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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Toward a new cognitive neuroscience: modeling natural brain dynamics
(2014-06-19)
Gramann, Klaus
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Jung, Tzyy-Ping
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Ferris, Daniel P.
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Lin, Chin-Teng
;
Makeig, Scott
Sustained Attention in Real Classroom Settings: An EEG Study
(2017-07-31)
Ko, Li-Wei
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Komarov, Oleksii
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Hairston, W. David
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Jung, Tzyy-Ping
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Lin, Chin-Teng
Sustained attention is a process that enables the maintenance of response persistence and continuous effort over extended periods of time. Performing attention-related tasks in real life involves the need to ignore a variety of distractions and inhibit attention shifts to irrelevant activities. This study investigates electroencephalography (EEG) spectral changes during a sustained attention task within a real classroom environment. Eighteen healthy students were instructed to recognize as fast as possible special visual targets that were displayed during regular university lectures. Sorting their EEG spectra with respect to response times, which indicated the level of visual alertness to randomly introduced visual stimuli, revealed significant changes in the brain oscillation patterns. The results of power-frequency analysis demonstrated a relationship between variations in the EEG spectral dynamics and impaired performance in the sustained attention task. Across subjects and sessions, prolongation of the response time was preceded by an increase in the delta and theta EEG powers over the occipital region, and decrease in the beta power over the occipital and temporal regions. Meanwhile, implementation of the complex attention task paradigm into a real-world classroom setting makes it possible to investigate specific mutual links between brain activities and factors that cause impaired behavioral performance, such as development and manifestation of classroom mental fatigue. The findings of the study set a basis for developing a system capable of estimating the level of visual attention during real classroom activities by monitoring changes in the EEG spectra.
Identifying changes in EEG information transfer during drowsy driving by transfer entropy
(2015-10-23)
Huang, Chih-Sheng
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Pal, Nikhil R.
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Chuang, Chun-Hsiang
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Lin, Chin-Teng
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電控工程研究所
Drowsy driving is a major cause of automobile accidents. Previous studies used neuroimaging based approaches such as analysis of electroencephalogram (EEG) activities to understand the brain dynamics of different cortical regions during drowsy driving. However, the coupling between brain regions responding to this vigilance change is still unclear. To have a comprehensive understanding of neural mechanisms underlying drowsy driving, in this study we use transfer entropy, a model-free measure of effective connectivity based on information theory. We investigate the pattern of information transfer between brain regions when the vigilance level, which is derived from the driving performance, changes from alertness to drowsiness. Results show that the couplings between pairs of frontal, central, and parietal areas increased at the intermediate level of vigilance, which suggests that an enhancement of the cortico-cortical interaction is necessary to maintain the task performance and prevent behavioral lapses. Additionally, the occipital-related connectivity magnitudes monotonically decreases as the vigilance level declines, which further supports the cortical gating of sensory stimuli during drowsiness. Neurophysiological evidence of mutual relationships between brain regions measured by transfer entropy might enhance the understanding of cortico-cortical communication during drowsy driving.
結合生物反饋之新世代腦機介面及其在移動載具控制之應用---子計畫三：運動想像腦電波之腦機介面系統(I)
(2008)
陳永昇
;
Chen Yong-Sheng
;
國立交通大學資訊工程學系(所)
本研究計畫中，我們將設計不同的運動想像實驗，並使用小波轉換、時間頻率分析、事件相關同步/非同步分析等許多離線訊號分析的方法，觀察受試者在各種不同的運動想像中量測到的腦電波訊號，藉以針對變化最顯著的運動想像來發展有效的空間濾波器技術。同時，我們將根據腦電波訊號源逆向估算的技術，搭配不同的限制式設計空間濾波器，對量測到的腦電波訊號作整體的濾波，得到較具代表意義的訊號，以提升後續研究工作的效能。後續再搭配總計畫與其他子計畫之推展與需求，設計由簡單到進階的腦機介面訓練系統，藉由生物反饋的機制，讓受試者能根據訓練系統的指示做自我訓練，此時就可以配合已發展的空間濾波器技術來最佳化量測的訊號，使生物反饋的根據有更高的準確度。由於使用者在不同的心智情況下腦電波生理訊號量測的結果會有所差異，因此我們也擬藉由多次的訓練實驗，發展自動化調整空間濾波器的技術，在線上的實驗中根據使用者當下的心智情況，對濾波器做即時的最佳化調整，使長時間訓練中濾波器仍保有準確的分辨效果。這一系列的研究工作相當繁複且環環相扣，我們規劃為三年期研究計畫，以循序漸進地推展各個重點項目。在執行中的第一年裡，我們設計難易度不同、部位不同、動作不同的想像運動實驗，配合許多已發展的技術分析離線訊號，確定在未來將使用何種活動作為命令控制的基礎。而在未來的第二年我們將開發有效的空間濾波器技術，根據先前相關研究成果，使用不同的限制式來設計濾波器，以最佳化訊號的特徵。第三年我們將配合總計畫與其他子計畫的研究發展，進行設計具有生物反饋的機制的線上腦機介面訓練系統，並發展線上自動調整濾波器的技術，同時也進行系統整合測試與評估。
Tonic and phasic EEG and behavioral changes induced by arousing feedback
(2010-08-15)
Lin, Chin-Teng
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Huang, Kuan-Chih
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Chao, Chih-Feng
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Chen, Jian-Ann
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Chiu, Tzai-Wen
This study investigates brain dynamics and behavioral changes in response to arousing auditory signals presented to individuals experiencing momentary cognitive lapses during a sustained-attention task. Electroencephalographic (EEG) and behavioral data were simultaneously collected during virtual-reality (VR) based driving experiments, in which subjects were instructed to maintain their cruising position and compensate for randomly induced lane deviations using the steering wheel. 30-channel EEG data were analyzed by independent component analysis and the short-time Fourier transform. Across subjects and sessions, intermittent performance during drowsiness was accompanied by characteristic spectral augmentation or suppression in the alpha- and theta-band spectra of a bilateral occipital component, corresponding to brief periods of normal (wakeful) and hypnagogic (sleeping) awareness and behavior. Arousing auditory feedback was delivered to the subjects in half of the non-responded lane-deviation events, which immediately agitated subject's responses to the events. The improved behavioral performance was accompanied by concurrent spectral suppression in the theta- and alpha-bands of the bilateral occipital component. The effects of auditory feedback on spectral changes lasted 30 s or longer. The results of this study demonstrate the amount of cognitive state information that can be extracted from noninvasively recorded EEG data and the feasibility of online assessment and rectification of brain networks exhibiting characteristic dynamic patterns in response to momentary cognitive challenges. (C) 2010 Elsevier Inc. All rights reserved.
Estimating driving performance based on EEG spectrum analysis
(2005)
Lin, CT
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Wu, RC
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Jung, TP
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Liang, SF
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Huang, TY
The growing number of traffic accidents in recent years has become a serious concern to society. Accidents caused by driver's drowsiness behind the steering wheel have a high fatality rate because of the marked decline in the driver's abilities of perception, recognition, and vehicle control abilities while sleepy. Preventing such accidents caused by drowsiness is highly desirable but requires techniques for continuously detecting, estimating, and predicting the level of alertness of drivers and delivering effective feedbacks to maintain their maximum performance. This paper proposes an EEG-based drowsiness estimation system that combines electroencephalogram (EEG) log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator. Our results demonstrated that it is feasible to accurately estimate quantitatively driving performance, expressed as deviation between the center of the vehicle and the center of the cruising lane, in a realistic driving simulator.
Kinesthesia in a sustained-attention driving task
(2014-05-01)
Chuang, Chun-Hsiang
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Ko, Li-Wei
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Jung, Tzyy-Ping
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Lin, Chin-Teng
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生物科技學系
This study investigated the effects of kinesthetic stimuli on brain activities during a sustained-attention task in an immersive driving simulator. Tonic and phasic brain responses on multiple timescales were analyzed using time-frequency analysis of electroencephalographic (EEG) sources identified by independent component analysis (ICA). Sorting EEG spectra with respect to reaction times (RT) to randomly introduced lane-departure events revealed distinct effects of kinesthetic stimuli on the brain under different performance levels. Experimental results indicated that EEG spectral dynamics highly correlated with performance lapses when driving involved kinesthetic feedback. Furthermore, in the realistic environment involving both visual and kinesthetic feedback, a transitive relationship of power spectra between optimal-, suboptimal-, and poor-performance groups was found predominately across most of the independent components. In contrast to the static environment with visual input only, kinesthetic feedback reduced theta-power augmentation in the central and frontal components when preparing for action and error monitoring, while strengthening alpha suppression in the central component while steering the wheel. In terms of behavior, subjects tended to have a short response time to process unexpected events with the assistance of kinesthesia, yet only when their performance was optimal. Decrease in attentional demand, facilitated by kinesthetic feedback, eventually significantly increased the reaction time in the suboptimal-performance state. Neurophysiological evidence of mutual relationships between behavioral performance and neurocognition in complex task paradigms and experimental environments, presented in this study, might elucidate our understanding of distributed brain dynamics, supporting natural human cognition and complex coordinated, multi-joint naturalistic behavior, and lead to improved understanding of brain-behavior relations in operating environments. (C) 2014 Elsevier Inc. All rights reserved.
Toward a new cognitive neuroscience: modeling natural brain dynamics
(2014-06-19)
Gramann, Klaus
;
Jung, Tzyy-Ping
;
Ferris, Daniel P.
;
Lin, Chin-Teng
;
Makeig, Scott
Brain oscillation and connectivity during a chemistry visual working memory task
(2013-11-01)
Huang, Li-Yu
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She, Hsiao-Ching
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Chou, Wen-Chi
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Chuang, Ming-Hua
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Duann, Jeng-Ren
Many studies have reported that frontal theta and posterior alpha activities are associated with working memory tasks. However, fewer studies have focused on examining whether or not the frontal alpha or posterior theta can play a role in the working memory task. This study investigates electroencephalography (EEG) dynamics and connectivity among different brain regions' theta and alpha oscillations. The EEG was collected from undergraduate students (n = 64) while they were performing a Sternberg-like working memory task involving chemistry concepts. The results showed that the frontal midline cluster exhibited sustained theta augmentation across the periods of stimulus presentations, maintenance, and probe presentation, suggesting that the frontal midline theta might associate with facilitating the central execute function to maintain information in the working memory. Study of the central parietal and the occipital clusters revealed a sequence of theta augmentation followed by alpha suppression at constant intervals after the onset of stimulus and probe presentations, suggesting that the posterior theta might be associated with sensory processing, theta gating, or stimulus selection. It further suggests that the posterior alpha event-related de-synchronization (ERD) might be linked to direct information flow into and out of the long-term memory (LTM) and precede stimulus recognition. An alternating phasic alpha event-related synchronization (ERS) and ERD following the 1st stimulus and probe presentations were observed at the occipital cluster, in which alpha ERS might be linked to the inhibition of irrelevant information. (C) 2013 Elsevier B.V. All rights reserved.
Co-modulatory spectral changes in independent brain processes are correlated with task performance
(2012-09-01)
Chuang, Shang-Wen
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Ko, Li-Wei
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Lin, Yuan-Pin
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Huang, Ruey-Song
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Jung, Tzyy-Ping
"This study investigates the independent modulators that mediate the power spectra of electrophysiological processes, measured by electroencephalogram (EEG), in a sustained-attention experiment. EEG and behavioral data were collected during 1-2 hour virtual-reality based driving experiments in which subjects were instructed to maintain their cruising position and compensate for randomly induced drift using the steering wheel. Independent component analysis (ICA) applied to 30-channel EEG data separated the recorded EEG signals into a sum of maximally temporally independent components (ICs) for each of 30 subjects. Logarithmic spectra of resultant IC activities were then decomposed by principal component analysis, followed by ICA, to find spectrally fixed and temporally independent modulators (IM). Across subjects, the spectral ICA consistently found four performance-related independent modulators: delta, delta-theta, alpha, and beta modulators that multiplicatively affected the spectra of spatially distinct IC processes when the participants experienced waves of alternating alertness and drowsiness during long-hour simulated driving. The activation of the delta-theta modulator increased monotonically as subjects' task performances decreased. Furthermore, the time courses of the theta-beta modulator were highly correlated with concurrent changes in driving errors across subjects (r = 0.77 +/- 0.13). (c) 2012 Elsevier Inc. All rights reserved."

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