Understanding, predicting, and learning from other people's actions are fundamental human soc... more Understanding, predicting, and learning from other people's actions are fundamental human social-cognitive skills. Little is known about how and when we consider other's actions and outcomes when making our own decisions. We developed a novel task to study social influence in decision-making: the social multi-armed bandit task. This task assesses how people learn policies for optimal choices based on their own outcomes and another player's (observed) outcomes. The majority of participants integrated information gained through observation of their partner similarly as information gained through their own actions. This lead to a suboptimal decision-making strategy. Interestingly, event-related potentials time-locked to stimulus onset qualitatively similar but the amplitudes are attenuated in the solo compared to the dyadic version. This might indicate that arousal and attention after receiving a reward are sustained when a second agent is present but not when playing alone.
Here we assume that emotional states correspond to functional dynamic states of brain and body, a... more Here we assume that emotional states correspond to functional dynamic states of brain and body, and attempt to characterize the appearance of these states in high-density scalp electroencephalographic (EEG) recordings acquired from 31 participants during 1-2 hour sessions, each including fifteen 3-5 min periods of self-induced emotion imagination using the method of guided imagery. EEG offers an objective and high-resolution measurement of whatever portion of cortical electrical dynamics is resolvable from scalp recordings. Despite preliminary progress in EEG-based emotion decoding using supervised machine learning methods, few studies have applied data-driven, unsupervised decomposition approaches to investigate the underlying EEG dynamics by characterizing brain temporal dynamics during emotional experience. This study applies an unsupervised approach – adaptive mixture independent component analysis (adaptive mixture ICA, AMICA) that learns a set of ICA models each accounted for ...
The Journal of the Acoustical Society of America, 1995
Articulatory and acoustic variability in the production of five American English vowels was exami... more Articulatory and acoustic variability in the production of five American English vowels was examined. The data were movement records for selected fleshpoints on the midsagittal tongue surface, recorded using the x-ray microbeam. An algorithm for nonlinearly transforming fleshpoint positions to a new Cartesian space in which the x and y axes represent, respectively, the distance of the fleshpoint along the opposing vocal tract wall and the distance perpendicular to the tract wall, is described. The transformation facilitates a test of Quantal Theory in which variability in the two dimensions is compared over many productions of a given vowel type. The data provide some support for the theory. For fleshpoints near ‘‘quantal’’ constriction sites, the primary variability was in the x dimension (constriction location). The y-dimension values were more tightly constrained, and the formant frequencies were more significantly correlated with the y values than with the x values. The greater ...
The Journal of the Acoustical Society of America, 1991
Tongue constriction features can be estimated from sagittal x-ray pictures of the tongue surface ... more Tongue constriction features can be estimated from sagittal x-ray pictures of the tongue surface and vocal tract wall. However, such records cannot be obtained in quantity, making them unsuitable for testing models such as Stevens's quantal theory. The x-ray microbeam allows larger data sets, but records flesh points rather than surfaces. This paper presents an algorithm for relating the two representations. The vocal tract wall is estimated from whole-head scans and a palate trace. Pellet positions are then “warped” into a Cartesian space where location along the tract and distance from it are the x and y values. The algorithm has been applied in a replication of Perkell and Nelson's test of quantal theory using principal component analysis. Quantal theory predicts that the pellet closest to the constriction site will show least variability, and that the most precision will be in the dimension perpendicular to the vocal tract wall for “quantal” vowels such as /i/. In the wa...
Objectives: Mindfulness-based stress reduction has been proven to improve mental health and quali... more Objectives: Mindfulness-based stress reduction has been proven to improve mental health and quality of life. This study examined how mindfulness training and various types of mindfulness practices altered brain activity.Methods: Specifically, the spectral powers of scalp electroencephalography of the mindfulness-based stress reduction (MBSR) group (n=17) who underwent an 8-week MBSR training—including mindful breathing and body-scan—were evaluated and compared with those of the waitlist controls (n=14).Results: Empirical results indicated that the post-intervention effect of MBSR significantly elevated the resting-state beta powers and reduced resting-state delta powers in both practices; such changes were not observed in the waitlist control. Compared with mindful breathing, body-scanning resulted in an overall decline in electroencephalograms (EEG) spectral powers at both delta and low-gamma bands among trained participants.Conclusion: Together with our preliminary data of expert ...
The modelling of trust values on agents is broadly considered fundamental for decision-making in ... more The modelling of trust values on agents is broadly considered fundamental for decision-making in human-autonomous teaming (HAT) systems. Compared to the evaluation of trust values for robotic agents, estimating human trust is more challenging due to trust miscalibration issues, including undertrust and overtrust problems. From a subjective perception, human trust could be altered along with dynamic human cognitive states, which makes trust values hard to calibrate properly. Thus, in an attempt to capture the dynamics of human trust, the present study evaluated the dynamic nature of trust for human agents through real-time multievidence measures, including human states of attention, stress and perception abilities. The proposed multievidence human trust model applied an adaptive fusion method based on fuzzy reinforcement learning to fuse multievidence from eye trackers, heart rate monitors and human awareness. In addition, fuzzy reinforcement learning was applied to generate rewards ...
Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) hav... more Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to the wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial attacks, e.g., the attacker can add tiny adversarial perturbations to a test sample to fool the model, or poison the training data to insert a secret backdoor. Previous research has shown that adversarial attacks are also possible for EEG-based BCIs. However, only adversarial perturbations have been considered, and the approaches are theoretically sound but very difficult to implement in practice. This article proposes to use narrow period pulse for poisoning attack of EEG-based BCIs, which is more feasible in practice and has never been considered before. One can create dangerous backdoors in the machine learning model by injecting poisoning samples into the trainin...
Understanding, predicting, and learning from other people's actions are fundamental human soc... more Understanding, predicting, and learning from other people's actions are fundamental human social-cognitive skills. Little is known about how and when we consider other's actions and outcomes when making our own decisions. We developed a novel task to study social influence in decision-making: the social multi-armed bandit task. This task assesses how people learn policies for optimal choices based on their own outcomes and another player's (observed) outcomes. The majority of participants integrated information gained through observation of their partner similarly as information gained through their own actions. This lead to a suboptimal decision-making strategy. Interestingly, event-related potentials time-locked to stimulus onset qualitatively similar but the amplitudes are attenuated in the solo compared to the dyadic version. This might indicate that arousal and attention after receiving a reward are sustained when a second agent is present but not when playing alone.
Here we assume that emotional states correspond to functional dynamic states of brain and body, a... more Here we assume that emotional states correspond to functional dynamic states of brain and body, and attempt to characterize the appearance of these states in high-density scalp electroencephalographic (EEG) recordings acquired from 31 participants during 1-2 hour sessions, each including fifteen 3-5 min periods of self-induced emotion imagination using the method of guided imagery. EEG offers an objective and high-resolution measurement of whatever portion of cortical electrical dynamics is resolvable from scalp recordings. Despite preliminary progress in EEG-based emotion decoding using supervised machine learning methods, few studies have applied data-driven, unsupervised decomposition approaches to investigate the underlying EEG dynamics by characterizing brain temporal dynamics during emotional experience. This study applies an unsupervised approach – adaptive mixture independent component analysis (adaptive mixture ICA, AMICA) that learns a set of ICA models each accounted for ...
The Journal of the Acoustical Society of America, 1995
Articulatory and acoustic variability in the production of five American English vowels was exami... more Articulatory and acoustic variability in the production of five American English vowels was examined. The data were movement records for selected fleshpoints on the midsagittal tongue surface, recorded using the x-ray microbeam. An algorithm for nonlinearly transforming fleshpoint positions to a new Cartesian space in which the x and y axes represent, respectively, the distance of the fleshpoint along the opposing vocal tract wall and the distance perpendicular to the tract wall, is described. The transformation facilitates a test of Quantal Theory in which variability in the two dimensions is compared over many productions of a given vowel type. The data provide some support for the theory. For fleshpoints near ‘‘quantal’’ constriction sites, the primary variability was in the x dimension (constriction location). The y-dimension values were more tightly constrained, and the formant frequencies were more significantly correlated with the y values than with the x values. The greater ...
The Journal of the Acoustical Society of America, 1991
Tongue constriction features can be estimated from sagittal x-ray pictures of the tongue surface ... more Tongue constriction features can be estimated from sagittal x-ray pictures of the tongue surface and vocal tract wall. However, such records cannot be obtained in quantity, making them unsuitable for testing models such as Stevens's quantal theory. The x-ray microbeam allows larger data sets, but records flesh points rather than surfaces. This paper presents an algorithm for relating the two representations. The vocal tract wall is estimated from whole-head scans and a palate trace. Pellet positions are then “warped” into a Cartesian space where location along the tract and distance from it are the x and y values. The algorithm has been applied in a replication of Perkell and Nelson's test of quantal theory using principal component analysis. Quantal theory predicts that the pellet closest to the constriction site will show least variability, and that the most precision will be in the dimension perpendicular to the vocal tract wall for “quantal” vowels such as /i/. In the wa...
Objectives: Mindfulness-based stress reduction has been proven to improve mental health and quali... more Objectives: Mindfulness-based stress reduction has been proven to improve mental health and quality of life. This study examined how mindfulness training and various types of mindfulness practices altered brain activity.Methods: Specifically, the spectral powers of scalp electroencephalography of the mindfulness-based stress reduction (MBSR) group (n=17) who underwent an 8-week MBSR training—including mindful breathing and body-scan—were evaluated and compared with those of the waitlist controls (n=14).Results: Empirical results indicated that the post-intervention effect of MBSR significantly elevated the resting-state beta powers and reduced resting-state delta powers in both practices; such changes were not observed in the waitlist control. Compared with mindful breathing, body-scanning resulted in an overall decline in electroencephalograms (EEG) spectral powers at both delta and low-gamma bands among trained participants.Conclusion: Together with our preliminary data of expert ...
The modelling of trust values on agents is broadly considered fundamental for decision-making in ... more The modelling of trust values on agents is broadly considered fundamental for decision-making in human-autonomous teaming (HAT) systems. Compared to the evaluation of trust values for robotic agents, estimating human trust is more challenging due to trust miscalibration issues, including undertrust and overtrust problems. From a subjective perception, human trust could be altered along with dynamic human cognitive states, which makes trust values hard to calibrate properly. Thus, in an attempt to capture the dynamics of human trust, the present study evaluated the dynamic nature of trust for human agents through real-time multievidence measures, including human states of attention, stress and perception abilities. The proposed multievidence human trust model applied an adaptive fusion method based on fuzzy reinforcement learning to fuse multievidence from eye trackers, heart rate monitors and human awareness. In addition, fuzzy reinforcement learning was applied to generate rewards ...
Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) hav... more Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to the wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial attacks, e.g., the attacker can add tiny adversarial perturbations to a test sample to fool the model, or poison the training data to insert a secret backdoor. Previous research has shown that adversarial attacks are also possible for EEG-based BCIs. However, only adversarial perturbations have been considered, and the approaches are theoretically sound but very difficult to implement in practice. This article proposes to use narrow period pulse for poisoning attack of EEG-based BCIs, which is more feasible in practice and has never been considered before. One can create dangerous backdoors in the machine learning model by injecting poisoning samples into the trainin...
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