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Collins G Assisi

Publications and source records attributed to Collins G Assisi.

3 recordsLinked to original sources

Multisensory integration for timing engages different 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.

Acoustic Stimulation↗

Dynamics of multifrequency coordination using parametric driving: theory and experiment.

The coupling of movement behavior and environmental signals has been extensively studied within the domain of rhythmic coordination tasks. However, in contrast to most traditional coordination studies, here we drive the coupled sensorimotor system far beyond the frequency regime in which these signals may be synchronized. Our goal is to identify the properties of the coupling between the human subject and the environment. Earlier studies have shown that the environmental signal may be parametrically coupled to the effectors. A necessary feature of parametrically driven oscillators is the existence of stable 1:1 and 1:2 coordination modes. Here, we test this prediction experimentally using a coordination paradigm in which subjects were asked to coincide peak finger flexion with an auditory metronome beat. The rate of the metronome was increased in steps of 0.5 Hz from 2.5 Hz to 12 Hz. It was observed that the subjects shifted involuntarily from a 1:1 to a 1:2 coordination mode at high driving frequencies, as predicted. These results are examined in the context of an extended form of the Haken-Kelso-Bunz (Haken et al. 1985) model (HKB) for bimanual coordination, which includes a parametric driving term (Jirsa et al. 2000). Unimanual coordination is treated as a special case of this extended model. An important feature of the HKB model is bistability and the presence of a phase transition from an anti-phase mode to in-phase mode of coordination. Our description of unimanual coordination leads to a mechanism for phase transitions that is distinct from that seen in the HKB model. The transition is mediated by the dynamics of both the amplitude and the phase of the oscillator. More generally, we propose the existence of two types of transitions in our extended theory, that is, phase-mediated and amplitude-mediated transitions. Both have characteristic features; in particular, their transients are mutually orthogonal in the plane spanned by the amplitude and phase of the oscillator. The analytical and numerical results of our theoretical model are demonstrated to compare favorably with our experimental results.

Adult↗

Synchrony and clustering in heterogeneous networks with global coupling and parameter dispersion.

Networks with nonidentical nodes and global coupling may display a large variety of dynamic behaviors, such as phase clustered solutions, synchrony, and oscillator death. The network dynamics is a function of the parameter dispersion and may be captured by conventional mean field approaches if it is close to the completely synchronous state. In this Letter we introduce a novel method based on a mode decomposition in the parameter space, which provides a low-dimensional network description for more complex dynamic behaviors and captures the mean field approach as a special case. The example of globally coupled Fitzhugh-Nagumo neurons is discussed.

Action Potentials↗