Task-related Events Research Articles

Do You Want to Make Your Robot Warmer? Make it More Reactive!

Endowing robots with the ability to respond appropriately to stimuli contributes to the perception of an illusion of “life” in robots, which is determinant for their acceptance as companions. This work aims to study how a series of bio-inspired reactive responses impact on the way in which participants perceive a social robot. In particular, the proposed system endows the robot with the ability to react to stimuli that are not only related to the current task but are also related to other external events. We conducted an experiment where the participants observed a video-recorded interaction with two robots: one was able to respond to both task-related and non-task-related events, while the other was only able to react to task-related events. To evaluate the experiment, we used the RoSAS questionnaire. The results yielded significant differences for two factors, showing that the addition of responses to non-task-related stimuli increased the robot’s warmth and competence.

The Development of Kansei-Based Work Events Scale

Research Aims: This research aims to discover work events that influence employees’ emotional states to construct a more comprehensive Kansei-based work events scale. Design/Methodology/Approach: A mixed-method approach was adopted by combining qualitative and quantitative techniques in an Exploratory Sequential Design. Research Findings: In study 1, the Kawakita Jiro (KJ) method (i.e., focus group study) (N = 28) identified four (4) categories of work events (i.e., interpersonal, task-related, organisational policies, and infrastructure and facilities). A new category, career development, was also discovered through this qualitative inquiry. Study 2 (N = 152) and Study 3 (N = 537), which used a quantitative approach, demonstrated that negative and positive emotional experiences are strongly linked to interpersonal and task-related events. This result further indicates that the scale is reliable for measuring emotional experiences at work. Theoretical Contribution/Originality: The study captured micro and macro work events using the Kansei Engineering approach, allowing for a better understanding of emotional experiences at work. Managerial Implication in the South East Asian Context: Strategies to promote positive events and prevent negative ones through routine practices and long-term plans relevant to the South East Asian context are discussed and presented in this paper. Research Limitation & Implications: Some limitations should be considered, such as cross-sectional design, lack of investigation on other Affective Events Theory (AET) factors, and the focus on non-academic staff from public universities. Future research could expand upon this study by using a longitudinal design, a diverse sample, and additional AET factors. Keywords: Work Events, Positive Events, Negative Events, Emotions, Kansei Engineering, Kawakita Jiro Method

Detecting Spontaneous Neural Oscillation Events in Primate Auditory Cortex.

Electrophysiological oscillations in the brain have been shown to occur as multicycle events, with onset and offset dependent on behavioral and cognitive state. To provide a baseline for state-related and task-related events, we quantified oscillation features in resting-state recordings. We developed an open-source wavelet-based tool to detect and characterize such oscillation events (OEvents) and exemplify the use of this tool in both simulations and two invasively-recorded electrophysiology datasets: one from human, and one from nonhuman primate (NHP) auditory system. After removing incidentally occurring event-related potentials (ERPs), we used OEvents to quantify oscillation features. We identified ∼2 million oscillation events, classified within traditional frequency bands: δ, θ, α, β, low γ, γ, and high γ. Oscillation events of 1–44 cycles could be identified in at least one frequency band 90% of the time in human and NHP recordings. Individual oscillation events were characterized by nonconstant frequency and amplitude. This result necessarily contrasts with prior studies which assumed frequency constancy, but is consistent with evidence from event-associated oscillations. We measured oscillation event duration, frequency span, and waveform shape. Oscillations tended to exhibit multiple cycles per event, verifiable by comparing filtered to unfiltered waveforms. In addition to the clear intraevent rhythmicity, there was also evidence of interevent rhythmicity within bands, demonstrated by finding that coefficient of variation of interval distributions and Fano factor (FF) measures differed significantly from a Poisson distribution assumption. Overall, our study provides an easy-to-use tool to study oscillation events at the single-trial level or in ongoing recordings, and demonstrates that rhythmic, multicycle oscillation events dominate auditory cortical dynamics.

Measuring Task-Related Brain Activity With Event-Related Potentials in Dynamic Task Scenario With Immersive Virtual Reality Environment.

Measurement of event-related potentials (ERPs) in simulated and real environments is advantageous for understanding cognition and behavior during practice of goal-directed activities. Recently, instead of using task-irrelevant “probe stimuli” to elicit ERPs, extraction of ERPs directly from events that occur in simulated and real environments has drawn increased attention. Among the previous ERP studies using immersive virtual reality, only a few cases elicited ERPs from task-related events in dynamic task settings. Furthermore, as far as we surveyed, there were no studies that examined the source of ERPs or correlation between ERPs and behavioral performance in 360-degree immersive virtual reality using head-mounted display. In this study, EEG signals were recorded from 16 participants while they were playing the first-person shooter game with immersive virtual reality environment. Error related negativity (ERN) and correct-(response)-related negativity (CRN) elicited by shooting-related events were successfully extracted. We found the ERN amplitudes to be correlated with the individual shooting performance. Interestingly, the main source of the ERN was the rostral anterior cingulate cortex (ACC), which is different from previous studies where the signal source was often estimated to be the more caudal part of ACC. The obtained results are expected to contribute to the evaluation of cognitive functions and behavioral performance by ERPs in a simulated environment.

Quantifying Dynamic Resilience using First-process Autoregressive Modelling: An Empirical Study

Dynamic resilience is a temporal process that reflects individuals’ capability to overcome task-induced stress and sustain their performance during task-related events. First-order autoregressive (AR(1)) modelling is posited for measuring individuals’ dynamic resilience over time. The current research investigated this by testing 30 adults in a dynamic decision-making task. AR(1) modelling was conducted on the data, and was compared against a modified seismic resilience metric for concurrent validity purposes. Results revealed that AR(1) modeled parameters are applicable in assessing participants’ dynamic resilience, with analyses supporting their use to distinguish between individuals that can overcome task-induced stress and those that cannot, as well as, in the classification of individuals’ dynamic resilience.

Pitfalls in Scalp High-Frequency Oscillation Detection From Long-Term EEG Monitoring.

Aims: Intracranially recorded high-frequency oscillations (>80 Hz) are considered a candidate epilepsy biomarker. Recent studies claimed their detectability on the scalp surface. We aimed to investigate the applicability of high-frequency oscillation analysis to routine surface EEG obtained at an epilepsy monitoring unit.Methods: We retrospectively analyzed surface EEGs of 18 patients with focal epilepsy and six controls, recorded during sleep under maximal medication withdrawal. As a proof of principle, the occurrence of motor task-related events during wakefulness was analyzed in a subsample of six patients with seizure- or syncope-related motor symptoms. Ripples (80–250 Hz) and fast ripples (>250 Hz) were identified by semi-automatic detection. Using semi-parametric statistics, differences in spontaneous and task-related occurrence rates were examined within subjects and between diagnostic groups considering the factors diagnosis, brain region, ripple type, and task condition.Results: We detected high-frequency oscillations in 17 out of 18 patients and in four out of six controls. Results did not show statistically significant differences in the mean rates of event occurrences, neither regarding the laterality of the epileptic focus, nor with respect to active and inactive task conditions, or the moving hand laterality. Significant differences in general spontaneous incidence [WTS(1) = 9.594; p = 0.005] that indicated higher rates of fast ripples compared to ripples, notably in patients with epilepsy compared to the control group, may be explained by variations in data quality.Conclusion: The current analysis methods are prone to biases. A common agreement on a standard operating procedure is needed to ensure reliable and economic detection of high-frequency oscillations.

Electrophysiological Evidence for Distinct Proactive Control Mechanisms in a Stop-Signal Task: An Individual Differences Approach.

Proactive control reflects a sustained, top-down maintenance of a goal representation prior to task-related events, whereas reactive control reflects a transient, bottom-up goal reactivation in response to them. We designed a manual stop-signal task to isolate electrophysiological signals specifically involved in proactive control. Participants performed a simple choice reaction time task but had to withhold their response to an infrequent stop signal, resulting in go- and stop-signal trials. We manipulated the stop-signal probability (30% vs. 10%) over different blocks of trials so that different proactive control levels were sustained within each block. The behavioral results indicated that most participants proactively changed their behaviors. The reaction times in the go trials increased and the number of response errors in the stop-signal trials decreased. However, those two behavioral measures did not correlate: individuals with an increased delayed reaction did not necessarily manifest a higher decrease in response errors in the stop-signal trials. To isolate the proactive control signal, we obtained event-related potentials (ERPs) locked to an uninformative fixation onset and compared the signals between the two stop-signal probability conditions. We found that the ERPs at the left hemisphere were more negatively shifted with the increasing stop-signal probability. Moreover, ERP differences obtained from a set of electrodes in the left hemisphere accounted for the changes in response errors in the stop-signal trials but did not explain the changes in reaction times of the go trials. Together, the behavioral and electrophysiological results suggest that proactive control mechanisms reducing erroneous responses of the stop-signal trials are different from mechanisms slowing reaction times of the go trials.

Effects of chronic cannabinoid exposure during adolescence on reward preference and mPFC activation in adulthood

Cannabis is one of the most commonly used drugs among adolescents, with initial use beginning between the ages of 12 to 17. Although often perceived as a ‘soft drug’, both short- and long-term use have been associated with numerous adverse outcomes, including cognitive impairment, increased risk of substance abuse, and heightened risk of psychosis or schizophrenia in individuals with a predisposition. Further, the severity of these impairments is closely linked to initiation of use, i.e. earlier use increases risk. It has been suggested that adolescent vulnerability to the adverse consequences of cannabis use is due to ongoing brain development occurring during this time. Indeed, the adolescent brain continues to be remodeled well into adolescence and early adulthood, particularly in the prefrontal cortex (PFC). The medial prefrontal cortex (mPFC) has been implicated in reward processing and decision-making and alterations in mPFC development due to adolescent cannabis exposure could impair these functions. To model the effects of cannabis on mPFC function, we administered the synthetic cannabinoid WIN 55, 212–2 (WIN) to male and female rats from postnatal day 30–60. Once animals reached adulthood, we used a Probabilistic Reward (PR) choice task to elicit PFC activity and measure how patterns of activity to task-related events were modulated by adolescent WIN-treatment. Adult animals showed subtle effects of WIN-treatment on choice patterns. During task performance, mPFC activity elicited by lever press at the time of choices and reward delivery following choices were reduced in WIN-treated animals. This lasting effect of WIN suggests an impairment of the maturation of excitatory-inhibitory balance of signals in mPFC during adolescence, which may alter executive function into adulthood.

Human midcingulate cortex encodes distributed representations of task progress

The function of midcingulate cortex (MCC) remains elusive despite decades of investigation and debate. Complicating matters, individual MCC neurons respond to highly diverse task-related events, and MCC activation is reported in most human neuroimaging studies employing a wide variety of task manipulations. Here we investigate this issue by applying a model-based cognitive neuroscience approach involving neural network simulations, functional magnetic resonance imaging, and representational similarity analysis. We demonstrate that human MCC encodes distributed, dynamically evolving representations of extended, goal-directed action sequences. These representations are uniquely sensitive to the stage and identity of each sequence, indicating that MCC sustains contextual information necessary for discriminating between task states. These results suggest that standard univariate approaches for analyzing MCC function overlook the major portion of task-related information encoded by this brain area and point to promising new avenues for investigation.

The Benefits and the Costs of Using Auditory Warning Messages in Dynamic Decision-Making Settings

The failure to notice critical changes in both visual and auditory scenes may have important consequences for performance in complex dynamic environments, especially those related to security, such as aviation, surveillance during major events, and command and control of emergency response. Previous work has shown that a significant number of situation changes remain undetected by operators in such environments. In the current study, we examined the impact of using auditory warning messages to support the detection of critical situation changes and to a broader extent the decision making required by the environment. Twenty-two participants performed a radar operator task involving multiple subtasks while detecting critical task-related events that were cued by a specific type of audio message. Results showed that about 22% of the critical changes remained undetected by participants, a percentage similar to that found in previous work using visual cues to support change detection. However, we found that audio messages tended to bias threat evaluation toward perceiving objects as more threatening than they were in reality. Such findings revealed both benefits and costs associated with using audio messages to support change detection in complex dynamic environments.

Cell-Type-Specific Activity in Prefrontal Cortex during Goal-Directed Behavior

The prefrontal cortex (PFC) plays a key role in controlling goal-directed behavior. Although a variety of task-related signals have been observed in the PFC, whether they are differentially encoded by various cell types remains unclear. Here we performed cellular-resolution microendoscopic Ca(2+) imaging from genetically defined cell types in the dorsomedial PFC of mice performing a PFC-dependent sensory discrimination task. We found that inhibitory interneurons of the same subtype were similar to each other, but different subtypes preferentially signaled different task-related events: somatostatin-positive neurons primarily signaled motor action (licking), vasoactive intestinal peptide-positive neurons responded strongly to action outcomes, whereas parvalbumin-positive neurons were less selective, responding to sensory cues, motor action, and trial outcomes. Compared to each interneuron subtype, pyramidal neurons showed much greater functional heterogeneity, and their responses varied across cortical layers. Such cell-type and laminar differences in neuronal functional properties may be crucial for local computation within the PFC microcircuit.

Multichannel EEG Signal Recording Analysis based on Cross Frequency Coupling Method

Abstract Cross-frequency coupling (CFCo) could be important to study task-relevant manner changes in time series (TS). CFCo might also serve as an instrument to distinguish between oscillatory states and interrelations in signals, and to exhibit characteristic changes. Presenting the use of phase-amplitude type Cross Frequency Coupling, named Phase-Amplitude-Coupling (PAC) is the objective of this presentation. PAC describes the statistical dependence between the phase of a low-frequency brain rhythm and the amplitude (or power) of the higher-frequency component of electrical activity in the brain. Two other varieties of signal coupling are possible. These are the cross-frequency phase synchronization (phase-phase CFCo) and cross-frequency amplitude envelope correlation (amplitude-amplitude CFCo). These procedures should be efficient to study possible mechanism to regulate interrelation of the multichannel recorded EEG signals. As it is known, EEG signals are nonlinear and non-stationary signals. Interdependence of the different frequency range EEG signals, must be studied to understand internal behaviour of signals generated by different cortical areas. The paper is based on multichannel EEG recordings. It is possible to detect correlations between distal cortical regions during different task related events as Event Related Potentials (ERP). Correlation factor of left-right hemisphere's signals, recorded in biologically symmetric scalp positions are important in ERP studies. The Hilbert transform based method is also involved to have a way to analyze the interrelations of different brain region activities.

간호대학생의 생활스트레스와 삶의 질

Purpose: This study was conducted to assess stressful life events and quality of life in nursing students. Methods: We performed a cross-sectional research design. A structured questionnaire was designed to collect data on participants' socio-demographics, stressful life events (interpersonal relationship & task-related events) and quality of life (WHOQOL-Bref) in September 2011. Descriptive statistics, t-test, one-way ANOVA, Pearson correlation coefficient and hierarchical multiple regression were applied to data analysis. Results: A total of 135 nursing students were surveyed. The score of the task-related stressful life events was higher than that of the interpersonal stressful life events. Physical domain score (<TEX>$13.53{\pm}2.33$</TEX>) was highest but environmental domain score (<TEX>$12.75{\pm}2.34$</TEX>) was lowest in quality of life. Satisfaction with campus life affected stressful life events (F=11.82, p<.001) and quality of life (F=17.77, p<.001), and extracurricular activities affect quality of life (t=-2.51, p=.013). Quality of life was negatively associated with task-related stressful life events (r=.-51, p<.001). Multiple regression analyses showed that extracurricular activities, satisfaction with campus life and task-related stressful life events were statistically significant in predicting quality of life with the explanatory power of 40.6%. Conclusion: This study could be a reference to improve the quality of life of nursing students.

Task-related, low-frequency task-residual, and resting state activity in the default mode network brain regions.

The hypothesis of a default mode network (DMN) of brain function is based on observations of task-independent decreases of brain activity during effort as participants are engaged in tasks in contrast to resting. On the other hand, studies also showed that DMN regions activate rather than deactivate in response to task-related events. Thus, does DMN “deactivate” during effort as compared to resting? We hypothesized that, with high-frequency event-related signals removed, the task-residual activities of the DMN would decrease as compared to resting. We addressed this hypothesis with two approaches. First, we examined DMN activities during resting, task residuals, and task conditions in the stop signal task using independent component analysis (ICA). Second, we compared the fractional amplitude of low-frequency fluctuation (fALFF) signals of DMN in resting, task residuals, and task data. In the results of ICA of 76 subjects, the precuneus and posterior cingulate cortex (PCC) showed increased activation during task as compared to resting and task residuals, indicating DMN responses to task events. Precuneus but not the PCC showed decreased activity during task residual as compared to resting. The latter finding was mirrored by fALFF, which is decreased in the precuneus during task residuals, as compared to resting and task. These results suggested that the low-frequency blood oxygen level-dependent signals of the precuneus may represent a useful index of effort during cognitive performance.

Paradigm free mapping with sparse regression automatically detects single-trial functional magnetic resonance imaging blood oxygenation level dependent responses.

The ability to detect single trial responses in functional magnetic resonance imaging (fMRI) studies is essential, particularly if investigating learning or adaptation processes or unpredictable events. We recently introduced paradigm free mapping (PFM), an analysis method that detects single trial blood oxygenation level dependent (BOLD) responses without specifying prior information on the timing of the events. PFM is based on the deconvolution of the fMRI signal using a linear hemodynamic convolution model. Our previous PFM method (Caballero-Gaudes et al., 2011: Hum Brain Mapp) used the ridge regression estimator for signal deconvolution and required a baseline signal period for statistical inference. In this work, we investigate the application of sparse regression techniques in PFM. In particular, a novel PFM approach is developed using the Dantzig selector estimator, solved via an efficient homotopy procedure, along with statistical model selection criteria. Simulation results demonstrated that, using the Bayesian information criterion to select the regularization parameter, this method obtains high detection rates of the BOLD responses, comparable with a model-based analysis, but requiring no information on the timing of the events and being robust against hemodynamic response function variability. The practical operation of this sparse PFM method was assessed with single-trial fMRI data acquired at 7T, where it automatically detected all task-related events, and was an improvement on our previous PFM method, as it does not require the definition of a baseline state and amplitude thresholding and does not compromise on specificity and sensitivity.

Neural Activity in Frontal Cortical Cell Layers: Evidence for Columnar Sensorimotor Processing

The mammalian frontal cortex (FCx) is at the top of the brain's sensorimotor hierarchy and includes cells in the supragranular Layer 2/3, which integrate convergent sensory information for transmission to infragranular Layer 5 cells to formulate motor system outputs that control behavioral responses. Functional interaction between these two layers of FCx was examined using custom-designed ceramic-based microelectrode arrays (MEAs) that allowed simultaneous recording of firing patterns of FCx neurons in Layer 2/3 and Layer 5 in nonhuman primates performing a simple go/no-go discrimination task. This unique recording arrangement showed differential encoding of task-related sensory events by cells in each layer with Layer 2/3 cells exhibiting larger firing peaks during presentation of go target and no-go target task images, whereas Layer 5 cells showed more activity during reward contingent motor responses in the task. Firing specificity to task-related events was further demonstrated by synchronized firing between pairs of cells in different layers that occupied the same vertically oriented "column" on the MEA. Pairs of cells in different layers recorded at adjacent "noncolumnar" orientations on the MEA did not show synchronized firing during the same task-related events. The results provide required evidence in support of previously suggested task-related sensorimotor processing in the FCx via functionally segregated minicolumns.

Contextual variables affecting aggressive behaviour in individuals with mild to borderline intellectual disabilities who live in a residential facility

Aggression is a common type of problem behaviour in clients with mild to borderline intellectual disability who live in a residential facility. We explored contextual events that elicit aggressive behaviour and variables that were associated with such events. Respondents were 87 direct-care staff members of 87 clients with aggressive behaviour who lived in a residential facility. Staff members completed the Contextual Assessment Inventory (CAI) and a questionnaire on demographic information and types, frequency and severity of aggressive behaviour. Internal consistency of the total CAI was excellent (alpha = 0.95), and Cronbach alpha's for the CAI sub-scales ranged from 0.75 to 0.93. Inter-rater agreement for the CAI could be considered good (mean intra-class correlation coefficient = 0.63). Both social and task-related events were reported to evoke aggressive behaviour of clients most often. Negative interactions, task characteristics and daily routines relatively often evoked aggressive behaviour while an uncomfortable environment, medication, illness and physiological states (i.e. physical and biological events) evoked aggressive behaviour least often. Mean CAI sub-scale scores were significantly related to gender, IQ and frequency of aggressive behaviour. The present study extends our knowledge regarding events that are associated with an increased probability of aggressive behaviour. Knowledge of these contextual variables may be helpful in designing programmes (e.g. applied behaviour analysis, social skills training and cognitive behavioural therapies) for the management and prevention of aggressive behaviour in clients with mild to borderline intellectual disability who live in a residential facility.

Lack of Spike-Count and Spike-Time Correlations in the Substantia Nigra Reticulata Despite Overlap of Neural Responses

Previous studies of single neurons in the substantia nigra reticulata (SNr) have shown that many of them respond to similar events. These results, as well as anatomical studies, suggest that SNr neurons share inputs and thus may have correlated activity. Different types of correlation can exist between pairs of neurons. These are traditionally classified as either spike-count ("signal" and "noise") or spike-timing (spike-to-spike and joint peristimulus time histograms) correlations. These measures of neuronal correlation are partially independent and have different implications. Our purpose was to probe the computational characteristics of the basal ganglia output nuclei through an analysis of these different types of correlation in the SNr. We carried out simultaneous multiple-electrode single-unit recordings in the SNr of two monkeys performing a probabilistic delayed visuomotor response task. A total of 113 neurons (yielding 355 simultaneously recorded pairs) were studied. Most SNr neurons responded to one or more task-related events, with instruction cue (69%) and reward (63%) predominating. Response-match analysis, comparing peristimulus time histograms, revealed a significant overlap between response vectors. However, no measure of average correlation differed significantly from zero. The lack of significant SNr spike-count population correlations appears to be an exceptional phenomenon in the brain, perhaps indicating unique event-related processing by basal ganglia output neurons to achieve better information transfer. The lack of spike-timing correlations suggests that the basal high-frequency discharge of SNr neurons is not driven by the common inputs and is probably intrinsic.

Statistics of Midbrain Dopamine Neuron Spike Trains in the Awake Primate

Work in behaving primates indicates that midbrain dopamine neurons encode a prediction error, the difference between an obtained reward and the reward expected. Studies of dopamine action potential timing in the alert and anesthetized rat indicate that dopamine neurons respond in tonic and phasic modes, a distinction that has been less well characterized in the primates. We used spike train models to examine the relationship between the tonic and burst modes of activity in dopamine neurons while monkeys were performing a reinforced visuo-saccadic movement task. We studied spiking activity during four task-related intervals; two of these were intervals during which no task-related events occurred, whereas two were periods marked by task-related phasic activity. We found that dopamine neuron spike trains during the intervals when no events occurred were well described as tonic. Action potentials appeared to be independent, to occur at low frequency, and to be almost equally well described by Gaussian and Poisson-like (gamma) processes. Unlike in the rat, interspike intervals as low as 20 ms were often observed during these presumptively tonic epochs. Having identified these periods of presumptively tonic activity, we were able to quantitatively define phasic modulations (both increases and decreases in activity) during the intervals in which task-related events occurred. This analysis revealed that the phasic modulations of these neurons include both bursting, as has been described previously, and pausing. Together bursts and pauses seemed to provide a continuous, although nonlinear, representation of the theoretically defined reward prediction error of reinforcement learning.

Progression of Cellular Adaptations in Medial Prefrontal and Orbitofrontal Cortex in Response to Repeated Amphetamine

Recent theories on addiction implicate adaptive changes in prefrontal cortex (PFC) neurons in reinforcing and psychotomimetic properties of psychostimulants, yet little is known about how neuronal responses to these drugs change over time. Here we describe electrophysiological evidence for a progressive and sustained change in the response of PFC neurons to amphetamine during repeated exposure. In spontaneously behaving rats and in rats engaged in an instrumental responding task, we followed the activity of medial PFC (mPFC) and orbitofrontal cortex (OFC) neurons during daily exposure to amphetamine and after a post-withdrawal challenge. Repeated amphetamine increased the number of responsive neurons and the magnitude of responses and modified spontaneous burst patterns. These changes were apparent after a few exposures to amphetamine, were amplified after withdrawal, and were region specific in that repeated amphetamine increasingly produced inhibitory responses in mPFC and excitatory responses in OFC. In behaviorally engaged animals, the gradual enhancement in mPFC inhibition and OFC overactivation correlated with a progressive impairment of instrumental responding. Furthermore, these changes were evident predominately in neurons that displayed phasic responses during task-related events. These rapid-onset and sustained cellular adaptations suggest that even limited exposure to psychostimulants may reduce the influence of mPFC neurons on behavior while at the same time exaggerating information encoded by OFC neurons.