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      Extended Reality for the Clinical, Affective, and Social Neurosciences

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          Abstract

          Brain science research often involves the use of low-dimensional tools and stimuli that lack several of the potentially valuable features of everyday activities and interactions. Although this research has provided important information about cognitive, affective, and social processes for both clinical and nonclinical populations, there is growing interest in high-dimensional simulations that extend reality. These high-dimensional simulations involve dynamic stimuli presented serially or concurrently to permit the assessment and training of perceivers’ integrative processes over time. Moreover, high-dimensional simulation platforms can contextually restrain interpretations of cues about a target’s internal states. Extended reality environments extend assessment and training platforms that balance experimental control with emotionally engaging background narratives aimed at extending the affective experience and social interactions. Herein, we highlight the promise of extended reality platforms for greater ecological validity in the clinical, affective, and social neurosciences.

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          Most cited references172

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          A default mode of brain function.

          A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
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            Functional connectivity in the resting brain: a network analysis of the default mode hypothesis.

            Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.
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              Subcortical and cortical brain activity during the feeling of self-generated emotions.

              In a series of [15O]PET experiments aimed at investigating the neural basis of emotion and feeling, 41 normal subjects recalled and re-experienced personal life episodes marked by sadness, happiness, anger or fear. We tested the hypothesis that the process of feeling emotions requires the participation of brain regions, such as the somatosensory cortices and the upper brainstem nuclei, that are involved in the mapping and/or regulation of internal organism states. Such areas were indeed engaged, underscoring the close relationship between emotion and homeostasis. The findings also lend support to the idea that the subjective process of feeling emotions is partly grounded in dynamic neural maps, which represent several aspects of the organism's continuously changing internal state.
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                Author and article information

                Journal
                Brain Sci
                Brain Sci
                brainsci
                Brain Sciences
                MDPI
                2076-3425
                30 November 2020
                December 2020
                : 10
                : 12
                : 922
                Affiliations
                [1 ]iCenter for Affective Neurotechnologies (iCAN), Denton, TX 76203, USA
                [2 ]Computational Neuropsychology and Simulation (CNS) Laboratory, University of North Texas, Denton, TX 76203, USA
                [3 ]College of Information, University of North Texas, Denton, TX 76203, USA
                [4 ]Humane Technology Lab, Università Cattolica del Sacro Cuore, 20123 Milan, Italy; andrea.gaggioli@ 123456unicatt.it (A.G.); giuseppe.riva@ 123456unicatt.it (G.R.)
                [5 ]Applied Technology for Neuro-Psychology Laboratory, Istituto Auxologico Italiano, 20145 Milan, Italy
                Author notes
                Author information
                https://orcid.org/0000-0003-0331-5019
                https://orcid.org/0000-0003-3657-106X
                Article
                brainsci-10-00922
                10.3390/brainsci10120922
                7761460
                33265932
                87a4ed33-f507-462f-b0ea-2feeb9a651cd
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 October 2020
                : 26 November 2020
                Categories
                Review

                social neuroscience,clinical neuroscience,affective neuroscience,presence,virtual reality,extended reality,neuropsychology

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