-
[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.
NeuroImage 12/2012; · 5.89 Impact Factor
-
-
[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. J. Magn. Reson. Imaging 2012. © 2012 Wiley Periodicals, Inc.
Journal of Magnetic Resonance Imaging 09/2012; · 2.70 Impact Factor
-
[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.
Neuron 05/2012; 74(4):753-64. · 14.74 Impact Factor
-
[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). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are confirmed by a comparison with a MEG tailored version of the self-organizing group ICA, which is largely used for fMRI IC clustering.
NeuroImage 05/2012; 62(3):1912-23. · 5.89 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: 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 were investigated by pharmacological magnetic resonance imaging (phMRI) at 4.7 T in adult isoflurane-anaesthetized rats. Axial echo-planar images were collected from the prefrontal cortex (PFC), ventral (nucleus accumbens, NAcc) and dorsal (dStr) striata, the hippocampus and the thalamus. After consecutive image collection for 30 min (50 baseline images), adult rats received either SB269970 (3mg/kg), 8-OH-DPAT (0.06 mg/kg) or saline intra-peritoneally (i.p.) via a remote cannula; the images were then collected for further 30 min (50 post-treatment images). Data were analysed 1) through an activation map generated on brain templates, obtained by using animals from each experimental group; 2) by a two-way ANOVA for the evaluation of temporal profiles, extracted within selected ROIs of each animal. Both compounds increased the BOLD signal in the areas of interest: SB269970, the selective 5-Ht7 antagonist, induced a significant effect in the PFC, particularly the orbital (oPFC) region, and in the NAcc. This effect started 6 to 12 min after drug administration, reached a maximum (+2.8%/+2.3%) at 12 to 18 min, and then moved to the dorsal thalamic nuclei. In contrast, the effects of 8-OH-DPAT were first observed in midline thalamic nuclei, and later appeared in forebrain regions: its effects were modest and transient within the NAcc and oPFC (+1.7% at 18 to 24 min after injection), whereas they were higher and long-lasting in the dStr and PFC, specifically the medial (mPFC) region (+3.1%/+4.0% from 15 min after drug administration onwards). The brain BOLD changes, reported as a consequence of selective 5-Ht7 antagonist administration, seemed restricted to the oPFC, NAcc and dorso-thalamic circuits, whereas the non-selective blockade of serotonergic receptors affected the mPFC, dStr and mid(line)-thalamic circuitry. The present findings revealed two differential serotonergic sub-pathways, as evidenced by the detection of physiological vascular feedback and/or neuronal activation.
NeuroImage 07/2011; 58(3):885-94. · 5.89 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: 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 brain components (ICs); next, the channel maps associated with the latter ones are projected into the source space and the resulting voxel-wise weights are used to linearly combine the IC time courses. An extensive description of the proposed pipeline is provided here, along with an assessment of its performances with respect to alternative approaches. The following investigations were carried out: (1) ICA decomposition algorithm. Synthetic data are used to assess the sensitivity of the ICA results to the decomposition algorithm, by testing FastICA, INFOMAX, and SOBI. FastICA with deflation approach, a standard solution, provides the best decomposition. (2) Recombination of brain ICs versus subtraction of artifactual ICs (at the channel level). Both the recombination of the brain ICs in the sensor space and the classical procedure of subtracting the artifactual ICs from the recordings provide a suitable reconstruction, with a lower distortion using the latter approach. (3) Recombination of brain ICs after localization versus localization of artifact-corrected recordings. The brain IC recombination after source localization, as implemented in the proposed pipeline, provides a lower source-level signal distortion. (4) Detection of RSNs. The accuracy in source-level reconstruction by the proposed pipeline is confirmed by an improved specificity in the retrieval of RSNs from experimental data.
Brain connectivity. 01/2011; 1(1):49-59.
-
Francesco de Pasquale,
Stefania Della Penna,
Abraham Z Snyder,
Christopher Lewis,
Dante Mantini,
Laura Marzetti,
Paolo Belardinelli,
Luca Ciancetta,
Vittorio Pizzella,
Gian Luca Romani,
Maurizio Corbetta
[show abstract]
[hide abstract]
ABSTRACT: 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, we describe magnetoencephalographic correspondents of two well-characterized RSNs: the dorsal attention and the default mode networks. Seed-based correlation mapping was performed using time-dependent MEG power reconstructed at each voxel within the brain. The topography of RSNs computed on the basis of extended (5 min) epochs was similar to that observed with fMRI but confined to the same hemisphere as the seed region. Analyses taking into account the nonstationarity of MEG activity showed transient formation of more complete RSNs, including nodes in the contralateral hemisphere. Spectral analysis indicated that RSNs manifest in MEG as synchronous modulation of band-limited power primarily within the theta, alpha, and beta bands-that is, in frequencies slower than those associated with the local electrophysiological correlates of event-related BOLD responses.
Proceedings of the National Academy of Sciences 03/2010; 107(13):6040-5. · 9.68 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Adolescent rodents differ markedly from adults in several neuro-behavioural parameters. Moreover, 'paradoxical' responses to psychostimulants have been reported at this age.
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 methylphenidate (MPH). We used pharmacological magnetic resonance imaging (phMRI) performed at 4.7 T under isoflurane anaesthesia. Following anatomical MRI, axial gradient echo images were collected continuously. After baseline recording (32 min), animals received MPH (0 or 4 mg/kg i.p.) and were recorded for further 32 min.
Region-specific changes in the blood-oxygenation level dependent (BOLD) signal were evident as a function of age. As expected, among adults MPH induced an increase of BOLD signal in nucleus accumbens (NAcc) and prefrontal cortex (PFC), with no effects in the hippocampus (Hip). Notably, among adolescents, MPH induced a marked and generalised decrease of BOLD signal, which occurred earlier in NAcc and PFC whilst being delayed in the Hip. Any bias in BOLD responses was excluded by the measurement of physiological parameters.
The present findings highlight the utility of phMRI in animal models. The peculiar negative BOLD effect found in adolescent rats may be suggestive of a reduced cerebro-vascular feedback and/or an increased MPH-induced neuronal activation. Data are relevant for a better understanding of brain/behavioural regulation during adolescent development. Moreover, a greater understanding of the differences between adult and adolescent drug responses will aid in the development of a more appropriate age-specific treatment strategy.
Psychopharmacologia 11/2008; 203(1):143-53. · 4.08 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: We propose an application of a Bayesian methodology to dynamic MR images of protons J-coupled to 13C nuclei for monitoring the in vivo 13C-glucose uptake of mouse brain. The very low population of these protons and the random noise make the analysis of these images extremely difficult. The proposed method restores the images and provides an "activation" map of the mouse brain by means of a hypothesis testing procedure. The restoration step is performed in the Bayesian framework so that among the other advantages of a stochastic approach, it is possible to model spatial and temporal information about neighboring pixels. This leads to a restoration procedure able to reduce the noise level while preserving the information about the edges of signal areas. Based on the restored images, the testing procedure provides us with a reliable map of pixels characterized by the 13C-glucose uptake.
Magnetic Resonance Imaging 06/2005; 23(4):577-84. · 1.99 Impact Factor
