Biomedical subjects

Viktor K Jirsa

Publications and source records attributed to Viktor K Jirsa.

12 recordsLinked to original sources

PubMed2006

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↗

PubMed2006

How do neural connectivity and time delays influence bimanual coordination?

Multilevel crosstalk as a neural basis for motor control has been widely discussed in the literature. Since no natural process is instantaneous, any crosstalk model should incorporate time delays, which are known to induce temporal coupling between functional elements and stabilize or destabilize a particular mode of coordination. In this article, we systematically study the dynamics of rhythmic bimanual coordination under the influence of varying connection topology as realized by callosal fibers, cortico-thalamic projections, and crossing peripheral fibers. Such connectivity contributes to various degrees of neural crosstalk between the effectors which we continuously parameterize in a mathematical model. We identify the stability regimes of bimanual coordination as a function of the degree of neural crosstalk, movement amplitude and the time delays involved due to signal processing. Prominent examples include explanations of the decreased stability of the antiphase mode of coordination in split brain patients and the role of coupling in mediating bimanual coordination.

Hand↗

PubMed2006

Synchronization in networks with random interactions: theory and applications.

Synchronization is an emergent property in networks of interacting dynamical elements. Here we review some recent results on synchronization in randomly coupled networks. Asymptotical behavior of random matrices is summarized and its impact on the synchronization of network dynamics is presented. Robert May's results on the stability of equilibrium points in linear dynamics are first extended to systems with time delayed coupling and then nonlinear systems where the synchronized dynamics can be periodic or chaotic. Finally, applications of our results to neuroscience, in particular, networks of Hodgkin-Huxley neurons, are included.

Action Potentials↗

PubMed2005

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↗

PubMed2005

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↗

PubMed2005

The excitator as a minimal model for the coordination dynamics of discrete and rhythmic movement generation.

The authors identify a class of excitable two-dimensional model systems, the excitators, that provide an entry point to the understanding of the mechanisms of discrete and rhythmic movement generation and a variety of related phenomena, such as false starts and the geometry of phase space trajectories. The starting point of their analysis is the topological properties of the phase flow. In particular, the phenomenon of false starts provides a characteristic structural condition for the phase flow, the separatrix, which partitions the phase space. Threshold phenomena, which are characteristic of excitable systems, as well as stable and unstable fixed points and periodic orbits, are discussed. Stable manifolds in the proximity of fixed points, resulting in an overshoot and a slow return phase after movement execution, are predicted in the analysis. To investigate coordination phenomena, the authors discuss the effects of two types of couplings, the sigmoidal coupling and a truncated version thereof, known as the Haken-Kelso-Bunz (HKB) coupling. They show analytically and numerically that the sigmoidal coupling leads to convergence phenomena in phase space, whereas the HKB coupling displays convergent as well as divergent behaviors. The authors suggest a specific representation of the excitator that allows the quantification of the predictions.

Humans↗

PubMed2004

Will a large complex system with time delays be stable?

In 1972 May showed that for a large linear system with random coupling the system size and the average coupling strength must together satisfy a simple inequality to ensure the stability of the equilibrium point. Here we extend the analysis to delay coupled systems. Our calculations establish that the same inequality obtained by May constrains the stability for systems randomly coupled through discrete and distributed delays.

Journal Article↗

PubMed2004

Enhancement of neural synchrony by time delay.

In a network of neuronal oscillators with time-delayed coupling, we uncover a phenomenon of enhancement of neural synchrony by time delay: a stable synchronized state exists at low coupling strengths for significant time delays. By formulating a master stability equation for time-delayed networks of Hindmarsh-Rose neurons, we show that there is always an extended region of stable synchronous activity corresponding to low coupling strengths. Such synchrony could be achieved in the undelayed system only by much higher coupling strengths. This phenomenon of enhanced neural synchrony by delay has important implications, in particular, in understanding synchronization of distant neurons and information processing in the brain.

Animals↗

PubMed2004

Transitions to synchrony in coupled bursting neurons.

Certain cells in the brain, for example, thalamic neurons during sleep, show spike-burst activity. We study such spike-burst neural activity and the transitions to a synchronized state using a model of coupled bursting neurons. In an electrically coupled network, we show that the increase of coupling strength increases incoherence first and then induces two different transitions to synchronized states, one associated with bursts and the other with spikes. These sequential transitions to synchronized states are determined by the zero crossings of the maximum transverse Lyapunov exponents. These results suggest that synchronization of spike-burst activity is a multi-time-scale phenomenon and burst synchrony is a precursor to spike synchrony.

Action Potentials↗

PubMed2004

Perceptual-cognitive control as a special case in equivalent multisensory-sensorimotor interactions.

In his primary thesis on the purely perceptual-cognitive nature of movement control, F. Mechsner (2004) entirely neglects, or in fact negates, the influences of action on perception. In this commentary, the author follows the logical steps of Mechsner, illustrates what he conceives to be an error in Mechsner's reasoning, and synthesizes those arguments in favor of a hypothesis of a system of equivalent elements (senses and effectors) in interaction.

Cognition↗

PubMed2004

Connectivity and dynamics of neural information processing.

In this article, we systematically review the current literature on neural connectivity and dynamics, or equivalently, structure and function. In particular, we discuss how changes in the connectivity of a neural network affect the spatiotemporal network dynamics qualitatively. The three major criteria of comparison are, first, the local dynamics at the network nodes which includes fixed point dynamics, oscillatory and chaotic dynamics; second, the presence of time delays via propagation along connecting pathways; and third, the properties of the connectivity matrix such as its statistics, symmetry, and translational invariance. Since the connection topology changes when anatomical scales are traversed, so will the corresponding network dynamics change. As a consequence different types of networks are encountered on different levels of neural organization.

Animals↗

PubMed2002

Spatiotemporal forward solution of the EEG and MEG using network modeling.

Dynamic systems have proven to be well suited to describe a broad spectrum of human coordination behavior such synchronization with auditory stimuli. Simultaneous measurements of the spatiotemporal dynamics of electroencephalographic (EEG) and magnetoencephalographic (MEG) data reveals that the dynamics of the brain signals is highly ordered and also accessible by dynamic systems theory. However, models of EEG and MEG dynamics have typically been formulated only in terms of phenomenological modeling such as fixed-current dipoles or spatial EEG and MEG patterns. In this paper, it is our goal to connect three levels of organization, that is the level of coordination behavior, the level of patterns observed in the EEG and MEG and the level of neuronal network dynamics. To do so, we develop a methodological framework, which defines the spatiotemporal dynamics of neural ensembles, the neural field, on a sphere in three dimensions. Using magnetic resonance imaging we map the neural field dynamics from the sphere onto the folded cortical surface of a hemisphere. The neural field represents the current flow perpendicular to the cortex and, thus, allows for the calculation of the electric potentials on the surface of the skull and the magnetic fields outside the skull to be measured by EEG and MEG, respectively. For demonstration of the dynamics, we present the propagation of activation at a single cortical site resulting from a transient input. Finally, a mapping between finger movement profile and EEG/MEG patterns is obtained using Volterra integrals.

Algorithms↗