Decoding negative affect personality trait from patterns of brain activation to threat stimuli

INTRODUCTION: Pattern recognition analysis (PRA) applied to functional magnetic resonance imaging (fMRI) has been used to decode cognitive processes and identify possible biomarkers for mental illness. In the present study, we investigated whether the positive affect (PA) or negative affect (NA) personality traits could be decoded from patterns of brain activation in response to a human threat using a healthy sample. METHODS: fMRI data from 34 volunteers (15 women) were acquired during a simple motor task while the volunteers viewed a set of threat stimuli that were directed either toward them or away from them and matched neutral pictures. For each participant, contrast images from a General Linear Model (GLM) between the threat versus neutral stimuli defined the spatial patterns used as input to the regression model. We applied a multiple kernel learning (MKL) regression combining information from different brain regions hierarchically in a whole brain model to decode the NA and PA from patterns of brain activation in response to threat stimuli. RESULTS: The MKL model was able to decode NA but not PA from the contrast images between threat stimuli directed away versus neutral with a significance above chance. The correlation and the mean squared error (MSE) between predicted and actual NA were 0.52 (p-value=0.01) and 24.43 (p-value=0.01), respectively. The MKL pattern regression model identified a network with 37 regions that contributed to the predictions. Some of the regions were related to perception (e.g., occipital and temporal regions) while others were related to emotional evaluation (e.g., caudate and prefrontal regions). CONCLUSION: These results suggest that there was an interaction between the individuals' NA and the brain response to the threat stimuli directed away, which enabled the MKL model to decode NA from the brain patterns. To our knowledge, this is the first evidence that PRA can be used to decode a personality trait from patterns of brain activation during emotional contexts

Decoding negative affect personality trait from patterns of brain activation to threat stimuli

INTRODUCTION: Pattern recognition analysis (PRA) applied to functional magnetic resonance imaging (fMRI) has been used to decode cognitive processes and identify possible biomarkers for mental illness. In the present study, we investigated whether the positive affect (PA) or negative affect (NA) personality traits could be decoded from patterns of brain activation in response to a human threat using a healthy sample. METHODS: fMRI data from 34 volunteers (15 women) were acquired during a simple motor task while the volunteers viewed a set of threat stimuli that were directed either toward them or away from them and matched neutral pictures. For each participant, contrast images from a General Linear Model (GLM) between the threat versus neutral stimuli defined the spatial patterns used as input to the regression model. We applied a multiple kernel learning (MKL) regression combining information from different brain regions hierarchically in a whole brain model to decode the NA and PA from patterns of brain activation in response to threat stimuli. RESULTS: The MKL model was able to decode NA but not PA from the contrast images between threat stimuli directed away versus neutral with a significance above chance. The correlation and the mean squared error (MSE) between predicted and actual NA were 0.52 (p-value=0.01) and 24.43 (p-value=0.01), respectively. The MKL pattern regression model identified a network with 37 regions that contributed to the predictions. Some of the regions were related to perception (e.g., occipital and temporal regions) while others were related to emotional evaluation (e.g., caudate and prefrontal regions). CONCLUSION: These results suggest that there was an interaction between the individuals' NA and the brain response to the threat stimuli directed away, which enabled the MKL model to decode NA from the brain patterns. To our knowledge, this is the first evidence that PRA can be used to decode a personality trait from patterns of brain activation during emotional contexts

Vulnerability and Protective Factors for PTSD and Depression Symptoms Among Healthcare Workers During COVID-19: A Machine Learning Approach

Background: Healthcare workers are at high risk for developing mental health problems during the COVID-19 pandemic. There is an urgent need to identify vulnerability and protective factors related to the severity of psychiatric symptoms among healthcare workers to implement targeted prevention and intervention programs to reduce the mental health burden worldwide during COVID-19. // Objective: The present study aimed to apply a machine learning approach to predict depression and PTSD symptoms based on psychometric questions that assessed: (1) the level of stress due to being isolated from one's family; (2) professional recognition before and during the pandemic; and (3) altruistic acceptance of risk during the COVID-19 pandemic among healthcare workers. // Methods: A total of 437 healthcare workers who experienced some level of isolation at the time of the pandemic participated in the study. Data were collected using a web survey conducted between June 12, 2020, and September 19, 2020. We trained two regression models to predict PTSD and depression symptoms. Pattern regression analyses consisted of a linear epsilon-insensitive support vector machine (ε-SVM). Predicted and actual clinical scores were compared using Pearson's correlation coefficient (r), the coefficient of determination (r2), and the normalized mean squared error (NMSE) to evaluate the model performance. A permutation test was applied to estimate significance levels. // Results: Results were significant using two different cross-validation strategies to significantly decode both PTSD and depression symptoms. For all of the models, the stress due to social isolation and professional recognition were the variables with the greatest contributions to the predictive function. Interestingly, professional recognition had a negative predictive value, indicating an inverse relationship with PTSD and depression symptoms. // Conclusions: Our findings emphasize the protective role of professional recognition and the vulnerability role of the level of stress due to social isolation in the severity of posttraumatic stress and depression symptoms. The insights gleaned from the current study will advance efforts in terms of intervention programs and public health messaging

Antecedent descriptions change brain reactivity to emotional stimuli: a Functional Magnetic Resonance imaging study of an extrinsic and incidental reappraisal strategy

In the present study we investigated whether individuals would take advantage of an extrinsic and incidental reappraisal strategy by giving them precedent descriptions to attenuate the emotional impact of unpleasant pictures. In fact, precedent descriptions have successfully promoted down-regulation of electrocortical activity and physiological responses to unpleasant pictures. However, the neuronal substrate underlying this effect remains unclear. Particularly, we investigated whether amygdala and insula responses, brain regions consistently implicated in emotional processing, would be modulated by this strategy. To achieve this, highly unpleasant pictures were shown in two contexts in which a prior description presented them as taken from movie scenes (fictitious) or real scenes. Results showed that the fictitious condition was characterized by down-regulation of amygdala and insula responses. Thus, the present study provides new evidence on reappraisal strategies to downregulate emotional reactions and suggest that amygdala and insula responses to emotional stimuli are adaptive and highly flexible

The Horizontal Optokinetic Reflex of the opossum (Didelphis marsupialis aurita): Physiological and Anatomical Studies in Normal and Early Monoenucleated Specimens

AbstractIn the opossum the symmetrical binocular horizontal optokinetic nystagmus gives way to an asymmetrical monocular reflex: the nasotemporal (NT) stimulation yielding lower gain than the temporonasal (TN). In adults, monocularly enucleated at postnatal days 21–25 (pnd21–25), the gain of NT responses is markedly increased, approaching that of TN. Severe cell loss was detected in the nucleus of the optic tract (NOT) on the deafferented side in early monoenucleated specimens. In normal animals retinal afferents to the NOT are all crossed, while in animals enucleated at pnd21–25 sparse uncrossed retinal elements were observed. Although this abnormal projection might influence the increase NT response in this subgroup, it is argued that the increased symmetry in monoenucleated opossums may be the result of changes mediated by the commissural connection between both NOTs. © 1997 Elsevier Science Ltd. All rights reserved