Francesco de Pasquale

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The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state(More)
Functional MRI (fMRI) studies have shown that low-frequency (<0.1 Hz) spontaneous fluctuations of the blood oxygenation level dependent (BOLD) signal during restful wakefulness are coherent within distributed large-scale cortical and subcortical networks (resting state networks, RSNs). The neuronal mechanisms underlying RSNs remain poorly understood. Here,(More)
The Human Connectome Project (HCP) seeks to map the structural and functional connections between network elements in the human brain. Magnetoencephalography (MEG) provides a temporally rich source of information on brain network dynamics and represents one source of functional connectivity data to be provided by the HCP. High quality MEG data will be(More)
Resting state networks (RSNs) are sets of brain regions exhibiting temporally coherent activity fluctuations in the absence of imposed task structure. RSNs have been extensively studied with fMRI in the infra-slow frequency range (nominally <10(-1)Hz). The topography of fMRI RSNs reflects stationary temporal correlation over minutes. However, neuronal(More)
RATIONALE Adolescent rodents differ markedly from adults in several neuro-behavioural parameters. Moreover, 'paradoxical' responses to psychostimulants have been reported at this age. OBJECTIVES Thus, we investigated the responses of adolescent (post-natal day, PND, 34 to 43) and adult (PND >60) Sprague-Dawley male rats to the psychostimulant drug(More)
To study functional connectivity using magnetoencephalographic (MEG) data, the high-quality source-level reconstruction of brain activity constitutes a critical element. MEG resting-state networks (RSNs) have been documented by means of a dedicated processing pipeline: MEG recordings are decomposed by independent component analysis (ICA) into artifact and(More)
We recently suggested that serotonin 7 (5-Ht7) receptors may play a role in ADHD-like symptoms, at least in animal models. A mixed 5-Ht(1a/7) agonist, 8-OH-DPAT, counteracted the augmented levels of basal impulsivity, observed after treatment with a selective 5-Ht7 antagonist, SB269970 (Leo et al., 2009). In the present study, these serotonergic compounds(More)
Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at(More)