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Abstract Processing facial expressions of emotion draws on a distributed brain network. In particular, judging ambiguous facial emotions involves coordination between multiple brain areas. Here, we applied multimodal functional connectivity analysis to achieve network-level understanding of the neural mechanisms underlying perceptual ambiguity in facial expressions. We found directional effective connectivity between the amygdala, dorsomedial prefrontal cortex (dmPFC), and ventromedial PFC, supporting both bottom-up affective processes for ambiguity representation/perception and top-down cognitive processes for ambiguity resolution/decision. Direct recordings from the human neurosurgical patients showed that the responses of amygdala and dmPFC neurons were modulated by the level of emotion ambiguity, and amygdala neurons responded earlier than dmPFC neurons, reflecting the bottom-up process for ambiguity processing. We further found parietal-frontal coherence and delta-alpha cross-frequency coupling involved in encoding emotion ambiguity. We replicated the EEG coherence result using independent experiments and further showed modulation of the coherence. EEG source connectivity revealed that the dmPFC top-down regulated the activities in other brain regions. Lastly, we showed altered behavioral responses in neuropsychiatric patients who may have dysfunctions in amygdala-PFC functional connectivity. Together, using multimodal experimental and analytical approaches, we have delineated a neural network that underlies processing of emotion ambiguity.
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A Neurocomputational Model of Posttraumatic Stress Disorder
Despite the well-defined behavioral criteria for posttraumatic stress disorder (PTSD), clinical care is com- plicated by the heterogeneity of biological factors underly- ing impairment. Eye movement tasks provide an opportunity to assess the relationships between aberrant neurobiological function and non-volitional performance metrics that are not dependent on self-report. A recent study using an emotional variant of the antisaccade task demonstrated attentional control biases that interfered with task performance in Veterans with PTSD. Here we present a neuroanatomically-inspired com- putational model based on gated attractor networks that is designed to replicate oculomotor behavior on an affective anti- saccade task. The model includes the putative neural circuitry underlying fear response (amygdala) and top-down inhibitory control (prefrontal cortex), and is capable of generating testable predictions about the causal implications of changes in this circuitry on task performance and neural activation associated with PTSD. Calibrating the model with the results of behavioral and neuroimaging studies on patient populations yields a pattern of connectivity changes characterized by increased amygdala sensitivity and reduced top-down prefrontal control that is consistent with the fear conditioning model of PTSD. In addition, the model makes experimentally verifiable predictions about the consequences of increased prefrontal connectivity associated with cognitive reappraisal training. Keywords: posttraumatic stress disorder, antisaccade task, inhibitory control deficits, attentional bias, cognitive control.
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- Award ID(s):
- 1632976
- PAR ID:
- 10287578
- Date Published:
- Journal Name:
- International IEEE/EMBS Conference on Neural Engineering 2021
- Page Range / eLocation ID:
- 107 to 110
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/NER49283.2021.9441345
