OBJECTIVE: Absence seizures impair psychosocial function, yet their detailed neuronal basis remains unknown. Recent work in a rat model suggests that cortical arousal state changes prior to seizures and that single neurons show diverse firing patterns during seizures. Our aim was to extend these investigations to a mouse model with studies of neuronal activity and arousal state to facilitate future fundamental investigations of absence epilepsy.
METHODS: We performed in vivo extracellular single unit recordings on awake head-fixed C3H/HeJ mice. Mice were implanted with tripolar electrodes for cortical electroencephalogram (EEG). Extracellular single unit recordings were obtained with glass micropipettes in the somatosensory barrel cortex, while animals ambulated freely on a running wheel. Signals were digitized and analyzed during seizures and baseline.
RESULTS: Neuronal activity was recorded from 36 cortical neurons in 19 mice while EEG showed characteristic 7-8 Hz spike-wave discharges. Different single neurons showed distinct firing patterns during seizures, but the overall mean population neuronal firing rate during seizures was no different from pre-seizure baseline. However, the rhythmicity of neuronal firing during seizures was significantly increased (p < 0.001). In addition, beginning 10s prior to seizure initiation, we observed a progressive decrease in cortical high frequency (>40 Hz) EEG and an increase in lower frequency (1-39 Hz) activity suggesting decreased arousal state.
CONCLUSIONS: We found that the awake head-fixed C3H/HeJ mouse model demonstrated rhythmic neuronal firing during seizures, and a decreased cortical arousal state prior to seizure onset. Unlike the rat model we did not observe an overall decrease in neuronal firing during seizures. Similarities and differences across species strengthen the ability to investigate fundamental key mechanisms. Future work in the mouse model will identify the molecular basis of neurons with different firing patterns, their role in seizure initiation and behavioral deficits, with ultimate translation to human absence epilepsy.

Arousal and motivation interact to profoundly influence behavior. For example, experience tells us that we have some capacity to control our arousal when appropriately motivated, such as staying awake while driving a motor vehicle. However, little is known about how arousal and motivation jointly influence decision computations, including if and how animals, such as rodents, adapt their arousal state to their needs. Here, we developed and show results from an auditory, feature-based, sustained-attention task with intermittently shifting task utility. We use pupil size to estimate arousal across a wide range of states and apply tailored signal-detection theoretic, hazard function, and accumulation-to-bound modeling approaches in a large cohort of mice. We find that pupil-linked arousal and task utility both have major impacts on multiple aspects of task performance. Although substantial arousal fluctuations persist across utility conditions, mice partially stabilize their arousal near an intermediate and optimal level when task utility is high. Behavioral analyses show that multiple elements of behavior improve during high task utility and that arousal influences some, but not all, of them. Specifically, arousal influences the likelihood and timescale of sensory evidence accumulation but not the quantity of evidence accumulated per time step while attending. In sum, the results establish specific decision-computational signatures of arousal, motivation, and their interaction in attention. So doing, we provide an experimental and analysis framework for studying arousal self-regulation in neurotypical brains and in diseases such as attention-deficit/hyperactivity disorder.

Emotional reactions to salient stimuli are well documented in psychophysiological research. However, some individual variables that can influence how people process emotions (i.e., empathy traits) have received little consideration. The present study investigated the relationship between emotions and empathy. Forty participants completed the Interpersonal Reactivity Index, a questionnaire that measure general and specific empathy dimensions. Then, emotional (erotic and mutilation) and non-emotional pictures were presented, during electroencephalographic recording. Valence and arousal were evaluated for each stimulus. Behavioral results revealed a positive correlation between the arousal induced by mutilation pictures and personal distress (i.e., feeling discomfort in emergency situations). At the electrophysiological level, theta activity elicited by positive and negative emotion processing in the superior frontal gyrus was associated with personal distress. Moreover, erotic-related theta in the middle frontal gyrus was associated with subjective judgement of erotic stimulus valence. Overall, theta activity modulated the interplay between emotions and empathy.

We introduce a novel dataset of affective, semantic, and descriptive norms for all facial emojis at the point of data collection. We gathered and examined subjective ratings of emojis from 138 German speakers along five essential dimensions: valence, arousal, familiarity, clarity, and visual complexity. Additionally, we provide absolute frequency counts of emoji use, drawn from an extensive Twitter corpus, as well as a much smaller WhatsApp database. Our results replicate the well-established quadratic relationship between arousal and valence of lexical items, also known for words. We also report associations among the variables: for example, the subjective familiarity of an emoji is strongly correlated with its usage frequency, and positively associated with its emotional valence and clarity of meaning. We establish the meanings associated with face emojis, by asking participants for up to three descriptions for each emoji. Using this linguistic data, we computed vector embeddings for each emoji, enabling an exploration of their distribution within the semantic space. Our description-based emoji vector embeddings not only capture typical meaning components of emojis, such as their valence, but also surpass simple definitions and direct emoji2vec models in reflecting the semantic relationship between emojis and words. Our dataset stands out due to its robust reliability and validity. This new semantic norm for face emojis impacts the future design of highly controlled experiments focused on the cognitive processing of emojis, their lexical representation, and their linguistic properties.

UNASSIGNED: Cochlear implants (CI) provide users with a spectrally degraded acoustic signal that could impact their auditory emotional experiences. This study evaluated the effects of CI-simulated spectral degradation on emotional valence and arousal elicited by environmental sounds.
UNASSIGNED: Thirty emotionally evocative sounds were filtered through a noise-band vocoder. Participants rated the perceived valence and arousal elicited by each of the full-spectrum and vocoded stimuli. These ratings were compared across acoustic conditions (full-spectrum, vocoded) and as a function of stimulus type (unpleasant, neutral, pleasant).
UNASSIGNED: Twenty-five young adults (age 19 to 34 years) with normal hearing.
UNASSIGNED: Emotional responses were less extreme for spectrally degraded (i.e., vocoded) sounds than for full-spectrum sounds. Specifically, spectrally degraded stimuli were perceived as more negative and less arousing than full-spectrum stimuli.
UNASSIGNED: By meticulously replicating CI spectral degradation while controlling for variables that are confounded within CI users, these findings indicate that CI spectral degradation can compress the range of sound-induced emotion independent of hearing loss and other idiosyncratic device- or person-level variables. Future work will characterize emotional reactions to sound in CI users via objective, psychoacoustic, and subjective measures.

UNASSIGNED: This study aimed to explore the arousal and valence that people experience in response to Hangul phonemes based on the gender of an AI speaker through comparison with Korean and Chinese cultures.
UNASSIGNED: To achieve this, 42 Hangul phonemes were used, in a combination of three Korean vowels and 14 Korean consonants, to explore cultural differences in arousal, valence, and the six foundational emotions based on the gender of an AI speaker. A total 136 Korean and Chinese women were recruited and randomly assigned to one of two conditions based on voice gender (man or woman).
UNASSIGNED: This study revealed significant differences in arousal levels between Korean and Chinese women when exposed to male voices. Specifically, Chinese women exhibited clear differences in emotional perceptions of male and female voices in response to voiced consonants. These results confirm that arousal and valence may differ with articulation types and vowels due to cultural differences and that voice gender can affect perceived emotions. This principle can be used as evidence for sound symbolism and has practical implications for voice gender and branding in AI applications.

Virtual reality (VR) exercise aims to offer positive affective and sensory experiences through an immersive experience rich in audiovisual stimuli. Notwithstanding, there is a paucity of large sample size studies comparing the acute effects of VR exercise compared with a matched exercise performed in a non-VR environment. The study compared the acute effects of a VR exercise session versus a matched non-VR exercise session in effect, pleasure, enjoyment, perceived exertion, and heart rate. This is a crossover randomized clinical trial. The time, difficulty, and exercise type of the non-VR exercise were matched to VR exercise. Before and immediately after each session, participants responded to the Borg\'s Perceived Exertion Scale, the Feeling Scale and the Felt Arousal Scale, and the Physical Activity Enjoyment Scale. The analyses were conducted with Generalized Linear Models, Wilcoxon\'s, and T-test for paired samples. A total of 83 adults (40 females) aged 35.46 years were included in the study. Participants in the VR condition had a greater increase in affect (mean change difference = 0.95, 95% confidence interval [CI] = 0.83-1.06, P < 0.001), arousal (mean change difference = 0.37, 95% CI = 0.23-9.50, P < 0.001). The pleasure and enjoyment median after the VR session were higher. In conclusion, the immersive VR exercise was more strenuous, but resulted in a better affective response, greater pleasure, and enjoyment.

Aiming at the problem that existing emotion recognition methods fail to make full use of the information in the time, frequency, and spatial domains in the EEG signals, which leads to the low accuracy of EEG emotion classification, this paper proposes a multi-feature, multi-frequency band-based cross-scale attention convolutional model (CATM). The model is mainly composed of a cross-scale attention module, a frequency-space attention module, a feature transition module, a temporal feature extraction module, and a depth classification module. First, the cross-scale attentional convolution module extracts spatial features at different scales for the preprocessed EEG signals; then, the frequency-space attention module assigns higher weights to important channels and spatial locations; next, the temporal feature extraction module extracts temporal features of the EEG signals; and, finally, the depth classification module categorizes the EEG signals into emotions. We evaluated the proposed method on the DEAP dataset with accuracies of 99.70% and 99.74% in the valence and arousal binary classification experiments, respectively; the accuracy in the valence-arousal four-classification experiment was 97.27%. In addition, considering the application of fewer channels, we also conducted 5-channel experiments, and the binary classification accuracies of valence and arousal were 97.96% and 98.11%, respectively. The valence-arousal four-classification accuracy was 92.86%. The experimental results show that the method proposed in this paper exhibits better results compared to other recent methods, and also achieves better results in few-channel experiments.

A low arousal threshold (LAT) is a pathophysiological trait of obstructive sleep apnea (OSA) that may be associated with brainstem ascending reticular activating system-cortical functional connectivity changes. We evaluated resting-state connectivity between the brainstem nuclei and 105 cortical/subcortical regions in OSA patients with or without a LAT and healthy controls. Twenty-five patients with moderate to severe OSA with an apnea-hypopnea index between 20 and 40/hr (15 with and 10 without a LAT) and 15 age- and sex-matched controls were evaluated. Participants underwent functional magnetic resonance imaging after overnight polysomnography. Three brainstem nuclei-the locus coeruleus (LC), laterodorsal tegmental nucleus (LDTg), and ventral tegmental area (VTA)-associated with OSA in our previous study were used as seeds. Functional connectivity values of the two brainstem nuclei (LC and LDTg) significantly differed among the three groups. The connectivity of the LC with the precuneus was stronger in OSA patients than in controls regardless of the concomitant LAT. The connectivity between the LDTg and the posterior cingulate cortex was also stronger in OSA patients regardless of the LAT. Moreover, OSA patients without a LAT showed stronger LDTg-posterior cingulate cortex connectivity than those with a LAT (post hoc p = 0.013), and this connectivity strength was negatively correlated with the minimum oxygen saturation in OSA patients (r = - 0.463, p = 0.023). The LAT in OSA patients was associated with altered LDTg-posterior cingulate cortex connectivity. This result may suggested that cholinergic activity may play a role in the LAT in OSA patients.

Recently the 1/f signal of human electroencephalography has attracted attention, as it could potentially reveal a quantitative measure of neural excitation and inhibition in the brain, that may be relevant in a clinical setting. The purpose of this short article is to show that the 1/f signal depends on the vigilance state of the brain in both humans and mice. Therefore, proper labelling of the EEG signal is important as improper labelling may obscure disease-related changes in the 1/f signal. We demonstrate this by comparing EEG results from a longitudinal study in a genetic mouse model for synaptic dysfunction in schizophrenia and autism spectrum disorders to results from a large European cohort study with schizophrenia and mild Alzheimer\'s disease patients. The comparison shows when the 1/f is corrected for vigilance state there is a difference between groups, and this effect disappears when vigilance state is not corrected for. In conclusion, more attention should be paid to the vigilance state during analysis of EEG signals regardless of the species.