Francesco de Pasquale

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

Are you Francesco de Pasquale?

Claim your profile

Publications (37)152.2 Total impact

  • [Show abstract] [Hide abstract]
    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.
    No preview · Article · Nov 2015 · Journal of neurotrauma
  • Source
    [Show abstract] [Hide abstract]
    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.
    Preview · Article · Nov 2015 · Neurology
  • Source
    F de Pasquale · S Della Penna · O Sporns · G L Romani · M Corbetta
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Sep 2015 · Cerebral Cortex
  • Source
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Jan 2015 · Functional neurology
  • N. Tuovinen · A. Hamamci · F. De Pasquale · U. Sabatini

    No preview · Article · Dec 2014 · Radiotherapy and Oncology
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background The spatial pattern of atrophy of a disease is related to its functional connectivity structure, mapped by resting-state fMRI. In Huntington disease (HD), the striatum is the most vulnerable brain structure, linked to specific frontal areas and thalamus by five parallel frontal-subcortical circuits. Motor (MN) and Default Mode (DMN) resting-state networks play a key role in HD. Aims We hypothesise that the striatum-related MN could be damaged in HD; while the DMN, not involving the striatum, could be instead relatively preserved. Therefore, we investigated these two networks and related them to grey matter loss. Methods Ten patientsand 10 controls underwent T1-weighted imaging (MDEFT sequence) and resting-state fMRI (gradient echo-EPI sequence: TR/TE=65/30 ms, voxel-size=2.5 mm3; 400 volumes) on a 3T Siemens scan. We computed the seed-based functional connectivity patterns from two seeds: the Posterior Cingulate cortex (PCC) and the Supplementary Motor area (SMA), considered cortical hubs of the DMN and the MN, respectively. We also analysed different grey matter loss areas in patients and controls by FSL-VBM. Results Patients showed grey matter loss in all cortical and subcortical areas involved in MN, with preservation of SMA, in spite of structural preservation of all the cortical areas involved in the DMN. Coherently, we found functional connectivity impairment in MN, with loss of connexions of SMA with primary and secondary sensory-motor areas and putamen and relatively preserved connexions in the DMN. Conclusions The striatum–related MN, but not the DMN, is impaired in HD. Even if all MN regions showed grey matter volume loss, SMA remains structurally and functionally preserved, at least at early HD stages. This might be linked to the central role of SMA, which allows the MN to integrate with other functional circuits. Thus, these results seem to suggest a pattern of damage from local to more central nodes.
    No preview · Article · Sep 2014 · Journal of Neurology Neurosurgery & Psychiatry
  • Source
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Aug 2014 · NeuroImage
  • [Show abstract] [Hide abstract]
    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.
    No preview · Article · Jun 2014 · Psychopharmacology

  • No preview · Article · Oct 2013 · Journal of the Neurological Sciences
  • Source
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Jul 2013 · Neuron
  • Source
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · May 2013 · NeuroImage
  • Source
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Apr 2013 · NeuroImage

  • No preview · Conference Paper · Apr 2013
  • Source
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Jan 2013 · Journal of Magnetic Resonance Imaging
  • [Show abstract] [Hide abstract]
    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.
    No preview · Article · Dec 2012 · NeuroImage
  • Source
    Dataset: Neuron

    Full-text · Dataset · Nov 2012
  • Francesco de Pasquale · Laura Marzetti
    [Show abstract] [Hide abstract]
    ABSTRACT: The existence of a structured pattern of neuronal activity in the brain at rest has been consistently reported in the neuroscience literature. Multiple techniques, such as fMRI, MEG and EEG, showed that spontaneous, slow fluctuations of cerebral activity are temporally coherent within distributed functional networks resembling those evoked by sensory, motor, and cognitive paradigms. Among these networks, the Default Mode network gained large interest because of its anatomical and functional architecture. In fact, this network seems to reflect the default brain activity at rest and it has been associated with internal mentation, autobiographical memory, thinking about one's future, theory of mind, self-referential and affective decision making. What processing demands are shared in common across such a variety of tasks is presently unclear, and to disentangle such high level tasks into component processes is challenging. Here, we address some of these aspects by reviewing the current MEG studies on this network. In fact, while MEG data confirm the observed fMRI spatial topography, some new intriguing temporal and frequency properties of this network are revealed. Such findings enrich the original fMRI scenario on the DMN functional roles in terms of internal coupling and cross-network communication in the brain at rest. The Default Mode Network's internal coupling seems to be characterized by slow frequencies in the alpha and beta range and the cross-network interaction reveals that the DMN plays a central role in the communication across many different resting state networks. © 2014 Springer-Verlag Berlin Heidelberg. All rights are reserved.
    No preview · Article · Jul 2012
  • Source
    Sara Spadone · Francesco de Pasquale · Dante Mantini · Stefania Della Penna
    [Show abstract] [Hide abstract]
    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).
    Full-text · Article · May 2012 · NeuroImage
  • Source
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · May 2012 · Neuron

  • No preview · Conference Paper · May 2012

Publication Stats

781 Citations
152.20 Total Impact Points

Institutions

  • 2008-2014
    • Università degli Studi G. d'Annunzio Chieti e Pescara
      • • Institute for Advanced Biomedical Technologies ITAB
      • • Department of Neuroscience & Imaging
      Chieta, Abruzzo, Italy
  • 2006-2014
    • Foundation Santa Lucia
      Roma, Latium, Italy
  • 2004-2009
    • University of Plymouth
      Plymouth, England, United Kingdom
  • 2002
    • National Institute of Geophysics and Volcanology
      Roma, Latium, Italy
  • 2000
    • Italian National Research Council
      Roma, Latium, Italy