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      A Neural Model of Empathic States in Attachment-Based Psychotherapy

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          Abstract

          We build on a neuroanatomical model of how empathic states can motivate caregiving behavior, via empathy circuit-driven activation of regions in the hypothalamus and amygdala, which in turn stimulate a mesolimbic–ventral pallidum pathway, by integrating findings related to the perception of pain in self and others. On this basis, we propose a network to capture states of personal distress and (weak and strong forms of) empathic concern, which are particularly relevant for psychotherapists conducting attachment-based interventions. This model is then extended for the case of self-attachment therapy, in which conceptualized components of the self serve as both the source of and target for empathic resonance. In particular, we consider how states of empathic concern involving an other that is perceived as being closely related to the self might enhance the motivation for self-directed bonding (which in turn is proposed to lead the individual toward more compassionate states) in terms of medial prefrontal cortex–mediated activation of these caregiving pathways. We simulate our model computationally and discuss the interplay between the bonding and empathy protocols of the therapy.

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          Most cited references117

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          Empathy for pain involves the affective but not sensory components of pain.

          Our ability to have an experience of another's pain is characteristic of empathy. Using functional imaging, we assessed brain activity while volunteers experienced a painful stimulus and compared it to that elicited when they observed a signal indicating that their loved one--present in the same room--was receiving a similar pain stimulus. Bilateral anterior insula (AI), rostral anterior cingulate cortex (ACC), brainstem, and cerebellum were activated when subjects received pain and also by a signal that a loved one experienced pain. AI and ACC activation correlated with individual empathy scores. Activity in the posterior insula/secondary somatosensory cortex, the sensorimotor cortex (SI/MI), and the caudal ACC was specific to receiving pain. Thus, a neural response in AI and rostral ACC, activated in common for "self" and "other" conditions, suggests that the neural substrate for empathic experience does not involve the entire "pain matrix." We conclude that only that part of the pain network associated with its affective qualities, but not its sensory qualities, mediates empathy.
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            Simple model of spiking neurons.

            A model is presented that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin-Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC.
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              Interneurons of the neocortical inhibitory system.

              Mammals adapt to a rapidly changing world because of the sophisticated cognitive functions that are supported by the neocortex. The neocortex, which forms almost 80% of the human brain, seems to have arisen from repeated duplication of a stereotypical microcircuit template with subtle specializations for different brain regions and species. The quest to unravel the blueprint of this template started more than a century ago and has revealed an immensely intricate design. The largest obstacle is the daunting variety of inhibitory interneurons that are found in the circuit. This review focuses on the organizing principles that govern the diversity of inhibitory interneurons and their circuits.
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                Author and article information

                Journal
                Comput Psychiatr
                Comput Psychiatr
                cpsy
                Computational Psychiatry (Cambridge, Mass.)
                MIT Press (One Rogers Street, Cambridge, MA 02142-1209USAjournals-info@mit.edu )
                2379-6227
                01 December 2017
                December 2017
                : 1
                : 132-167
                Affiliations
                [1]Algorithmic Human Development, Department of Computing, Imperial College London, London, United Kingdom
                Author notes

                Competing Interests: The authors declare no conflicts of interests.

                [* ]Corresponding author: davidcittern@ 123456gmail.com .
                Article
                CPSY_a_00006
                10.1162/CPSY_a_00006
                6067830
                2be6c2ea-4f96-46b0-b28a-c172586e56a7
                © 2017 Massachusetts Institute of Technology

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 04 July 2016
                : 21 April 2017
                Page count
                Figures: 12, References: 168, Pages: 36
                Funding
                Funded by: Medical Research Council, FundRef http://dx.doi.org/10.13039/501100000265;
                Award ID: MR/K024280/1
                Funded by: National Institute of Mental Health, FundRef http://dx.doi.org/10.13039/100000025;
                Award ID: 1R21MH108421-01A1
                Categories
                Research
                Custom metadata
                Cittern, D., & Edalat, A. (2017). A neural model of empathic states in attachment–based psychotherapy. Computational Psychiatry, 1, 132–167. https://doi.org/10.1162/ cpsy_a_00006

                self-attachment,caregiving behavior,self-other pain,compassion,neurobiology

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