Po Lei Lee

Orthographic and phonological processing of Chinese characters: an fMRI study

The present study used functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms underlying the orthographic and phonological processing of Chinese characters. Four tasks were devised, including one homophone judgment and three physical judgments of characters, pseudo-characters, and Korean-like nonsense figures. While the left occipitotemporal region, left dorsal processing stream, and right middle frontal gyrus constitute a network for orthographic processing, the left premotor gyrus, left middle/inferior frontal gyrus, supplementary motor area (SMA), and the left temporoparietal region work in concert for phonological processing. The ventral part of the left inferior frontal cortex responds specifically to the character stimuli, suggesting a general lexical processing role for this region for linguistic material. The stronger activation of the dorsal visual stream by Chinese homophone judgment pinpoints a tight coupling between phonological representation of Chinese characters and corresponding orthographic percepts. The concomitant engagement of sets of regions for different levels of Chinese orthographic and phonological processing is consistent with the notion of distributed parallel processing.

The Brain Computer Interface Using Flash Visual Evoked Potential and Independent Component Analysis

In this study flashing stimuli, such as digits or letters, are displayed on a LCD screen to induce flash visual evoked potentials (FVEPs). The aim of the proposed interface is to generate desired strings while one stares at target stimulus one after one. To effectively extract visually-induced neural activities with superior signal-to-noise ratio, independent component analysis (ICA) is employed to decompose the measured EEG and task-related components are subsequently selected for data reconstruction. In addition, all the flickering sequences are designed to be mutually independent in order to remove the contamination induced by surrounding non-target stimuli from the ICA-recovered signals. Since FVEPs are time-locked and phase-locked to flash onsets of gazed stimulus, segmented epochs from ICA-recovered signals based on flash onsets of gazed stimulus will be sharpen after averaging whereas those based on flash onsets of non-gazed stimuli will be suppressed after averaging. The stimulus inducing the largest averaged FVEPs is identified as the gazed target and corresponding digit or letter is sent out. Five subjects were asked to gaze at each stimulus. The mean detection accuracy resulted from averaging 15 epochs was 99.7%. Another experiment was to generate a specified string ‘0287513694E’. The mean accuracy and information transfer rates were 83% and 23.06xa0bits/min, respectively.

Mutual-Information-Based Approach for Neural Connectivity during Self-Paced Finger Lifting Task

Frequency‐dependent modulation between neuronal assemblies may provide insightful mechanisms of functional organization in the context of neural connectivity. We present a conjoined time‐frequency cross mutual information (TFCMI) method to explore the subtle brain neural connectivity by magnetoencephalography (MEG) during a self‐paced finger lifting task. Surface electromyogram (sEMG) was obtained from the extensor digitorum communis. Both within‐modality (MEG‐MEG) and between‐modality studies (sEMG‐MEG) were conducted. The TFCMI method measures both the linear and nonlinear dependencies of the temporal dynamics of signal power within a pre‐specified frequency band. Each single trial of MEG across channels and sEMG signals was transformed into time‐frequency domain with use of the Morlet wavelet to obtain better temporal spectral (power) information. As compared to coherence approach (linear dependency only) in broadband analysis, the TFCMI method demonstrated advantages in encompassing detection for the mesial frontocentral cortex and bilateral primary sensorimotor areas, clear demarcation of event‐ and non‐event‐related regions, and robustness for sEMG ‐ MEG between‐modality study, i.e., corticomuscular communication. We conclude that this novel TFCMI method promises a possibility to better unravel the intricate functional organizations of brain in the context of oscillation‐coded communication. Hum Brain Mapp, 2008.

Evaluate the Feasibility of Using Frontal SSVEP to Implement an SSVEP-Based BCI in Young, Elderly and ALS Groups

This paper studies the amplitude-frequency characteristic of frontal steady-state visual evoked potential (SSVEP) and its feasibility as a control signal for brain computer interface (BCI). SSVEPs induced by different stimulation frequencies, from 13 ~ 31 Hz in 2 Hz steps, were measured in eight young subjects, eight elders and seven ALS patients. Each subject was requested to participate in a calibration study and an application study. The calibration study was designed to find the amplitude-frequency characteristics of SSVEPs recorded from Oz and Fpz positions, while the application study was designed to test the feasibility of using frontal SSVEP to control a two-command SSVEP-based BCI. The SSVEP amplitude was detected by an epoch-average process which enables artifact-contaminated epochs can be removed. The seven ALS patients were severely impaired, and four patients, who were incapable of completing our BCI task, were excluded from calculation of BCI performance. The averaged accuracies, command transfer intervals and information transfer rates in operating frontal SSVEP-based BCI were 96.1%, 3.43 s/command, and 14.42 bits/min in young subjects; 91.8%, 6.22 s/command, and 6.16 bits/min in elders; 81.2%, 12.14 s/command, and 1.51 bits/min in ALS patients, respectively. The frontal SSVEP could be an alternative choice to design SSVEP-based BCI.

Improvement of classification accuracy in a phase-tagged steady-state visual evoked potential-based brain computer interface using multiclass support vector machine

BackgroundBrain computer interface (BCI) is an emerging technology for paralyzed patients to communicate with external environments. Among current BCIs, the steady-state visual evoked potential (SSVEP)-based BCI has drawn great attention due to its characteristics of easy preparation, high information transfer rate (ITR), high accuracy, and low cost. However, electroencephalogram (EEG) signals are electrophysiological responses reflecting the underlying neural activities which are dependent upon subject’s physiological states (e.g., emotion, attention, etc.) and usually variant among different individuals. The development of classification approaches to account for each individual’s difference in SSVEP is needed but was seldom reported.MethodsThis paper presents a multiclass support vector machine (SVM)-based classification approach for gaze-target detections in a phase-tagged SSVEP-based BCI. In the training steps, the amplitude and phase features of SSVEP from off-line recordings were used to train a multiclass SVM for each subject. In the on-line application study, effective epochs which contained sufficient SSVEP information of gaze targets were first determined using Kolmogorov-Smirnov (K-S) test, and the amplitude and phase features of effective epochs were subsequently inputted to the multiclass SVM to recognize user’s gaze targets.ResultsThe on-line performance using the proposed approach has achieved high accuracy (89.88u2009±u20094.76%), fast responding time (effective epoch lengthu2009=u20091.13u2009±u20090.02 s), and the information transfer rate (ITR) was 50.91u2009±u20098.70 bits/min.ConclusionsThe multiclass SVM-based classification approach has been successfully implemented to improve the classification accuracy in a phase-tagged SSVEP-based BCI. The present study has shown the multiclass SVM can be effectively adapted to each subject’s SSVEPs to discriminate SSVEP phase information from gazing at different gazed targets.

Association of polymorphisms in BDNF, MTHFR, and genes involved in the dopaminergic pathway with memory in a healthy Chinese population.

The contribution of genetic factors to the memory is widely acknowledged. Research suggests that these factors include genes involved in the dopaminergic pathway, as well as the genes for brain-derived neurotrophic factor (BDNF) and methylenetetrahydrofolate reductase (MTHFR). The activity of the products of these genes is affected by single nucleotide polymorphisms (SNPs) within the genes. This study investigates the association between memory and SNPs in genes involved in the dopaminergic pathway, as well as in the BDNF and MTHFR genes, in a sample of healthy individuals. The sample includes 134 Taiwanese undergraduate volunteers of similar cognitive ability. The Chinese versions of the Wechsler Memory Scale (WMS-III) and Wechsler Adult Intelligence Scale (WAIS-III) were employed. Our findings indicate that the BDNF Met66Val polymorphism and dopamine receptor D3 (DRD3) Ser9Gly polymorphism are associated significantly with long-term auditory memory. Further analysis detects no significant associations in the other polymorphisms and indices. Future replicated studies with larger sample sizes, and studies that consider different ethnic groups, are encouraged.

Quantifying Spasticity With Limited Swinging Cycles Using Pendulum Test Based on Phase Amplitude Coupling

Parameters derived from the goniometer measures in the Pendulum test are insufficient in describing the function of abnormal muscle activity in the spasticity. To explore a quantitative evaluation of muscle activation-movement interaction, we propose a novel index based on phase amplitude coupling (PAC) analysis with the consideration of the relations between movement and surface electromyography (SEMG) activity among 22 hemiplegic stroke patients. To take off trend and noise, we use the empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs) of the angular velocity due to its superior decomposing ability in nonlinear oscillations. Shannon entropy based on angular velocity (phase)-envelope of EMG (amplitude) distribution was calculated to demonstrate characteristics of the coupling between SEMG activity and joint movement. We also compare our results with those from traditional methods such as the normalized relaxation index derived from the Pendulum test and the mean root mean square (RMS) of the SEMG signals in the study. Our results show effective discrimination ability between spastic and nonaffected limbs using our method . This study indicates the feasibility of using the novel indices based on the PAC in evaluation the spasticity among the hemiplegic stroke patients with less than three swinging cycles.

Empirical Mode Decomposition-Based Approach for Intertrial Analysis of Olfactory Event-Related Potential Features

This study presents an empirical mode decomposition (EMD)-based method to study the intertrial variability of olfactory event-related potential (OERP) features. The olfactory stimulus in this study was a mixture of 60xa0% humidity air and 40xa0% phenyl ethanol alcohol generated by a computer-controlled olfactometer with a constant flow rate of 8xa0L/min. A 32-channel whole-head EEG system was utilized to investigate the olfactory responses in 12 healthy subjects. Each EEG epoch was segmented based on the olfactory stimulus onset and subsequently decomposed into a set of intrinsic mode functions (IMFs) by using EMD. Only IMFs that met both frequency and spatial dual criteria were chosen as OERP-related IMFs for reconstructing the noise-suppressed single-trial activity, and those significant trials with N1/P2 amplitudes lower/greater than the mean minus/plus two times the standard deviations of baseline amplitudes were denoted as single-trial OERP for intertrial variability analysis. The present approach enables the capability to study intertrial OERP features, such as the latencies and amplitudes of N1 and P2 peaks, on trial-by-trial basis, which may be helpful to shed light on future olfactory dysfunction studies.

Novel application of a Wii remote to measure spasticity with the pendulum test: Proof of concept

BACKGROUNDnThe pendulum test is a standard clinical test for quantifying the severity of spasticity. In the test, an electrogoniometer is typically used to measure the knee angular motion. The device is costly and difficult to set up such that the pendulum test is normally time consuming.nnnOBJECTIVEnThe goal of this study is to determine whether a Nintendo Wii remote can replace the electrogroniometer for reliable assessment of the angular motion of the knee in the pendulum test.nnnMETHODSnThe pendulum test was performed in three control participants and 13 hemiplegic stroke patients using both a Wii remote and an electrogoniometer. The correlation coefficient and the Bland-Altman difference plot were used to compare the results obtained from the two devices. The Wilcoxon signed-rank test was used to compare the difference between hemiplegia-affected and nonaffected sides in the hemiplegic stroke patients.nnnRESULTSnThere was a fair to strong correlation between measurements from the Wii remote and the electrogoniometer (0.513<R(2)<0.800). Small but consistent differences between the Wii remote and electrogoniometer were identified from the Bland-Altman difference plot. Within the hemiplegic stroke patients, both devices successfully distinguished the hemiplegia-affected (spastic) side from the nonaffected (nonspastic) side (both with p<.0001*). In addition, the intraclass correlation coefficient, standard error of measurement, and minimum detectable differences were highly consistent for both devices.nnnCONCLUSIONnOur findings suggest that the Wii remote may serve as a convenient and cost-efficient tool for the assessment of spasticity.

Study of Repetitive Movements Induced Oscillatory Activities in Healthy Subjects and Chronic Stroke Patients

Repetitive movements at a constant rate require the integration of internal time counting and motor neural networks. Previous studies have proved that humans can follow short durations automatically (automatic timing) but require more cognitive efforts to track or estimate long durations. In this study, we studied sensorimotor oscillatory activities in healthy subjects and chronic stroke patients when subjects were performing repetitive finger movements. We found the movement-modulated changes in alpha and beta oscillatory activities were decreased with the increase of movement rates in finger lifting of healthy subjects and the non-paretic hands in stroke patients, whereas no difference was found in the paretic-hand movements at different movement rates in stroke patients. The significant difference in oscillatory activities between movements of non-paretic hands and paretic hands could imply the requirement of higher cognitive efforts to perform fast repetitive movements in paretic hands. The sensorimotor oscillatory response in fast repetitive movements could be a possible indicator to probe the recovery of motor function in stroke patients.