Attentional State Research Articles

Acoustic Biotopes, Listeners and Sound-Induced Action: A Case Study of Operating Rooms

As socio-technological environments shape and direct listener behaviour, an ecological account is needed that encompasses listening in complexity (i.e., multiple listeners, multiple sounds and their sources, and multiple sound-induced actions that ensure the success of a mission). In this study, we explored sound-induced action under the framework of "acoustic biotopes" (a notion of ecological acoustics by Smolders, Aertsen, and Johanessma, 1979 and 1982) in a specific socio-technological environment, i.e., the context of an orthopaedic operating room. Our approach is based on literature research into the topics of environmental psychology and auditory perception and action and in situ observations in healthcare with field recordings, participatory observations, and interviews on the spot. The results suggest a human-centered definition of sound-induced action in acoustic biotopes: Acoustic biotope is an active and shared sound environment with entangled interactions and sound-induced actions taking place in a specific space that has a critical function. Listening in highly functional environments is an individual experience and is influenced by hearing function, physical position and role in an environment, and the task at hand. There is a range of active and passive sound listeners as a function of their attentive state and listeners as sound sources within the acoustic biotope. There are many different sound sources and sound locals in socio-technological environments and sounds have great potential to serve critical information to operators. Overall, our study provides a holistic, multi-layered and yet a listener-centric view on the organisation of complex spaces and the results can immediately be applicable for rethinking the acoustic environment for ORs for better listening and sound-induced action.

Drivers’ gaze patterns when resuming control with a head-up-display: Effects of automation level and time budget

The removal of drivers’ active engagement in driving tasks can lead to erratic gaze patterns in SAE Level 2 (L2) and Level 3 (L3) automation, which has been linked to their subsequential degraded take-over performance. To further address how changes in gaze patterns evolve during the take-over phase, and whether they are influenced by the take-over urgency and the location of the human-machine interface, this driving simulator study used a head-up display (HUD) to relay information about the automation status and conducted take-over driving experiments where the ego car was about to exit the highway with variations in the automation level (L2, L3) and time budget (2 s, 6 s). In L2 automation, drivers were required to monitor the environment, while in L3, they were engaged with a visual non-driving related task. Manual driving was also embodied in the experiments as the baseline. Results showed that, compared to manual driving, drivers in L2 automation focused more on the HUD and Far Road (roadway beyond 2 s time headway ahead), and less on the Near Road (roadway within 2 s time headway ahead); while in L3, drivers’ attention was predominantly allocated on the non-driving related task. After receiving take-over requests (TORs), there was a gradual diversion of attention from the Far Road to the Near Road in L2 take-overs. This trend changed nearly in proportion to the time within the time budget and it exaggerated given a shorter time budget of 2 s. While in L3, drivers’ gaze distribution was similar in the early stage of take-overs for both time budget conditions (2 s vs. 6 s), where they prioritized their early glances to Near Road with a gradual increase in attention towards Far Road. The HUD used in the present study showed the potential to maintain drivers’ attention around the road center during automation and to encourage drivers to glance the road earlier after TORs by reducing glances to the instrument cluster, which might be of significance to take-over safety. These findings were discussed based on an extended conceptual gaze control model, which advances our understanding of gaze patterns around control transitions and their underlying gaze control causations. Implications can be contributed to the design of autonomous vehicles to facilitate the transition of control by guiding drivers’ attention appropriately according to drivers’ attentional state and the take-over urgency.

EEG source derived salience network coupling supports real-world attention switching

While the brain mechanisms underlying selective attention have been studied in great detail in controlled laboratory settings, it is less clear how these processes function in the context of a real-world self-paced task. Here, we investigated engagement on a real-world computerized task equivalent to a standard academic test that consisted of solving high-school level problems in a self-paced manner. In this task, we used EEG-source derived estimates of effective coupling between brain sources to characterize the neural mechanisms underlying switches of sustained attention from the attentive on-task state to the distracted off-task state. Specifically, since the salience network has been implicated in sustained attention and attention switching, we conducted a hypothesis-driven analysis of effective coupling between the core nodes of the salience network, the anterior insula (AI) and the anterior cingulate cortex (ACC). As per our hypothesis, we found an increase in AI - > ACC effective coupling that occurs during the transitions of attention from on-task focused to off-task distracted state. This research may inform the development of future neural function-targeted brain-computer interfaces to enhance sustained attention.

Tracking momentary fluctuations in human attention with a cognitive brain-machine interface.

Selective attention produces systematic effects on neural states. It is unclear whether, conversely, momentary fluctuations in neural states have behavioral significance for attention. We investigated this question in the human brain with a cognitive brain-machine interface (cBMI) for tracking electrophysiological steady-state visually evoked potentials (SSVEPs) in real-time. Discrimination accuracy (d') was significantly higher when target stimuli were triggered at high, versus low, SSVEP power states. Target and distractor SSVEP power was uncorrelated across the hemifields, and target d' was unaffected by distractor SSVEP power states. Next, we trained participants on an auditory neurofeedback paradigm to generate biased, cross-hemispheric competitive interactions between target and distractor SSVEPs. The strongest behavioral effects emerged when competitive SSVEP dynamics unfolded at a timescale corresponding to the deployment of endogenous attention. In sum, SSVEP power dynamics provide a reliable readout of attentional state, a result with critical implications for tracking and training human attention.

Foreground and Background in Mental Models.

Foreground and Background in Mental Models.

Baromania: A contrarian epidemic.

As the world grapples with a rapidly increasing prevalence of obesity, epidemiologists, health care professionals and policy makers are working together to increase awareness about its prevention and management. However, what is also increasingly visible in a subset of not very obese individuals, is an undue concern about their weight, a condition we call Baromania. Akin to orthorexia nervosa, anorexia and bulimia. we define baromania as "a state of extreme attention towards one's own weight, accompanied by elation and excitement regarding weight loss and maintenance". This paper describes the different clinical presentations, diagnosis and management of persons with Baromania.

Measuring and Computing Cognitive Statuses of Construction Workers Based on Electroencephalogram: A Critical Review

Construction workers’ cognitive statuses affecting their safety and productivity are essential for successful construction management. Electroencephalogram (EEG) provides a potential objective tool for measuring and computing the cognitive status of construction workers. This study aims to answer how to adopt EEG for measuring and computing construction workers’ cognitive statuses through a critical review. The literature search and selection process included 21 eligible articles. The content analysis was then conducted from three aspects of investigated cognitive statuses, experiment design, and data analysis. The investigated cognitive statuses include vigilance, mental fatigue, mental stress, attention, mental workload, and emotional state. The experiment design is reviewed from the perspective of participant selection, device selection and electrode deployment, task design, and label selection. The data analysis involves EEG signal preprocessing, feature extraction, and cognitive status computation. Five major limitations of the existing studies have been identified, and five future research directions are proposed to address these limitations. This review provides guidance for researchers to use EEG for measuring and computing various cognitive statuses of construction workers. It also provides valuable suggestions for future research and on-site construction management.

PREVALÊNCIA DE COMPROMETIMENTO COGNITIVO EM INDÍGENAS BRASILEIROS DO AMAZONAS

ABSTRACT. Studies on the prevalence of dementia in the indigenous population are still scarce worldwide. In the few available studies, prevalence evidence varies from low to very high, with early onset of the disease and high mortality rate after the initial diagnosis. Still, little is known about the rate of dementia in indigenous populations from low- and middle-income countries, where the dementia prevalence in the general population is estimated to increase significantly in the next decades. Objective: This study aimed to determine the prevalence of cognitive impairment and associated factors in Brazilian indigenous people of the Mura ethnicity in Amazonas, Brazil. Methods: A total of 217 indigenous individuals aged 50 years and older from Amazonas, Brazil, were submitted to cognitive assessment. Attention, memory, verbal fluency, visuospatial performance, and mood state composed the cognitive impairment diagnosis. Results: The prevalence of cognitive impairment was 43.3% (95%CI 36.6-49.7) and varied according to age [OR=1.03 (95%CI 1.00-1.06)], education [OR=0.74 (95%CI 0.62-0.87)], body mass index [OR=0.91 (95%CI 0.83-0.98)], and income [OR=0.52 (95%CI 0.27-0.99)]. Conclusions: Cognitive impairment had an early onset in an indigenous community, and its prevalence was greater in older individuals with low education and low family income. These findings highlight the importance of implementing public indigenous health policies focusing on health professional training for early cognitive impairment detection.

Voluntary self-initiation of the stimuli onset improves working memory and accelerates visual and attentional processing

The ability of an organism to voluntarily control the stimuli onset modulates perceptual and attentional functions. Since stimulus encoding is an essential component of working memory (WM), we conjectured that controlling the initiation of the perceptual process would positively modulate WM. To corroborate this proposition, we tested twenty-five healthy subjects in a modified-Sternberg WM task under three stimuli presentation conditions: an automatic presentation of the stimuli, a self-initiated presentation of the stimuli (through a button press), and a self-initiated presentation with random-delay stimuli onset. Concurrently, we recorded the subjects' electroencephalographic signals during WM encoding. We found that the self-initiated condition was associated with better WM accuracy, and earlier latencies of N1, P2 and P3 evoked potential components representing visual, attentional and mental review of the stimuli processes, respectively. Our work demonstrates that self-initiated stimuli enhance WM performance and accelerate early visual and attentional processes deployed during WM encoding. We also found that self-initiated stimuli correlate with an increased attentional state compared to the other two conditions, suggesting a role for temporal stimuli predictability. Our study remarks on the relevance of self-control of the stimuli onset in sensory, attentional and memory updating processing for WM.

Drowsiness Detection in the Era of Industry 4.0: Are We Ready?

Interconnectivity and smart automation of Internet of Things in recent times have led to the concept of Industry 4.0. Together with the improvement in productivity and new business models, employment conditions should take advantage of these new technologies. Safety in the workplace is one of the most sensitive topics on matters that needs targeted and accurate solutions. The safety can be guaranteed by investigating the attention states of the workers, and in particular, their drowsiness levels. Several technologies have faced this problem by using biometrics, but how many of them are applicable in a real-case-use scenario of Industry 4.0? This article aims to answer this question by discussing available data and methods that can be used in specific workplaces. We highlight their limitations and accuracy to sketch out the recent literature that may contribute to worker safety in Industry 4.0. Finally, we point out a gap that needs to be filled in order to implement these strategies on a large scale.

Decoding the cognitive states of attention and distraction in a real-life setting using EEG

Lapses in attention can have serious consequences in situations such as driving a car, hence there is considerable interest in tracking it using neural measures. However, as most of these studies have been done in highly controlled and artificial laboratory settings, we want to explore whether it is also possible to determine attention and distraction using electroencephalogram (EEG) data collected in a natural setting using machine/deep learning. 24 participants volunteered for the study. Data were collected from pairs of participants simultaneously while they engaged in Tibetan Monastic debate, a practice that is interesting because it is a real-life situation that generates substantial variability in attention states. We found that attention was on average associated with increased left frontal alpha, increased left parietal theta, and decreased central delta compared to distraction. In an attempt to predict attention and distraction, we found that a Long Short Term Memory model classified attention and distraction with maximum accuracy of 95.86% and 95.4% corresponding to delta and theta waves respectively. This study demonstrates that EEG data collected in a real-life setting can be used to predict attention states in participants with good accuracy, opening doors for developing Brain-Computer Interfaces that track attention in real-time using data extracted in daily life settings, rendering them much more usable.

Threat induction biases processing of emotional expressions.

Threats can derive from our physical or social surroundings and bias the way we perceive and interpret a given situation. They can be signaled by peers through facial expressions, as expressed anger or fear can represent the source of perceived threat. The current study seeks to investigate enhanced attentional state and defensive reflexes associated with contextual threat induced through aversive sounds presented in an emotion recognition paradigm. In a sample of 120 healthy participants, response and gaze behavior revealed differences in perceiving emotional facial expressions between threat and safety conditions: Responses were slower under threat and less accurate. Happy and neutral facial expressions were classified correctly more often in a safety context and misclassified more often as fearful under threat. This unidirectional misclassification suggests that threat applies a negative filter to the perception of neutral and positive information. Eye movements were initiated later under threat, but fixation changes were more frequent and dwell times shorter compared to a safety context. These findings demonstrate that such experimental paradigms are capable of providing insight into how context alters emotion processing at cognitive, physiological, and behavioral levels. Such alterations may derive from evolutionary adaptations necessary for biasing cognitive processing to survive disadvantageous situations. This perspective sets up new testable hypotheses regarding how such levels of explanation may be dysfunctional in patient populations.

The restorative effects of short-term exposure to nature in immersive virtual environments (IVEs) as evidenced by participants' brain activities

Short-term exposure to nature has excellent potential to be used as a public health intervention measure. Nevertheless, the physiological and psychological mechanisms of this health benefit are still unclear. In this study, we intend to verify the effects of short-term exposure to nature on psychological functioning and to explore the underlying mechanism through experiments conducted in immersive virtual environments (IVEs). Participants were randomly exposed to videos of an urban forest and an indoor environment in IVEs. Before and after the exposure, a participant's self-perceived stress and cognitive performance were measured using the PSS-14 form and the Stroop task, respectively. Their brain activities during the exposure were measured using the electroencephalogram (EEG). The PSS-14 and the Stroop task results confirmed the benefits of stress reduction and cognitive performance improvements from short-term nature exposure. At the same time, rhythmic brain activities during nature exposure indicated better attentional states. The electrodes around the parietal region detected significantly stronger power spectral density of the theta band than other bands. Also, participants showed high functional connectivity among different brain parts during nature exposure, which revealed better cognitive flexibility. The topographic pattern of the differences in functional connectivity overlapped well with the default mode network (DMN)—a “task-negative” network active during the resting state. The overlap indicated a lower cognitive processing load when exposing to nature. Our results support the hypothesis that nature's restorative effects mainly come from effortless processing in natural environments.

Learned feature regularities enable suppression of spatially overlapping stimuli

Contemporary theories of attentional control state that information can be prioritized based on selection history. Even though theories agree that selection history can impact representations of spatial location, which in turn helps guide attention, there remains disagreement on whether nonspatial features (e.g., color) are modulated in a similar way. While previous work has demonstrated color suppression using visual search tasks, it is possible that the location corresponding to the distractor was suppressed, consistent with a spatial mechanism of suppression. Here, we sought to rule out this possibility by testing whether similar suppression of a learned distractor color can occur for spatially overlapping visual stimuli. On a given trial, two spatially superimposed stimuli (line arrays) were tilted either left or right of vertical and presented in one of four distinct colors. Subjects performed a speeded report of the orientation of the “target” array with the most lines. Critically, the distractor array was regularly one color, and this high-probability color was never the color of the target array, which encouraged learned suppression. In two experiments, responses to the target array were fastest when the distractor array was in the high-probability color, suggesting participants suppressed the distractor color. Additionally, when regularities were removed, the high-probability distractor color continued to benefit speeded target identification for individual subjects (E1) but slowed target identification (E2) when presented in the target array. Together, these results indicate that learned suppression of feature-based regularities modulates target detection performance independent of spatial location and persists over time.

Human visual processing during walking: Dissociable pre- and post-stimulus influences

Walking influences visual processing but the underlying mechanism remains poorly understood. In this study, we investigated the influence of walking on pre-stimulus and stimulus-induced visual neural activity and behavioural performance in a discrimination task while participants were standing or freely walking. The results showed dissociable pre- and post-stimulus influences by the movement state. Walking was associated with a reduced pre-stimulus alpha power, which predicted enhanced N1 and decreased P3 components during walking. This pre-stimulus alpha activity was additionally modulated by time on the task, which was paralleled by a similar behavioural modulation. In contrast, the post-stimulus alpha power was reduced in its modulation due to stimulus onset during walking but showed no evidence of modulation by time on the task. Additionally, stimulus parameters (eccentricity, laterality, distractor presence significantly influenced post-stimulus alpha power, whereas the visually evoked components showed no evidence of such an influence. There was further no evidence of a correlation between pre-stimulus and post stimulus alpha power. We conclude that walking has two dissociable influences on visual processing: while the walking induced reduction in alpha power suggests an attentional state change that relates to visual awareness, the post-stimulus influence on alpha power modulation indicates changed spatial visual processing during walking.

Anodal Transcranial Direct Current Stimulation Reduces Competitive Anxiety and Modulates Heart Rate Variability in an eSports Player.

Previous research has recently shown that high cognitive and somatic anxiety and low self-confidence, before and during sport competitions have a significant correlation with heart rate variability (HRV) changes and can reduce overall athletic performance. Therefore, interventions, such as transcranial direct current stimulation (tDCS), can be a potential tool to reduce psychophysiological anxiety-related and enhance athletic performance. We present a case of a male professional athlete of eSports. We explored the effects of a single session of anodal tDCS (a-tDCS) at 2mA over the dosrsolateral prefrontal cortex (DLPFC) on competitive anxiety and HRV assessed in baseline (BL), pre-tDCS, post-tDCS and post-game moments and compared between moments. Here, we found a decrease in somatic and cognitive anxiety, as well as an increase in self-confidence and in SDNN index in the post-tDCS moment compared with BL, pre-tDCS and post-game moments. These findings can be a result of an acute change in the attentional state, influencing the processing of threatening information essential for cognitive anxiety and of a self-regulatory process, which can regulate physiological arousal response, such as HRV.

Effects of Different Acute Plyometric Training Intensities on Attention and Psychological States

The objective of this investigation was to explore in a sample of female students the effects of several acute plyometric training intensities (low, moderate, and high-55-65%, 70-80%, and 90-100% of maximal vertical jump performance, respectively) on cognition (attention) and psychological states (mood). Thirty-seven female students (mean age = 19.72 ± 0.73 years, mean body mass index = 19.51) participated in the current study. They were randomly allocated to one of three conditions: a high-intensity plyometric exercise (HIPE), a moderate-intensity plyometric exercise (MIPE), and a low-intensity plyometric exercise (LIPE). Before and immediately after each session for the three conditions, all participants underwent a cognitive performance test (d2 test) and filled in a battery of psychological questionnaires (the Rating of Perceived Exertion (RPE), and the Brunel Mood Scale (BRUMS)). The data reported higher concentration performance and a lower number of errors in the MIPE when compared with HIPE (all, p-value < 0.05) groups, whereas no significant difference was found between other conditions (p-value > 0.05). The RPE value was higher in the HIPE (p-value < 0.001) and MIPE (p = 0.01) than in the LIPE, and in the HIPE than in the MIPE (p = 0.001) conditions. Concerning the BRUMS scale, fatigue (p = 0.005) was significantly different among the various conditions, being higher in HIPE with respect to MIPE and LIPE (all, p-value < 0.05) conditions. In conclusion, moderate-intensity plyometric exercise can be considered the best activity to improve visual attention. Practitioners may practice moderate-intensity plyometric exercises to improve concentration performance. However, due to the limitations of the present study (lack of a control group and between-subjects study design), further research in the field is warranted.

Eye movement patterns in complex tasks: Characteristics of ambient and focal processing

Analyzing the time course of eye movements during scene viewing often indicates that people progress through two distinct modes of visual processing: an ambient mode, which is associated with overall spatial orientation in a scene, followed by a focal mode, which requires central vision of an object. However, the shifts between ambient and focal processing modes have mainly been identified relative to changes in the environment, such as relative to the onset of various visual stimuli but also following scene cuts or subjective event boundaries in dynamic stimuli. The results so far do not allow conclusions about the nature of the two processing mechanisms beyond the influence of externally triggered events. It remains unclear whether people shift back and forth from ambient to focal processing also based on internal triggers, such as switching between different tasks while no external event is given. The present study therefore investigated ambient to focal processing shifts in an active task solving paradigm. The Rubik's Cube task introduced here is a multi-step task, which can be broken down into smaller sub-tasks that are performed serially. The time course of eye movements was analyzed at multiple levels of this Rubik's Cube task, including when there were no external changes to the stimuli but when internal representations of the task were hypothesized to change (i.e., switching between different sub-tasks). Results suggest that initial ambient exploration is followed by a switch to more focal viewing across various levels of task processing with and without external changes to the stimuli. More importantly, the present findings suggest that ambient and focal eye movement characteristics might serve as a probe for the attentional state in task processing, which does not seem to be influenced by changes in task performance.

Modelling the Trust Value for Human Agents Based on Real-Time Human States in Human-Autonomous Teaming Systems

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 via a fuzzy logic inference process that has tolerance for uncertainty in human physiological signals. The results of robot simulation suggest that the proposed trust model can generate reliable human trust values based on real-time cognitive states in the process of ongoing tasks. Moreover, the human-autonomous team with the proposed trust model improved the system efficiency by over 50% compared to the team with only autonomous agents. These results may demonstrate that the proposed model could provide insight into the real-time adaptation of HAT systems based on human states and, thus, might help develop new ways to enhance future HAT systems better.

The effect of letter-case type on the semantic processing of words and sentences during attentive and mind-wandering states

AbstractThe task of finding a case type that, on average, enhances the processing of verbal material has yielded mixed results in the literature. This study tackled this issue with an eye to the issue of processing textual information on road signs and the additional consideration of readers’ attentive states. Participants (n = 104) completed three experiments, the first two of which made use of both short (i.e., attentive state) and long (i.e., nonattentive or mind-wandering state) inter-trial intervals (ITIs). Experiment I consisted of a living versus non-living category-decision task involving the presentation of single words. Experiment II consisted of a sensical versus nonsensical sentence-judgment task. Experiment III consisted of a recognition memory task for words presented during the category-decision task. No significant difference in letter-case-type effectiveness was found for either the semantic categorization of or memory for single words. On the other hand, sensical sentences were correctly judged more quickly in lower case (or, more precisely, sentence case with the first letter of the first word capitalized). Such results point to either a more fluent processing of or enhanced conceptual resonance for sentences presented in lower case.