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Several neuroimaging studies reported that a common set of regions is 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., (Copyright © 2014 Elsevier Inc. All rights reserved.)

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 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., (Copyright © 2013 Elsevier Inc. All rights reserved.)

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., (Copyright © 2012 Elsevier Inc. All rights reserved.)

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., (Copyright © 2012 Elsevier Inc. All rights reserved.)

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., (Copyright © 2011 Elsevier Inc. All rights reserved.)