Broadband Arrhythmic Activity (BAA) are valuable conceptualizations extensively used to interpret brain data, with NOs linked to communication and synchronization and BAA encompassing scale-free dynamics and neuronal avalanches. Although both frameworks offer critical in-sights into brain function, they have largely evolved in parallel, with limited integration and no unifying mechanistic account of how these dynamics interact to generate transient, Salient Events (SEs). This gap is particularly pressing given recent interest in how SEs--brief ({approx} 100 ms) bursts of activity coordinated across brain regions--relate to large-scale brain function and cognition. To address this, we introduce a signal-level framework that links the Fourier spectral properties (oscillation-domain) of neural signals to the emergence of realistic SEs in the time-domain from NOs and BAA. MethodsOur approach is grounded in a novel concept--Spectral Group Delay Consistency (SGDC)--along with associated measures that quantify the temporal alignment of spectral components and capture the conditions under which Nos and BAA coalesce into transient, burst-like events. Unlike traditional power- or phase-based measures, or higher-order statistical metrics such as kurtosis and cokurtosis, SGDC provides a signal-level mechanistic account of how local and large-scale SEs emerge from the spectral structure of the underlying signals. Empirical validation is provided using source-reconstructed MEG data from a large cohort and a comprehensive array of features characterizing the statistical, spatiotemporal and spectral properties of observed SEs. ResultsWe found that the SEs identified in our empirical MEG dataset can be segregated based on their spectral signature in two main groups having different propagation patterns. Using generative models based on the SGDC mechanism we provide a theoretical framework to interpret these experimental results showing that cluster 2 events are specifically related to the long-range spread of narrowband alpha bursts across the brain network (i.e., SNEs: Salient Network Events), whereas cluster 1 events correspond to more short-lived and spatially localized fluctuations mainly promoted by the BAA (i.e., SLEs: Salient Local Events). We also provide analytical arguments and numerical simulations showing that a) high SGDC in specific narrow frequency bands, b) transient cross-regional coherent NOs and c) BAA, are all key ingredients for the emergence of realistic SNEs. SignificanceWe combine experimental evidence supported by a signal-level analytical framework and numerical simulations based on generative models to demonstrate that transient phase-structured alpha bursts, shaped by the SGDC mechanism, contribute to long-range coordination during rest. This extends the communication-through-coherence hypothesis to the transient domain. Additionally, SGDC links to findings that NOs interact with fast microstates ({approx}100 - 200 ms) and may modulate long-range dependencies across timescales. While previous studies have described SEs within the framework of neuronal avalanches, they often lacked a generative, signal-level account. Here, we bridge that divide by offering a mathematically grounded and empirically validated framework that accounts for oscillatory and aperiodic bursts perspectives on brain activity. HighlightsO_LISalient network events propagating across the brain during spontaneous resting state activity, are highly structured in terms of their spatial, temporal and spectral properties. C_LIO_LIThe spectral group delay consistency framework provides a signal-level mechanism that accounts for transient salient network events emerging from oscillatory components of the brain activity. C_LIO_LINarrowband oscillations and broadband arrhythmic activity interact to shape the timing and spatial extent of salient events. C_LIO_LISpectral group delay consistency, transient cross-regional coherent narrowband oscillations and broadband arrhythmic activity, are all key ingredients for the emergence of realistic salient network events. C_LIO_LISalient network events during rest reflect large-scale spreading of synchronized alpha band activity, which may play a functional role as a long-range interaction mechanism in the human brain. C_LI

neuroscience↗

Improved Temporal and Spatial Focality of Non-invasive Deep-brain Stimulation using Multipolar Single-pulse Temporal Interference with Applications in Epilepsy

Temporal Interference (TI) is an emerging method to non-invasively stimulate deep brain structures. This innovative technique is increasingly recognized for its potential applications in the treatment of various neurological disorders, including epilepsy, depression, and Alzheimers disease. However, several drawbacks to the TI method exist that we aim to improve upon. To begin, the applied electric field in the TI target is not much higher than what non-invasive transcranial alternating current stimulation (TACS) provides in the cortex. Additionally, the TI stimulation onset is dependent on the envelope of the amplitude modulated (AM) signal, where for example 1 Hz and 100 Hz envelopes have significantly different rise times to reach maximum envelope amplitude - unlike square biphasic pulses. This limitation in turn prevents classic TI, from applying bursts of pulses. Finally, the electric field intensity of TI cannot be increased or decreased at the target without dramatically altering the spatial profile of the stimulation focus. In the work presented here, we efficiently address all three of these limitations. First, we performed two-photon calcium imaging to show that individual neurons selectively respond to the TI envelope frequency, providing evidence that TI modulates neural activity with temporal specificity. This marks a significant advancement, representing the first empirical demonstration of neuronal activation at the {Delta}f frequency within the context of TI and in an imaging modality. Subsequently, we compared the AM signals of TI with phase-shift keying (PSK) modulated signals to highlight the superior effectiveness of noninvasive pulses in contrast to the traditional TI method, particularly in inducing epileptic activity (after-discharges) in mice. We also added a multipolar configuration to create a significant increase in the electric field at the target without significantly altering the spatial profile and applied Fourier components to replicate classic biphasic bursts of square pulses - all transcranially, without the use of penetrating electrodes. These innovations aim to enhance the precision and efficacy of TI stimulation, to advance its application in neurological research and therapy. Key Points / HighlightsO_LINon-invasive temporal interference stimulation modulates the activity of individual neurons at the envelope frequency. C_LIO_LIA non-invasive multi-pulse TI stimulation paradigm improves both temporal and spatial focality in the deep target neural tissue when compared to traditional continuous wave (amplitude-modulated) TI stimulation. C_LIO_LIPulse TI paradigms can stimulate deep neural targets with reduced amplitude of the topical high-frequency stimulation, decreasing off-target stimulation when compared to continuous wave TI patterns. As a consequence, pulse TI stimulation reduces the risk of undesired side effects such as high-frequency conduction block in off-target tissues or cortical areas. C_LIO_LIBoth temporal and spatial focality of the TI stimulation pattern positively correlate with the efficacy of the stimulation to induce seizures in the mouse hippocampus. C_LI

neuroscience↗

On the complex interplay between spectral harmonicity and different types of cross frequency couplings in non linear oscillators and biologically plausible neural network models

BackgroundCross-frequency coupling (CFC) refers to the non linear interaction between oscillations in different frequency bands, and it is a rather ubiquitous phenomenon that has been observed in a variety of physical and biophysical systems. In particular, the coupling between the phase of slow oscillations and the amplitude of fast oscillations, referred as phase-amplitude coupling (PAC), has been intensively explored in the brain activity recorded from animals and humans. However, the interpretation of these CFC patterns remains challenging since harmonic spectral correlations characterizing non sinusoidal oscillatory dynamics can act as a confounding factor. MethodsSpecialized signal processing techniques are proposed to address the complex interplay between spectral harmonicity and different types of CFC, not restricted only to PAC. For this, we provide an in-depth characterization of the Time Locked Index (TLI) as a novel tool aimed to efficiently quantify the harmonic content of noisy time series. It is shown that the proposed TLI measure is more robust and outperform traditional phase coherence metrics (e.g. Phase Locking Value, Pairwise Phase Consistency) in several aspects. ResultsWe found that a non linear oscillator under the effect of additive noise can produce spurious CFC with low spectral harmonic content. On the other hand, two coupled oscillatory dynamics with independent fundamental frequencies can produce true CFC with high spectral harmonic content via a rectification mechanism or other post-interaction nonlinear processing mechanisms. These results reveal a complex interplay between CFC and harmonicity emerging in the dynamics of biologically plausible neural network models and more generic non linear and parametric oscillators. ConclusionsWe show that, contrary to what is usually assumed in the literature, the high harmonic content observed in non sinusoidal oscillatory dynamics, is neither sufficient nor necessary condition to interpret the associated CFC patterns as epiphenomenal. There is mounting evidence suggesting that the combination of multimodal recordings, specialized signal processing techniques and theoretical modeling is becoming a required step to completely understand CFC patterns observed in oscillatory rich dynamics of physical and biophysical systems. HighlightsO_LITime locked index efficiently quantifies the harmonic content of noisy time series. C_LIO_LIA non linear oscillator under the effect of additive noise can produce spurious cross frequency couplings (CFC) with low spectral harmonic content. C_LIO_LITwo coupled oscillatory dynamics with independent fundamental frequencies can produce true CFC with high spectral harmonic content via rectification mechanisms or other post-interaction nonlinear processing mechanisms. C_LIO_LIA non sinusoidal oscillatory dynamics with high harmonic content is neither sufficient nor necessary condition for spurious CFC. C_LIO_LIA complex interplay between CFC and harmonicity emerges from the dynamics of nonlinear, parametric and biologically plausible oscillators. C_LI

neuroscience↗

Spectral harmonicity distinguishes two types of ictal phase-amplitude cross frequency couplings in patients candidate to epilepsy surgery

ObjectiveSpectral harmonicity of the ictal activity was analyzed regarding two clinically relevant aspects, (1) as a confounding factor producing spurious phase-amplitude couplings (PAC) which may lead to wrong conclusions about the underlying ictal mechanisms, and (2) its role in how good PAC is in correspondence to the seizure onset zone (SOZ) classification performed by the epileptologists. MethodsPAC patterns observed in intracerebral electroencephalography (iEEG) recordings were retrospectively studied during seizures of seven patients with pharmacoresistant focal epilepsy. The time locked index (TLI) measure was introduced to quantify the degree of harmonicity between frequency bands associated to the emergence of PAC during epileptic seizures. Results(1) Harmonic and non harmonic PAC patterns coexist during the seizure dynamics in iEEG recordings with macroelectrodes. (2) Harmonic PAC patterns are an emergent property of the periodic non sinusoidal waveform constituting the epileptiform activity. (3) The TLI metric allows to distinguish the non harmonic PAC pattern, which has been previously associated with the ictal core through the paroxysmal depolarizing shifts mechanism of seizure propagation. ConclusionsOur results suggest that the spectral harmonicity of the ictal activity plays a relevant role in the visual analysis of the iEEG recordings performed by the epileptologists to define the SOZ, and that it should be considered for the proper interpretation of ictal mechanisms. SignificanceThe proposed harmonicity analysis can be used to improve the delineation of the SOZ by reliably identifying non harmonic PAC patterns emerging from fully recruited cortical and subcortical areas. HighlightsO_LIHarmonic and non harmonic phase-amplitude couplings coexist in epileptiform local field potentials. C_LIO_LIThe time locked index quantitatively differentiates harmonic and non harmonic ictal PAC patterns. C_LIO_LISpectral harmonicity plays a relevant role in the interpretation of underlying ictal mechanisms. C_LI

neuroscience↗