Many studies in affective neuroscience rely on statistical procedures designed to estimate population averages and base their main conclusions on group averages. However, the obvious unit of analysis in affective neuroscience is the individual, not the group, because emotions are individual phenomena that typically vary across individuals. Conclusions based on group averages may therefore be misleading or wrong, if interpreted as statements about emotions of an individual, or meaningless, if interpreted as statements about the group, which has no emotions. We therefore advocate the Single-N design as the default strategy in research on emotions, testing one or several individuals extensively with the primary purpose of obtaining results at the individual level. In neuroscience, the equivalent to the Single-N design is deep imaging, the emerging trend of extensive measurements of activity in single brains. Apart from the fact that individuals react differently to emotional stimuli, they also vary in shape and size of their brains. Group-based analysis of brain imaging data therefore refers to an “average brain” that was activated in a way that may not be representative of the physiology of any of the tested individual brains, nor of how these brains responded to the experimental stimuli. Deep imaging avoids such group-averaging artifacts by simply focusing on the individual brain. This methodological shift toward individual analysis has already opened new research areas in fields like vision science. Inspired by this, we call for a corresponding shift in affective neuroscience, away from group averages, and toward experimental designs targeting the individual.

Vocal sound imitations provide a new challenge for understanding the coupling between articulatory mechanisms and the resulting audio. In this study, the classification of three articulatory categories, phonation, supraglottal myoelastic vibrations, and turbulence, have been modeled from audio recordings. Two data sets were assembled, consisting of different vocal imitations by four professional imitators and four non-professional speakers in two different experiments. The audio data were manually annotated by two experienced phoneticians using a detailed articulatory description scheme. A separate set of audio features was developed specifically for each category using both time-domain and spectral methods. For all time-frequency transformations, and for some secondary processing, the recently developed Auditory Receptive Fields Toolbox was used. Three different machine learning methods were applied for predicting the final articulatory categories. The result with the best generalization was found using an ensemble of multilayer perceptrons. The cross-validated classification accuracy was 96.8% for phonation, 90.8% for supraglottal myoelastic vibrations, and 89.0% for turbulence using all the 84 developed features. A final feature reduction to 22 features yielded similar results.

Individuals may have a different body odor, when they are sick compared to healthy. In the non-human animal literature, olfactory cues have been shown to predict avoidance of sick individuals. We tested whether the mere experimental activation of the innate immune system in healthy human individuals can make an individuals' body odor be perceived as more aversive (intense, unpleasant, and disgusting). Following an endotoxin injection (lipopolysaccharide; 0.6 ng/kg) that creates a transient systemic inflammation, individuals smelled more unpleasant compared to a placebo group (saline injection). Behavioral and chemical analyses of the body odor samples suggest that the volatile components of samples from sick individuals changed qualitatively rather than quantitatively. Our findings support the hypothesis that odor cues of inflammation in axillary sweat are detectable just a few hours after experimental activation of the innate immune system. As such, they may trigger behavioral avoidance, hence constituting a first line of defense against pathogens of infected conspecifics.

BACKGROUND: Although most patients with post-traumatic olfactory dysfunction (PTOD) undergo MRI, there is no consensus about its diagnostic or prognostic value.The aims were: 1) to classify the extent of post-traumatic neurodegeneration; 2) todetermine its relationship with chemosensory dysfunction (smell, taste, trigeminal); and 3) to establish whether MRI can predict olfactory improvement. METHODOLOGY: We conducted a retrospective cohort study based on a series of 56 patients with PTOD. All patients underwent validated psychophysical tests of their smell, taste, and trigeminal functions, otorhinolaryngologic evaluation, and MRI. An experiencedradiologist blinded to patient data evaluated 40 chemosensory-relevant brain regions according to a four-point scale (0=no lesion to 3=large lesion). Follow up data after 4 years (on average) were available in 46 patients. RESULTS:The cluster analysis showed 4 brain lesion patterns that differed in lesion localization and severity. They are associatedwith diagnostic categories: anosmia, hyposmia and normosmia. Two clusters were highly specific for anosmia (100% specificity)and could accurately predict this condition (100% positive predictive value). No clusters were associated with trigeminal or tastedysfunction. Regarding improvement, 72.7% of patients in the cluster with mild lesions experienced subjective and measurable olfactory improvement whereas this was only the case in 21.7-37.5% of patients with larger lesions. The odds of subjective smellimprovement were 5.9 times higher in patients within the milder cluster compared to larger ones. CONCLUSIONS: The analysis of brain lesions in PTOD allows corroboration of smell test results and prediction of subjective and measurable improvement.

Studies have reported substantial variability in emotion recognition ability (ERA) – an important social skill – but possible neural underpinnings for such individual differences are not well understood. This functional magnetic resonance imaging (fMRI) study investigated neural responses during emotion recognition in young adults (N=49) who were selected for inclusion based on their performance (high or low) during previous testing of ERA. Participants were asked to judge brief video recordings in a forced-choice emotion recognition task, wherein stimuli were presented in visual, auditory and multimodal (audiovisual) blocks. Emotion recognition rates during brain scanning confirmed that individuals with high (vs. low) ERA received higher accuracy for all presentation blocks. fMRI-analyses focused on key regions of interest (ROIs) involved in the processing of multimodal emotion expressions, based on previous meta-analyses. In neural response to emotional stimuli contrasted with neutral stimuli, individuals with high (vs. low) ERA showed higher activation in the following ROIs during the multimodal condition: right middle superior temporal gyrus (mSTG), right posterior superior temporal sulcus (PSTS), and right inferior frontal cortex (IFC). Overall, results suggest that individual variability in ERA may be reflected across several stages of decisional processing, including extraction (mSTG), integration (PSTS) and evaluation (IFC) of emotional information.

In an earlier study, we analyzed how audio signals obtained from three professional opera singers varied when they sang one octave wide eight-tone scales in ten different emotional colors. The results showed systematic variations in voice source and long-term-average spectrum (LTAS) parameters associated with major emotion families. For two of the singers, subglottal pressure (P-Sub) also was recorded, thus allowing analysis of an additional main physiological voice control parameter, glottal resistance (defined as the ratio between P-Sub and glottal flow), and related to glottal adduction. In the present study, we analyze voice source and LTAS parameters derived from the audio signal and their correlation with P-sub and glottal resistance. The measured parameters showed a systematic relationship with the four emotion families observed in our previous study. They also varied systematically with values of the ten emotions along the valence, power, and arousal dimensions; valence showed a significant correlation with the ratio between acoustic voice source energy and subglottal pressure, while Power varied significantly with sound level and two measures related to the spectral dominance of the lowest spectrum partial. the fundamental.

Several studies suggest that breathing entrains neural oscillations and thereby improves visual detection and memory performance during nasal inhalation. However, the evidence for this association is mixed, with some studies finding no, minor, or opposite effects. Here, we tested whether nasal breathing phase influences memory of repeated images presented in a rapid serial visual presentation (RSVP) task. The RSVP task is ideal for studying the effects of respiratory-entrained oscillations on visual memory because it engages critical aspects of sensory encoding that depend on oscillatory activity, such as fast processing of natural images, repetition detection, memory encoding, and retrieval. It also enables the presentation of a large number of stimuli during each phase of the breathing cycle. In two separate experiments (n = 72 and n = 142, respectively) where participants were explicitly asked to breathe through their nose, we found that nasal breathing phase at target presentation did not significantly affect memory performance. An exploratory analysis in the first experiment suggested a potential benefit for targets appearing approximately 1 s after inhalation. However, this finding was not replicated in the pre-registered second experiment with a larger sample. Thus, in two large sample experiments, we found no measurable impact of breathing phase on memory performance in the RSVP task. These results suggest that the natural breathing cycle does not have a significant impact on memory for repeated images and raise doubts about the idea that visual memory is broadly affected by the breathing phase.

Some cognitive abilities are suggested to be the result of a complex social life, allowing individuals to achieve higher fitness through advanced strategies. However, most evidence is correlative. Here, we provide an experimental investigation of how group size and composition affect brain and cognitive development in the guppy (Poecilia reticulata). For 6 months, we reared sexually mature females in one of 3 social treatments: a small conspecific group of 3 guppies, a large heterospecific group of 3 guppies and 3 splash tetras (Copella arnoldi)—a species that co-occurs with the guppy in the wild, and a large conspecific group of 6 guppies. We then tested the guppies’ performance in self-control (inhibitory control), operant conditioning (associative learning), and cognitive flexibility (reversal learning) tasks. Using X-ray imaging, we measured their brain size and major brain regions. Larger groups of 6 individuals, both conspecific and heterospecific groups, showed better cognitive flexibility than smaller groups but no difference in self-control and operant conditioning tests. Interestingly, while social manipulation had no significant effect on brain morphology, relatively larger telencephalons were associated with better cognitive flexibility. This suggests alternative mechanisms beyond brain region size enabled greater cognitive flexibility in individuals from larger groups. Although there is no clear evidence for the impact on brain morphology, our research shows that living in larger social groups can enhance cognitive flexibility. This indicates that the social environment plays a role in the cognitive development of guppies.

Introduction: Olfactory dysfunction is one of many long-lasting symptoms associated with COVID-19, estimated to affect approximately 60% of individuals and often lasting several months after infection. The associated daily life problems can cause a decreased quality of life.

Methods: Here, we assessed the association between perceived quality of life and both qualitative and quantitative olfactory function (distorted and weakened sense of smell, respectively) in 58 individuals who had undergone confirmed SARS-CoV-2 infection and who complained about olfactory dysfunction.

Results: Participants with large quantitative olfactory dysfunction experienced a greater reduction in their quality of life. Moreover, our participants had a high prevalence of qualitative olfactory dysfunction (81%) with a significant correlation between qualitative olfactory dysfunction and daily life impairment. Strong drivers of low quality of life assessments were lack of enjoyment of food as well as worries related to coping with long-term dysfunctions.

Discussion: These results stress the clinical importance of assessing qualitative olfactory dysfunction and the need to develop relevant interventions. Given the poor self-rated quality of life observed, healthcare systems should consider developing support structures, dietary advice, and guidelines adapted to individuals experiencing qualitative olfactory dysfunction.

At-wavelength metrology of X-ray optics plays a crucial role in evaluating the performance of optics under actual beamline operating conditions, enabling in situ diagnostics and optimization. Techniques utilizing a wavefront random modulator have gained increasing attention in recent years. However, accurately mapping the measured wavefront slope to a curved X-ray mirror surface when the modulator is downstream of the mirror has posed a challenge. To address this problem, an iterative method has been developed in this study. The results demonstrate a significant improvement compared with conventional approaches and agree with offline measurements obtained from optical metrology. We believe that the proposed method enhances the accuracy of at-wavelength metrology techniques, and empowers them to play a greater role in beamline operation and optics fabrication.