Monetary reward and punishment to response inhibition modulate activation and synchronization within the inhibitory brain network

© 2018 Chikara, Chang, Lu, Lin, Lin and Ko. A reward or punishment can modulate motivation and emotions, which in turn affect cognitive processing. The present simultaneous functional magnetic resonance imaging-electroencephalography study examines neural mechanisms of response inhibition under the influence of a monetary reward or punishment by implementing a modified stop-signal task in a virtual battlefield scenario. The participants were instructed to play as snipers who open fire at a terrorist target but withhold shooting in the presence of a hostage. The participants performed the task under three different feedback conditions in counterbalanced order: a reward condition where each successfully withheld response added a bonus (i.e., positive feedback) to the startup credit, a punishment condition where each failure in stopping deduced a penalty (i.e., negative feedback), and a no-feedback condition where response outcome had no consequences and served as a control setting. Behaviorally both reward and punishment conditions led to significantly down-regulated inhibitory function in terms of the critical stop-signal delay. As for the neuroimaging results, increased activities were found for the no-feedback condition in regions previously reported to be associated with response inhibition, including the right inferior frontal gyrus and the pre-supplementary motor area. Moreover, higher activation of the lingual gyrus, posterior cingulate gyrus (PCG) and inferior parietal lobule were found in the reward condition, while stronger activation of the precuneus gyrus was found in the punishment condition. The positive feedback was also associated with stronger changes of delta, theta, and alpha synchronization in the PCG than were the negative or no-feedback conditions. These findings depicted the intertwining relationship between response inhibition and motivation networks

Single channel wireless EEG device for real-time fatigue level detection

© 2015 IEEE. Driver fatigue problem is one of the important factors of traffic accidents. Recent years, many research had investigated that using EEG signals can effectively detect driver's drowsiness level. However, real-time monitoring system is required to apply these fatigue level detection techniques in the practical application, especially in the real-road driving. Therefore, it required less channels, portable and wireless, real-time monitoring and processing techniques for developing the real-time monitoring system. In this study, we develop a single channel wireless EEG device which can real-time detect driver's fatigue level on the mobile device such as smart phone or tablet. The developed device is investigated to obtain a better and precise understanding of brain activities of mental fatigue under driving, which is of great benefit for devolvement of detection of driving fatigue system. This system consists of a Bluetooth-enabled one channel EEG, a regression model, and smartphone, which was a platform recording and transforming the raw EEG data to useful driving status. In the experiment, this was a sustained-attention driving task to implement in a virtual-reality (VR) driving simulator. To training model and develop the system, we were performed for 15 subjects to study Electroencephalography (EEG) brain dynamics by using a mobile and wireless EEG device. Based on the outstanding training results, the leave-one-subject-out cross validation test obtained 90% fatigue detection accuracy. These results indicate that the combination of a smartphone and wireless EEG device constitutes an effective and easy wearable solution for detecting and preventing driver fatigue in real driving environments

A novel 16-channel wireless system for electroencephalography measurements with dry spring-loaded sensors

Understanding brain function using electroencephalography (EEG) is an important issue for cerebral nervous system diseases, especially for epilepsy and Alzheimer's disease. Many EEG measurement systems are used reliably to study these diseases, but their bulky size and the use of wet sensors make them uncomfortable and inconvenient for users. To overcome the limitations of conventional EEG measurement systems, a wireless and wearable multichannel EEG measurement system is proposed in this paper. This system includes a wireless data acquisition device, dry spring-loaded sensors, and a sizeadjustable soft cap. We compared the performance of the proposed system using dry versus conventional wet sensors. A significant positive correlation between readings from wet and dry sensors was achieved, thus demonstrating the performance of the system. Moreover, four different features of EEG signals (i.e., normal, eye-blinking, closed-eyes, and teeth-clenching signals) were measured by 16 dry sensors to ensure that they could be detected in real-life cognitive neuroscience applications. Thus, we have shown that it is possible to reliably measure EEG signals using the proposed system. This paper presents novel insights into the field of cognitive neuroscience, showing the possibility of studying brain function under real-life conditions. © 2014 IEEE

Au/n-ZnO rectifying contact fabricated with hydrogen peroxide pretreatment

Au contacts were deposited on n -type ZnO single crystals with and without hydrogen peroxide pretreatment for the ZnO substrate. The Au/ZnO contacts fabricated on substrates without H2 O2 pretreatment were Ohmic and those with H2 O2 pretreatment were rectifying. With an aim of fabricating a good quality Schottky contact, the rectifying property of the Au/ZnO contact was systemically investigated by varying the treatment temperature and duration. The best performing Schottky contact was found to have an ideality factor of 1.15 and a leakage current of ∼ 10-7 A cm-2. A multispectroscopic study, including scanning electron microscopy, positron annihilation spectroscopy, deep level transient spectroscopy, x-ray photoelectron spectroscopy, and photoluminescence, showed that the H2 O2 treatment removed the OH impurity and created Zn-vacancy related defects hence decreasing the conductivity of the ZnO surface layer, a condition favorable for forming good Schottky contact. However, the H2 O2 treatment also resulted in a deterioration of the surface morphology, leading to an increase in the Schottky contact ideality factor and leakage current in the case of nonoptimal treatment time and temperature. © 2008 American Institute of Physics.published_or_final_versio

Investigation of a novel composite sorbent for improved sorption characteristic

Novel composite sorbents are developed. Strontium chloride (SrCl2) is selected whereas expanded natural graphite and nanoparticle i.e. carbon coated nickel are integrated as the additive with different densities for the better heat transfer and sorption performance. Thermal properties such as thermal diffusivity and conductivity are investigated by the laser flash method. The sorption performance is tested by the unit which is especially designed. It is indicated that the highest thermal diffusivity could reach 2.242 mm2\ub7s-1 when the density is 1000 kg\ub7m-3 and testing temperature is 20oC. For different testing temperature and density, the thermal diffusivity range from 1.3 mm2\ub7s-1 to 2.242 mm2\ub7s-1. Also worth noting that the highest thermal conductivity could reach 2.5 mm2\ub7s-1 for the environmental temperature. One paramount factor i.e. the global conversion rate of the novel composite SrCl2 is compared and analyzed under different working conditions. It can be found that the higher desorption temperature results in the faster variation of the global conversion rate. In addition, It takes about 15 minutes and 40 minutes to finish the reaction SrCl2 8-1 and 1-0 when the desorption temperature is 180oC and 130oC, respectively. For sorption process, it is indicated that the global conversion rate varies faster with the increase of the sorption temperature. When the global conversion is 0.7, it takes about 14 to 28 minutes when sorption temperature range from -5oC to 15oC

Deep level defects in a nitrogen-implanted ZnO homogeneous p-n junction

Nitrogen ions were implanted into undoped melt grown ZnO single crystals. A light-emitting p-n junction was subsequently formed by postimplantation annealing in air. Deep level transient spectroscopy was used to investigate deep level defects induced by N+ implantation and the effect of air annealing. The N+ implantation enhanced the electron trap at E C -(0.31±0.01) eV (E3) and introduced another one at E C -(0.95±0.02) eV (D1), which were removed after annealing at 900 and 750 °C, respectively. Another trap D2 (Ea =0.17±0.01 eV) was formed after the 750 °C annealing and persisted at 1200 °C. © 2008 American Institute of Physics.published_or_final_versio

Hydrogen peroxide treatment induced rectifying behavior of Aun-ZnO contact

Conversion of the Aun-ZnO contact from Ohmic to rectifying with H2 O2 pretreatment was studied systematically using I-V measurements, x-ray photoemission spectroscopy, positron annihilation spectroscopy, and deep level transient spectroscopy. H2 O2 treatment did not affect the carbon surface contamination or the EC -0.31 eV deep level, but it resulted in a significant decrease of the surface OH contamination and the formation of vacancy-type defects (Zn vacancy or vacancy cluster) close to the surface. The formation of a rectifying contact can be attributed to the reduced conductivity of the surface region due to the removal of OH and the formation of vacancy-type defects. © 2007 American Institute of Physics.published_or_final_versio

Multimodal fuzzy fusion for enhancing the motor-imagery-based brain computer interface

© 2005-2012 IEEE. Brain-computer interface technologies, such as steady-state visually evoked potential, P300, and motor imagery are methods of communication between the human brain and the external devices. Motor imagery-based brain-computer interfaces are popular because they avoid unnecessary external stimuli. Although feature extraction methods have been illustrated in several machine intelligent systems in motor imagery-based brain-computer interface studies, the performance remains unsatisfactory. There is increasing interest in the use of the fuzzy integrals, the Choquet and Sugeno integrals, that are appropriate for use in applications in which fusion of data must consider possible data interactions. To enhance the classification accuracy of brain-computer interfaces, we adopted fuzzy integrals, after employing the classification method of traditional brain-computer interfaces, to consider possible links between the data. Subsequently, we proposed a novel classification framework called the multimodal fuzzy fusion-based brain-computer interface system. Ten volunteers performed a motor imagery-based brain-computer interface experiment, and we acquired electroencephalography signals simultaneously. The multimodal fuzzy fusion-based brain-computer interface system enhanced performance compared with traditional brain-computer interface systems. Furthermore, when using the motor imagery-relevant electroencephalography frequency alpha and beta bands for the input features, the system achieved the highest accuracy, up to 78.81% and 78.45% with the Choquet and Sugeno integrals, respectively. Herein, we present a novel concept for enhancing brain-computer interface systems that adopts fuzzy integrals, especially in the fusion for classifying brain-computer interface commands

Stressor- and Corticotropin releasing Factor-induced Reinstatement and Active Stress-related Behavioral Responses are Augmented Following Long-access Cocaine Self-administration by Rats

Rationale Stressful events during periods of drug abstinence likely contribute to relapse in cocaine-dependent individuals. Excessive cocaine use may increase susceptibility to stressor-induced relapse through alterations in brain corticotropin-releasing factor (CRF) responsiveness. Objectives This study examined stressor- and CRF-induced cocaine seeking and other stress-related behaviors in rats with different histories of cocaine self-administration (SA). Materials and methods Rats self-administered cocaine under short-access (ShA; 2 h daily) or long-access (LgA; 6 h daily) conditions for 14 days or were provided access to saline and were tested for reinstatement by a stressor (electric footshock), cocaine or an icv injection of CRF and for behavioral responsiveness on the elevated plus maze, in a novel environment and in the light–dark box after a 14- to 17-day extinction/withdrawal period. Results LgA rats showed escalating patterns of cocaine SA and were more susceptible to reinstatement by cocaine, EFS, or icv CRF than ShA rats. Overall, cocaine SA increased activity in the center field of a novel environment, on the open arms of the elevated plus maze, and in the light compartment of a light–dark box. In most cases, the effects of cocaine SA were dependent on the pattern/amount of cocaine intake with statistically significant differences from saline self-administering controls only observed in LgA rats. Conclusions When examined after several weeks of extinction/ withdrawal, cocaine SA promotes a more active pattern of behavior during times of stress that is associated with a heightened susceptibility to stressor-induced cocaine-seeking behavior and may be the consequence of augmented CRF regulation of addiction-related neurocircuitry