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Bimanual coordination engages a distributed network of brain areas, the spatiotemporal organization of which has given rise to intense debates. Do bimanual movements require information processing in the same set of brain areas that are engaged by movements of the individual components (left and right hands)? Or is it necessary that other brain areas are recruited to help in the act of coordination? These two possibilities are often considered as mutually exclusive, with studies yielding support for one or the other depending on techniques and hypotheses. However, as yet there is no account of how the two views may work together dynamically. Using the method of Mode-Level Cognitive Subtraction (MLCS) on high density EEG recorded during unimanual and bimanual movements, we expose spatiotemporal reorganization of large-scale cortical networks during stable inphase and antiphase coordination and transitions between them. During execution of stable bimanual coordination patterns, neural dynamics were dominated by temporal modulation of unimanual networks. At instability and transition, there was evidence for recruitment of additional areas. Our study provides a framework to quantify large-scale network mechanisms underlying complex cognitive tasks often studied with macroscopic neurophysiological recordings., (Copyright © 2012 Elsevier Inc. All rights reserved.)

This study sought to investigate the effects of manipulating social coordination on brain synchronization/de-synchronization in the mu band. Mu activation is associated with understanding and coordinating motor acts and may play a key role in mediating social interaction. Members of a dyad were required to interact with one another in a rhythmic finger movement coordination task under various instructions: intrinsic where each member of the dyad was instructed to maintain their own and ignore their partner's movement; in-phase where they were asked to synchronize with their partner's movement; and anti-phase where they were instructed to syncopate with their partner's movement. EEG and movement data were recorded simultaneously from both subjects during all three tasks and a control condition. Log power ratios of EEG activity in the active conditions versus control were used to assess the effect of task context on synchronization/de-synchronization in the mu spectral domain. Results showed clear and systematic modulation of mu band activity in the 10-12 Hz range as a function of coordination context. In the left hemisphere general levels of alpha-mu suppression increased progressively as one moved from intrinsic through in-phase to anti-phase contexts but with no specific central-parietal focus. In contrast the right hemisphere displayed context-specific changes in the central-parietal region. The intrinsic condition showed a right synchronization which disappeared with the in-phase context even as de-synchronization remained greater in the left hemisphere. Anti-phase was associated with larger mu suppression in the right in comparison with left at central-parietal region. Such asymmetrical changes were highly correlated with changing behavioral dynamics. These specific patterns of activation and deactivation of mu activity suggest that localized neural circuitry in right central-parietal regions mediates how individuals interpret the movements of others in the context of their own actions. A right sided mechanism in the 10-12 Hz range appears to be involved in integrating the mutual information among the members of a dyad that enables the dynamics of social interaction to unfold in time., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Contemporary brain theories of cognitive function posit spatial, temporal and spatiotemporal reorganization as mechanisms for neural information processing. Corresponding brain imaging results underwrite this perspective of large-scale reorganization. As we show here, a suitable choice of experimental control tasks allows the disambiguation of the spatial and temporal components of reorganization to a quantifiable degree of certainty. When using electro- or magnetoencephalography (EEG or MEG), our approach relies on the identification of lower dimensional spaces obtained from the high dimensional data of suitably chosen control task conditions. Encephalographic data from task conditions are reconstructed within these control spaces. We show that the residual signal (part of the task signal not captured by the control spaces) allows the quantification of the degree of spatial reorganization, such as recruitment of additional brain networks.

How does the brain integrate information from different senses into a unitary percept? What factors influence such multisensory integration? Using a rhythmic behavioral paradigm and functional magnetic resonance imaging, we identified networks of brain regions for perceptions of physically synchronous and asynchronous auditory-visual events. Measures of behavioral performance revealed the existence of three distinct perceptual states. Perception of asynchrony activated a network of the primary sensory, prefrontal, and inferior parietal cortices, perception of synchrony disengaged the inferior parietal cortex and further recruited the superior colliculus, and when no clear percept was established, only the residual areas comprised of prefrontal and sensory areas were active. These results indicate that distinct percepts arise within specific brain sub-networks, the components of which are differentially engaged and disengaged depending on the timing of environmental signals.

Growing evidence suggests that interval timing in humans is supported by distributed brain networks. Recently, we demonstrated that the specific network recruited for the performance of rhythmic timing is not static but is influenced by the coordination pattern employed during interval acquisition. Here we expand on this previous work to investigate the role of stimulus modality and coordination pattern in determining the brain areas recruited for performance of a self-paced rhythmic timing task. Subjects were paced with either a visual or an auditory metronome in either a synchronized (on the beat) or syncopated (off the beat) coordination pattern. The pacing stimulus was then removed and subjects continued to move based on the required interval. When compared with networks recruited for auditory pacing and continuation, the visual-specific activity was observed in the classic dorsal visual stream that included bilateral MT/V5, bilateral superior parietal lobe, and right ventral premotor cortex. Activity in these regions was present not only during pacing, when visual information is used to guide motor behavior, but also during continuation, when visual information specifying the temporal interval was no longer present. These results suggest a role for modality-specific areas in processing and representing temporal information. The cognitive demands imposed by syncopated coordination resulted in increased activity in a broad network that included supplementary motor area, lateral pre-motor cortex, bilateral insula, and cerebellum. This coordination-dependent activity persisted during the subsequent continuation period, when stimuli were removed and no coordination constraints were imposed. Taken together, the present results provide additional evidence that time and timing are served by a context-dependent distributed network rooted in basic sensorimotor processes.

A full-head 143-channel superconducting quantum interference device was used to study changes occurring in the magnetic activity of the human brain during performance of an auditory-motor coordination task in which the rate of coordination was systematically increased. Previous research using the same task paradigm demonstrated that spontaneous switches in timing behavior that arise with higher coordination rates are accompanied by qualitative changes in spatiotemporal brain activity measured by electro- and magnetoencephalography. Here we show how these patterns can be decomposed into basic physiological events, i.e., evoked brain responses to acoustic tones and self-initiated finger movements. The frequency dependence of the amplitudes of these component responses may shed new light onto why spontaneous timing transitions occur in the first place., (Copyright 2000 Academic Press.)

Earlier research established that spontaneous changes in human sensorimotor coordination are accompanied by qualitative changes in the spatiotemporal dynamics of neural activity measured by multisensor electroencephalography and magnetoencephalography. More recent research has demonstrated that a robust relation exists between brain activity and the movement profile produced. In particular, brain activity has been shown to correlate strongly with movement velocity independent of movement direction and mode of coordination. Using a recently developed field theoretical model of large-scale brain activity itself based on neuroanatomical and neurophysiological constraints we show here how these experimental findings relate to the field theory and how it is possible to reconstruct the movement profile via spatial and temporal integration of the brain signal. There is a unique relation between the quantities in the theory and the experimental data, and fit between the shape of the measured and the reconstructed time series for the movement is remarkably good given that there are no free parameters., (Copyright 2000 Academic Press.)