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Mingzhou Ding

Publications and source records attributed to Mingzhou Ding.

22 records · Page 2Linked to original sources

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↗