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Selecting appropriate stimuli to induce emotional states is essential in affective research. Only a few standardized affective stimulus databases have been created for auditory, language, and visual materials. Numerous studies have extensively employed these databases using both behavioral and neuroimaging methods. However, some limitations of the existing databases have recently been reported, including limited numbers of stimuli in specific categories or poor picture quality of the visual stimuli. In the present article, we introduce the Nencki Affective Picture System (NAPS), which consists of 1,356 realistic, high-quality photographs that are divided into five categories (people, faces, animals, objects, and landscapes). Affective ratings were collected from 204 mostly European participants. The pictures were rated according to the valence, arousal, and approach–avoidance dimensions using computerized bipolar semantic slider scales. Normative ratings for the categories are presented for each dimension. Validation of the ratings was obtained by comparing them to ratings generated using the Self-Assessment Manikin and the International Affective Picture System. In addition, the physical properties of the photographs are reported, including luminance, contrast, and entropy. The new database, with accompanying ratings and image parameters, allows researchers to select a variety of visual stimulus materials specific to their experimental questions of interest. The NAPS system is freely accessible to the scientific community for noncommercial use by request at http://naps.nencki.gov.pl .

Visual perception is an important part of human life. In the context of facial recognition, it allows us to distinguish between emotions and important facial features that distinguish one person from another. However, subjects suffering from memory loss face significant facial processing problems. If the perception of facial features is affected by memory impairment, then it is possible to classify visual stimuli using brain activity data from the visual processing regions of the brain. This study differentiates the aspects of familiarity and emotion by the inversion effect of the face and uses convolutional neural network (CNN) models (EEGNet, EEGNet SSVEP (steady-state visual evoked potentials), and DeepConvNet) to learn discriminative features from raw electroencephalography (EEG) signals. Due to the limited number of available EEG data samples, Generative Adversarial Networks (GAN) and Variational Autoencoders (VAE) are introduced to generate synthetic EEG signals. The generated data are used to pretrain the models, and the learned weights are initialized to train them on the real EEG data. We investigate minor facial characteristics in brain signals and the ability of deep CNN models to learn them. The effect of face inversion was studied, and it was observed that the N170 component has a considerable and sustained delay. As a result, emotional and familiarity stimuli were divided into two categories based on the posture of the face. The categories of upright and inverted stimuli have the smallest incidences of confusion. The model’s ability to learn the face-inversion effect is demonstrated once more.

Slow-paced breathing (SB) reduces anxiety, but its effects on frontal alpha asymmetry (also termed relative left frontal activity, rLFA) and the persistence of these effects after aversive stimuli remain unclear. This study investigated whether SB reduces state anxiety and enhances rLFA, and whether these effects persist immediately after exposure to aversive images from the International Affective Picture System (IAPS) following the breathing task. Seventeen healthy participants (7 females) completed sessions of SB (4 s inhalation, 6 s exhalation) and resting breathing (RB). Electroencephalography (EEG), heart rate variability (HRV), respiratory parameters, and State-Trait Anxiety Inventory-State (STAI-S) scores were measured at baseline (pre-task), post-task, and post-stimuli. HRV was evaluated by the root mean square of successive differences (RMSSD) and the low-frequency/high-frequency ratio (LF/HF ratio). Respiratory measurements included respiratory rate, coefficient of variation of respiratory intervals (CVRR), and end-tidal CO (ETCO ). rLFA, measured by alpha wave activity, was calculated at midfrontal (F4-F3) and lateral frontal (F8-F7) EEG sites. STAI-S scores in SB condition were significantly lower than in RB condition, both post-task (  < 0.001, Cohen's d = -1.46) and post-stimuli (  < 0.001, Cohen's d = -1.25). Midfrontal rLFA (F4-F3) also significantly increased with SB post-task (  < 0.01, Cohen's d = 1.03) and post-stimuli (  < 0.05, Cohen's d = 0.84), whereas lateral frontal rLFA (F8-F7) showed no significant changes. A significant interaction between intervention and time was observed for RMSSD (  < 0.01, η G = 0.18). Post-task RMSSD was significantly lower in SB condition compared to RB condition (  < 0.001), but this difference was absent post-stimuli. These findings suggest that SB effectively reduces state anxiety while enhancing rLFA, with these effects persisting after exposure to visual stressors. The anxiety-buffering effect of SB may be mediated by enhanced rLFA in the midfrontal region, reflecting improved prefrontal regulatory control over emotion. This indicates that SB could be a practical intervention to enhance neurophysiological resilience against acute stress.

Although many studies have demonstrated the positive effects of natural visual and auditory stimuli on human physiological and psychological states, there is limited empirical evidence on the effects on subjective comfort under different thermal environments. This study used a climatic chamber experiment to evaluate the impact of three types of natural stimuli (visual, auditory, and combined audio-visual) on physiological and psychological responses under three operative temperature conditions (26 °C, 28 °C, and 32 °C). In total, 24 participants were recruited. Physiological indicators, including heart rate variability, skin conductance level (SCL), skin temperature (ST), and blood pressure, as well as psychological indicators including thermal sensation (TSV), thermal comfort (TCV), visual comfort (VCV), and acoustic comfort (ACV), were collected. The results show that TCV was significantly and positively correlated with both VCV and ACV. The visual stimuli produced the most significant decrease in TSV and the greatest increase in TCV, while combined audio-visual stimuli had the most significant impact on physiological responses. At 26 °C, the combined audio-visual stimuli group reduced heart rate by 6.08%. However, at 32 °C, most physiological and psychological restoration indicators showed no significant changes. These findings provide theoretical references for health-oriented multisensory environmental design in urban areas.

Virtual reality environments offer great opportunities to study the performance of brain-computer interfaces (BCIs) in real-world contexts. As real-world stimuli are typically multimodal, their neuronal integration elicits complex response patterns. To investigate the effect of additional auditory cues on the processing of visual information, we used virtual reality to mimic safety-related events in an industrial environment while we concomitantly recorded electroencephalography (EEG) signals. We simulated a box traveling on a conveyor belt system where two types of stimuli – an exploding and a burning box – interrupt regular operation. The recordings from 16 subjects were divided into two subsets, a visual-only and an audio-visual experiment. In the visual-only experiment, the response patterns for both stimuli elicited a similar pattern – a visual evoked potential (VEP) followed by an event-related potential (ERP) over the occipital-parietal lobe. Moreover, we found the perceived severity of the event to be reflected in the signal amplitude. Interestingly, the additional auditory cues had a twofold effect on the previous findings: The P1 component was significantly suppressed in the case of the exploding box stimulus, whereas the N2c showed an enhancement for the burning box stimulus. This result highlights the impact of multisensory integration on the performance of realistic BCI applications. Indeed, we observed alterations in the offline classification accuracy for a detection task based on a mixed feature extraction (variance, power spectral density, and discrete wavelet transform) and a support vector machine classifier. In the case of the explosion, the accuracy slightly decreased by -1.64 % p. in an audio-visual experiment compared to the visual-only. Contrarily, the classification accuracy for the burning box increased by 5.58% p. when additional auditory cues were present. Hence, we conclude, that especially in challenging detection tasks, it is favorable to consider the potential of multisensory integration when BCIs are supposed to operate under (multimodal) real-world conditions.

Odor environments in living spaces can influence human physiological and psychological states. To elucidate the effect of volatile organic compounds (VOCs) of wood in living spaces on the modulations of cognitive processing, we built two experimental huts to simulate wooden construction living spaces. One hut was made of cedarwood ( Cryptomeria japonica ), and the other was made of resin. We used cedarwood and resin, because they are often used as construction materials in Japan. In both huts, we measured the participants’ first positivity in the early visual cortex (P1), the third positivity elicited by voluntary attention (P3b), and the automatic occipital negativity to infrequent visual stimuli in event-related potentials (ERPs), while they performed a visual discrimination task. The VOCs in both huts were measured by gas chromatography–mass spectrometry. The concentration of volatile sesquiterpenes was significantly increased in the cedarwood hut. Neither P1 nor P3b was affected by the cedarwood hut. Compared to the resin hut, we observed significantly larger occipital negativities to the infrequent stimuli in the cedarwood hut in the time windows of 280–300 ms at the mid-occipital region. These findings suggest that the increased concentration of volatile sesquiterpenes emitted from cedarwood facilitates the human brain’s response to changes in visual stimuli.

Modern computer hardware makes it possible to produce visual stimuli in ways not previously possible. Arbitrary scenes, from traditional sinusoidal gratings to naturalistic 3D scenes can now be specified on a frame-by-frame basis in realtime. A programming library called the Vision Egg that aims to make it easy to take advantage of these innovations. The Vision Egg is a free, open-source library making use of OpenGL and written in the high-level language Python with extensions in C. Careful attention has been paid to the issues of luminance and temporal calibration, and several interfacing techniques to input devices such as mice, movement tracking systems, and digital triggers are discussed. Together, these make the Vision Egg suitable for many psychophysical, electrophysiological, and behavioral experiments. This software is available for free download at visionegg.org.

During speech perception, listeners rely on multimodal input and make use of both auditory and visual information. When presented with speech, for example syllables, the differences in brain responses to distinct stimuli are not, however, caused merely by the acoustic or visual features of the stimuli. The congruency of the auditory and visual information and the familiarity of a syllable, that is, whether it appears in the listener's native language or not, also modulates brain responses. We investigated how the congruency and familiarity of the presented stimuli affect brain responses to audio-visual (AV) speech in 12 adult Finnish native speakers and 12 adult Chinese native speakers. They watched videos of a Chinese speaker pronouncing syllables (/pa/, /pha/, /ta/, /tha/, /fa/) during a magnetoencephalography (MEG) measurement where only /pa/ and /ta/ were part of Finnish phonology while all the stimuli were part of Chinese phonology. The stimuli were presented in audio-visual (congruent or incongruent), audio only, or visual only conditions. The brain responses were examined in five time-windows: 75-125, 150-200, 200-300, 300-400, and 400-600 ms. We found significant differences for the congruency comparison in the fourth time-window (300-400 ms) in both sensor and source level analysis. Larger responses were observed for the incongruent stimuli than for the congruent stimuli. For the familiarity comparisons no significant differences were found. The results are in line with earlier studies reporting on the modulation of brain responses for audio-visual congruency around 250-500 ms. This suggests a much stronger process for the general detection of a mismatch between predictions based on lip movements and the auditory signal than for the top-down modulation of brain responses based on phonological information.

The anterior insula (AI) is the core hub of salience network that serves to identify the most relevant stimuli among vast sensory inputs and forward them to higher cognitive regions to guide behaviour. As blind subjects were usually reported with changed perceptive abilities for salient non-visual stimuli, we hypothesized that the resting-state functional network of the AI is selectively reorganized after visual deprivation. The resting-state functional connectivity (FC) of the bilateral dorsal and ventral AI was calculated for twenty congenitally blind (CB), 27 early blind (EB), 44 late blind (LB) individuals and 50 sighted controls (SCs). The FCs of the dorsal AI were strengthened with the dorsal visual stream, while weakened with the ventral visual stream in the blind than the SCs; in contrast, the FCs of the ventral AI of the blind was strengthened with the ventral visual stream. Furthermore, these strengthened FCs of both the dorsal and ventral AI were partially negatively associated with the onset age of blindness. Our result indicates two parallel pathways that selectively transfer non-visual salient information between the deprived “visual” cortex and salience network in blind subjects.

How is it that groups of neurons dispersed through the brain interact to generate complex behaviors? Three papers in this issue present brain-scale studies of neuronal activity and dynamics (see the Perspective by Huk and Hart). Allen et al. found that in thirsty mice, there is widespread neural activity related to stimuli that elicit licking and drinking. Individual neurons encoded task-specific responses, but every brain area contained neurons with different types of response. Optogenetic stimulation of thirst-sensing neurons in one area of the brain reinstated drinking and neuronal activity across the brain that previously signaled thirst. Gründemann et al. investigated the activity of mouse basal amygdala neurons in relation to behavior during different tasks. Two ensembles of neurons showed orthogonal activity during exploratory and nonexploratory behaviors, possibly reflecting different levels of anxiety experienced in these areas. Stringer et al. analyzed spontaneous neuronal firing, finding that neurons in the primary visual cortex encoded both visual information and motor activity related to facial movements. The variability of neuronal responses to visual stimuli in the primary visual area is mainly related to arousal and reflects the encoding of latent behavioral states. Science , this issue p. eaav3932 , p. eaav8736 , p. eaav7893 ; see also p. 236 Neurons in the primary visual cortex encode both visual information and motor activity. Neuronal populations in sensory cortex produce variable responses to sensory stimuli and exhibit intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables. Recording more than 10,000 neurons in mouse visual cortex, we observed that spontaneous activity reliably encoded a high-dimensional latent state, which was partially related to the mouse’s ongoing behavior and was represented not just in visual cortex but also across the forebrain. Sensory inputs did not interrupt this ongoing signal but added onto it a representation of external stimuli in orthogonal dimensions. Thus, visual cortical population activity, despite its apparently noisy structure, reliably encodes an orthogonal fusion of sensory and multidimensional behavioral information.