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Dynamics of human sensorimotor coordination: From behavior to brain activity
Title
Dynamics of human sensorimotor coordination: From behavior to brain activity.
Creator
Chen, Yanqing, Florida Atlantic University, Ding, Mingzhou, Kelso, J. A. Scott
Abstract/Description
The dynamics of human sensorimotor coordination are studied at behavioral and neural levels through temporal synchronization and syncopation tasks. In experiment 1, subjects synchronized their finger movements (in-phase) with a metronome at 2.0Hz and 1.25Hz for 1200 cycles. Fluctuations of timing errors were analyzed through correlation, power spectrum analyses and Maximum Likelihood Estimation (MLE). Results indicated that the synchronization error time series was characterized by a 1/falpha...
Show moreThe dynamics of human sensorimotor coordination are studied at behavioral and neural levels through temporal synchronization and syncopation tasks. In experiment 1, subjects synchronized their finger movements (in-phase) with a metronome at 2.0Hz and 1.25Hz for 1200 cycles. Fluctuations of timing errors were analyzed through correlation, power spectrum analyses and Maximum Likelihood Estimation (MLE). Results indicated that the synchronization error time series was characterized by a 1/falpha type of long memory process with alpha = 0.5. Previous timing models based upon motor program or simple "central clock" ideas were reviewed to show that they could not explain such long range correlations in the synchronization task. To explore the possible cognitive origins of long range correlation, experiment 2 required subjects to synchronize (on the beat) or syncopate (off the beat) to a metronome at 1Hz using different cognitive strategies. Timing fluctuations were again found to be 1/f alpha type, with alpha = 0.5 in synchronization and alpha = 0.8 in syncopation. When subjects employed a synchronization strategy to successfully syncopate, timing fluctuations shifted toward 1/f 0.5 type. This experiment indicated that the scaling exponent in timing fluctuations was related to task requirements and specific coordination strategies. Further, they suggest that the sources of such long memory originated from higher level cognitive processing in the human brain. Experiment 3 analyzed magnetoencephalography (MEG) data associated with synchronization and syncopation tasks. Brain oscillations at alpha (8--14Hz), beta (15--20Hz) and gamma (35--40Hz) frequency ranges were shown to correlate with different aspects of the coordination behavior. Specifically, through power and coherence analyses, alpha activity was linked to sensorimotor integration and "binding", beta activity was related to task requirements (synchronization or syncopation), and gamma activity was related to movement kinematics (trajectory). These results supported the idea that the 1/f alpha type of timing fluctuations originated from collective neural activities in the brain acting on multiple time scales.
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Date Issued
2000
PURL
http://purl.flvc.org/fcla/dt/12649
Subject Headings
Sensorimotor integration, Cognitive neuroscience
Format
Document (PDF)
Time series analysis and correlation dimension estimation: Mathematical foundation and applications
Title
Time series analysis and correlation dimension estimation: Mathematical foundation and applications.
Creator
Jiang, Wangye, Florida Atlantic University, Ding, Mingzhou, Charles E. Schmidt College of Science, Department of Mathematical Sciences
Abstract/Description
A time series is a data set of a single quantity sampled at intervals T time units apart. It is widely used to represent a chaotic dynamical system. The correlation dimension measures the complexity of a dynamical system. Using the delay-coordinate map and the extended GP algorithm one can estimate the correlation dimension of an experimental dynamical system from measured time series. This thesis discusses the mathematical foundation of the methods and the corresponding applications. The...
Show moreA time series is a data set of a single quantity sampled at intervals T time units apart. It is widely used to represent a chaotic dynamical system. The correlation dimension measures the complexity of a dynamical system. Using the delay-coordinate map and the extended GP algorithm one can estimate the correlation dimension of an experimental dynamical system from measured time series. This thesis discusses the mathematical foundation of the methods and the corresponding applications. The embedding theorems and their relationship with dimension preservation are reviewed in detail, but more attention is focussed on the concept development.
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Date Issued
1995
PURL
http://purl.flvc.org/fcla/dt/15213
Subject Headings
Time-series analysis--Mathematical models, Chaotic behavior in systems
Format
Document (PDF)