Beauty is in the nose of the beholder: Fragrance modulates attractiveness, confidence and femininity ratings and neural responses to faces of self and others.

Previous research investigated cross-modal influence of olfactory stimuli on perception and evaluation of faces. However, little is known about the neural dynamics underpinning this multisensory perception, and no research examined perception for images of oneself, and others, in presence of fragrances. This study investigated the neural mechanisms of olfactory-visual processing using electroencephalography (EEG) and subjective evaluations of self- and other-images. 22 female participants evaluated images of female actors and themselves while being exposed to the fragrance of a commercially available body wash or clean air delivered via olfactometer. Participants rated faces for attractiveness, femininity, confidence and glamorousness on visual analogue scales. EEG data was recorded and event-related potentials (ERPs) associated with onset of face stimuli were analysed to consider effects of fragrance presence on face processing, and interactions between fragrance and self-other image-type. Subjective ratings of confidence, attractiveness and femininity were increased for both image-types in pleasant fragrance relative to clean air condition. ERP components covering early-to-late stages of face processing were modulated by the presence of fragrance. Findings also revealed a cross-modal fragrance-face interaction, with pleasant fragrance particularly affecting ERPs to self-images in mid-latency ERP components. Results showed that the pleasant fragrance of the commercially available body wash impacted how participants perceived faces of self and others. Self- and other-image faces were subjectively rated as more attractive, confident and feminine in the presence of the pleasant fragrance compared to an un-fragranced control. The pleasant fragrance also modulated underlying electrophysiological activity. For the first time, an effect of pleasant fragrance on face perception was observed in the N1 component, suggesting impact within 100 ms. Pleasant fragrance also demonstrated greater impact on subsequent neural processing for self, relative to other-faces. The findings have implications for understanding multisensory integration during evaluations of oneself and others.

Small fibre pathology, small fibre symptoms and pain in fibromyalgia syndrome.

A proportion of people with fibromyalgia demonstrate small fibre pathology (SFP). However, it is unclear how SFP directly relates to pain phenomenology. Thirty-three individuals with FMS and ten healthy volunteers underwent assessment of SFP and sensory phenotyping using corneal confocal microscopy, validated questionnaires and quantitative sensory testing (QST). Corneal nerve fibre length was used to stratify participants with fibromyalgia into with SFP [SFP+] and without SFP [SFP-]. SFP was detected in 50% of the fibromyalgia cohort. Current pain score and QST parameters did not differ between SFP+ and SFP-. Mechanical pain sensitivity (MPS) demonstrated a significant gain-of-function in the SFP- cohort compared to healthy-volunteers (p = 0.014, F = 4.806, η2 = 0.22). Further stratification revealed a cohort without structural SFP but with symptoms compatible with small fibre neuropathy symptoms and a significant gain in function in MPS (p = 0.020 Chi-square). Additionally, this cohort reported higher scores for both depression (p = 0.039, H = 8.483, η2 = 0.312) and anxiety (p = 0.022, F = 3.587, η2 = 0.293). This study confirms that SFP is present in a proportion of people with fibromyalgia. We also show that in a proportion of people with fibromyalgia, small fibre neuropathy symptoms are present in the absence of structural SFP. Greater mechanical pain sensitivity, depression and anxiety are seen in these individuals.

Effects of Lockdown Restrictions and Impact of Anxiety and Depression Symptoms in People With Chronic Pain During the Covid-19 Pandemic: A 13-Wave Longitudinal Study.

In early 2020, countries across the world imposed lockdown restrictions to curb the spread of the Covid-19 coronavirus. Lockdown conditions, including social and physical distancing measures and recommended self-isolation for clinically vulnerable groups, were proposed to disproportionately affect those living with chronic pain, who already report reduced access to social support and increased isolation. Yet, empirical evidence from longitudinal studies tracking the effects of prolonged and fluctuating lockdown conditions, and potential psychological factors mediating the effects of such restrictions on outcomes in chronic pain populations, is lacking. Accordingly, in the present 13-wave longitudinal study, we surveyed pain intensity, pain interference, and tiredness in people with chronic pain over the course of 11 months of the Covid-19 pandemic (April 2020-March 2021). Of N = 431 participants at baseline, average completion rate was ∼50% of time points, and all available data points were included in linear mixed models. We examined the impact of varying levels of lockdown restrictions on these outcomes and investigated whether psychological distress levels mediated effects. We found that a full national lockdown was related to greater pain intensity, and these effects were partially mediated by depressive symptoms. No effects of lockdown level were found for pain interference and tiredness, which were instead predicted by higher levels of depression, anxiety, pain catastrophising, and reduced exercise. Our findings are relevant for improving patient care in current and future crises. Offering remote management options for low mood could be particularly beneficial for this vulnerable population in the event of future implementation of lockdown restrictions. PERSPECTIVE: This longitudinal study demonstrates the impact of Covid-19 lockdown restrictions on people with chronic pain. Findings suggest a complex interaction of psychosocial factors that impacted various aspects of pain experience in patients, which offer the potential to inform clinical strategies for remote medicine and future crises.

Machine learning and EEG can classify passive viewing of discrete categories of visual stimuli but not the observation of pain.

Previous studies have demonstrated the potential of machine learning (ML) in classifying physical pain from non-pain states using electroencephalographic (EEG) data. However, the application of ML to EEG data to categorise the observation of pain versus non-pain images of human facial expressions or scenes depicting pain being inflicted has not been explored. The present study aimed to address this by training Random Forest (RF) models on cortical event-related potentials (ERPs) recorded while participants passively viewed faces displaying either pain or neutral expressions, as well as action scenes depicting pain or matched non-pain (neutral) scenarios. Ninety-one participants were recruited across three samples, which included a model development group (n = 40) and a cross-subject validation group (n = 51). Additionally, 25 participants from the model development group completed a second experimental session, providing a within-subject temporal validation sample. The analysis of ERPs revealed an enhanced N170 component in response to faces compared to action scenes. Moreover, an increased late positive potential (LPP) was observed during the viewing of pain scenes compared to neutral scenes. Additionally, an enhanced P3 response was found when participants viewed faces displaying pain expressions compared to neutral expressions. Subsequently, three RF models were developed to classify images into faces and scenes, neutral and pain scenes, and neutral and pain expressions. The RF model achieved classification accuracies of 75%, 64%, and 69% for cross-validation, cross-subject, and within-subject classifications, respectively, along with reasonably calibrated predictions for the classification of face versus scene images. However, the RF model was unable to classify pain versus neutral stimuli above chance levels when presented with subsequent tasks involving images from either category. These results expand upon previous findings by externally validating the use of ML in classifying ERPs related to different categories of visual images, namely faces and scenes. The results also indicate the limitations of ML in distinguishing pain and non-pain connotations using ERP responses to the passive viewing of visually similar images.

The neural correlates of texture perception: A systematic review and activation likelihood estimation meta-analysis of functional magnetic resonance imaging studies.

INTRODUCTION: Humans use discriminative touch to perceive texture through dynamic interactions with surfaces, activating low-threshold mechanoreceptors in the skin. It was largely assumed that texture was processed in primary somatosensory regions in the brain; however, imaging studies indicate heterogeneous patterns of brain activity associated with texture processing. METHODS: To address this, we conducted a coordinate-based activation likelihood estimation meta-analysis of 13 functional magnetic resonance imaging studies (comprising 15 experiments contributing 228 participants and 275 foci) selected by a systematic review. RESULTS: Concordant activations for texture perception occurred in the left primary somatosensory and motor regions, with bilateral activations in the secondary somatosensory, posterior insula, and premotor and supplementary motor cortices. We also evaluated differences between studies that compared touch processing to non-haptic control (e.g., rest or visual control) or those that used haptic control (e.g., shape or orientation perception) to specifically investigate texture encoding. Studies employing a haptic control revealed concordance for texture processing only in the left secondary somatosensory cortex. Contrast analyses demonstrated greater concordance of activations in the left primary somatosensory regions and inferior parietal cortex for studies with a non-haptic control, compared to experiments accounting for other haptic aspects. CONCLUSION: These findings suggest that texture processing may recruit higher order integrative structures, and the secondary somatosensory cortex may play a key role in encoding textural properties. The present study provides unique insight into the neural correlates of texture-related processing by assessing the influence of non-textural haptic elements and identifies opportunities for a future research design to understand the neural processing of texture.

Tactile estimation of hedonic and sensory properties during active touch: An electroencephalography study.

Perceptual judgements about our physical environment are informed by somatosensory information. In real-world exploration, this often involves dynamic hand movements to contact surfaces, termed active touch. The current study investigated cortical oscillatory changes during active exploration to inform the estimation of surface properties and hedonic preferences of two textured stimuli: smooth silk and rough hessian. A purpose-built touch sensor quantified active touch, and oscillatory brain activity was recorded from 129-channel electroencephalography. By fusing these data streams at a single trial level, oscillatory changes within the brain were examined while controlling for objective touch parameters (i.e., friction). Time-frequency analysis was used to quantify changes in cortical oscillatory activity in alpha (8-12 Hz) and beta (16-24 Hz) frequency bands. Results reproduce findings from our lab, whereby active exploration of rough textures increased alpha-band event-related desynchronisation in contralateral sensorimotor areas. Hedonic processing of less preferred textures resulted in an increase in temporoparietal beta-band and frontal alpha-band event-related desynchronisation relative to most preferred textures, suggesting that higher order brain regions are involved in the hedonic processing of texture. Overall, the current study provides novel insight into the neural mechanisms underlying texture perception during active touch and how this process is influenced by cognitive tasks.

Neural correlates of perceptual texture change during active touch.

Introduction: Texture changes occur frequently during real-world haptic explorations, but the neural processes that encode perceptual texture change remain relatively unknown. The present study examines cortical oscillatory changes during transitions between different surface textures during active touch. Methods: Participants explored two differing textures whilst oscillatory brain activity and finger position data were recorded using 129-channel electroencephalography and a purpose-built touch sensor. These data streams were fused to calculate epochs relative to the time when the moving finger crossed the textural boundary on a 3D-printed sample. Changes in oscillatory band power in alpha (8-12 Hz), beta (16-24 Hz) and theta (4-7 Hz) frequency bands were investigated. Results: Alpha-band power reduced over bilateral sensorimotor areas during the transition period relative to ongoing texture processing, indicating that alpha-band activity is modulated by perceptual texture change during complex ongoing tactile exploration. Further, reduced beta-band power was observed in central sensorimotor areas when participants transitioned from rough to smooth relative to transitioning from smooth to rough textures, supporting previous research that beta-band activity is mediated by high-frequency vibrotactile cues. Discussion: The present findings suggest that perceptual texture change is encoded in the brain in alpha-band oscillatory activity whilst completing continuous naturalistic movements across textures.

External validation of binary machine learning models for pain intensity perception classification from EEG in healthy individuals.

Discrimination of pain intensity using machine learning (ML) and electroencephalography (EEG) has significant potential for clinical applications, especially in scenarios where self-report is unsuitable. However, existing research is limited due to a lack of external validation (assessing performance using novel data). We aimed for the first external validation study for pain intensity classification with EEG. Pneumatic pressure stimuli were delivered to the fingernail bed at high and low pain intensities during two independent EEG experiments with healthy participants. Study one (n = 25) was utilised for training and cross-validation. Study two (n = 15) was used for external validation one (identical stimulation parameters to study one) and external validation two (new stimulation parameters). Time-frequency features of peri-stimulus EEG were computed on a single-trial basis for all electrodes. ML training and analysis were performed on a subset of features, identified through feature selection, which were distributed across scalp electrodes and included frontal, central, and parietal regions. Results demonstrated that ML models outperformed chance. The Random Forest (RF) achieved the greatest accuracies of 73.18, 68.32 and 60.42% for cross-validation, external validation one and two, respectively. Importantly, this research is the first to externally validate ML and EEG for the classification of intensity during experimental pain, demonstrating promising performance which generalises to novel samples and paradigms. These findings offer the most rigorous estimates of ML's clinical potential for pain classification.

Pulse Intensity Effects of Burst and Tonic Spinal Cord Stimulation on Neural Responses to Brushing in Patients With Neuropathic Pain.

OBJECTIVES: Tonic spinal cord stimulation (SCS) is accompanied by paresthesia in affected body regions. Comparatively, the absence of paresthesia with burst SCS suggests different involvement of the dorsal column system conveying afferent impulses from low-threshold mechanoreceptors. This study evaluated cortical activation changes during gentle brushing of a pain-free leg during four SCS pulse intensities to assess the effect of intensity on recruitment of dorsal column system fibers during burst and tonic SCS. MATERIALS AND METHODS: Twenty patients using SCS (11 burst, nine tonic) for neuropathic leg pain participated. Brushing was administered to a pain-free area of the leg during four SCS intensities: therapeutic (100%), medium (66%), low (33%), and no stimulation. Whole-brain electroencephalography was continuously recorded. Changes in spectral power during brushing were evaluated using the event-related desynchronization (ERD) method in theta (4-7 Hz), alpha (8-13 Hz), and beta (16-24 Hz) frequency bands. RESULTS: Brushing was accompanied by a suppression of cortical oscillations in the range 4-24 Hz. Stronger intensities of burst and tonic SCS led to less suppression of 4-7 Hz and 8-13 Hz bands in parietal electrodes, and in central electrodes in the 16-24 Hz band, with the strongest, statistically significant suppression at medium intensity. Tonic SCS showed a stronger reduction in 4-7 Hz oscillations over right sensorimotor electrodes, and over right frontal and left sensorimotor electrodes in the 8-13 Hz band, compared to burst SCS. CONCLUSIONS: Results suggest that burst and tonic SCS are mediated by both different and shared mechanisms. Attenuated brushing-related ERD with tonic SCS suggests a gating of cortical activation by afferent impulses in the dorsal column, whereas burst may engage different pathways. Diminished brushing-related ERD at medium and therapeutic intensities of burst and tonic SCS points towards a nonlinear effect of SCS on somatosensory processing.

Sign-tracking modulates reward-related neural activation to reward cues, but not reward feedback.

Research shows cognitive and neurobiological overlap between sign-tracking [value-modulated attentional capture (VMAC) by response-irrelevant, discrete cues] and maladaptive behaviour (e.g. substance abuse). We investigated the neural correlates of sign-tracking in 20 adults using an additional singleton task (AST) and functional magnetic resonance imaging (fMRI). Participants responded to a target to win monetary reward, the amount of which was signalled by singleton type (reward cue: high value vs. low value). Singleton responses resulted in monetary deductions. Sign-tracking-greater distraction by high-value vs. low-value singletons (H > L)-was observed, with high-value singletons producing slower responses to the target than low-value singletons. Controlling for age and sex, analyses revealed no differential brain activity across H > L singletons. Including sign-tracking as a regressor of interest revealed increased activity (H > L singletons) in cortico-subcortical loops, regions associated with Pavlovian conditioning, reward processing, attention shifts and relative value coding. Further analyses investigated responses to reward feedback (H > L). Controlling for age and sex, increased activity (H > L reward feedback) was found in regions associated with reward anticipation, attentional control, success monitoring and emotion regulation. Including sign-tracking as a regressor of interest revealed increased activity in the temporal pole, a region related to value discrimination. Results suggest sign-tracking is associated with activation of the 'attention and salience network' in response to reward cues but not reward feedback, suggesting parcellation between the two at the level of the brain. Results add to the literature showing considerable overlap in neural systems implicated in reward processing, learning, habit formation, emotion regulation and substance craving.

Intensity-dependent modulation of cortical somatosensory processing during external, low-frequency peripheral nerve stimulation in humans.

External low-frequency peripheral nerve stimulation (LFS) has been proposed as a novel method for neuropathic pain relief. Previous studies have reported that LFS elicits long-term depression-like effects on human pain perception when delivered at noxious intensities, whereas lower intensities are ineffective. To shed light on cortical regions mediating the effects of LFS, we investigated changes in somatosensory-evoked potentials (SEPs) during four LFS intensities. LFS was applied to the radial nerve (600 pulses, 1 Hz) of 24 healthy participants at perception (1 times), low (5 times), medium (10 times), and high intensities (15 times detection threshold). SEPs were recorded during LFS, and averaged SEPs in 10 consecutive 1-min epochs of LFS were analyzed using source dipole modeling. Changes in resting electroencephalography (EEG) were investigated after each LFS block. Source activity in the midcingulate cortex (MCC) decreased linearly during LFS, with greater attenuation at stronger LFS intensities, and in the ipsilateral operculo-insular cortex during the two lowest LFS stimulus intensities. Increased LFS intensities resulted in greater augmentation of contralateral primary sensorimotor cortex (SI/MI) activity. Stronger LFS intensities were followed by increased α (alpha, 9-11 Hz) band power in SI/MI and decreased θ (theta, 3-5 Hz) band power in MCC. Intensity-dependent attenuation of MCC activity with LFS is consistent with a state of long-term depression. Sustained increases in contralateral SI/MI activity suggests that effects of LFS on somatosensory processing may also be dependent on satiation of SI/MI. Further research could clarify if the activation of SI/MI during LFS competes with nociceptive processing in neuropathic pain.NEW & NOTEWORTHY Somatosensory-evoked potentials during low-frequency stimulation of peripheral nerves were examined at graded stimulus intensities. Low-frequency stimulation was associated with decreased responsiveness in the midcingulate cortex and increased responsiveness in primary sensorimotor cortex. Greater intensities were associated with increased midcingulate cortex θ band power and decreased sensorimotor cortex α band power. Results further previous evidence of an inhibition of somatosensory processing during and after low-frequency stimulation and point toward a potential augmentation of activity in somatosensory processing regions.

Neural correlates of texture perception during active touch.

Previous studies have shown attenuation of cortical oscillations over bilateral sensorimotor cortex areas during passive perception of smooth textures applied to the skin. However, humans typically explore surfaces using dynamic hand movements. As movements may both modulate texture-related cortical activity and induce movement-related cortical activation, data from passive texture perception cannot be extrapolated to active texture perception. In the present study, we used electroencephalography to investigate cortical oscillatory changes during texture perception throughout active touch exploration. Three natural textured stimuli were selected: smooth silk, soft brushed cotton, and rough hessian. Texture samples were mounted on a purpose-built touch sensor which measured the load and position of the index finger, whilst electroencephalography from 129 channels recorded oscillatory brain activity. The data were fused to investigate oscillatory changes relating to active touch. Changes in oscillatory band power, event-related desynchronisation/synchronisation (ERD/ERS), were investigated in alpha (8-12 Hz) and beta (16-24 Hz) frequency bands. Active texture exploration revealed bilateral activation patterns over sensorimotor cortical areas. Beta-band ERD increased over contralateral sensorimotor regions for soft and smooth textures, and over ipsilateral sensorimotor areas for the smoothest texture. Analysis of covariance revealed that individual differences in perception of softness and smoothness were related to variations in cortical oscillatory activity. Differences may be due to increased high frequency vibrations for smooth and soft textures compared to rough. For the first time, active touch was quantified and fused with electroencephalography data streams, contributing to the understanding of the neural correlates of texture perception during active touch.

Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data.

Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. The primary aim of this review was to evaluate the effectiveness of ML algorithms for predicting pain intensity, phenotypes or treatment response from EEG. Electronic databases MEDLINE, EMBASE, Web of Science, PsycINFO and The Cochrane Library were searched. A total of 44 eligible studies were identified, with 22 presenting attempts to predict pain intensity, 15 investigating the prediction of pain phenotypes and seven assessing the prediction of treatment response. A meta-analysis was not considered appropriate for this review due to heterogeneous methods and reporting. Consequently, data were narratively synthesized. The results demonstrate that the best performing model of the individual studies allows for the prediction of pain intensity, phenotypes and treatment response with accuracies ranging between 62 to 100%, 57 to 99% and 65 to 95.24%, respectively. The results suggest that ML has the potential to effectively predict pain outcomes, which may eventually be used to assist clinical care. However, inadequate reporting and potential bias reduce confidence in the results. Future research should improve reporting standards and externally validate models to decrease bias, which would increase the feasibility of clinical translation. PERSPECTIVE: This systematic review explores the state-of-the-art machine learning methods for predicting pain intensity, phenotype or treatment response from EEG data. Results suggest that machine learning may demonstrate clinical utility, pending further research and development. Areas for improvement, including standardized processing, reporting and the need for better methodological assessment tools, are discussed.

Adverse effects of COVID-19-related lockdown on pain, physical activity and psychological well-being in people with chronic pain.

Countries across the world imposed lockdown restrictions during the COVID-19 pandemic. It has been proposed that lockdown conditions, including social and physical distancing measures, may disproportionately impact those living with chronic pain and require rapid adaptation to treatment and care strategies. Using an online methodology, we investigated how lockdown restrictions in the United Kingdom impacted individuals with chronic pain (N = 431) relative to a healthy control group (N = 88). Data were collected during the most stringent period of lockdown in the United Kingdom (mid-April to early-May 2020). In accordance with the fear-avoidance model, we hypothesised lockdown-related increases in pain and psychological distress, which would be mediated by levels of pain catastrophising. Responses indicated that people with chronic pain perceived increased pain severity, compared to their estimation of typical pain levels prior to lockdown (p < .001). They were also more adversely affected by lockdown conditions compared to pain-free individuals, demonstrating greater self-perceived increases in anxiety and depressed mood, increased loneliness and reduced levels of physical exercise (p ⩽ .001). Hierarchical regression analysis revealed that pain catastrophising was an important factor relating to the extent of self-perceived increases in pain severity during lockdown (ß = .27, p < .001) and also mediated the relationship between decreased mood and pain. Perceived decreases in levels of physical exercise also related to perceptions of increased pain (ß = .15, p < .001). Interestingly, levels of pain intensity (measured at two time points at pre and during lockdown) in a subgroup (N = 85) did not demonstrate a significant change. However, individuals in this subgroup still reported self-perceived pain increases during lockdown, which were also predicted by baseline levels of pain catastrophising. Overall, the findings indicate that people with chronic pain suffer adverse effects of lockdown including self-perceived increases in their pain. Remote pain management provision to target reduction of pain catastrophising and increase health behaviours including physical activity could be beneficial for this vulnerable population.

Probabilistic mapping of thalamic nuclei and thalamocortical functional connectivity in idiopathic generalised epilepsy.

It is well established that abnormal thalamocortical systems play an important role in the generation and maintenance of primary generalised seizures. However, it is currently unknown which thalamic nuclei and how nuclear-specific thalamocortical functional connectivity are differentially impacted in patients with medically refractory and non-refractory idiopathic generalised epilepsy (IGE). In the present study, we performed structural and resting-state functional magnetic resonance imaging (MRI) in patients with refractory and non-refractory IGE, segmented the thalamus into constituent nuclear regions using a probabilistic MRI segmentation method and determined thalamocortical functional connectivity using seed-to-voxel connectivity analyses. We report significant volume reduction of the left and right anterior thalamic nuclei only in patients with refractory IGE. Compared to healthy controls, patients with refractory and non-refractory IGE had significant alterations of functional connectivity between the centromedian nucleus and cortex, but only patients with refractory IGE had altered cortical connectivity with the ventral lateral nuclear group. Patients with refractory IGE had significantly increased functional connectivity between the left and right ventral lateral posterior nuclei and cortical regions compared to patients with non-refractory IGE. Cortical effects were predominantly located in the frontal lobe. Atrophy of the anterior thalamic nuclei and resting-state functional hyperconnectivity between ventral lateral nuclei and cerebral cortex may be imaging markers of pharmacoresistance in patients with IGE. These structural and functional abnormalities fit well with the known importance of thalamocortical systems in the generation and maintenance of primary generalised seizures, and the increasing recognition of the importance of limbic pathways in IGE.

Inhibition of cortical somatosensory processing during and after low frequency peripheral nerve stimulation in humans.

OBJECTIVE: Transcutaneous low-frequency stimulation (LFS) elicits long-term depression-like effects on human pain perception. However, the neural mechanisms underlying LFS are poorly understood. We investigated cortical activation changes occurring during LFS and if changes were associated with reduced nociceptive processing and increased amplitude of spontaneous cortical oscillations post-treatment. METHODS: LFS was applied to the radial nerve of 25 healthy volunteers over two sessions using active (1 Hz) or sham (0.02 Hz) frequencies. Changes in resting electroencephalography (EEG) and laser-evoked potentials (LEPs) were investigated before and after LFS. Somatosensory-evoked potentials were recorded during LFS and source analysis was carried out. RESULTS: Ipsilateral midcingulate and operculo-insular cortex source activity declined linearly during LFS. Active LFS was associated with attenuated long-latency LEP amplitude in ipsilateral frontocentral electrodes and increased resting alpha (8-12 Hz) and beta (16-24 Hz) band power in electrodes overlying operculo-insular, sensorimotor and frontal cortical regions. Reduced ipsilateral operculo-insular cortex source activity during LFS correlated with a smaller post-treatment alpha-band power increase. CONCLUSIONS: LFS attenuated somatosensory processing both during and after stimulation. SIGNIFICANCE: Results further our understanding of the attenuation of somatosensory processing both during and after LFS.

A Behavioral and Electrophysiological Investigation of Effects of Visual Congruence on Olfactory Sensitivity During Habituation to Prolonged Odors.

Congruent visual cues augment sensitivity to brief olfactory presentations and habituation of odor perception is modulated by central-cognitive processing including context. However, it is not known whether habituation to odors could interact with cross-modal congruent stimuli. The present research investigated the effect of visual congruence on odor detection sensitivity during continuous odor exposures. We utilized a multimethod approach, including subjective behavioral responses and reaction times (RTs; study 1) and electroencephalography (EEG, study 2). Study 1: 25 participants received 2-min presentations of moderate-intensity floral odor delivered via olfactometer with congruent (flower) and incongruent (object) image presentations. Participants indicated odor perception after each image. Detection sensitivity and RTs were analyzed in epochs covering the period of habituation. Study 2: 25 new participants underwent EEG recordings during 145-s blocks of odor presentations with congruent or incongruent images. Participants passively observed images and intermittently rated the perceived intensity of odor. Event-related potential analysis was utilized to evaluate brain processing related to odor-visual pairs across the period of habituation. Odor detection sensitivity and RTs were improved by congruent visual cues. Results highlighted a diminishing influence of visual congruence on odor detection sensitivity as habituation occurred. Event-related potential analysis revealed an effect of congruency on electrophysiological processing in the N400 component. This was only evident in early periods of odor exposure when perception was strong. For the first time, this demonstrates the modulation of central processing of odor-visual pairs by habituation. Frontal negativity (N400) responses encode the aspects of cross-modal congruence for odor-vision cross-modal tasks.

Shared and distinct functional networks for empathy and pain processing: a systematic review and meta-analysis of fMRI studies.

BACKGROUND: Empathy for pain is a complex phenomenon incorporating sensory, cognitive and affective processes. Functional neuroimaging studies indicate a rich network of brain activations for empathic processing. However, previous research focused on core activations in bilateral anterior insula (AI) and anterior cingulate/anterior midcingulate cortex (ACC/aMCC) which are also typically present during nociceptive (pain) processing. Theoretical understanding of empathy would benefit from empirical investigation of shared and contrasting brain activations for empathic and nociceptive processing. METHOD: Thirty-nine empathy for observed pain studies (1112 participants; 527 foci) were selected by systematic review. Coordinate based meta-analysis (activation likelihood estimation) was performed and novel contrast analyses compared neurobiological processing of empathy with a comprehensive meta-analysis of 180 studies of nociceptive processing (Tanasescu et al., 2016). RESULTS: Conjunction analysis indicated overlapping activations for empathy and nociception in AI, aMCC, somatosensory and inferior frontal regions. Contrast analysis revealed increased likelihood of activation for empathy, relative to nociception, in bilateral supramarginal, inferior frontal and occipitotemporal regions. Nociception preferentially activated bilateral posterior insula, somatosensory cortex and aMCC. CONCLUSION: Our findings support the likelihood of shared and distinct neural networks for empathic, relative to nociceptive, processing. This offers succinct empirical support for recent tiered or modular theoretical accounts of empathy.

A Systematic Review and Activation Likelihood Estimation Meta-Analysis of fMRI Studies on Sweet Taste in Humans.

BACKGROUND: The reward value of palatable foods is often cited as an important influence on eating behaviors, including intake of sugars. However, human neuroimaging studies have generated conflicting evidence on the basic neural representation of taste and reward responses to caloric sweeteners (sucrose and glucose), and most relevant studies have used small subject numbers. OBJECTIVE: We conducted a systematic review and a coordinate-based meta-analysis of studies reporting brain responses to oral sugar solutions. METHODS: A systematic search of MEDLINE, Scopus, and PsycINFO through October 2019 identified fMRI studies (in healthy human adults, including those with overweight or obesity) assessing differences in responses to purified sweet and nonsweet taste stimuli. Data were extracted with the primary objective of quantifying evidence for the activation of brain regions associated with caloric sweet taste sensation. We used activation likelihood estimation meta-analysis methods. We also performed multiple sensitivity analyses to assess the generality of effects. RESULTS: Of 455 unique articles, 15 met the criteria for inclusion. These contributed to 2 primary meta-analyses: 1) sucrose (13 experiments, 179 coordinates, n = 241) and 2) sucrose + glucose (16 experiments, 209 coordinates, n = 262). Consistent activation was apparent in primary taste areas: insula (69.2% of studies) and opercular cortex (76.9% of studies), precentral gyri (53.9% of studies), and globus pallidus and postcentral gyrus (30.8% of studies for each). Evidence of reward activity (caudate) was seen in the primary analyses (30.8% of studies) but not in sensitivity analysis. CONCLUSIONS: We confirm the importance of primary taste areas for gustatory processing in human adults. We also provide tentative evidence for reward-related caudate activity in relation to the sweet taste of caloric sugars. A number of factors affect the observation and interpretation of brain responses, including reward-related activity. Firm conclusions require confirmation with large data set studies.

Neural underpinnings of value-guided choice during auction tasks: An eye-fixation related potentials study.

Values are attributed to goods during free viewing of objects which entails multi- and trans-saccadic cognitive processes. Using electroencephalographic eye-fixation related potentials, the present study investigated how neural signals related to value-guided choice evolved over time when viewing household and office products during an auction task. Participants completed a Becker-DeGroot-Marschak auction task whereby half of the stimuli were presented in either a free or forced bid protocol to obtain willingness-to-pay. Stimuli were assigned to three value categories of low, medium and high value based on subjective willingness-to-pay. Eye fixations were organised into five 800 ms time-bins spanning the objects total viewing time. Independent component analysis was applied to eye-fixation related potentials. One independent component (IC) was found to represent fixations for high value products with increased activation over the left parietal region of the scalp. An IC with a spatial maximum over a fronto-central region of the scalp coded the intermediate values. Finally, one IC displaying activity that extends over the right frontal scalp region responded to intermediate- and low-value items. Each of these components responded early on during viewing an object and remained active over the entire viewing period, both during free and forced bid trials. Results suggest that the subjective value of goods are encoded using sets of brain activation patterns which are tuned to respond uniquely to either low, medium, or high values. Data indicates that the right frontal region of the brain responds to low and the left frontal region to high values. Values of goods are determined at an early point in the decision making process and carried for the duration of the decision period via trans-saccadic processes.