PubMed Health⌕ Search

Biomedical subjects

Mingzhou Ding

Publications and source records attributed to Mingzhou Ding.

7 recordsLinked to original sources

General stability analysis of synchronized dynamics in coupled systems.

We consider the stability of synchronized states (including equilibrium point, periodic orbit, or chaotic attractor) in arbitrarily coupled dynamical systems (maps or ordinary differential equations). We develop a general approach, based on the master stability function and Gershgörin disk theory, to yield constraints on the coupling strengths to ensure the stability of synchronized dynamics. Systems with specific coupling schemes are used as examples to illustrate our general method.

Journal Article↗

Synchronized activity in prefrontal cortex during anticipation of visuomotor processing.

It is commonly presumed, though not well established, that the prefrontal cortex exerts top-down control of sensory processing. One aspect of this control is thought to be a facilitation of sensory pathways in anticipation of such processing. To investigate the possible involvement of prefrontal cortex in anticipatory top-down control, we studied the statistical relations between prefrontal activity, recorded while a macaque monkey waited for presentation of a visual stimulus, and subsequent sensory and motor events. Local field potentials were simultaneously recorded from prefrontal, motor, occipital and temporal cortical sites in the left cerebral hemisphere. Spectral power and coherence analysis revealed that during stimulus anticipation three of five prefrontal sites participated in a coherent oscillatory network synchronized in the beta-frequency range. Pre-stimulus network power and coherence were highly correlated with the amplitude and latency of early visual evoked potential components in visual cortical areas, and with response time. The results suggest that synchronized oscillatory networks in prefrontal cortex are involved in top-down anticipatory mechanisms that facilitate subsequent sensory processing in visual cortex. They further imply that stronger top-down control leads to larger and faster sensory responses, and a subsequently faster motor response.

Animals↗

Task-related power and coherence changes in neuromagnetic activity during visuomotor coordination.

We analyzed a set of full-head (66 channels, CTF Inc.) magnetoencephalography (MEG) data recorded when 5 subjects performed rhythmic right index-finger flexion and extension movements on the beat (synchronization) or off the beat (syncopation) with a visual metronome at 1 Hz. Neuromagnetic activities in the alpha (8-14 Hz), beta (15-30 Hz) and gamma (30-50 Hz) ranges were shown to correlate with different aspects of the task. Specifically, we found that, compared with the control condition in which subjects only looked at the visual metronome without making any movement, all the movement conditions were accompanied by a decrease of power in the alpha range (8-14 Hz) in sensorimotor channels of both hemispheres, and an increase of coherence among a subset of these channels. The same comparison showed that power changes in the beta range differentiate task conditions by exhibiting power increases for synchronization and power decreases for syncopation. Changes in the gamma range power were found to be related to the kinematics of movement trajectories (flexion versus extension). These results suggest that three important cortical oscillations play different functional roles in a visuomotor timing task.

Alpha Rhythm↗

Statistical analysis of timing errors.

Human rhythmic activities are variable. Cycle-to-cycle fluctuations form the behavioral observable. Traditional analysis focuses on statistical measures such as mean and variance. In this article we show that, by treating the fluctuations as a time series, one can apply techniques such as power spectra and rescaled range analysis to gain insight into the mechanisms underlying the remarkable abilities of humans to perform a variety of rhythmic movements, from maintaining memorized temporal patterns to anticipating and timing their movements to predictable sensory stimuli.

Humans↗

Trial-to-trial variability of cortical evoked responses: implications for the analysis of functional connectivity.

OBJECTIVES: The time series of single trial cortical evoked potentials typically have a random appearance, and their trial-to-trial variability is commonly explained by a model in which random ongoing background noise activity is linearly combined with a stereotyped evoked response. In this paper, we demonstrate that more realistic models, incorporating amplitude and latency variability of the evoked response itself, can explain statistical properties of cortical potentials that have often been attributed to stimulus-related changes in functional connectivity or other intrinsic neural parameters. METHODS: Implications of trial-to-trial evoked potential variability for variance, power spectrum, and interdependence measures like cross-correlation and spectral coherence, are first derived analytically. These implications are then illustrated using model simulations and verified experimentally by the analysis of intracortical local field potentials recorded from monkeys performing a visual pattern discrimination task. To further investigate the effects of trial-to-trial variability on the aforementioned statistical measures, a Bayesian inference technique is used to separate single-trial evoked responses from the ongoing background activity. RESULTS: We show that, when the average event-related potential (AERP) is subtracted from single-trial local field potential time series, a stimulus phase-locked component remains in the residual time series, in stark contrast to the assumption of the common model that no such phase-locked component should exist. Two main consequences of this observation are demonstrated for statistical measures that are computed on the residual time series. First, even though the AERP has been subtracted, the power spectral density, computed as a function of time with a short sliding window, can nonetheless show signs of modulation by the AERP waveform. Second, if the residual time series of two channels co-vary, then their cross-correlation and spectral coherence time functions can also be modulated according to the shape of the AERP waveform. Bayesian estimation of single-trial evoked responses provides further proof that these time-dependent statistical changes are due to remnants of the evoked phase-locked component in the residual time series. CONCLUSIONS: Because trial-to-trial variability of the evoked response is commonly ignored as a contributing factor in evoked potential studies, stimulus-related modulations of power spectral density, cross-correlation, and spectral coherence measures is often attributed to dynamic changes of the connectivity within and among neural populations. This work demonstrates that trial-to-trial variability of the evoked response must be considered as a possible explanation of such modulation.

Animals↗

Control and synchronization of chaos in high dimensional systems: Review of some recent results.

Controlling chaos and synchronization of chaos have evolved for a number of years as essentially two separate areas of research. Only recently it has been realized that both subjects share a common root in control theory. In addition, as limitations of low dimensional chaotic systems in modeling real world phenomena become increasingly apparent, investigations into the control and synchronization of high dimensional chaotic systems are beginning to attract more interest. We review some recent advances in control and synchronization of chaos in high dimensional systems. Efforts will be made to stress the common origins of the two subjects. (c) 1997 American Institute of Physics.

Journal Article↗

Characterizing the dynamics of auditory perception.

After listening to a sound that is presented repeatedly, subjects report hearing different transforms of the original sound. The frequency of reported transforms is a sensitive index of some speech disorders as well as cognitive flexibility in aging. In this paper, we propose and investigate quantitative measures that characterize the dynamics of this phenomenon, known as the verbal transformation effect. In particular, we show that the distribution of the dwell time, the time spent perceiving a string of a given phonemic form before switching to another form, obeys a power law for normal subjects with an exponent valued between 1 and 2. This result suggests that within this paradigm there is no characteristic time scale for the perceptual process. Additionally, we analyze the correlation properties of the transforms. We suggest that the complexity measures and techniques introduced here might be useful diagnostic tools for a number of speech and cognitive disorders. (c) 1995 American Institute of Physics.

Journal Article↗