[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.
[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.
[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.
[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.
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).
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.
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.
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.
[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.
[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.
[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.
[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.
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.
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
[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.
[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).
[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.
[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.
[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.
[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. DOI:10.1073/pnas.0913863107 · 9.67 Impact Factor