Low Arousal Condition Research Articles

Neocortical long-range inhibition promotes cortical synchrony and sleep.

Behavioral states such as sleep and wake are highly correlated with specific patterns of rhythmic activity in the cortex. During low arousal states such as slow wave sleep, the cortex is synchronized and dominated by low frequency rhythms coordinated across multiple regions. Although recent evidence suggests that GABAergic inhibitory neurons are key players in cortical state modulation, the in vivo circuit mechanisms coordinating synchronized activity among local and distant neocortical networks are not well understood. Here, we show that somatostatin and chondrolectin co-expressing cells (Sst-Chodl cells), a sparse and unique class of neocortical inhibitory neurons, are selectively active during low arousal states and are largely silent during periods of high arousal. In contrast to other neocortical inhibitory neurons, we show these neurons have long-range axons that project across neocortical areas. Activation of Sst-Chodl cells is sufficient to promote synchronized cortical states characteristic of low arousal, with increased spike co-firing and low frequency brain rhythms, and to alter behavioral states by promoting sleep. Contrary to the prevailing belief that sleep is exclusively driven by subcortical mechanisms, our findings reveal that these long-range inhibitory neurons not only track changes in behavioral state but are sufficient to induce both sleep-like cortical states and sleep behavior, establishing a crucial circuit component in regulating behavioral states.

Staying in control: Characterizing the mechanisms underlying cognitive control in high and low arousal states.

Throughout the day, humans show natural fluctuations in arousal that impact cognitive function. To study the behavioural dynamics of cognitive control during high and low arousal states, healthy participants performed an auditory conflict task during high-intensity physical exercise (N = 39) or drowsiness (N = 33). In line with the pre-registered hypotheses, conflict and conflict adaptation effects were preserved during both altered arousal states. Overall task performance was markedly poorer during low arousal, but not for high arousal. Modelling behavioural dynamics with drift diffusion analysis revealed evidence accumulation and non-decision time decelerated, and decisional boundaries became wider during low arousal, whereas high arousal was unexpectedly associated with a decrease in the interference of task-irrelevant information processing. These findings show how arousal differentially modulates cognitive control at both sides of normal alertness, and further validate drowsiness and physical exercise as key experimental models to disentangle the interaction between physiological fluctuations on cognitive dynamics.

Linking activity dyshomeostasis and sleep disturbances in Alzheimer disease.

The presymptomatic phase of Alzheimer disease (AD) starts with the deposition of amyloid-β in the cortex and begins a decade or more before the emergence of cognitive decline. The trajectory towards dementia and neurodegeneration is shaped by the pathological load and the resilience of neural circuits to the effects of this pathology. In this Perspective, I focus on recent advances that have uncovered the vulnerability of neural circuits at early stages of AD to hyperexcitability, particularly when the brain is in a low-arousal states (such as sleep and anaesthesia). Notably, this hyperexcitability manifests before overt symptoms such as sleep and memory deficits. Using the principles of control theory, I analyse the bidirectional relationship between homeostasis of neuronal activity and sleep and propose that impaired activity homeostasis during sleep leads to hyperexcitability and subsequent sleep disturbances, whereas sleep disturbances mitigate hyperexcitability via negative feedback. Understanding the interplay among activity homeostasis, neuronal excitability and sleep is crucial for elucidating the mechanisms of vulnerability to and resilience against AD pathology and for identifying new therapeutic avenues.

A Unified Dynamic Model for the Decomposition of Skin Conductance and the Inference of Sudomotor Nerve Activities.

Electrodermal activity (EDA), commonly measured as skin conductance (SC), is a widely used physiological signal in psychological research and behavioral health applications. EDA is considered an indicator of arousal, a key aspect of emotion and stress. This work proposes a data-driven dynamic system model that characterizes the temporal dynamics of skin conductance and infers the latent arousal signal, utilizing techniques from system identification and sparse optimization. It introduces a fourth-order, linear time-invariant model for the overall skin conductance signal, including both the tonic and phasic components. The model was applied to a large dataset of over 200 participants to evaluate model fit. Furthermore, a three-component decomposition of skin conductance is introduced, based on mathematical definitions derived from the model, which provides key insights into the temporal dynamics of skin conductance. Comparative evaluation shows that the estimated latent neural signal effectively differentiates between high and low arousal states, while maintaining expected physiological properties. This work lays the foundation for numerous behavioral health applications and paves the road for designing physiology-based interventions aimed at regulating arousal.

The neural correlates of arousal: Ventral posterolateral nucleus-global transient co-activation

Arousal and awareness are two components of consciousness whose neural mechanisms remain unclear. Spontaneous peaks of global (brain-wide) blood-oxygenation-level-dependent (BOLD) signal have been found to be sensitive to changes in arousal. By contrasting BOLD signals at different arousal levels, we find decreased activation of the ventral posterolateral nucleus (VPL) during transient peaks in the global signal in low arousal and awareness states (non-rapid eye movement sleep and anesthesia) compared to wakefulness and in eyes-closed compared to eyes-open conditions in healthy awake individuals. Intriguingly, VPL-global co-activation remains high in patients with unresponsive wakefulness syndrome (UWS), who exhibit high arousal without awareness, while it reduces in rapid eye movement sleep, a state characterized by low arousal but high awareness. Furthermore, lower co-activation is found in individuals during N3 sleep compared to patients with UWS. These results demonstrate that co-activation of VPL and global activity is critical to arousal but not to awareness.

Sensory neurons couple arousal and foraging decisions in Caenorhabditis elegans

Foraging animals optimize feeding decisions by adjusting both common and rare behavioral patterns. Here, we characterize the relationship between an animal’s arousal state and a rare decision to leave a patch of bacterial food. Using long-term tracking and behavioral state classification, we find that food leaving decisions in Caenorhabditis elegans are coupled to arousal states across multiple timescales. Leaving emerges probabilistically over minutes from the high arousal roaming state, but is suppressed during the low arousal dwelling state. Immediately before leaving, animals have a brief acceleration in speed that appears as a characteristic signature of this behavioral motif. Neuromodulatory mutants and optogenetic manipulations that increase roaming have a coupled increase in leaving rates, and similarly acute manipulations that inhibit feeding induce both roaming and leaving. By contrast, inactivating a set of chemosensory neurons that depend on the cGMP-gated transduction channel TAX-4 uncouples roaming and leaving dynamics. In addition, tax-4-expressing sensory neurons promote lawn-leaving behaviors that are elicited by feeding inhibition. Our results indicate that sensory neurons responsive to both internal and external cues play an integrative role in arousal and foraging decisions.

Sensory neurons couple arousal and foraging decisions in Caenorhabditis elegans.

Foraging animals optimize feeding decisions by adjusting both common and rare behavioral patterns. Here, we characterize the relationship between an animal's arousal state and a rare decision to leave a patch of bacterial food. Using long-term tracking and behavioral state classification, we find that food leaving decisions in Caenorhabditis elegans are coupled to arousal states across multiple timescales. Leaving emerges probabilistically over minutes from the high arousal roaming state, but is suppressed during the low arousal dwelling state. Immediately before leaving, animals have a brief acceleration in speed that appears as a characteristic signature of this behavioral motif. Neuromodulatory mutants and optogenetic manipulations that increase roaming have a coupled increase in leaving rates, and similarly acute manipulations that inhibit feeding induce both roaming and leaving. By contrast, inactivating a set of chemosensory neurons that depend on the cGMP-gated transduction channel TAX-4 uncouples roaming and leaving dynamics. In addition, tax-4-expressing sensory neurons promote lawn-leaving behaviors that are elicited by feeding inhibition. Our results indicate that sensory neurons responsive to both internal and external cues play an integrative role in arousal and foraging decisions.

Electrodermal activity: A continuous monitor of well-being

A smart society should not only support the efficiency and effectiveness of processes, they should also have the ability to comprehend and support its inhabitants well-being. To enable this, we need continuous information on individual’s well-being. As a first step, we suggest to evaluate people’s long term stress level, as it sheds light on their well-being. We propose using the biosignal Electrodermal Activity (EDA), a proven measure of people’s arousal or stress. Moreover, EDA can be measured continuously, in real-time, and unobtrusively via wearables. To assess this idea’s feasibility, the CASE, CEAP-360VR, and K-EmoCon datasets, including both continuous EDA recordings and continuous subjective self-reported arousal, were analyzed. With CASE and CEAP-360VR, a multilevel analysis unveiled that the frequency and amplitude of EDA’s non-specific skin conductance responses significantly correlated with the self-reported arousal. With K-EmoCon, this correlation was absent, which can be explained by the low arousal condition of this dataset. The latter also signals a main limitation: the lack of sensitivity of the proposed signal. Nevertheless, the results are promising as they show potential for EDA as a continuous stress monitor. Therefore, we are optimistic that a future smart society can be enabled to monitor and improve their inhabitant’s well-being.

The world prefers a calm life, but not everyone gets to have one: global trends in valuing and experiencing calmness in the Gallup World Poll

ABSTRACT Psychology has paid relatively little attention to low arousal positive states like calmness. To remedy this lacuna, this study draws on the most globally comprehensive study to date on calmness (121,207 participants in 116 countries in the 2020 Gallup World Poll), featuring two items asking whether people: (a) prefer a calm life or an exciting life; and (b) experienced calmness yesterday. By intersecting these, we could categorise people in four categories of calmness: satisfied (both prefer and experience it); unwanted (experience calmness but prefer excitement); longed-for (prefer calmness but don’t experience it); and unmissed (neither prefer nor experience it). The results reveal a nuanced picture that challenges certain stereotypes (e.g. calmness had no particular association here with Eastern cultures), and shed new light on this overlooked topic (e.g. poorer people and countries are more likely to prefer calmness yet are less likely to actually experience it).

Noradrenaline tracks emotional modulation of attention in human amygdala

The noradrenaline (NA) system is one of the brain's major neuromodulatory systems; it originates in a small midbrain nucleus, the locus coeruleus (LC), and projects widely throughout the brain.1,2 The LC-NA system is believed to regulate arousal and attention3,4 and is a pharmacological target in multiple clinical conditions.5,6,7 Yet our understanding of its role in health and disease has been impeded by a lack of direct recordings in humans. Here, we address this problem by showing that electrochemical estimates of sub-second NA dynamics can be obtained using clinical depth electrodes implanted for epilepsy monitoring. We made these recordings in the amygdala, an evolutionarily ancient structure that supports emotional processing8,9 and receives dense LC-NA projections,10 while patients (n= 3) performed a visual affective oddball task. The task was designed to induce different cognitive states, with the oddball stimuli involving emotionally evocative images,11 which varied in terms of arousal (low versus high) and valence (negative versus positive). Consistent with theory, the NA estimates tracked the emotional modulation of attention, with a stronger oddball response in a high-arousal state. Parallel estimates of pupil dilation, a common behavioral proxy for LC-NA activity,12 supported a hypothesis that pupil-NA coupling changes with cognitive state,13,14 with the pupil and NA estimates being positively correlated for oddball stimuli in a high-arousal but not a low-arousal state. Our study provides proof of concept that neuromodulator monitoring is now possible using depth electrodes in standard clinical use.

AITST—Affective EEG-based person identification via interrelated temporal–spatial transformer

Compared with other biometrics, such as fingerprints and irises, EEG signals contain richer identity information due to their high subject dependence. In this study, we proposed an affective EEG-based person identification by using an affective interrelated temporal–spatial transformer (AITST) to overcome the influence of different emotional states in affective EEG-based person identification. The AITST contains an interrelated temporal–spatial attention that can preserve the interrelationships of temporal and spatial domains while extracting temporal and spatial features of the EEG signal. We evaluated the proposed AITST on the public emotional database DEAP. The experimental results show that our AITST can reach an average recognition accuracy of 98.94±0.04% in the low valence, low arousal state, 99.06±0.02% in low valence, high arousal state, 98.97±0.02% in high valence, low arousal state, and 99.21±0.03% in the high valence, high arousal state, significantly outperforming the other compared models and overcoming the influence of different emotional states. Furthermore, we explored the contribution of different frequency bands, different emotional states and different features of EEG for EEG-based person identification. The results showed that gamma band of EEG, power spectrum density (PSD), and high arousal state have the greatest contribution to affective EEG-based person identification. Source code is available at https://github.com/JerryKingQAQ/AITST.

0143 Trait Emotion Reactivity Predicts Change in Negative but Not Positive Affect During Total Sleep Deprivation

Abstract Introduction During laboratory-based, voluntary exposure to total sleep deprivation (TSD), relatively large decreases in positive mood and relatively small increases in negative mood have been observed, with the magnitudes of change varying across individuals. People differ in their trait emotion reactivity, i.e., their sensitivity to emotion-evoking stimuli or events. As higher reactivity is associated with greater difficulty regulating emotion, we hypothesized this trait could moderate mood changes during TSD. Methods N=96 healthy adults (ages 21-38, 47% female) participated in one of three 4-day/3-night in-laboratory TSD studies. In each study, after 10h baseline sleep, participants were exposed to 38h TSD, followed by 10h recovery sleep. Participants completed the Emotion Reactivity Scale (ERS), and their self-reported affect was assessed every 2-4h during wake using the Positive and Negative Affect Schedule (PANAS). The 11 test bouts during TSD shared across studies were included in analyses (day 2: 09:00, 13:00, 21:00, 23:00; day 3: 01:00, 03:00, 05:00, 07:00, 09:00, 13:00, 21:00). Positive and negative affect ratings were analyzed with linear mixed-effects regression with fixed effects of test bout (categorical), ERS score (continuous), and their interaction, covariates for study, sex, and age, and a random intercept over participants. Results Participants showed the expected decrease in positive affect as a function of test bout (time awake and time of day, p< 0.001), and a smaller, non-significant increase in negative affect (p=0.17). Higher ERS scores were associated with increased negative affect during TSD (p=0.002), but this effect was small, and negative affect showed a floor effect. Emotion reactivity was not a significant predictor of decreased positive affect during TSD (p=0.97). Conclusion As hypothesized, emotion reactivity predicted individual variability in negative affect during TSD, but unexpectedly it did not predict the decrease in positive affect associated with TSD. This suggests that the trait measured by the ERS may be biased toward negative affect, and/or that positive affective changes may be more difficult to predict during the low arousal state induced by TSD. Studies inducing greater variability in negative affect during TSD (e.g., through exposure to a stressor) are needed to confirm our findings. Support (if any) NIH CA167691, ONR N00014-13-1-0302, and CDMRP W81XWH-16-1-0319 and W81XWH-20-1-0442.

Effect of homeostatic pressure on daytime vigilance performance: Evidence from behaviour and resting-state EEG.

Vigilance is highly sensitive to the time-of-day effect and goes through the daytime trough during the period of the post-noon dip. A midday nap could maintain individuals' vigilance at an optimal level. Thus, homeostatic sleep pressure is one of the main reasons for the post-noon dip in daytime vigilance. The current study focussed on the role of homeostatic sleep pressure in the diurnal variation of vigilance performance with normal circadian rhythms and the corresponding neural basis. With 34 healthy adults, we recorded the resting-state electroencephalogram activities and the following vigilance performance measured by psychomotor vigilance test in the morning, the no-nap mid afternoon, and the nap mid afternoon. The circadian process was controlled by measuring vigilance and resting-state electroencephalogram activities at the same time point in the nap and no-nap conditions. Homeostatic sleep pressure accumulated from morning to mid afternoon induced the declined vigilance performance and a global increase in resting-state delta, theta, alpha, and beta1 bands power, and a local increase in beta2 band power in the central region. Furthermore, the more the spontaneous beta2 power increased, the less vigilance declined from morning to mid afternoon. The current findings suggest that homeostatic sleep pressure increased cortical excitability but decreased cortical communication efficiency from morning to mid afternoon. In addition, the activity of the high beta waves probably reflected the compensatory effort to counteract the negative impact of the low arousal state on the following vigilance task by performing more action preparation in the no-nap afternoon.

Immersive Experience and Climate Change Monitoring in Digital Landscapes: Evidence from Somatosensory Sense and Comfort.

In this study, the virtual engine software (Unity 2019, Unity Software Inc., San Francisco, California, the U.S.) was used to generate a digital landscape model, forming a virtual immersive environment. Through field investigation and emotional preference experiments, the ancient tree ecological area and the sunlight-exposed area were respectively monitored, and the somatosensory comfort evaluation model was established. The subjects showed the highest degree of interest in the ancient tree ecological area after landscape roaming experience, and the mean variance in SC fluctuation was 13.23% in experiments. The subjects were in a low arousal state and had a significant degree of interest in the digital landscape roaming scene, and there was a significant correlation between positive emotion, somatosensory comfort and the Rating of Perceived Exertion index; moreover, the somatosensory comfort of the ancient tree ecological area was higher than that of the sunlight-exposed area. Meanwhile, it was found that somatosensory comfort level can effectively distinguish the comfort level between the ancient tree ecological area and the sunlight-exposed area, which provides an important basis for monitoring extreme heat. This study concludes that, in terms of the goal of harmonious coexistence between human and nature, the evaluation model of somatosensory comfort can contribute to reducing people's adverse views on extreme weather conditions.

Emotion Recognition System Based on Two-Level Ensemble of Deep-Convolutional Neural Network Models

Emotions play a crucial role in human interaction and healthcare. This study introduces an automatic emotion recognition system based on deep learning using electroencephalogram signals. A lightweight pyramidal one-dimensional convolutional neural network model is proposed that involves a small number of learnable parameters. Using the model, a two-level ensemble classifier is designed. Each channel is scanned incrementally in the first level to generate predictions, which are fused using the majority vote. The second level fuses the predictions of all the channels of a signal using a majority vote to predict the emotional state. The method was validated using the public domain challenging benchmark dataset. The electroencephalogram signals over five brain regions were analyzed. The results indicate that the frontal brain region plays a dominant role in two emotion recognition problems (distinguishing high valence vs. low valence and high arousal vs. low arousal states).

The motivational dynamics of arousal and values in promoting sustainable behavior: A cognitive energetics perspective

This research applies Cognitive Energetics Theory (CET) to explain when and why consumers engage in sustainable behavior. Across six studies, we find a positive interaction effect of arousal and openness-to-change on sustainable behaviors. In particular, openness-to-change (vs conservation) increases the likelihood of engaging in effortful sustainable behaviors in a high-arousal state rather than in a low-arousal state. Interestingly, our results reveal that this interactive effect is explained by the tendency of consumers to believe that the target sustainable behavior requires less effort, when they are in a high-arousal state and endorsing openness-to-change. Moreover, perceived effort is positively related to sustainable behavior for experienced consumers but negatively related to the behavior for less experienced consumers. In addition, the effect of value and arousal on perceived effort is stronger among less experienced consumers but attenuated among more experienced consumers. Thus, arousal can serve as a catalyst to enhance value-consistent sustainable behaviors and help the less experienced consumers form habits. These findings contribute to CET by highlighting the important roles that values and arousal play in the motivational forces that drive and restrain sustainable behaviors. The results improve our understanding of how to motivate value-consistent sustainable behaviors, with implications for both marketers and policy-makers.

Exploring the perception of stress in childhood and early adolescence

Stressful life experiences may jeopardize the healthy development of children. To improve interventions, more knowledge is needed on the perception of stress by children. In adults, stress is regarded as a state of low valence and high arousal. It is unclear whether children perceive stress similarly. In the current study, 35 children of the general population completed three tasks aiming to provide insight into their knowledge of the concept stress. In the first task, participants were asked about their verbal knowledge of the concept stress. In the second task, they rated the valence and arousal of eight emotion-evoking vignettes. In the final task, participants completed an experience sampling survey for at least 1 day, consisting of a stress thermometer and pictorial scales of valence and arousal. Participants’ perception of stress was found to be mainly valence focused. Age and sex were found to play a role in the degree of arousal focus. Older participants differentiated more in arousal levels than younger participants, as did girls in comparison with boys. Because the perception of stress depends on developmental and other individual factors, using stress as a single measurement dimension in a survey is not recommended.

Passive visual stimulation induces fatigue under conditions of high arousal elicited by auditory tasks.

Theories of cognitive fatigue disagree on whether performance decrement is caused by motivational or functional alterations. Here, drawing inspiration from the habituation and visual adaptation literature, we tested the assumption that keeping neural networks active for an extensive period of time entails consequences at the subjective and objective level-the defining characteristics of fatigue-when confounds such as motivation, boredom, and level of skill are controlled. In Experiment 1, we revealed that passive visual stimulation affected the performance of a subsequent task that was carried out in the same portion of visual space. While under conditions of low cognitive load and arousal, participants improved their performance in the stimulated quadrant; the reverse was observed under high arousal conditions. This latter performance decrement correlated also with the reported subjective level of fatigue and occurred while neural responses to the saturating stimulus remained constant, as assessed through steady-state EEG. In subsequent experiments, we replicated and further characterized this performance deterioration effect, revealing its specificity to the stimulated eye and stimulus orientation. Across the three experiments, the decrease in performance was correlated with pupil-linked arousal, suggesting its mediating effect in this phenomenon. In sum, we show that repeated stimulation of neural networks under high-arousal conditions leads to their altered functional performance, a mechanism which may play a role in the development of global cognitive fatigue. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

EEG-Based Emotion Recognition Using Convolutional Recurrent Neural Network with Multi-Head Self-Attention

In recent years, deep learning has been widely used in emotion recognition, but the models and algorithms in practical applications still have much room for improvement. With the development of graph convolutional neural networks, new ideas for emotional recognition based on EEG have arisen. In this paper, we propose a novel deep learning model-based emotion recognition method. First, the EEG signal is spatially filtered by using the common spatial pattern (CSP), and the filtered signal is converted into a time–frequency map by continuous wavelet transform (CWT). This is used as the input data of the network; then the feature extraction and classification are performed by the deep learning model. We called this model CNN-BiLSTM-MHSA, which consists of a convolutional neural network (CNN), bi-directional long and short-term memory network (BiLSTM), and multi-head self-attention (MHSA). This network is capable of learning the time series and spatial information of EEG emotion signals in depth, smoothing EEG signals and extracting deep features with CNN, learning emotion information of future and past time series with BiLSTM, and improving recognition accuracy with MHSA by reassigning weights to emotion features. Finally, we conducted experiments on the DEAP dataset for sentiment classification, and the experimental results showed that the method has better results than the existing classification. The accuracy of high and low valence, arousal, dominance, and liking state recognition is 98.10%, and the accuracy of four classifications of high and low valence-arousal recognition is 89.33%.

Variability in intensively assessed mood: Systematic sources and factor structure in outpatients with opioid use disorder.

In intensive longitudinal studies using ecological momentary assessment, mood is typically assessed by repeatedly obtaining ratings for a large set of adjectives. Summarizing and analyzing these mood data can be problematic because the reliability and factor structure of such measures have rarely been evaluated in this context, which-unlike cross-sectional studies-captures between- and within-person processes. Our study examined how mood ratings (obtained thrice daily for 8 weeks; n = 306, person moments = 39,321) systematically vary and covary in outpatients receiving medication for opioid use disorder (MOUD). We used generalizability theory to quantify several aspects of reliability, and multilevel confirmatory factor analysis (MCFA) to detect factor structures within and across people. Generalizability analyses showed that the largest proportion of systematic variance across mood items was at the person level, followed by the person-by-day interaction and the (comparatively small) person-by-moment interaction for items reflecting low arousal. The best-fitting MCFA model had a three-factor structure both at the between- and within-person levels: positive mood, negative mood, and low-arousal states (with low arousal considered as either a separate factor or a subfactor of negative mood). We conclude that (a) mood varied more between days than between moments and (b) low arousal may be worth scoring and reporting separately from positive and negative mood states, at least in a MOUD population. Our three-factor structure differs from prior analyses of mood; more work is needed to understand the extent to which it generalizes to other populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).