Background:Research consistently shows that depression and suicidal ideation (SI) often cooccur. However, SI can arise without elevated depressive symptoms, suggesting that additional factors may also contribute. This study investigated the protective and vulnerability factors associated with SI beyond depressive symptomatology in the academic community. Methods:We employed multiple kernel learning (MKL) to distinguish participants with SI from those without SI. MKL incorporates the contribution of each psychometric instrument and specific items to the predictive model. Data were drawn from a large-scale online survey of the Brazilian academic community (N = 3828; 67.6% women; 33.2% black; mean age 38.28 years; SD 12.89 [95% CI: 31.6-33.1]). The models incorporated measures of depressive symptoms, optimism, loneliness, childhood maltreatment, and demographic characteristics. Findings:The MKL model accurately distinguished individuals with and without SI, achieving a mean balanced accuracy of 77.61% (95% CI: 77.40-77.82) and an area under the curve (AUC) of 0.862 (95% CI: 0.860-0.864). While depressive symptoms were strong predictors, other variables, such as optimism, loneliness, childhood emotional maltreatment, and demographic characteristics together accounted for half the total weight in the classification model. Interpretation:These findings underscore the need for suicidal ideation screening protocols that consider a broader range of emotional and behavioral factors beyond depressive symptoms, particularly within academic communities. These insights may inform the design of targeted interventions to promote mental well-being in academic settings. Funding:Carlos Chagas Filho Foundation of Research Support in Rio de Janeiro (FAPERJ: E-26.201.678/2022; E-26.201.118/2021).

Major depressive disorder (MDD) affects 3.8

Environmental cues can guide behavior, which in substance use disorders contributes to maladaptive outcomes. Currently, ultra-processed food (UPF) cues dominate food environments, and growing evidence suggests that their consumption may share characteristics with substance use disorders. The attribution of heightened incentive salience to food cues relative to other highly rewarding stimuli has been linked to food addiction (FA). Here, we investigate whether FA is specifically associated with greater incentive salience for UPF. A remote version of the normative rating procedure for the International Affective Picture System (IAPS) was conducted with 212 Brazilians. The arousal dimension of emotion was used as an index of incentive salience and was assessed through the Self-Assessment Manikin scale. We presented 70 pictures from the IAPS (from various emotion categories, including erotic cues due to their rewarding properties) and an additional set of 11 UPF and 11 unprocessed or minimally processed foods (UMPF) pictures. The modified Yale Food Addiction Scale 2.0 was applied to assess FA. Results indicated that both groups of individuals (with and without FA) attributed greater incentive salience to UPF cues than to UMPF cues. However, only individuals with FA attributed similar incentive salience to UPF and erotic cues. These findings highlight the significance of UPF in the development of FA and could support public policies aimed at overcoming the appealing and potentially addictive aspects of UPF.

Background: Psychological violence, defined as interpersonal acts intended to humiliate or diminish others without physical force, has been linked to significant psychological suffering. Despite its prevalence and association with mental health disorders, it is not classified as a potentially traumatic event under the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria for post-traumatic stress disorder (PTSD) diagnosis.Objective: This study examines whether psychological violence, when identified as the index trauma, is associated with PTSD symptoms at levels comparable to those elicited by DSM-5-recognized traumas.Method: In this cross-sectional study, 530 Brazilian undergraduate students completed the Trauma History Questionnaire (THQ) and the PTSD Checklist for DSM-5 (PCL-5). Negative binomial regression and logistic regression models were used to examine associations between trauma type and PTSD symptom severity and probable diagnosis.Results: Compared to crime- and disaster-related trauma, psychological violence was associated with greater PTSD symptom severity and higher odds of probable PTSD diagnosis. Its impact was comparable to that of physical and sexual violence.Conclusions: These findings emphasize the importance of raising awareness about the emotional consequences of psychological violence and highlight the need for greater recognition of psychological violence as part of the spectrum of experiences associated with PTSD. Recognizing psychological trauma as a threat to the fundamental human need for social connection has critical implications for diagnostic refinement and treatment protocols.

Background: Posttraumatic stress disorder (PTSD) is a multifactorial condition shaped by numerous biopsychosocial risk and protective factors. Machine learning methods provide powerful tools to model these complex and interacting influences on symptom expression, although many existing approaches rely on data that are impractical for large-scale application.Objective: In this study, we combined accessible psychometric measures with heart rate variability (HRV) to model vulnerability and resilience factors associated with PTSD symptoms in trauma-exposed individuals from a nonclinical sample. Importantly, a longitudinal follow-up complemented the cross-sectional design, allowing us to examine whether early psychological and physiological markers predict subsequent PTSD symptoms.Method: Regression models were implemented using a sparse multiple kernel learning (MKL) approach, allowing an estimation of the relative contribution of predictors both at the construct level (e.g. psychometric and HRV measures) and at the individual item level. The sample comprised 176 undergraduate students who completed psychometric scales assessing tonic immobility, optimism, positive and negative affect, coping strategies, and childhood maltreatment. HRV during exposure to negative stimuli was included as an autonomic predictor. PTSD symptom severity (PCL-5) was assessed cross-sectionally (T1) and after 18 months (T2).Results: MKL successfully predicted PTSD symptom severity at both time points. Across cross-sectional and longitudinal models, negative affect was identified consistently as the most influential predictor at T1 and T2. Additional relevant predictors included tonic immobility, childhood maltreatment, and coping strategies.Conclusions: These findings emphasise the potential of combining easily measurable predictors to enhance the early detection of PTSD risk and to guide the development of more personalised prevention and intervention strategies.

Background: Childhood sexual abuse (CSA) is associated with significant negative lifelong consequences for physical and mental health. However, the impact of CSA history on danger perception and response has been understudied. In this study, we explored how autonomic reactivity to threats is influenced by the history of CSA in a nonclinical sample. Methods: Participants were undergraduate students with no current diagnosis of cardiovascular disease or mental disorders. After exclusion criteria were applied, the sample consisted of 135 participants. Among these 135 participants, 48 (mean age, 20.43 years; SD, 3.07; 9 men) reported having experienced significant CSA (CSA group), and 87 (mean age, 20.89 years; SD, 4.99; 30 men) reported not having had such experiences (non-CSA group). The participants viewed trauma-unrelated threatening or neutral pictures while their skin conductance response and heart rate data were collected. Results: Compared with the neutral pictures, when viewing trauma-unrelated threatening pictures, the non-CSA group presented bradycardia, which is a typical cardiac response upon exposure to negative images. In contrast, the CSA group presented a blunted cardiac response. Furthermore, we observed an overrepresentation of skin conductance nonresponders in the CSA group. Conclusions: Taken together, these findings suggest that youth who are exposed to CSA seem to have blunted autonomic responsiveness to threats. This blunted responsiveness is an atypical pattern that may represent a biomarker of many unfavorable physiological and psychological outcomes.

BACKGROUND:Graduate students face higher depression rates worldwide, which were further exacerbated during the COVID-19 pandemic. This study employed a machine learning approach to predict depressive symptoms using academic-related stressors. METHODS:We surveyed students across four graduate programs at a Federal University in Brazil between October 15, 2021, and March 26, 2022, when most activities were restricted to taking place online due to the pandemic. Through an online self-reported screening, participants rated ten academic stressors and completed the Patient Health Questionnaire (PHQ-9). Machine learning analysis tested whether the stressors would predict depressive symptoms. Gender, age, and race and ethnicity were used as covariates in the predictive model. RESULTS:Participants (n=172), 67.4 % women, mean age: 28.0 (SD: 4.53) fully completed the online questionnaires. The machine learning approach, employing an epsilon-insensitive support vector regression (Ɛ-SVR) with a k-fold (k=5) cross-validation strategy, effectively predicted depressive symptoms (r=0.51; R2=0.26; NMSE=0.79; all p=0.001). Among the academic stressors, those that made the greatest contribution to the predictive model were "fear and worry about academic performance", "financial difficulties", "fear and worry about academic progress and plans", and "fear and worry about academic deadlines". CONCLUSIONS:This study highlights the vulnerability of graduate students to depressive symptoms caused by academic-related stressors during the COVID-19 pandemic through an artificial intelligence methodology. These findings have the potential to guide policy development to create intervention programs and public health initiatives targeted towards graduate students.

Background: A recurring theme in fMRI studies is the inconsistent findings in amygdala and insula hyperreactivity among patients with PTSD vs. trauma-exposed controls. This study reanalyzed data from Bastos et al. (2022) investigating group effects to aversive stimuli in those regions. Methods: Patients with PTSD (n = 20) and trauma-exposed controls (n = 23) briefly viewed neutral and mutilation pictures. Amygdala and insula ROIs were analyzed for valence and group effects. Subsequently, regressor duration was extended to determine whether a longer regressor would capture a lasting valence effect beyond picture presentation. Results: Significant main effects of valence were observed in the amygdala and insula ROIs, for both regressor durations. In both regions there were no significant main effects for group. Further no interactions between valence and group were found, indicating lack of consistent hyperresponsivity in patients with PTSD. Conclusions: Our results help to challenge hyperreactivity as a proxy of PTSD. In fact, multiple traumatic experiences and/or childhood maltreatment were shown to be associated with hyporeactivity in PTSD. If this is not taken into consideration, the average pattern of reactivity recorded from a mixed sample with both hypo and hyper responders can be indistinguishable from controls.

This study investigated the impact of childhood sexual abuse (CSA) on brain responses to aversive stimuli in patients with Posttraumatic Stress Disorder (PTSD). Whole-brain and regions-of-interest analyses revealed that participants who reported higher severity of CSA had smaller brain reactivity to mutilation versus neutral pictures in the right postcentral and supramarginal gyrus, and in the left midcingulate, suggesting that CSA may blunt brain reactivity to aversive stimuli in areas involved in sensory and emo-motoric processing. This study adds evidence for long-lasting effects of CSA on brain processing and attests the need for specific diagnosis and treatment for the affected patients with PTSD.

The negative impact of loneliness on the health of the elderly is particularly noticeable because of the effects of central control on the autonomic nervous system. Such an impact can be assessed through heart rate variability (HRV) analysis and can be modified using HRV biofeedback training. This study aimed to investigate the impact of different levels of social interaction reported by the elderly on HRV before and after training with HRV biofeedback and after a follow-up period. The participants of this pilot study comprised 16 elderly people of both sexes with a mean age of 71.20 ± 4.92 years. The participants were divided into two groups, the loneliness group (N = 8) and the no-loneliness group (N = 8), based on a combination of both criteria: the institutionalization condition (institutionalized or not) and the score on the loneliness scale (high or low). All participants had their HRV components recorded at baseline, after 14 training sessions with HRV biofeedback (three times a week, 15 min each for 4.5 weeks), and after 4.5 weeks of follow-up without training. After HRV biofeedback training, HRV components increased in both groups. However, the gains lasted at follow-up only in the no-loneliness group. In conclusion, loneliness can influence the maintenance of HRV after interruption of training with HRV biofeedback in the elderly. HRV biofeedback training can be an innovative and effective tool for complementary treatment of elderly individuals, but its effects on lonely elderly individuals need to be further investigated.

Accumulating evidence suggests that interactions between the brain and gut microbiota significantly impact brain function and mental health. In the present study, we aimed to investigate whether young, healthy adults without psychiatric diagnoses exhibit differences in metabolic stool and microbiota profiles based on depression/anxiety scores and heart rate variability (HRV) parameters. Untargeted nuclear magnetic resonance-based metabolomics was used to identify fecal metabolic profiles. Results were subjected to multivariate analysis through principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), and the metabolites were identified through VIP score. Metabolites separating asymptomatic and symptomatic groups were acetate, valine, and glutamate, followed by sugar regions, glutamine, acetone, valerate, and acetoacetate. The main metabolites identified in high vagal tone (HVT) and low vagal tone (LVT) groups were acetate, valerate, and glutamate, followed by propionate and butyrate. In addition to the metabolites identified by the PLS-DA test, significant differences in aspartate, sarcosine, malate, and methionine were observed between the groups. Levels of acetoacetate were higher in both symptomatic and LVT groups. Valerate levels were significantly increased in the symptomatic group, while isovalerate, propionate, glutamate, and acetone levels were significantly increased in the LVT group. Furthermore, distinct abundance between groups was only confirmed for the Firmicutes phylum. Differences between participants with high and low vagal tone suggest that certain metabolites are involved in communication between the vagus nerve and the brain.

University students are vulnerable to mental health issues during their academic lives. During the COVID-19 pandemic, university students faced mental distress due to lockdowns and the transition to e-learning. However, it is not known whether these students were also affected specifically by COVID-19-related traumatic events. This study examined the impact of COVID-19-related traumatic events on 2277 university students from two federal institutions of higher education in Brazil. The university students completed an online questionnaire covering demographics, lifestyle habits, health characteristics, COVID-19-related traumatic events, and depression, anxiety, and stress symptoms. The results showed that an increased intensity of COVID-19-related traumatic events was positively associated with stress, anxiety, and depressive symptoms, and each specific type of event was associated with these symptoms. In addition, we found a negative association between these symptoms and male sex and age and a positive association with having or having had a history of cardiovascular, respiratory, neurological, or mental disorders or another disease diagnosed by a physician. In conclusion, this study emphasizes the heightened risk of mental health issues in university students in the face of COVID-19-related traumatic events. Women, young people and people who have or have had a history of disease were the most vulnerable to mental health issues during the COVID-19 pandemic.

BackgroundThe Self-Assessment Manikin (SAM), a pictorial scale for the measurement of pleasure and arousal dimensions of emotions, is one of the most applied tools in the emotion research field.ObjectiveWe present a detailed description of a remote method to collect affective ratings in response to pictures by using the SAM scale.MethodsTo empirically validate our remote method, we conducted a study using a digitized version of the SAM scale and delivered online didactic instructions that followed the normative rating procedure for the International Affective Picture System (IAPS) to the participants. We presented 70 pictures from the IAPS and an additional set of 22 food pictures to the participants.ResultsWe found strong correlations between the ratings of IAPS pictures obtained in our sample and those reported by North American and Brazilian participants in previous in-person studies that applied the same pictures and methodology. We were also able to obtain an additional standardized set of food pictures.ConclusionThe protocols described here may be useful for researchers interested in collecting remotely valid and reliable affecting ratings.

Features of threatening cues and the associated context influence the perceived imminence of threat and the defensive responses evoked. To provide additional knowledge about how the directionality of a threat (i.e. directed-towards or away from the viewer) might impact defensive responses in humans, participants were shown pictures of a man carrying a gun (threat) or nonlethal object (neutral) directed-away from or towards the participant. Cardiac and electrodermal responses were collected. Compared to neutral images, threatening images depicting a gun directed-towards the participant induced sustained bradycardia and an increased electrodermal response, interpreted as immobility under attack. This defensive immobility reaction is evoked by high perceived threat and inescapable situations and indicates intense action preparation. Pictures of guns directed-away from the participant induced shorter bradycardia and no significant modulation of the electrodermal response compared to neutral pictures, which might be consistent with the perception of a less threatening situation. The results show that the directionality of threat stimuli is a key factor that prompts different patterns of defensive responses.

During the COVID-19 pandemic healthcare workers were repeatedly exposed to traumatic experiences. Facing life-threatening events and repeated exposure to traumatic duty-related situations may cause posttraumatic stress disorder (PTSD). While tonic immobility has been considered a key vulnerability factor for PTSD, little is known about this relationship in the long term. In this study, we aimed to determine whether peritraumatic tonic immobility triggered by COVID-19-related trauma predicts PTSD symptom severity six to twelve months later. We conducted an online longitudinal survey using the PTSD Checklist for the DSM-5 (PCL-5) and the Tonic Immobility Scale to assess PTSD symptoms and the tonic immobility response, respectively. Multivariate regression models revealed a significant association between tonic immobility and PTSD symptoms. Each one-unit increase in the tonic immobility score was associated with a 1.5 % increase in the average PTSD symptom score six to twelve months after the traumatic event that triggered the tonic immobility. Furthermore, participants who showed significant or extreme levels of tonic immobility were 3.5 times or 7.3 times more likely to have a probable PTSD diagnosis, respectively. Hence, peritraumatic tonic immobility seems to have a lasting deleterious effect on mental health. Psychological treatment for health care professionals is urgent, and psychoeducation about the involuntary, biological nature of tonic immobility is essential to reduce suffering.

Background The present study aimed to apply multivariate pattern recognition methods to predict posttraumatic stress symptoms from whole-brain activation patterns during two contexts where the aversiveness of unpleasant pictures was manipulated by the presence or absence of safety cues. Methods Trauma-exposed participants were presented with neutral and mutilation pictures during functional magnetic resonance imaging (fMRI) collection. Before the presentation of pictures, a text informed the subjects that the pictures were fictitious (“safe context”) or real-life scenes (“real context”). We trained machine learning regression models (Gaussian process regression (GPR)) to predict PTSD symptoms in real and safe contexts. Results The GPR model could predict PTSD symptoms from brain responses to mutilation pictures in the real context but not in the safe context. The brain regions with the highest contribution to the model were the occipito-parietal regions, including the superior parietal gyrus, inferior parietal gyrus, and supramarginal gyrus. Additional analysis showed that GPR regression models accurately predicted clusters of PTSD symptoms, nominal intrusion, avoidance, and alterations in cognition. As expected, we obtained very similar results as those obtained in a model predicting PTSD total symptoms. Conclusion This study is the first to show that machine learning applied to fMRI data collected in an aversive context can predict not only PTSD total symptoms but also clusters of PTSD symptoms in a more aversive context. Furthermore, this approach was able to identify potential biomarkers for PTSD, especially in occipitoparietal regions.

Gender equity has been a significant concern among scientific societies. Here we analyzed the gender proportions of speakers at the 9th IBRO World Congress of Neuroscience (2015) held in Rio de Janeiro (Brazil). The survey was based on the online scientific programme. Gender was defined as a binary concept. Photos and pronouns were searched on personal and/or institutional websites. Plenary lectures had the lowest percentage of women - only 2 out of 10 (20%). Gender disparity was also observed in contributed talks. For symposia and mini-symposia speakers, 25 out of 80 (31,3%) and 17 out of 59 (28,8%) were women, respectively. Additionally, chairs were predominantly men; women chaired 8 of the 20 symposia (40%) and 6 of the 16 mini-symposia (37,5%). Besides, the gender imbalance of speakers was much worse in men-chaired ones. When the 9th Congress was held (2015), a gender gap was present among IBRO's Officers. Until 2020, no woman had been President, only 3 had been Secretary General (17.6%) and none had been Treasurer. The present gender disparities in meetings and directory boards replicate surveys from other neuroscience events and societies meetings. Auspiciously, the online programme of the present 11th IBRO World Congress of Neuroscience (2023) depicts an equal distribution of women and men (50%) lecturers, certainly reflecting the result of recent advances in pursuing gender equity. Importantly, the current IBRO`s officers in the Presidency and Secretary General posts are women. IBRO`s leading initiative of gender equity in invited lectures has the potential to act as a model and spread to several societies from different countries joining the 11th IBRO World Congress. Moreover, it is important to continuously collect data for bias in gender, race and other minoritized groups to guide future actions targeting equity, diversity, and inclusion in the neuroscience community. Declaration of Interest Statement: None

O objetivo do presente estudo foi verificar a possibilidade de predição dos sintomas do Transtorno de Estresse Pós-Traumático (TEPT) a partir dos padrões de atividade cerebral. Os participantes expostos a situações traumáticas foram submetidos a exames de Ressonância Magnética Funcional (RMf) enquanto eram expostos a fotos neutras e de corpos mutilados. Neste experimento, foram criados dois contextos de imagens aversivas (real e seguro). O modelo de aprendizado de máquina foi capaz de predizer sintomas de TEPT a partir de padrões de atividade cerebral em resposta às imagens de mutilação no contexto real, mas não no contexto seguro. As regiões cerebrais que apresentaram maior contribuição para o modelo foram as regiões occipitoparietais, incluindo o giro parietal superior e inferior, e o giro supramarginal.