Francesco de Pasquale

Università degli Studi G. d'Annunzio Chieti e Pescara, Chieta, Abruzzo, Italy

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Publications (66)192.21 Total impact

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    ABSTRACT: To study the functional connectivity in severe acquired brain injury patients is very challenging for their high level of disability due to a prolonged period of coma, extended lesions, and several cognitive and behavioral disorders. In this work, we investigated in these patients, the Default Mode Network and Somatomotor connectivity changes at rest longitudinally, in the subacute and late phase after brain injury. The aim of the study is to characterize such connectivity patterns and relate the observed changes to clinical and neuropsychological outcomes of these patients after a period of intensive neuro-rehabilitation. Our findings show within the Default Mode Network a disruption of connectivity of medial prefrontal regions and a significant change of amplitude of internal connections. Notably, strongest changes in functional connectivity significantly correlated to consistent clinical and cognitive recovery. This evidence seems to indicate that the re-organization of the Default mode network may represent a valid biomarker for the cognitive recovery in severe acquired brain injury patients.
    Journal of neurotrauma 11/2015; DOI:10.1089/neu.2015.4003 · 3.71 Impact Factor
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    ABSTRACT: Objective: We hypothesize that the major consciousness deficit observed in coma is due to the breakdown of long-range neuronal communication supported by precuneus and posterior cingulate cortex (PCC), and that prognosis depends on a specific connectivity pattern in these networks. Methods: We compared 27 prospectively recruited comatose patients who had severe brain injury (Glasgow Coma Scale score <8; 14 traumatic and 13 anoxic cases) with 14 age-matched healthy participants. Standardized clinical assessment and fMRI were performed on average 4 ± 2 days after withdrawal of sedation. Analysis of resting-state fMRI connectivity involved a hypothesis-driven, region of interest-based strategy. We assessed patient outcome after 3 months using the Coma Recovery Scale-Revised (CRS-R). Results: Patients who were comatose showed a significant disruption of functional connectivity of brain areas spontaneously synchronized with PCC, globally notwithstanding etiology. The functional connectivity strength between PCC and medial prefrontal cortex (mPFC) was significantly different between comatose patients who went on to recover and those who eventually scored an unfavorable outcome 3 months after brain injury (Kruskal-Wallis test, p < 0.001; linear regression between CRS-R and PCC-mPFC activity coupling at rest, Spearman ρ = 0.93, p < 0.003). Conclusion: In both etiology groups (traumatic and anoxic), changes in the connectivity of PCC-centered, spontaneously synchronized, large-scale networks account for the loss of external and internal self-centered awareness observed during coma. Sparing of functional connectivity between PCC and mPFC may predict patient outcome, and further studies are needed to substantiate this potential prognosis biomarker.
    Neurology 11/2015; DOI:10.1212/WNL.0000000000002196 · 8.29 Impact Factor
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    F de Pasquale · S Della Penna · O Sporns · G L Romani · M Corbetta ·
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    ABSTRACT: Spontaneous brain activity is spatially and temporally organized in the absence of any stimulation or task in networks of cortical and subcortical regions that appear largely segregated when imaged at slow temporal resolution with functional magnetic resonance imaging (fMRI). When imaged at high temporal resolution with magneto-encephalography (MEG), these resting-state networks (RSNs) show correlated fluctuations of band-limited power in the beta frequency band (14-25 Hz) that alternate between epochs of strong and weak internal coupling. This study presents 2 novel findings on the fundamental issue of how different brain regions or networks interact in the resting state. First, we demonstrate the existence of multiple dynamic hubs that allow for across-network coupling. Second, dynamic network coupling and related variations in hub centrality correspond to increased global efficiency. These findings suggest that the dynamic organization of across-network interactions represents a property of the brain aimed at optimizing the efficiency of communication between distinct functional domains (memory, sensory-attention, motor). They also support the hypothesis of a dynamic core network model in which a set of network hubs alternating over time ensure efficient global communication in the whole brain.
    Cerebral Cortex 09/2015; DOI:10.1093/cercor/bhv185 · 8.67 Impact Factor
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    ABSTRACT: To progress toward understanding of the mechanisms underlying the functional organization of the human brain, either a bottom-up or a top-down approach may be adopted. The former starts from the study of the detailed functioning of a small number of neuronal assemblies, while the latter tries to decode brain functioning by considering the brain as a whole. This review discusses the top-down approach and the use of magnetoencephalography (MEG) to describe global brain properties. The main idea behind this approach is that the concurrence of several areas is required for the brain to instantiate a specific behavior/functioning. A central issue is therefore the study of brain functional connectivity and the concept of brain networks as ensembles of distant brain areas that preferentially exchange information. Importantly, the human brain is a dynamic device, and MEG is ideally suited to investigate phenomena on behaviorally relevant timescales, also offering the possibility of capturing behaviorally-related brain connectivity dynamics.
    Functional neurology 01/2015; 29(4):1-13. · 1.86 Impact Factor
  • N. Tuovinen · A. Hamamci · F. De Pasquale · U. Sabatini ·

    Radiotherapy and Oncology 12/2014; 111:S253. DOI:10.1016/S0167-8140(15)31832-6 · 4.36 Impact Factor
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    ABSTRACT: Several neuroimaging studies reported that a common set of regions are recruited during action observation and execution and it has been proposed that the modulation of the μ rhythm, in terms of oscillations in the alpha and beta bands might represent the electrophysiological correlate of the underlying brain mechanisms. However, the specific functional role of these bands within the μ rhythm is still unclear. Here, we used magnetoencephalography (MEG) to analyze the spectral and temporal properties of the alpha and beta bands in healthy subjects during an action observation and execution task. We associated the modulation of the alpha and beta power to a broad action observation network comprising several parieto-frontal areas previously detected in fMRI studies. Of note, we observed a dissociation between alpha and beta bands with a slow-down of beta oscillations compared to alpha during action observation. We hypothesize that this segregation is linked to a different sequence of information processing and we interpret these modulations in terms of internal models (forward and inverse). In fact, these processes showed opposite temporal sequences of occurrence: anterior-posterior during action (both in alpha and beta bands) and roughly posterior-anterior during observation (in the alpha band). The observed differentiation between alpha and beta suggests that these two bands might pursue different functions in the action observation and execution processes.
    NeuroImage 08/2014; 102. DOI:10.1016/j.neuroimage.2014.08.031 · 6.36 Impact Factor
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    ABSTRACT: Rationale The serotonin 7 receptor (5-HT7-R) is part of a neuro-transmission system with a proposed role in neural plasticity and in mood, cognitive or sleep regulation. Objectives We investigated long-term consequences of sub-chronic treatment, during adolescence (43–45 to 47–49 days old) in rats, with a novel 5-HT7-R agonist (LP-211, 0 or 0.250 mg/kg/day). Methods We evaluated behavioural changes as well as forebrain structural/functional modifications by in vivo magnetic resonance (MR) in a 4.7 T system, followed by ex vivo histology. Results Adult rats pre-treated during adolescence showed reduced anxiety-related behaviour, in terms of reduced avoidance in the light/dark test and a less fragmented pattern of exploration in the novel object recognition test. Diffusion tensor imaging (DTI) revealed decreased mean diffusivity (MD) in the amygdala, increased fractional anisotropy (FA) in the hippocampus (Hip) and reduced axial (D||) together with increased radial (D⊥) diffusivity in the nucleus accumbens (NAcc). An increased neural dendritic arborization was confirmed in the NAcc by ex vivo histology. Seed-based functional MR imaging (fMRI) identified increased strength of connectivity within and between “limbic” and “cortical” loops, with affected cross-correlations between amygdala, NAcc and Hip. The latter displayed enhanced connections through the dorsal striatum (dStr) to dorso-lateral prefrontal cortex (dl-PFC) and cerebellum. Functional connection also increased between amygdala and limbic elements such as NAcc, orbito-frontal cortex (OFC) and hypothalamus. MR spectroscopy (1H-MRS) indicated that adolescent LP-211 exposure increased glutamate and total creatine in the adult Hip. Conclusions Persistent MR-detectable modifications indicate a rearrangement within forebrain networks, accounting for long-lasting behavioural changes as a function of developmental 5-HT7-R stimulation.
    Psychopharmacology 06/2014; 232(1). DOI:10.1007/s00213-014-3639-6 · 3.88 Impact Factor

  • Journal of the Neurological Sciences 10/2013; 333:e554-e555. DOI:10.1016/j.jns.2013.07.1945 · 2.47 Impact Factor
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    ABSTRACT: Spontaneous fMRI fluctuations are organized in large-scale spatiotemporal structures, or resting-state networks (RSN). However, it is unknown how task performance affects RSN dynamics. We use MEG to measure slow (∼0.1 Hz) coherent fluctuations of band-limited power (BLP), a robust correlate of RSN, during rest and movie observation and compare them to fMRI-RSN. BLP correlation, especially in α band, dropped in multiple RSN during movie although overall topography was maintained. Variability of power correlation increased in visual occipital cortex, and transient decrements corresponded to scenes perceived as "event boundaries." Additionally, stronger task-dependent interactions developed between vision and language networks in θ and β bands, and default and language networks in γ band. The topography of fMRI connectivity and relative changes induced by the movie were well matched to MEG. We conclude that resting-state and task network interactions are clearly different in the frequency domain despite maintenance of underlying network topography.
    Neuron 07/2013; 79(4). DOI:10.1016/j.neuron.2013.06.022 · 15.05 Impact Factor
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    ABSTRACT: 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 fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently have studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations.
    NeuroImage 05/2013; 80. DOI:10.1016/j.neuroimage.2013.05.079 · 6.36 Impact Factor
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    ABSTRACT: 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 communication occurs on a much faster time scale, at frequencies nominally in the range of 10(0) - 10(2) Hz. We examined phase-shifted interactions in the delta (2-3.5 Hz), theta (4-7 Hz), alpha (8-12 Hz) and beta (13-30 Hz) frequency bands of resting-state source space MEG signals. These analyses were conducted between nodes of the dorsal attention network (DAN), one of the most robust RSNs, and between the DAN and other networks. Phase shifted interactions were mapped by the Multivariate Interaction Measure (MIM), a measure of true interaction constructed from the maximization of imaginary coherency in the virtual channels comprised of voxel signals in source space. Non zero-phase interactions occurred between homologous left and right hemisphere regions of the DAN in the delta and alpha frequency bands. Even stronger non zero-phase interactions were detected between networks. Visual regions bilaterally showed phase-shifted interactions in the alpha band with regions of the DAN. Bilateral somatomotor regions interacted with DAN nodes in the beta band. These results demonstrate the existence of consistent, frequency specific phase-shifted interactions on a millisecond time scale between cortical regions within RSN as well as across RSNs.
    NeuroImage 04/2013; 79. DOI:10.1016/j.neuroimage.2013.04.062 · 6.36 Impact Factor

  • 21st Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM); 04/2013
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    Francesco de Pasquale · Andrea Cherubini · Patrice Péran · Carlo Caltagirone · Umberto Sabatini ·
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    ABSTRACT: Purpose: To investigate white matter heterogeneity using a multichannel segmentation of a large sample of structural and diffusion magnetic resonance imaging (MRI) data. Materials and methods: A sample of 50 subjects was segmented using channels comprising exclusively structural (longitudinal and transverse relaxation times T1 and T2 and transverse relaxation rate R2*) and diffusion-based MRI indices (mean diffusivity and fractional anisotropy). These data were analyzed using a data driven approach in which no prior information was used. Results: The analysis revealed the splitting of white matter into two subclasses in which the longitudinal fasciculi were distinguished from inferior/superior ones. The distribution of the adopted indices in the obtained clusters showed that R2* was mainly responsible for this splitting. Conclusion: This result supports the observation, previously hypothesized in the literature, that R2* is influenced by the fiber orientation.
    Journal of Magnetic Resonance Imaging 01/2013; 37(1). DOI:10.1002/jmri.23801 · 3.21 Impact Factor
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    ABSTRACT: The principles of functional specialization and integration in the resting brain are implemented in a complex system of specialized networks that share some degree of interaction. Recent studies have identified wider functional modules compared to previously defined networks and reported a small-world architecture of brain activity in which central nodes balance the pressure to evolve segregated pathways with the integration of local systems. The accurate identification of such central nodes is crucial but might be challenging for several reasons, e.g. inter-subject variability and physiological/pathological network plasticity, and recent works reported partially inconsistent results concerning the properties of these cortical hubs. Here, we applied a whole-brain data-driven approach to extract cortical functional cores and examined their connectivity from a resting state fMRI experiment on healthy subjects. Two main statistically significant cores, centered on the Posterior Cingulate Cortex and the Supplementary Motor Area, were extracted and their functional connectivity maps, thresholded at three statistical levels, revealed the presence of two complex systems. One system is consistent with the Default Mode Network (DMN) and gradually connects to visual regions, the other centered on motor regions and gradually connects to more sensory-specific portions of cortex. These two large scale networks eventually converged to regions belonging to the medial aspect of the DMN, potentially allowing inter-network interactions.
    NeuroImage 12/2012; 69. DOI:10.1016/j.neuroimage.2012.11.051 · 6.36 Impact Factor
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    Dataset: Neuron

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    Sara Spadone · Francesco de Pasquale · Dante Mantini · Stefania Della Penna ·
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    ABSTRACT: 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 the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK).
    NeuroImage 05/2012; 62(3):1912-23. DOI:10.1016/j.neuroimage.2012.05.051 · 6.36 Impact Factor
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    ABSTRACT: We used magneto-encephalography to study the temporal dynamics of band-limited power correlation at rest within and across six brain networks previously defined by prior functional magnetic resonance imaging (fMRI) studies. Epochs of transiently high within-network band limited power (BLP) correlation were identified and correlation of BLP time-series across networks was assessed in these epochs. These analyses demonstrate that functional networks are not equivalent with respect to cross-network interactions. The default-mode network and the posterior cingulate cortex, in particular, exhibit the highest degree of transient BLP correlation with other networks especially in the 14-25 Hz (β band) frequency range. Our results indicate that the previously demonstrated neuroanatomical centrality of the PCC and DMN has a physiological counterpart in the temporal dynamics of network interaction at behaviorally relevant timescales. This interaction involved subsets of nodes from other networks during periods in which their internal correlation was low.
    Neuron 05/2012; 74(4):753-64. DOI:10.1016/j.neuron.2012.03.031 · 15.05 Impact Factor

  • 20th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM); 05/2012
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    D.feinberg · S.ciuchi · Pasquale ·
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    ABSTRACT: The molecular crystal model of electrons coupled to Einstein phonons is studied as a function of the two parameters: the coupling constant A and the ratio of the electron-phonon coupling energy to the phonon energy, denoted by α. Both the one-electron and the many-electron models are studied, starting (for the former) from the adiabatic limit and (for the latter) from the anti-adiabatic one. In the “multiphonon” regime α>1, the sharp crossover between quasi-free electrons (λ≪1) and small polarons (λ≫1) is investigated, emphasizing the anomalous lattice fluctuations which occur in the intermediate regime (λ≈1). These fluctuations are due to the band motion of the electrons strongly coupled to the lattice and are shown in turn to weaken the electron mass renormalization inherent to self-trapping. In a relevant part of the intermediate region the effective electron mass slowly increases with λ, due to a competition between the phonon dressing effect and the reduction of lattice momentum fluctuations. This reduction is reminiscent of squeezing phenomena occurring in quantum optics. In a gaussian approximation squeezed phonon states imply a dynamical phonon softening.
    International Journal of Modern Physics B 01/2012; 04(07n08). DOI:10.1142/S0217979290000656 · 0.94 Impact Factor
  • S.fratini · Pasquale · S.ciuchi ·
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    ABSTRACT: We apply the dynamical mean field theory to calculate the low-density limit of the small polaron optical conductivity in the Holstein model. Classical schemes of approximation are recovered in weak coupling and in the adiabatic and anti-adiabatic strong coupling limits. Such schemes are not suitable for the intermediate coupling regime, where our theory gives an anomalous behaviour of the spectral weight at low energy as the temperature decreases.
    International Journal of Modern Physics B 01/2012; 14(25n27). DOI:10.1142/S0217979200003241 · 0.94 Impact Factor

Publication Stats

1k Citations
192.21 Total Impact Points


  • 2008-2014
    • Università degli Studi G. d'Annunzio Chieti e Pescara
      • • Institute for Advanced Biomedical Technologies ITAB
      • • Department of Neuroscience & Imaging
      Chieta, Abruzzo, Italy
  • 2012
    • Foundation Santa Lucia
      • Department of Radiology
      Roma, Latium, Italy
  • 1997-2012
    • Sapienza University of Rome
      • Department of Physics
      Roma, Latium, Italy
  • 2004-2009
    • University of Plymouth
      Plymouth, England, United Kingdom
    • The American University of Rome
      Roma, Latium, Italy
  • 1994-2007
    • Università degli Studi dell'Aquila
      • Department of Chemistry, Chemical Engineering and Materials
      Aquila, Abruzzo, Italy
  • 2002
    • National Institute of Geophysics and Volcanology
      Roma, Latium, Italy
  • 2000
    • Italian National Research Council
      Roma, Latium, Italy
  • 1998
    • Università degli Studi Europea di Roma
      Roma, Latium, Italy
  • 1987
    • The University of Manchester
      • School of Chemistry
      Manchester, England, United Kingdom