57 research outputs found

    Editorial: Insights into structural and functional organization of the brain: evidence from neuroimaging and non-invasive brain stimulation techniques

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    The brain is a complex and dynamic system that underlies our behavior, emotions, and cognition (1–3). To better understand the structural and functional organization of the brain, neuroimaging and brain stimulation techniques have emerged as powerful tools (Nyatega et al.) (4–9)

    Investigation of Brain Activation Patterns Related to the Feminization or Masculinization of Body and Face Images across Genders

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    Previous studies demonstrated sex-related differences in several areas of the human brain, including patterns of brain activation in males and females when observing their own bodies and faces (versus other bodies/faces or morphed versions of themselves), but a complex paradigm touching multiple aspects of embodied self-identity is still lacking. We enrolled 24 healthy individuals (12 M, 12 F) in 3 different fMRI experiments: the vision of prototypical body silhouettes, the vision of static images of the face of the participants morphed with prototypical male and female faces, the vision of short videos showing the dynamic transformation of the morphing. We found differential sexual activations in areas linked to self-identity and to the ability to attribute mental states: In Experiment 1, the male group activated more the bilateral thalamus when looking at sex congruent body images, while the female group activated more the middle and inferior temporal gyrus. In Experiment 2, the male group activated more the supplementary motor area when looking at their faces; the female group activated more the dorsomedial prefrontal cortex (dmPFC). In Experiment 3, the female group activated more the dmPFC when observing either the feminization or the masculinization of their face. The defeminization produced more activations in females in the left superior parietal lobule and middle occipital gyrus. The performance of all classifiers built using single ROIs exceeded chance level, reaching an area under the ROC curves > 0.85 in some cases (notably, for Experiment 2 using the V1 ROI). The results of the fMRI tasks showed good agreement with previously published studies, even if our sample size was small. Therefore, our functional MRI protocol showed significantly different patterns of activation in males and females, but further research is needed both to investigate the gender-related differences in activation when observing a morphing of their face/body, and to validate our paradigm using a larger sample

    A deep neural network model of the primate superior colliculus for emotion recognition

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    Although sensory processing is pivotal to nearly every theory of emotion, the evaluation of the visual input as ‘emotional’ (e.g. a smile as signalling happiness) has been traditionally assumed to take place in supramodal ‘limbic’ brain regions. Accordingly, subcortical structures of ancient evolutionary origin that receive direct input from the retina, such as the superior colliculus (SC), are traditionally conceptualized as passive relay centres. However, mounting evidence suggests that the SC is endowed with the necessary infrastructure and computational capabilities for the innate recognition and initial categorization of emotionally salient features from retinal information. Here, we built a neurobiologically inspired convolutional deep neural network (DNN) model that approximates physiological, anatomical and connectional properties of the retino-collicular circuit. This enabled us to characterize and isolate the initial computations and discriminations that the DNN model of the SC can perform on facial expressions, based uniquely on the information it directly receives from the virtual retina. Trained to discriminate facial expressions of basic emotions, our model matches human error patterns and above chance, yet suboptimal, classification accuracy analogous to that reported in patients with V1 damage, who rely on retino-collicular pathways for non-conscious vision of emotional attributes. When presented with gratings of different spatial frequencies and orientations never ‘seen’ before, the SC model exhibits spontaneous tuning to low spatial frequencies and reduced orientation discrimination, as can be expected from the prevalence of the magnocellular (M) over parvocellular (P) projections. Likewise, face manipulation that biases processing towards the M or P pathway affects expression recognition in the SC model accordingly, an effect that dovetails with variations of activity in the human SC purposely measured with ultra-high field functional magnetic resonance imaging. Lastly, the DNN generates saliency maps and extracts visual features, demonstrating that certain face parts, like the mouth or the eyes, provide higher discriminative information than other parts as a function of emotional expressions like happiness and sadness. The present findings support the contention that the SC possesses the necessary infrastructure to analyse the visual features that define facial emotional stimuli also without additional processing stages in the visual cortex or in ‘limbic’ areas

    Default and Control Networks Connectivity Dynamics Track the Stream of Affect at Multiple Timescales

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    In everyday life, the stream of affect results from the interaction between past experiences, expectations and the unfolding of events. How the brain represents the relationship between time and affect has been hardly explored, as it requires modeling the complexity of everyday life in the laboratory setting. Movies condense into hours a multitude of emotional responses, synchronized across subjects and characterized by temporal dynamics alike real-world experiences. Here, we use time-varying intersubject brain synchronization and real-time behavioral reports to test whether connectivity dynamics track changes in affect during movie watching. The results show that polarity and intensity of experiences relate to the connectivity of the default mode and control networks and converge in the right temporoparietal cortex. We validate these results in two experiments including four independent samples, two movies and alternative analysis workflows. Finally, we reveal chronotopic connectivity maps within the temporoparietal and prefrontal cortex, where adjacent areas preferentially encode affect at specific timescales
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