Nicolas Coquery

Pig vocalizations convey information about the emotional states of individuals, varying with arousal and valence. Studies show that different call types reflect distinct emotional contexts and social interactions for the receivers. However, little is known about the brain mechanisms behind the perception of conspecifics’ vocalizations. This study used BOLD fMRI to explore how pigs’ brains respond to emotionally varied vocalizations, with the aim to identify activity in regions linked to emotion, reward, and social processing. Eight healthy 2-month-old pigs underwent auditory brainstem response (ABR) testing and BOLD fMRI to assess brain responses to pig vocalizations with different hedonic valence. Sounds were delivered via MRI-compatible earphones, and imaging was performed on a 1.5T scanner. Data were analyzed using voxel-based and ROI-based statistics in SPM12 with small volume correction (SVC). Due to hearing anomalies or MRI artefacts, only 5 pigs were included in the final analysis. Functional MRI revealed that vocalizations activated regions of the auditory pathway and the left amygdala (pFWE at peak < 0.05 after SVC for all), with specific differences between positive and negative sounds. Clusters of activated voxels covering part of hippocampal areas, caudate nuclei and putamen were found with both positive and aversive vocal sounds. Limbic regions, including the amygdala and insula (p<0.05), as well as the right hippocampus after SVC (pFWE = 0.015) were uniquely engaged during the perception of negative conspecific vocalizations, indicating distinct processing based on emotional valence. This study shows for the first time that piglets’ brain can process and differentiate emotional vocalizations from other pigs, even under general anesthesia. Positive and negative vocal sound playbacks activated distinct brain regions related to hearing, emotion and reward. These findings highlight pigs’ cognitive and emotional processing of vocal cues. This study is part of a wider research program aimed at developing the fMRI protocol with acoustic stimulation in juvenile pigs.

Electroacupuncture (EA), a modern adaptation of traditional acupuncture, is increasingly used to treat various conditions, including gastrointestinal disorders, although its mechanisms remain debated. Previous work in healthy minipigs showed that acute EA modulates gut–brain axis activity, with notable effects on brain responses. This study examined the effects of chronic EA on brain function, physiology, and behavior in obese minipigs.Sixteen adult Yucatan minipigs were fed a high-fat/high-sucrose diet for two months, then assigned to either a control group (n=8) or a chronic EA group (n=8), which received 12 sessions of 20-minute EA targeting Sanwan/Dafengmen acupoints. Brain activity was assessed using BOLD fMRI during acute EA (before and after diet) and oral sucrose stimulation (after treatment). Behavioral tests, blood sampling, and post-mortem gene expression analyses across four brain regions were also conducted.Acute EA modulated cortical-limbic-striatal circuits differently in normal-weight versus obese animals. Chronic EA altered brain responses to sucrose in regions involved in cognitive control, reward, decision-making, and memory (p<0.05). Gene expression analyses revealed region-specific effects on 15 genes related to blood–brain barrier integrity, inflammation, neurotransmission, synaptic plasticity, and metabolism. Following return to a normal diet, both groups lost weight, but only EA-treated animals showed greater reductions in adiposity (p<0.001) and plasma free fatty acids (p=0.028). Differences in dopamine and tryptophan levels were also observed (p<0.05).These findings demonstrate that chronic EA modulates brain function and metabolic pathways in obese minipigs, supporting its potential role in treating obesity and related disorders.

Objectives: To estimate the proportion of female university students reporting overeating (EO) in response to emotions during the COVID-19 university closures, and to investigate social and psychological factors associated with this response to stress. Design: Online survey gathered sociodemographic data, alcohol/drugs use disorders, boredom proneness and impulsivity using validated questionnaires, and EO using the Emotional Overeating Questionnaire (EOQ) assessing eating in response to six emotions (anxiety, sadness, loneliness, anger, fatigue, happiness), whose structure remains to be determined. Participants: Sample of 302 female students from Rennes University, France. Main outcome measure: Frequencies of emotional overeating. Analysis: The frequency of emotional overeating was expressed for each emotion as percentages. Exploratory Factor analyses (EFA) were used to determine EOQ structure and provide an index of all EOQ items used for further analysis. Linear regression models were used to explore relationships between EO and others covariates. Results: Nine in ten participants reported intermittent EO in the last 28 days, mostly during 6 to 12 days, in response to Anxiety (75.5%), Sadness (64.5%), Happiness (59.9%), Loneliness (57.9%), Tiredness (51.7%), and to a lesser extent to Anger (31.1%). EFA evidenced a one-factor latent variable reflecting “Distress-Induced Overeating” positively correlated with internal boredom proneness, tobacco use, attentional impulsivity, inability to resist emotional cues, and loss of control over food intake, and negatively with age and well-being. EO was unrelated to body mass index or substance abuse. Conclusion and implications: Nine in ten female students reported emotional overeating during the COVID-19 university closure. This response to stress was related to eating tendencies typical of young women, but also to personality/behavioral patterns such as boredom and impulsivity proneness. Better understanding of the mechanisms underlying EO in response to stress and lack of external/social stimulation would improve preventive interventions.

Neurofeedback (NF) training is a promising preventive and therapeutic approach for brain and behavioral impairments, the dorsolateral prefrontal cortex (DL-PFC) being a relevant region of interest. Functional near-infrared spectroscopy (NIRS) has recently been applied in NF training. However, this approach is highly sensitive to extra-cerebral vascularization, which could bias measurements of cortical activity. Here, we examined the feasibility of a NF training targeting the DL-PFC and its specificity by assessing the impact of physiological confounds on NF success via short-channel offline correction under different signal filtering conditions. We also explored whether the individual mental strategies affect the NF success. Thirty volunteers participated in a single 15-trial NF session in which they had to increase the oxy-hemoglobin (HbO2) level of their bilateral DL-PFC. We found that 0.01–0.09 Hz band-pass filtering was more suited than the 0.01–0.2 Hz band-pass filter to highlight brain activation restricted to the NF channels in the DL-PFC. Retaining the 10 out of 15 best trials, we found that 18 participants (60%) managed to control their DL-PFC. This number dropped to 13 (43%) with short-channel correction. Half of the participants reported a positive subjective feeling of control, and the “cheering” strategy appeared to be more effective in men (p<0.05). Our results showed successful DL-PFC fNIRS-NF in a single session and highlighted the value of accounting for extra cortical signals, which can profoundly affect the success and specificity of NF training.

Objectives To estimate the proportion of female university students reporting overeating (EO) in response to emotions during the COVID-19 university closures, and to investigate social and psychological factors associated with this response to stress. Design Online survey gathered sociodemographic data, alcohol/drugs use disorders, boredom proneness and impulsivity using validated questionnaires, and EO using the Emotional Overeating Questionnaire (EOQ) assessing eating in response to six emotions (anxiety, sadness, loneliness, anger, fatigue, happiness), whose structure remains to be determined. Participants Sample of 302 female students from Rennes University, France. Main Outcome Measure Frequencies of emotional overeating. Analysis The frequency of emotional overeating was expressed for each emotion as percentages. Exploratory Factor analyses (EFA) were used to determine EOQ structure and provide an index of all EOQ items used for further analysis. Linear regression models were used to explore relationships between EO and others covariates. Results Nine in ten participants reported intermittent EO in the last 28 days, mostly during 6 to 12 days, in response to Anxiety (75.5%), Sadness (64.5%), Happiness (59.9%), Loneliness (57.9%), Tiredness (51.7%), and to a lesser extent to Anger (31.1%). EFA evidenced a one-factor latent variable reflecting “Distress-Induced Overeating” positively correlated with internal boredom proneness, tobacco use, attentional impulsivity, inability to resist emotional cues, and loss of control over food intake, and negatively with age and well-being. EO was unrelated to body mass index or substance abuse. Conclusion and Implications Nine in ten female students reported emotional overeating during the COVID-19 university closure. This response to stress was related to eating tendencies typical of young women, but also to personality/behavioral patterns such as boredom and impulsivity proneness. Better understanding of the mechanisms underlying EO in response to stress and lack of external/social stimulation would improve preventive interventions.

This study aimed to compare the gut-brain axis responses to acute electroacupuncture (EA) at different acupoint combinations in the minipig model. Four adult Yucatan minipigs were subjected twice to four acute EA treatments (25-minute acute sessions) including sham (false acupoints) and control (no EA), during anesthesia and according to a Latin-square design paradigm. Acupoint combinations (4 loci each) are head-abdomen (#70 Dafengmen, #35 Sanwan), back (bilateral #27 Pishu, #28 Weishu), leg (bilateral #79 Hangou, #63 Housanli), and sham (2 bilateral points that are not acupoints). Electrocardiograms were performed to explore heart rate variability (HRV). Infrared thermography was used to measure skin temperature at the stimulation points. Saliva (cortisol) and blood samples (leptin, total/active ghrelin, insulin, and glucose) were collected for further analyses before and after acute EA. All animals were also subjected to BOLD fMRI to investigate the brain responses to EA. Acute EA significantly modulated several physiological and metabolic parameters compared to basal, sham, and/or control conditions, with contrasting effects in terms of BOLD responses in brain regions involved in the hedonic and cognitive control of food intake. The head-abdomen combination appeared to be the most promising combination in terms of brain modulation of the corticostriatal circuit, with upregulation of the dorsolateral prefrontal cortex, dorsal striatum, and anterior cingulate cortex. It also induced significantly lower plasma ghrelin levels compared to sham, suggesting anorectic effects, as well as no temperature drop at the stimulation site. This study opens the way to a further preclinical trial aimed at investigating chronic EA in obese minipigs.

Emotional eating is commonly defined as the tendency to (over)eat in response to emotion. Insofar as it involves the (over)consumption of high-calorie palatable foods, emotional eating is a maladaptive behavior that can lead to eating disorders, and ultimately to metabolic disorders and obesity. Emotional eating is associated with eating disorder subtypes and with abnormalities in emotion processing at a behavioral level. However, not enough is known about the neural pathways involved in both emotion processing and food intake. In this review, we provide an overview of recent neuroimaging studies, highlighting the brain correlates between emotions and eating behavior that may be involved in emotional eating. Interaction between neural and neuro-endocrine pathways (HPA axis) may be involved. In addition to behavioral interventions, there is a need for a holistic approach encompassing both neural and physiological levels to prevent emotional eating. Based on recent imaging, this review indicates that more attention should be paid to prefrontal areas, the insular and orbitofrontal cortices, and reward pathways, in addition to regions that play a major role in both the cognitive control of emotions and eating behavior. Identifying these brain regions could allow for neuromodulation interventions, including neurofeedback training, which deserves further investigation.