Tzai-Wen Chiu

Noninvasive Neural Prostheses Using Mobile and Wireless EEG

Neural prosthetic technologies have helped many patients by restoring vision, hearing, or movement and relieving chronic pain or neurological disorders. While most neural prosthetic systems to date have used invasive or implantable devices for patients with inoperative or malfunctioning external body parts or internal organs, a much larger population of ldquohealthyrdquo people who suffer episodic or progressive cognitive impairments in daily life can benefit from noninvasive neural prostheses. For example, reduced alertness, lack of attention, or poor decision-making during monotonous, routine tasks can have catastrophic consequences. This study proposes a noninvasive mobile prosthetic platform for continuously monitoring high-temporal resolution brain dynamics without requiring application of conductive gels on the scalp. The proposed system features dry microelectromechanical system electroencephalography sensors, low-power signal acquisition, amplification and digitization, wireless telemetry, online artifact cancellation, and signal processing. Its implications for neural prostheses are examined in two sample studies: 1) cognitive-state monitoring of participants performing realistic driving tasks in the virtual-reality-based dynamic driving simulator and 2) the neural correlates of motion sickness in driving. The experimental results of these studies provide new insights into the understanding of complex brain functions of participants actively performing ordinary tasks in natural body positions and situations within real operational environments.

Tonic and phasic EEG and behavioral changes induced by arousing feedback

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 subjects 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 30s 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.

EEG correlates of spatial orientation in the human retrosplenial complex.

Studies on spatial navigation reliably demonstrate that the retrosplenial complex (RSC) plays a pivotal role for allocentric spatial information processing by transforming egocentric and allocentric spatial information into the respective other spatial reference frame (SRF). While more and more imaging studies investigate the role of the RSC in spatial tasks, high temporal resolution measures such as electroencephalography (EEG) are missing. To investigate the function of the RSC in spatial navigation with high temporal resolution we used EEG to analyze spectral perturbations during navigation based on allocentric and egocentric SRF. Participants performed a path integration task in a clearly structured virtual environment providing allothetic information. Continuous EEG recordings were decomposed by independent component analysis (ICA) with subsequent source reconstruction of independent time source series using equivalent dipole modeling. Time-frequency transformation was used to investigate reference frame-specific orientation processes during navigation as compared to a control condition with identical visual input but no orientation task. Our results demonstrate that navigation based on an egocentric reference frame recruited a network including the parietal, motor, and occipital cortices with dominant perturbations in the alpha band and theta modulation in frontal cortex. Allocentric navigation was accompanied by performance-related desynchronization of the 8-13 Hz frequency band and synchronization in the 12-14 Hz band in the RSC. The results support the claim that the retrosplenial complex is central to translating egocentric spatial information into allocentric reference frames. Modulations in different frequencies with different time courses in the RSC further provide first evidence of two distinct neural processes reflecting translation of spatial information based on distinct reference frames and the computation of heading changes.

Arousing feedback rectifies lapse in performance and corresponding EEG power spectrum

This study explores electroencephalographic (EEG) dynamics and behavioral changes in response to arousing auditory signals presented to individuals experiencing momentary cognitive lapses. Arousing auditory feedback was delivered to the subjects in half of the non-responded lane-deviation events during a sustained-attention driving task, which immediately agitated subjects responses to the events. The improved behavioral performance was accompanied by concurrent power suppression in the theta- and alpha-bands in the lateral occipital cortices. This study further explores the feasibility of estimating the efficacy of arousing feedback presented to the drowsy subjects by monitoring the changes in EEG power spectra.

Distraction-related EEG dynamics in virtual reality driving simulation

Driver distraction has been recognized as a significant cause of traffic incidents. Therefore, the aim of this study was to investigate electroencephalography (EEG) dynamics in response to distraction during driving. To study human cognition under specific driving task, we used virtual reality (VR) based driving simulation to simulate events including unexpected car deviations and mathematics questions (math) in real driving. For further assessing effects of the stimulus onset asynchrony (SOA) between the deviation onset and math presented on the EEG dynamics, we designed five cases with different SOA. The scalp-recorded EEG channel signals were first separated into independent brain sources by independent component analysis (ICA). Then, the event-related-spectral-perturbations (ERSP) measuring changes of EEG power spectra were used to evaluate the brain dynamics in time-frequency domains. Results showed that increases of theta band (5~7.8 Hz) and beta band (12.2~17 Hz) power were observed in the frontal cortex. Results demonstrated that reaction time and multiple cortical EEG sources responded to the driving deviations and math occurrences differentially in the stimulus onset asynchrony. Results also suggested that the theta band power increase in frontal area could be used as the distracted indexes for early detecting drivers inattention in the future.

Effect of respiratory modulation on relationship between heart rate variability and motion sickness

This study investigates the interplay among heart rate variability (HRV), respiration, and the severity of motion sickness (MS) in a realistic passive driving task. Although HRV is a commonly used metrically in physiological research or even believed to be a direct measure of sympathovagal activities, the results of MS-effected HRV remain mixed across studies. The goal of this study is to find the source of these contradicting results of HRV associated with MS. Experimental results of this study showed that the group trend of the low-frequency (LF) component and the LF/HF ratio increased and high-frequency (HF) component decreased significantly as self-reported MS level increased (p<0.001), consistent with a perception-driven autonomic response of the cardiovascular system. However, in one of the subjects, the relationship was reversed when individuals intentionally adjust themselves (deep breathing) to relieve the discomfort of MS during the experiments. It appears that the correlations between HRV and MS level were higher when individuals made fewer adjustments (the number of deep breathing) during the passive driving experiments.

An ultra-high-density 256-channel/25mm2 neural sensing microsystem using TSV-embedded neural probes

Highly integrated neural sensing microsystems are crucial to capture accurate signals for brain function investigations. In this paper, a 256-channel/25 mm2 neural sensing microsystem is presented based on through-silicon-via (TSV) 2.5D integration. This microsystem composes of dissolvable μ-needles, TSV-embedded μ-probes, 256-channel neural amplifiers, 11-bit area-power-efficient SAR ADCs and serializers. Based on the dissolvable μ-needles and TSV 2.5D integration, this microsystem can detect 256 ECoG/LFP signals within the small area of 5mm × 5mm. Additionally, the neural amplifier realizes 57.8dB gain with only 9.8μW for each channel, and the 9.7-bit ENOB of the SAR ADC at 32kS/s can be achieved with 0.42μW and 0.036 mm2. The overall power of this microsystem is only 3.79mW for 256-channel neural sensing.

An implantable 128-channel wireless neural-sensing microsystem using TSV-embedded dissolvable μ-needle array and flexible interposer

For implanted neural-sensing devices, one of the remaining challenges is to transmit stable power/data (P/D) transmission for high spatiotemporal resolution neural data. This paper presents a miniaturized implantable 128-channel wireless neural-sensing microsystem using TSV-embedded dissolvable μ-needle array, a flexible interposer and 4 dies by 2.5D/3D TSV heterogeneous SiP technology. The 4 dies are 2 neural-signal acquisition ICs implemented by 90nm CMOS, 1 neural-signal processor by 40nm CMOS and 1 wireless P/D transmission circuitry by 0.18μm CMOS. Thus, the proposed wireless microsystem realizes 128-channel neural-signal sensing within the area of 5mm × 5mm, neural feature extraction and wireless P/D transmission using an on-interposer inductor. The overall average power of the circuits in this microsystem is only 9.85mW.

A 64-channel wireless neural sensing microsystem with TSV-embedded micro-probe array for neural signal acquisition

To enhance the signal integrity of high-density neural-sensing signals, this work presents an implantable high spatial resolution μ-probe array with through-silicon via (TSV) 2.5D integration technology that realizes a miniaturized implantable device on flexible printed circuit (FPC) interposer. The proposed microsystem was composed of two 32-channel neural sensing chips and one radio frequency chip for neural signal processing. The μ-probe array can achieve better signal-to-noise ratio with neural-signal acquisition and processing circuit composed of a pseudo-resistor-based analog front-end amplifier. Moreover, a receiving antenna is also implemented on the backside of FPC for wireless data and power transmission. The feasibility of the proposed μ-probe array, Tx and Rx antenna, 32-channel neural sensing circuits in the 64-channel wireless microsystem have been successfully demonstrated for future integration and animal experiments.

An Advanced 2.5-D Heterogeneous Integration Packaging for High-Density Neural Sensing Microsystem

In the traditional neural sensing microstructure, the limited metal line pitch and the metal layer numbers restrict the neural signal routing ability from electrodes to circuit chips. Miniature packaging and excessive noise interference bottlenecks are some of the challenges faced by the electrodes and circuit chips integration with traditional wire bonding. This paper proposes a 2.5-D heterogeneous integration neural sensing microsystem based on the silicon substrate to overcome these issues. With standard semiconductor and 3-D integration processes, high-channel-density (256 channels at 25 mm2) neural sensing microsystem is achieved. Through silicon via provides the shortest vertical interconnection and dramatically minimizes the packaging. Furthermore, the interposer can carry multiple chips to enhance the function of the biosensor. Electrical characteristics and reliability examinations reveal its high quality and great performance as compared to traditional approaches. This novel highly integrated neural sensing microsystem is expected to contribute to the biomedical field for exploring and solving unknown biological mysteries.