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Modolo, J.

Publications and source records attributed to Modolo, J..

22 records · Page 2Linked to original sources

Probing the circuits of conscious perception with magnetophosphenes

BackgroundConscious perception is thought to involve the large-scale, coordinated activation of distant brain regions, a process termed ignition in the Global Workspace Theory and integration in Integrated Information Theory, which are two of the major theories of consciousness.\n\nMethodsHere, we provide evidence for this process in humans by combining a magnetically-induced phosphene perception task with electroencephalography. Functional cortical networks were identified and characterized using graph theory to quantify the impact of conscious perception on local (segregation) and distant (integration) processing.\n\nResultsConscious phosphene perception activated frequency-specific networks, each associated with a specific spatial scale of information processing. Integration increased within an alpha-band functional network, while segregation occurred in the beta band.\n\nConclusionsThese results bring novel evidence for the functional role of distinct brain oscillations and confirm the key role of integration processes for conscious perception in humans.

neuroscience↗

Magnetophospenes in humans exposed to ELF MF up to 50 mT, a threshold study

Although magnetophosphene perception is the most reliable reported effect on acute human neurophysiological responses to extremely low frequency (ELF) magnetic field (MF) exposure, current knowledge is based on small sample size, non-replicated experiments. In this study, we established MF levels triggering magnetophosphenes at 20, 50, 60 and 100 Hz in humans. Magnetophosphene perception and EEG were collected in 55 magnetic flux density conditions randomly delivered in each frequency group (2 experiments, total n=145). Results indicate that threshold values 1) need to be reported as a function of dB/dt instead of flux density, and 2) are frequency-dependent (higher sensitivity to lower frequencies). No clear trend was found in EEG data.

biophysics↗

Psychological resilience correlates with EEG source-space brain network flexibility

ObjectiveWe aimed at identifying the potential relationship between the dynamical properties of the human functional network at rest and one of the most prominent traits of personality, namely resilience.\n\nApproachTo tackle this issue, we used resting-state EEG data recorded from 45 healthy subjects. Resilience was quantified using the 10-items Connor-Davidson Resilience Scale (CD-RISC). Using a sliding windows approach, brain networks in each EEG frequency band (delta, theta, alpha and beta) were constructed using the EEG source-space connectivity method. Brain networks dynamics were evaluated using the network flexibility, linked with the tendency of a given node to change its modular affiliation over time.\n\nMain ResultsThe results revealed a negative correlation between the psychological resilience and the brain network flexibility for a limited number of brain regions within the delta, alpha and beta bands.\n\nSignificanceThis study provides evidence that network flexibility, a metric of dynamic functional networks, is strongly correlated with psychological resilience as assessed from personality testing. Beyond this proof-of-principle that reliable EEG-based quantities representative of personality traits can be identified, this motivates further investigation regarding the full spectrum of personality aspects and their relationship with functional networks.

neuroscience↗

Reconstruction of post-synaptic potentials by reverse modeling of local field potentials

Among electrophysiological signals, Local Field Potentials (LFPs) are extensively used to study brain activity, either in vivo or in vitro. LFPs are recorded with extracellular electrodes implanted in brain tissue. They reflect intermingled excitatory and inhibitory processes in neuronal assemblies. In cortical structures, LFPs mainly originate from the summation of post-synaptic potentials (PSPs), either excitatory (ePSPs) and inhibitory (iPSPs) generated at the level of pyramidal cells. The challenging issue, addressed in this paper, is to estimate, from a single extracellularly-recorded signal, both ePSP and iPSP components of the LFP. The proposed method is based on a model-based reverse engineering approach in which the measured LFP is fed into a physiologically-grounded neural mass model (mesoscopic level) in order to estimate the synaptic activity of a sub-population of pyramidal cells interacting with local GABAergic interneurons. The method was first validated using simulated LFPs for which excitatory and inhibitory components are known a priori and can thus serve as a ground truth. It was then evaluated on in vivo data (PTZ-induced seizures, rat; PTZ-induced excitability increase, mouse; epileptiform discharges, mouse) and on in clinico data (human seizures recorded with depth-EEG electrodes). Under these various conditions, results showed that the proposed reverse engineering method provides a reliable estimation of the average excitatory and inhibitory post-synaptic potentials at the origin of the measured LFPs. They also indicated that the method allows for monitoring of the excitation/inhibition ratio. The method has potential for multiple applications in neuroscience, typically when a time tracking of local excitability changes is required.

neuroscience↗