Perception and action are inextricably linked, down to the level of single cells which have both visual and motor response properties - dubbed 'mirror neurons'. The mirror neuron system is generally associated with direct-matching or resonance between observed and executed actions (and goals). Yet in everyday interactions responding to another's movements with matching actions (or goals) is not always appropriate. Here we examine processes associated with intentionally not imitating, as separable from merely detecting an observed action as mismatching one's own. Using fMRI, we test how matched and mismatched stimulus-response mapping for actions is modulated depending on task-relevance. Participants were either cued to intentionally copy or oppose a presented action (intentional imitation or counter-imitation), or cued to perform a predefined action regardless of the presented action (incidental imitation or counter-imitation). We found distinct cortical networks underlying imitation compared to counter-imitation, involving areas typically associated with an action observation network and widespread occipital activation. Intentionally counter-imitating particularly involved frontal-parietal networks, including the insula and cingulate cortices. This task-dependent recruitment of frontal networks for the intentional selection of opposing responses supports previous evidence for the preparatory suppression of imitative responses. Sensorimotor mirroring is modulated via control processes, which complex human interactions often require.

When the human brain manifests the birth of organised communication among local and large-scale neuronal populations activity remains undescribed. We report, in resting-state EEG source-estimates of 100 infants at term age, the existence of macro-scale dynamic functional connectivity, which have rich topological organisations, distinct spectral fingerprints and scale-invariance temporal dynamics. These functional networks encompass the default mode, primary sensory-limbic system, thalamo-frontal, thalamo-sensorimotor and visual-limbic system confined in the delta and low-alpha frequency intervals (1-8 Hz). The temporal dynamics of these networks not only are nested within much slower timescale (<0.1 Hz) but also correlated in a hierarchical leading-following organisation. We show that the anatomically constrained richly organised spatial topologies, spectral contents and temporal fluctuations of resting-state networks reflect an established intrinsic dynamic functional connectome in the human brain at term age. The graph theoretical analysis of the spatial architectures of the networks revealed small-world topology and distinct rich-club organisations of interconnected cortical hubs that exhibit rich synchronous dynamics at multiple timescales. The approach opens new avenues to advance our understanding about the early configuration organisation of dynamic networks in the human brain and offers a novel monitoring platform to investigate functional brain network development in sick preterm infants.

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Synchronous oscillations of neuronal populations support resting-state cortical activity.Recent studies indicate that resting-state functional connectivity is not static, but exhibits complex dynamics. The mechanisms underlying the complex dynamics of cortical activity have not been well characterised. Here, we directly apply singular value decomposition (SVD) in source-reconstructed electroencephalography (EEG) in order to characterise the dynamics of spatiotemporal patterns of resting-state functional connectivity. We found that changes in resting-state functional connectivity were associated with distinct complex topological features, "Rich-Club organisation", of the default mode network, salience network, and motor network. Rich-club topology of the salience network revealed greater functional connectivity between ventrolateral prefrontal cortex and anterior insula, whereas Rich-club topologies of the default mode networks revealed bilateral functional connectivity between fronto-parietal and posterior cortices. Spectral analysis of the dynamics underlying Rich-club organisations of these source-space network patterns revealed that resting-state cortical activity exhibit distinct dynamical regimes whose intrinsic expressions contain fast oscillations in the alphabeta band and with the envelope-signal in the timescale of < 0.1 Hz. Our findings thus demonstrated that multivariate eigen-decomposition of source-reconstructed EEG is a reliable computational technique to explore how dynamics of spatiotemporal features of the resting-state cortical activity occur that oscillate at distinct frequencies.